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A case of a four-year-old child adopted at eight months with unusual mood patterns and significant polypharmacy

• Magdalena Romanowicz   ORCID: orcid.org/0000-0002-4916-0625 1 ,
• Alastair J. McKean 1 &
• Jennifer Vande Voort 1  

BMC Psychiatry volume  17 , Article number:  330 ( 2017 ) Cite this article

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Long-term effects of neglect in early life are still widely unknown. Diversity of outcomes can be explained by differences in genetic risk, epigenetics, prenatal factors, exposure to stress and/or substances, and parent-child interactions. Very common sub-threshold presentations of children with history of early trauma are challenging not only to diagnose but also in treatment.

Case presentation

A Caucasian 4-year-old, adopted at 8 months, male patient with early history of neglect presented to pediatrician with symptoms of behavioral dyscontrol, emotional dysregulation, anxiety, hyperactivity and inattention, obsessions with food, and attachment issues. He was subsequently seen by two different child psychiatrists. Pharmacotherapy treatment attempted included guanfacine, fluoxetine and amphetamine salts as well as quetiapine, aripiprazole and thioridazine without much improvement. Risperidone initiated by primary care seemed to help with his symptoms of dyscontrol initially but later the dose had to be escalated to 6 mg total for the same result. After an episode of significant aggression, the patient was admitted to inpatient child psychiatric unit for stabilization and taper of the medicine.

Conclusions

The case illustrates difficulties in management of children with early history of neglect. A particular danger in this patient population is polypharmacy, which is often used to manage transdiagnostic symptoms that significantly impacts functioning with long term consequences.

Peer Review reports

There is a paucity of studies that address long-term effects of deprivation, trauma and neglect in early life, with what little data is available coming from institutionalized children [ 1 ]. Rutter [ 2 ], who studied formerly-institutionalized Romanian children adopted into UK families, found that this group exhibited prominent attachment disturbances, attention-deficit/hyperactivity disorder (ADHD), quasi-autistic features and cognitive delays. Interestingly, no other increases in psychopathology were noted [ 2 ].

Even more challenging to properly diagnose and treat are so called sub-threshold presentations of children with histories of early trauma [ 3 ]. Pincus, McQueen, & Elinson [ 4 ] described a group of children who presented with a combination of co-morbid symptoms of various diagnoses such as conduct disorder, ADHD, post-traumatic stress disorder (PTSD), depression and anxiety. As per Shankman et al. [ 5 ], these patients may escalate to fulfill the criteria for these disorders. The lack of proper diagnosis imposes significant challenges in terms of management [ 3 ].

J is a 4-year-old adopted Caucasian male who at the age of 2 years and 4 months was brought by his adoptive mother to primary care with symptoms of behavioral dyscontrol, emotional dysregulation, anxiety, hyperactivity and inattention, obsessions with food, and attachment issues. J was given diagnoses of reactive attachment disorder (RAD) and ADHD. No medications were recommended at that time and a referral was made for behavioral therapy.

She subsequently took him to two different child psychiatrists who diagnosed disruptive mood dysregulation disorder (DMDD), PTSD, anxiety and a mood disorder. To help with mood and inattention symptoms, guanfacine, fluoxetine, methylphenidate and amphetamine salts were all prescribed without significant improvement. Later quetiapine, aripiprazole and thioridazine were tried consecutively without behavioral improvement (please see Table  1 for details).

No significant drug/substance interactions were noted (Table 1 ). There were no concerns regarding adherence and serum drug concentrations were not ordered. On review of patient’s history of medication trials guanfacine and methylphenidate seemed to have no effect on J’s hyperactive and impulsive behavior as well as his lack of focus. Amphetamine salts that were initiated during hospitalization were stopped by the patient’s mother due to significant increase in aggressive behaviors and irritability. Aripiprazole was tried for a brief period of time and seemed to have no effect. Quetiapine was initially helpful at 150 mg (50 mg three times a day), unfortunately its effects wore off quickly and increase in dose to 300 mg (100 mg three times a day) did not seem to make a difference. Fluoxetine that was tried for anxiety did not seem to improve the behaviors and was stopped after less than a month on mother’s request.

J’s condition continued to deteriorate and his primary care provider started risperidone. While initially helpful, escalating doses were required until he was on 6 mg daily. In spite of this treatment, J attempted to stab a girl at preschool with scissors necessitating emergent evaluation, whereupon he was admitted to inpatient care for safety and observation. Risperidone was discontinued and J was referred to outpatient psychiatry for continuing medical monitoring and therapy.

Little is known about J’s early history. There is suspicion that his mother was neglectful with feeding and frequently left him crying, unattended or with strangers. He was taken away from his mother’s care at 7 months due to neglect and placed with his aunt. After 1 month, his aunt declined to collect him from daycare, deciding she was unable to manage him. The owner of the daycare called Child Services and offered to care for J, eventually becoming his present adoptive parent.

J was a very needy baby who would wake screaming and was hard to console. More recently he wakes in the mornings anxious and agitated. He is often indiscriminate and inappropriate interpersonally, unable to play with other children. When in significant distress he regresses, and behaves as a cat, meowing and scratching the floor. Though J bonded with his adoptive mother well and was able to express affection towards her, his affection is frequently indiscriminate and he rarely shows any signs of separation anxiety.

At the age of 2 years and 8 months there was a suspicion for speech delay and J was evaluated by a speech pathologist who concluded that J was exhibiting speech and language skills that were solidly in the average range for age, with developmental speech errors that should be monitored over time. They did not think that issues with communication contributed significantly to his behavioral difficulties. Assessment of intellectual functioning was performed at the age of 2 years and 5 months by a special education teacher. Based on Bailey Infant and Toddler Development Scale, fine and gross motor, cognitive and social communication were all within normal range.

J’s adoptive mother and in-home therapist expressed significant concerns in regards to his appetite. She reports that J’s biological father would come and visit him infrequently, but always with food and sweets. J often eats to the point of throwing up and there have been occasions where he has eaten his own vomit and dog feces. Mother noticed there is an association between his mood and eating behaviors. J’s episodes of insatiable and indiscriminate hunger frequently co-occur with increased energy, diminished need for sleep, and increased speech. This typically lasts a few days to a week and is followed by a period of reduced appetite, low energy, hypersomnia, tearfulness, sadness, rocking behavior and slurred speech. Those episodes last for one to 3 days. Additionally, there are times when his symptomatology seems to be more manageable with fewer outbursts and less difficulty regarding food behaviors.

J’s family history is poorly understood, with his biological mother having a personality disorder and ADHD, and a biological father with substance abuse. Both maternally and paternally there is concern for bipolar disorder.

J has a clear history of disrupted attachment. He is somewhat indiscriminate in his relationship to strangers and struggles with impulsivity, aggression, sleep and feeding issues. In addition to early life neglect and possible trauma, J has a strong family history of psychiatric illness. His mood, anxiety and sleep issues might suggest underlying PTSD. His prominent hyperactivity could be due to trauma or related to ADHD. With his history of neglect, indiscrimination towards strangers, mood liability, attention difficulties, and heightened emotional state, the possibility of Disinhibited Social Engagement Disorder (DSED) is likely. J’s prominent mood lability, irritability and family history of bipolar disorder, are concerning for what future mood diagnosis this portends.

As evidenced above, J presents as a diagnostic conundrum suffering from a combination of transdiagnostic symptoms that broadly impact his functioning. Unfortunately, although various diagnoses such as ADHD, PTSD, Depression, DMDD or DSED may be entertained, the patient does not fall neatly into any of the categories.

This is a case report that describes a diagnostic conundrum in a young boy with prominent early life deprivation who presented with multidimensional symptoms managed with polypharmacy.

A sub-threshold presentation in this patient partially explains difficulties with diagnosis. There is no doubt that negative effects of early childhood deprivation had significant impact on developmental outcomes in this patient, but the mechanisms that could explain the associations are still widely unknown. Significant family history of mental illness also predisposes him to early challenges. The clinical picture is further complicated by the potential dynamic factors that could explain some of the patient’s behaviors. Careful examination of J’s early life history would suggest such a pattern of being able to engage with his biological caregivers, being given food, being tended to; followed by periods of neglect where he would withdraw, regress and engage in rocking as a self-soothing behavior. His adoptive mother observed that visitations with his biological father were accompanied by being given a lot of food. It is also possible that when he was under the care of his biological mother, he was either attended to with access to food or neglected, left hungry and screaming for hours.

The current healthcare model, being centered on obtaining accurate diagnosis, poses difficulties for treatment in these patients. Given the complicated transdiagnostic symptomatology, clear guidelines surrounding treatment are unavailable. To date, there have been no psychopharmacological intervention trials for attachment issues. In patients with disordered attachment, pharmacologic treatment is typically focused on co-morbid disorders, even with sub-threshold presentations, with the goal of symptom reduction [ 6 ]. A study by dosReis [ 7 ] found that psychotropic usage in community foster care patients ranged from 14% to 30%, going to 67% in therapeutic foster care and as high as 77% in group homes. Another study by Breland-Noble [ 8 ] showed that many children receive more than one psychotropic medication, with 22% using two medications from the same class.

It is important to note that our patient received four different neuroleptic medications (quetiapine, aripiprazole, risperidone and thioridazine) for disruptive behaviors and impulsivity at a very young age. Olfson et al. [ 9 ] noted that between 1999 and 2007 there has been a significant increase in the use of neuroleptics for very young children who present with difficult behaviors. A preliminary study by Ercan et al. [ 10 ] showed promising results with the use of risperidone in preschool children with behavioral dyscontrol. Review by Memarzia et al. [ 11 ] suggested that risperidone decreased behavioral problems and improved cognitive-motor functions in preschoolers. The study also raised concerns in regards to side effects from neuroleptic medications in such a vulnerable patient population. Younger children seemed to be much more susceptible to side effects in comparison to older children and adults with weight gain being the most common. Weight gain associated with risperidone was most pronounced in pre-adolescents (Safer) [ 12 ]. Quetiapine and aripiprazole were also associated with higher rates of weight gain (Correll et al.) [ 13 ].

Pharmacokinetics of medications is difficult to assess in very young children with ongoing development of the liver and the kidneys. It has been observed that psychotropic medications in children have shorter half-lives (Kearns et al.) [ 14 ], which would require use of higher doses for body weight in comparison to adults for same plasma level. Unfortunately, that in turn significantly increases the likelihood and severity of potential side effects.

There is also a question on effects of early exposure to antipsychotics on neurodevelopment. In particular in the first 3 years of life there are many changes in developing brains, such as increase in synaptic density, pruning and increase in neuronal myelination to list just a few [ 11 ]. Unfortunately at this point in time there is a significant paucity of data that would allow drawing any conclusions.

Our case report presents a preschool patient with history of adoption, early life abuse and neglect who exhibited significant behavioral challenges and was treated with various psychotropic medications with limited results. It is important to emphasize that subthreshold presentation and poor diagnostic clarity leads to dangerous and excessive medication regimens that, as evidenced above is fairly common in this patient population.

Neglect and/or abuse experienced early in life is a risk factor for mental health problems even after adoption. Differences in genetic risk, epigenetics, prenatal factors (e.g., malnutrition or poor nutrition), exposure to stress and/or substances, and parent-child interactions may explain the diversity of outcomes among these individuals, both in terms of mood and behavioral patterns [ 15 , 16 , 17 ]. Considering that these children often present with significant functional impairment and a wide variety of symptoms, further studies are needed regarding diagnosis and treatment.

Abbreviations

Attention-Deficit/Hyperactivity Disorder

Disruptive Mood Dysregulation Disorder

Disinhibited Social Engagement Disorder

Post-Traumatic Stress Disorder

Reactive Attachment disorder

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Romanowicz, M., McKean, A.J. & Vande Voort, J. A case of a four-year-old child adopted at eight months with unusual mood patterns and significant polypharmacy. BMC Psychiatry 17 , 330 (2017). https://doi.org/10.1186/s12888-017-1492-y

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REVIEW article

Child and adolescent depression: a review of theories, evaluation instruments, prevention programs, and treatments.

• 1 Developmental and Educational Department, University of the Basque Country, Donostia/San Sebastián, Spain
• 2 Developmental and Educational Psychology Department, University of the Basque Country, Lejona, Spain
• 3 Personality, Evaluation and Psychological Treatments Department, University of the Basque Country, Donostia/San Sebastián, Spain

Depression is the principal cause of illness and disability in the world. Studies charting the prevalence of depression among children and adolescents report high percentages of youngsters in both groups with depressive symptoms. This review analyzes the construct and explanatory theories of depression and offers a succinct overview of the main evaluation instruments used to measure this disorder in children and adolescents, as well as the prevention programs developed for the school environment and the different types of clinical treatment provided. The analysis reveals that in mental classifications, the child depression construct is no different from the adult one, and that multiple explanatory theories must be taken into account in order to arrive at a full understanding of depression. Consequently, both treatment and prevention should also be multifactorial in nature. Although universal programs may be more appropriate due to their broad scope of application, the results are inconclusive and fail to demonstrate any solid long-term efficacy. In conclusion, we can state that: (1) There are biological factors (such as tryptophan—a building block for serotonin-depletion, for example) which strongly influence the appearance of depressive disorders; (2) Currently, negative interpersonal relations and relations with one's environment, coupled with social-cultural changes, may explain the increase observed in the prevalence of depression; (3) Many instruments can be used to evaluate depression, but it is necessary to continue to adapt tests for diagnosing the condition at an early age; (4) Prevention programs should be developed for and implemented at an early age; and (5) The majority of treatments are becoming increasingly rigorous and effective. Given that initial manifestations of depression may occur from a very early age, further and more in-depth research is required into the biological, psychological and social factors that, in an interrelated manner, may explain the appearance, development, and treatment of depression.

Introduction

Depression is the principal cause of illness and disability in the world. The World Health Organization (WHO) has been issuing warnings about this pathology for years, given that it affects over 300 million people all over the world and is characterized by a high risk of suicide (the second most common cause of death in those aged between 15 and 29) [ World Health Organization (WHO), 2017 ]. Studies on the child population which use self-reports to evaluate severe symptoms of depression, specifically the Children's Depression Inventory (CDI, Kovacs, 1992 ) and the Children's Depression Scale (CDS, Lang and Tisher, 1978 ), have observed prevalence rates of, for example, 4% in Spain ( Demir et al., 2011 ; Bernaras et al., 2013 ), 6% in Finland ( Puura et al., 1997 ), 8% in Greece ( Kleftaras and Didaskalou, 2006 ), 10% in Australia ( McCabe et al., 2011 ), and 25% in Colombia ( Vinaccia et al., 2006 ). The main classifications of mental disorders are the Diagnostic and Statistical Manual of Mental Disorders, DSM-5 ( American Psychiatric Association, 2014 ), published by the American Psychiatric Association, which has become a key reference in clinical practice, and version 10 of the International Classification of Diseases (ICD-10, 1992), published by the WHO, which classifies and codifies all diseases, although initially its aim was to chart mortality rates. The new ICD-11 classification will be presented for approval to Member States at the World Health Assembly in May 2019, and is expected to come into effect on January 1, 2022 [ World Health Organization (WHO), 2018 ]. The two classifications offer different categorizations of depressive disorders, although certain similarities do exist, and it should be borne in mind also that both have been criticized for hardly distinguishing at all between child and adult depression.

Throughout history, there have been many different explanatory theories of depression. Biological and psychological theories are the ones which have mainly tried to explain the origin of this mental disorder. Biological theories have, from a variety of different perspectives, postulated that depression may occur due to noradrenalin deficits (e.g., Schildkraut, 1965 ; Narbona, 2014 ), endocrine disorders (e.g. Birmaher et al., 1996 ), sleep-related disorders (e.g., Sivertsen et al., 2014 ; Pariante, 2017 ), alterations in brain structure ( Whittle et al., 2014 ), or the influence of genetics ( Scourfield et al., 2003 ). Psychological theories have attempted to explain depression on the basis of psychoanalysis and, more specifically, in terms of attachment theories (e.g., Bowlby, 1976 ; Ainsworth et al., 1978 ; Blatt, 2004 ; Bigelow et al., 2018 ), behavioral models (e.g., Skinner, 1953 ; Ferster, 1966 ; Lewinsohn, 1975 ), cognitive models (e.g., Seligman, 1975 ; Abramson et al., 1978 ; Beck, 1987 ), the self-control model (e.g., Rehm, 1977 ; Rehm et al., 1979 ), interpersonal theory (e.g., Markowitz and Weissman, 1995 ; Milrod et al., 2014 ), stressful life events (e.g., Reinherz et al., 1993 ; Frank et al., 1994 ), and sociocultural models (e.g., Lorenzo-Blanco et al., 2012 ; Chang et al., 2013 ; Reeves et al., 2014 ).

Evaluating depression accurately has been another concern upon which psychology has focused, with attention being centered specifically around diagnosing this pathology in childhood and adolescence. Although many diagnostic instruments have been developed and validated, mainly for the adolescent and adult stages of life, it is still difficult to find diagnostic tests for evaluating depression in children. Preventing depression is another aspect to which much importance is attached by the World Health Organization (WHO) (2017) , which argues that school programs, interventions aimed at parents and specific exercises for the elderly population help reduce the prevalence of this pathology. Depression prevention programs do exist, but they are mainly targeted at adolescents and very few focus on children under the age of 10.

The treatment of depression is another aspect that should not be overlooked. In 2016, the WHO and the World Bank announced that investing in the treatment of depression and anxiety leads to four-fold returns, since these pathologies cost the global economy one trillion US dollars each year. Furthermore, they claimed that humanitarian emergencies and conflicts highlight a pressing need to broaden current therapeutic options. In this sense, the multiple different explanatory theories of depression have given rise to a plethora of different treatments (psychotherapeutic, behavioral, cognitive-behavioral, interpersonal, etc.) which are currently being analyzed with a high degree of precision and scientific rigor.

In light of the different aspects related to depression outlined above, the present study has the following aims: (1) To analyze the construct of depression offered by the two main mental disorder classifications (DSM-5 and ICD-10); (2) To provide an overview of the main explanatory theories of depression; (3) To outline the child and adolescent depression evaluation instruments most commonly used in scientific literature; (4) To provide a brief overview of child and adolescent depression prevention programs in the school environment; and (5) To describe the most scientifically rigorous and effective clinical treatments for this mental disorder.

The databases used for carrying out the searches were PubMed, PsycINFO, Web of Science, Scopus, Science Direct and Google Scholar, along with a range of different manuscripts. With the constant key word being depression, the search for information cross-referenced a series of other key words also, namely: childhood, adolescence, explanatory theories, etiology, evaluation instruments, prevention programs, and treatment. Searches were conducted for information published between 1970 and 2017.

Thus, first we describe the construct of depression and summarize the main explanatory theories. Next, we present the main evaluation instruments used to measure child and adolescent depression and report the results of a bibliographical review of prevention programs in school settings. Finally, we outline the main clinical treatments used nowadays to treat child and adolescent depression.

The Construct of Depression: DSM-5 and ICD-10

Depression features in both of the two most important global classifications: the DSM-5 and the ICD-10. As stated earlier in the introduction, the new ICD-11 classification will be presented for approval to Member States at the World Health Assembly in May 2019, and is expected to come into effect on January 1, 2022. The presentation of the new classification in 2019 will enable countries to plan for its implementation, prepare the necessary translations and train professionals accordingly [ World Health Organization (WHO), 2018 ]. In texts published by WHO collaborators ( Luciano, 2017 ), it has been suggested that the ICD-11 will include mood disorders within the mental and behavioral disorder category. However, until the final version is published, this information cannot be fully verified.

The two classifications (DSM-5 e IDC-10) offer different categorizations of depressive disorders, as shown in Table 1 . The WHO includes depressive disorders in the mood disorders category, although this review only focuses on Sections F32, F33, F34, and F38, which include the most frequent depressive disorders and which, in turn, contain subsections that will be further specified later on.

Table 1 . Depressive disorders according to the DSM-5 and the ICD-10.

According to the DSM-5, depressive disorders all have one common feature, namely the presence of sad, empty or irritable mood, accompanied by somatic and cognitive changes that significantly affect the individual's capacity to function (DSM-5). They may become a serious health problem if allowed to persist for long periods of time and occur with a moderate-to-severe degree of intensity. One important consequence of depression is the risk of suicide, which is, according the World Health Organization (WHO) (2017) , the second most common cause of death among young people aged between 15 and 29.

The main novelty offered by the DSM-5 in its section on depressive disorders is the introduction to Disruptive mood dysregulation disorder (which should not be diagnosed before the age of 6 or after the age of 18). This disorder is characterized by severe recurrent temper outbursts manifested verbally (e.g., verbal rages) and/or behaviorally (e.g., physical aggression toward people or property). These outbursts often occur as the result of frustration and in order to be considered a diagnostic criterion must be inconsistent with the individual's developmental level, occur three or more times per week for at least a year in a number of different settings (at home, at school, etc.) and be severe in at least one of these. This disorder was added to the DSM-5 due to doubts arising in relation to how to classify and treat children presenting with chronic persistent irritability as opposed to other related disorders, specifically pediatric bipolar disorder. The prevalence of this disorder has been estimated at between 2 and 5%, with male children and teenage boys being more likely to suffer from it than their female counterparts.

Major Depressive Disorder

Major depressive disorder is characterized by a depressed mood most of the day, nearly every day, although in children and adolescents this mood may be irritable rather than depressed. The disorder causes a markedly diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day, significant weight loss or gain, insomnia or hypersomnia, psychomotor agitation or retardation, fatigue or loss of energy, feelings of worthlessness, or excessive or inappropriate guilt, diminished ability to think or concentrate, recurrent thoughts of death, recurrent suicidal ideation without a specific plan, or a suicide attempt or a specific plan for committing suicide. These symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning. In the United States, the 12-month prevalence is ~7%, although it is three times higher among those aged between 18 and 29 than among those aged 60 or over. Moreover, the prevalence rates for women are ~1.5–3 times higher than for men.

Persistent Depressive Disorder (Dysthymia)

Persistent depressive disorder (dysthymia) is a consolidation of DSM-5-defined chronic major depressive disorder and dysthymic disorder, and is characterized by a depressed mood for most of the day, for more days than not, for at least 2 years. In children and adolescents, mood can be irritable and duration must be at least 1 year. The DSM-5 specifies that patients presenting symptoms that comply with the diagnostic criteria for major depressive disorder for 2 years should also be diagnosed with persistent depressive disorder. When the individual in question is experiencing a depressive mood episode, they must also present at least two of the following symptoms: poor appetite or overeating, insomnia or hypersomnia, low energy or fatigue, low self-esteem, poor concentration, or difficulty making decisions and feelings of hopelessness. The prevalence of this disorder in the United States is 0.5%.

Premenstrual Dysphoric Disorder

The diagnostic criterion for premenstrual dysphoric disorder states that, in the majority of menstrual cycles, at least five symptoms must be present during the last week before the start of menstruation, and individuals should start to feel better a few days later, with all symptoms disappearing completely or almost completely during the week after menstruation. The most important characteristics of this disorder are affective lability, intense irritability or anger, or increased interpersonal conflicts, markedly depressed mood and/or over-excitation, and symptoms of anxiety which may be accompanied by behavioral and somatic symptoms. Symptoms must be present during most menstrual cycles during the past year and must negatively affect occupational and social functioning. The most rigorous estimations of the prevalence of this disorder claim that 1.8% of women comply with the criterion but have no functional impairment, while 1.3% comply with the criterion and suffer functional impairment and other concomitant symptoms of another mental disorder.

Substance/Medication-Induced Depressive Disorder

Substance/medication-induced depressive disorder is characterized by the presence of the symptoms of a depressive disorder, such as major depressive disorder, induced by the consumption, inhalation or injection of a substance, with said symptoms persisting after the physiological effects or the effects of intoxication or withdrawal have disappeared. Some medication may generate depressive symptoms, which is why it is important to determine whether the symptoms were actually induced by the taking of the drug or whether the depressive disorder simply appeared during the period in which the medication was being taken. The prevalence of this disorder in the United States is 0.26%.

Depressive Disorder Due to Another Medical Condition

Depressive disorder due to another medical condition is characterized by the appearance of a depressed mood and a markedly diminished interest or pleasure in all activities within the context of another medical condition. The DSM-5 offers no information about the prevalence of this disorder.

The category Other specified depressive disorder is used when the symptoms characteristic of a depressive disorder appear and cause significant distress or impairment in social, occupational or other areas of functioning but do not comply with all the criteria of any depressive disorder, and the clinician opts to communicate the specific reason for this. In the Other unspecified depressive disorder category , on the other hand, the difference is that the clinician prefers not to specify the reason why the presentation fails to comply with all the criteria of a specific disorder and includes presentations about which there is insufficient information for giving a more specific diagnosis.

In the ICD-10, depressive disorders are included within the mood disorders category. The following disorders are analyzed below: single depressive episode, recurrent depressive disorder, and persistent mood (affective) disorders.

Single Depressive Episode

The classification Single depressive episode distinguishes between depressive episodes of varying severity: mild, moderate, and severe without psychotic symptoms. Characteristics common to all of them include lowering of mood, reduction of energy, and decrease in daily activity. There is a loss of interest in formerly pleasurable pursuits, a decrease in the capacity for concentration, and an increase in tiredness, even during activities requiring minimum effort. Changes occur in appetite, sleep is disturbed, self-esteem and self-confidence drop, ideas of guilt or worthlessness are present and the symptoms vary little from day to day. In its mildest form, two or three of the symptoms described above may be present, and the patient is able to continue with most of their daily activities. When the episode is moderate, four or more of the symptoms are usually present and the patient is likely to have difficulty continuing with ordinary activities. In its most severe form, several of the symptoms are marked and distressing, typically loss of self-esteem and ideas of worthlessness or guilt. Suicidal thoughts and acts are common and a number of somatic symptoms are usually present. If the depressive episode is with psychotic symptoms, it is characterized by the presence of hallucinations, delusions, psychomotor retardation, or stupor so severe that ordinary social activities are impossible; there may be danger to life from suicide, dehydration, or starvation.

Recurrent Depressive Disorder

Recurrent depressive disorder is characterized by repeated episodes of depression similar to those described above for single depressive episodes without mania. There may be brief episodes of mild mood elevation and over activity (hypomania) immediately after a depressive episode, sometimes precipitated by antidepressant treatment. The more severe forms of this disorder are very similar to manic-depressive depression, melancholia, vital depression, and endogenous depression. The first episode may occur at any age, from childhood to old age. The onset may be either acute or insidious and can last from a few weeks to many months. Recurrent depressive disorder can be mild or moderate, but in neither of these is there any history of mania. This section also includes recurrent depressive disorder currently in remission, in which the patient may have had two or more depressive episodes in the past, but has been free from depressive symptoms for several months.

Persistent Mood [Affective] Disorders

Persistent mood [affective] disorders are persistent and usually fluctuating disorders in which the majority of episodes are not sufficiently severe to warrant being diagnosed as hypomanic or mild depressive episodes. Since they last for many years and affect the patient's normal life, they involve considerable distress and disability. This section also includes cyclothymia and dysthymia. Cyclothymia is a persistent instability of mood involving numerous periods of depression and mild elation, none of which are sufficiently prolonged to justify a diagnosis of bipolar affective disorder or recurrent depressive disorder. This disorder is frequently found among the relatives of patients with bipolar affective disorder and some patients with cyclothymia eventually develop bipolar affective disorder. For its part, dysthymia is a chronic depression of mood, lasting at least several years, which is not sufficiently severe, or in which individual episodes are not sufficiently prolonged, to justify a diagnosis of mild, moderate, or severe recurrent depressive disorder.

Other Mood (Affective) Disorders

Finally, other mood (affective) disorders include any mood disorders that do not fall into the categories described above because they are not of sufficient severity or duration. They may be single, recurrent (brief), or specified episodes.

The manifestations and symptoms of depression vary in accordance with age and level of development. However, it is clear that the DSM-5 and the ICD-10 do not distinguish between adult and child depression, although by including disruptive mood dysregulation disorder, the DSM-5 does take into account the fact that children and young people aged between 7 and 18 may express their distress in other ways, through chronic, severe, and recurrent irritability manifested verbally and/or behaviorally. Similarly, major depressive disorder specifies that in children the mood may be irritable rather than depressed. However, no distinctions of this kind are found in the ICD-10, an absence which may lead to the faulty inference that the characteristics of child and adolescent depression are similar to those of adult depression.

Explanatory Theories of Depression

Depressive disorders cannot be explained by any single theory, since many different variables are involved in their onset and persistence. The principal biological and psychological theories were therefore taken as the main references for this section. Subsequently, the contributions made by each of these theories regarding depression were studied by conducting searches in PubMed, Web of Science, Science direct, and Google Scholar. With the constant key words being depression, child depression and adolescent depression, the search for information cross-referenced a series of other key words also in accordance with the specific theory in question. Due to the importance of some seminal works in relation to the development of psychological theories of depression, certain authors have remained key references for decades. A total of 64 bibliographical references were used. The following is a summary of the various explanations for the onset of depression, according to the different theoretical frameworks.

Biological Theories

If a mood disorder cannot be explained by family history or stressful life events, then it may be that the child or adolescent in question is suffering from a neurological disease. In such a case, depressive symptoms may manifest early in children and adolescents as epileptic syndromes, sleep disorders, chronic recurrent cephalalgias, several neurometabolic diseases, and intracranial tumors ( Narbona, 2014 ).

Noradrenalin Deficit

Serotonin is a monoamine linked to adrenaline, norepinephrine, and dopamine which plays a key role, particularly in the brain, since it is involved in important life regulation functions (appetite, sleep, memory, learning, temperature regulation, and social behaviors, etc.), as well as many psychiatric pathologies ( Nique et al., 2014 ). Serotonin modulates neuroplasticity, particularly during the early years of life, and dysfunctions in both systems contribute to the physiopathology of depression ( Kraus et al., 2017 ). MRI tests in animals have revealed that a reduction in neuron density and size, as well as a reduction in hippocampal volume among depressive patients may be due to serotonergic neuroplasticity changes. Branchi (2011) , however, argues that improving serotonin levels may increase the likelihood of both developing and recovering from the psychopathology, and underscores the role played by the social environment in this process. In this sense, Curley et al. (2011) point out that the quality of the social environment may influence the development and activity of neural systems, which in turn have an impact on behavioral, physiological, and emotional responses.

Endocrine Alterations

Age-related changes and the presence of biological risk factors, including endocrine, inflammatory or immune, cardiovascular and neuroanatomical factors, make people more vulnerable to depression ( Clarke and Currie, 2009 ). Indeed, some studies suggest that depression may be linked to endocrine alterations: nocturnal cortisol secretions ( Birmaher et al., 1996 ), nocturnal growth hormone secretion ( Ryan et al., 1994 ), thyroid stimulating hormone secretion ( Puig-Antich, 1987 ), melatonin and prolactin secretions ( Waterman et al., 1994 ), high cortisol levels ( Herane-Vives et al., 2018 ), or decreased growth hormone production ( Dahl et al., 2000 ). Puberty and the accompanying hormonal and physical changes require special attention because it has been proposed that they could be associated with an increased incidence of depression ( Reinecke and Simons, 2005 ).

Sleep Disorders

Sleep problems are often associated with situations of social deprivation, unemployment, or stressful life events (divorce, bad life habits, or poor working conditions) ( Garbarino et al., 2016 ). It also seems, however, that sleep disorders are linked to the development of depression. This relationship occurs as a result of how insufficient sleep affects the hippocampus, heightening neural sensitivity to excitotoxic insult and vulnerability to neurotoxic challenges, resulting in a net decrease in gray matter in the hippocampus in the left orbitofrontal cortex ( Novati et al., 2012 ).

For their part, Franzen and Buysse (2008) state that bidirectional associations between sleep disturbances (particularly insomnia) and depression make it more difficult to distinguish cause-effect relations between them. It is therefore unclear whether depression causes sleep disturbances or whether chronic sleep disturbances lead to the appearance of depression. What does seem clear, however, is that treating sleep disturbances (both insomnia and hypersomnia) may help reduce the severity of depression and accelerate recovery ( Franzen and Buysse, 2008 ).

Longitudinal studies have identified insomnia as a risk factor for the onset or recurrence of depression in young people and adults ( Sivertsen et al., 2014 ). In comparison with the non-clinical population, depressed children and adolescents report both trouble sleeping and longer sleep duration ( Accardo et al., 2012 ).

For their part, Foley and Weinraub (2017) observed that, among preadolescent girls, early and later sleep problems directly or indirectly predicted a wide variety of social and emotional adjustment disorders (depressive symptoms, low school competence, poor emotion regulation, and risk-taking behaviors).

Altered Neurotransmission

Studies conducted over the past 20 years have shown that increased inflammation and hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis may explain major depression ( Pariante, 2017 ). Some of the pathophysiological mechanisms of depression include altered neurotransmission, HPA axis abnormalities involved in chronic stress, inflammation, reduced neuroplasticity, and network dysfunction ( Dean and Keshavan, 2017 ). Other studies report alterations in the brain structure: smaller hippocampus, amygdala, and frontal lobe ( Whittle et al., 2014 ). Nevertheless, the underlying molecular and clinical mechanisms have yet to be discovered ( Pariante, 2017 ). Major depressive disorder in children and adolescents has been associated with increased intracortical facilitation, a direct neurophysiological result of excessive glutamatergic neurotransmission. However, contrary to the findings in adults with depression, no deficits in cortical inhibition were found in children and adolescents with major depressive disorder ( Croarkin et al., 2013 ).

Genetic Factors

Other studies have highlighted the importance of genetics in the onset of depression (40%) ( Scourfield et al., 2003 ). It is important to recognize that a genetic predisposition to an excessive amygdala response to stress, or a hyperactive HPA axis (moderate hyperphenylalaninemia) due to stress during early childhood may trigger an excessive effect or alter an otherwise healthy psychological system ( Dean and Keshavan, 2017 ). Kaufman et al. (2018) support a potential role for genes related to the homeobox 2 gene of Orthodenticle (OTX2) and to the OTX2-related gene in the physiopathology of stress-related depressive disorders in children. Furthermore, genetic anomalies in serotonergic transmission have been linked to depression. The serotonin-linked polymorphic region (5-HTTLPR) is a degenerate repeat in the gene which codes for the serotonin transporter (SLC6A4). The s/s genotype of this region is associated with a reduction serotonin expression, in turn linked to greater vulnerability to depression ( Caspi et al., 2010 ).

For their part, Oken et al. (2015) claim that psychological disturbances may trigger changes in physiological parameters, such as DNA transcription, or may result in epigenetic modifications which alter the sensitivity of the neurotransmitter receptor.

Psychological Theories

This section outlines the different psychological theories which have attempted to explain the phenomenon of depression. Depression is a highly complex disorder influenced by multiple factors, and it is clear that no single theory can fully explain its etiology and persistence. It is likely that a more eclectic outlook must be adopted if we are to make any progress in determining the origin, development, and maintenance of this pathology.

Attachment-Informed Theories

Attachment theory was the term used by Bowlby (1976) to refer to a specific conceptualization of human beings' propensity to establish strong and long-lasting affective ties with other people. Bowlby (1969 , 1973) proposes that consistency, nurturance, protectiveness, and responsiveness in early interactions with caregivers contribute to the development of schemas or mental representations about the relationships of oneself with others, and that these schemas serve as models for later relationships. Bowlby's ethological model of attachment postulates that vulnerability to depression stems from early experiences which failed to satisfy the child's need for security, care and comfort, as well as from the current state of their intimate relations ( Bowlby, 1969 , 1973 , 1988 ). Adverse early experiences can contribute to disturbances in early attachments, which may be associated with vulnerability for depression ( Cummings and Cicchetti, 1990 ; Joiner and Coyne, 1999 ). Associations between insecure attachment among children and negative self-concept, sensitivity to loss, and an increased risk of depression in childhood and adolescence have been reported ( Armsden et al., 1990 ; Koback et al., 1991 ; Kenny et al., 1993 ; Roelofs et al., 2006 ; Allen et al., 2007 ; Chorot et al., 2017 ). Relationships between secure attachment and depression seem also to be mediated by the development of maladaptive beliefs or schemas ( Roberts et al., 1996 ; Reinecke and Rogers, 2001 ).

Thus, attachment theory has become a useful construct for conceptualizing many different disorders and provides valuable information for the treatment of depression ( Reinecke and Simons, 2005 ).

Ainsworth described three attachment styles, in accordance with the child's response to the presence, absence, and return of the mother (or main caregiver): secure, anxious-avoidant, and anxious-resistant ( Ainsworth et al., 1978 ). The least secure attachment styles may give rise to traumatic experiences during childhood, which in turn may result in the appearance of depressive symptoms.

Similarly, Hesse and Main (2000) argued that the central mechanism regulating infant emotional survival was proximity to attachment figures, i.e., those figures who help the child cope with frightening situations. Using Ainsworth's strange situation procedure, Main (1996) found that abused children engaged in more disorganized, disruptive, aggressive, and dissociative behaviors during both childhood and adolescence. Main (1996) also found that many people with clinical disorders have insecure attachment and that psychological-disoriented and disorganized children are more vulnerable.

For his part, Blatt (2004) explored the nature of depression and the life experiences which contribute to its appearance in more depth, identifying two types of depression which, despite a common set of symptoms, nevertheless have very different roots: (1) anaclitic depression, which arises from feelings of loneliness and abandonment; and (2) introjective depression, which stems from feelings of failure and worthlessness. This distinction is consistent with psychoanalytical formulations, since it considers defenselessness/dependency and desperation/negative feelings about oneself to be two key issues in depression.

Brazelton et al. (1975) found that at age 3 weeks, babies demonstrate a series of interactive behaviors during face-to-face mother-infant interactions. These behaviors were not found to be present in more disturbed interactions, which may trigger infant anxiety.

In a longitudinal study focusing on the relationship between risk of maternal depression and infant attachment behavior, Bigelow et al. (2018) analyzed babies at age 6 weeks, 4 and 12 months, finding that mothers at risk of depression soon after the birth of their child may have difficulty responding appropriately to their infant's attachment needs, giving rise to disorganized attachment, with all the psychological consequences that this may involve. Similarly, Beeghly et al. (2017) found that among infants aged between 2 and 18 months, greater maternal social support was linked to decreasing levels of maternal depressive symptoms over time, and that boys were more vulnerable than girls to early caregiving risks such as maternal depression, with negative consequences for mother-child attachment security during toddlerhood.

Authors such as Shedler and Westen (2004) have attempted to find solutions to the problems arising in relation to the DSM diagnostic categories, developing the Shedler Westen Assessment Procedure (SWAP-200) to capture the wealth and complexity of clinical personality descriptions and to identify possible diagnostic criteria which may better define personality disorders.

For their part, Ju and Lee (2018) argue that peer attachment reduces depression levels in at-risk children, and also highlight the curative aspect of attachment between adolescent peers.

Behavioral Models

The first explanations proposed by this model argued that depression occurs due to the lack of reinforcement of previously reinforced behaviors ( Skinner, 1953 ; Ferster, 1966 ; Lewinsohn, 1975 ), an excess of avoidance behaviors and the lack of positive reinforcement ( Ferster, 1966 ) or the loss of efficiency of positive reinforcements ( Costello, 1972 ). A child with depression initially receives a lot of attention from his social environment (family, friends…), and behaviors such as crying, complaints or expressions of guilt are reinforced. When these depressive behaviors increase, the relationship with the child becomes aversive, and the people who used to accompany the child avoid being with him, which contributes to aggravating his depression ( Lewinsohn, 1974 ). Low reinforcement rates can be explained by maternal rejection and lower parental support ( Simons and Miller, 1987 ), by a lower rate of reinforcement offered to their children by mothers of depressed children ( Cole and Rehm, 1986 ), or by low social competence ( Shah and Morgan, 1996 ).

Depression is mainly a learned phenomenon, related to negative interactions between the individual and his or her environment (e.g., low rate of reinforcement or unsatisfactory social relations). These interactions are influenced by cognitions, behaviors and emotions ( Antonuccio et al., 1989 ).

Cognitive Models

The attributional reformulation of the learned helplessness model ( Abramson et al., 1978 ) and Beck's cognitive theory ( Beck et al., 1979 ) are the two most widely-accepted cognitive theories among contemporary cognitive models of depression ( Vázquez et al., 2000 ).

Learned helplessness is related to cognitive attributions, which can be specific/global, internal/external, and stable/unstable ( Hiroto and Seligman, 1975 ; Abramson et al., 1978 ). Global attribution implies the conviction that the negative event is contextually consistent rather than specific to a particular circumstance. Internal attribution is related to the belief that the aversive situation occurs due to individual conditions rather than to external circumstances. Stable attribution is the belief that the aversive situation is unchanging over time ( Miller and Seligman, 1975 ). People prone to depression attribute negative events to internal, stable and global factors and make external, unstable, and specific attributions for success ( Abramson et al., 1978 ; Peterson et al., 1993 ), a cognitive style also present in children and adolescents with depression ( Gladstone and Kaslow, 1995 ).

The Information Processing model ( Beck, 1967 ; Beck et al., 1979 ) postulates that depression is caused by particular stresses that evoke the activation of a schema that screens and codes the depressed individual's experience in a negative fashion ( Ingram, 1984 , p. 443). Beck suggests that this distortion of reality is expressed in three areas, which he calls the “cognitive triad”: negative views about oneself, the world and the future as a result of their learning history ( Beck et al., 1983 ). These beliefs are triggered by life events which hold special meaning for the subject ( Beck and Alford, 2009 ).

Self-Control Model

This theory assumes that depression is due to deficits in the self-control process, which consists of three phases: self-monitoring, self-evaluation, and self-administration of consequences ( Rehm, 1977 ; Rehm et al., 1979 ). In the self-monitoring phase, individuals attend only to negative events and tend to recognize only immediate, short-term consequences. In the self-evaluation phase, depressed individuals establish unrealistic evaluation criteria and inaccurately attribute their successes and failures. If self-evaluation is negative, in the self-administration of consequences phase the individual tends to engage very little in self-reinforcement and very frequently in self-punishment.

Both Rehm's self-control model ( Rehm, 1977 ) and Bandura's conception of child depression ( Bandura, 1977 ) assume that children internalize external control guidelines. These guidelines are related to family interaction patterns and both may contribute to the etiology or persistence of depression in children.

In a study conducted with children aged between 8 and 12 years, Kaslow et al. (1988) found that depressed children had a more depressive attributional style and more self-control problems.

Interpersonal Theory

This model, which is closely linked to attachment theories, aims to identify and find solutions for an individual's problems with depression in their interpersonal functioning. It suggests that the difficulties experienced are linked to unresolved grief, interpersonal disputes, transition roles and interpersonal deficits ( Markowitz and Weissman, 1995 ).

Milrod et al. (2014) argue that pathological attachment during early childhood has serious consequences for adults' ability to experience and internalize positive relationships.

Similarly, various different studies have highlighted the fact that one of the variables that best predicts depression in children is peer relations ( Bernaras et al., 2013 ; Garaigordobil et al., 2017 ).

Stressful Life Events

Studies focusing on the adult population have reported that between 60 and 70% of depressed adults experienced one or more stressful events during the year prior to the onset of major depression ( Frank et al., 1994 ). In children and adolescents, modest associations have been found between stressful life events and depression ( Williamson et al., 1995 ). For their part, Shapero et al. (2013) found that people who had suffered severe emotional abuse during childhood experienced higher levels of depressive symptoms when faced with current stressors. Sokratous et al. (2013) argue that the onset of depression is not only triggered by major stressful events, but rather, minor life events (dropping out of school, your father losing his job, financial difficulties in the family, losing friends, or the illness of a family member) may also influence the appearance of depressive symptoms.

Events such as the loss of loved ones, divorce of parents, mourning or exposure to suicide (either individually or collectively) have all been associated with the onset of depression in childhood ( Reinherz et al., 1993 ). Factors such as a history of additional interpersonal losses, added stress factors, a history of psychiatric problems in the family and prior psychopathology (including depression) increase the risk of depression in adolescents ( Brent et al., 1993 ). Birmaher et al. (1996) found that prior research into stressful life events in relation to early-onset depression had been based on data obtained from self-reports, making it difficult to determine the causal relationship, since events may be both the cause and consequence of depression.

However, not everyone exposed to this kind of traumatic experience becomes depressed. Personality and the moment at which events occur are both involved in the relationship between depression and stressful life events, although biological factors such as serotonergic functioning ( Caspi et al., 2010 ) also exert an influence.

Sociocultural Models

These models postulate that cultural variables are responsible for the appearance of depressive symptoms. These variables are mainly acculturation and enculturation. In acculturation, structural changes are observed (economic, political, and demographic), along with changes in people's psychological behavior ( Casullo, 2001 ). Some studies link increased suicide rates with economic recession ( Chang et al., 2013 ; Reeves et al., 2014 ). Enculturation occurs when the older generation invites, induces or forces the younger generation to adopt traditional mindsets and behaviors.

In an attempt to better understand the influence of culture and family on depressive symptoms, Lorenzo-Blanco et al. (2012) tested an acculturation, cultural values and family functioning model with Hispanic students born in the United States. The results revealed that both family conflict and family cohesion were related to depressive symptoms.

Another study carried out with girls aged 7–10 years ( Evans et al., 2013 ) observed that internalizing an unrealistically thin ideal body predicted disordered eating attitudes through body dissatisfaction, dietary restraint and depression.

Finally, the importance of family interactions in the onset of depressive symptoms cannot be overlooked. Parenting style has been identified as a key factor in children's and adolescents' psychosocial adjustment ( Lengua and Kovacs, 2005 ). Parental behavior has been studied from two different perspectives: warmth and control. Warmth is linked to aspects such as engagement and expression of affection, respect, and positive concern by parents and/or principal caregivers ( Rohner and Khaleque, 2003 ). In this sense, prior studies have identified a significant association between parental warmth and positive adjustment among adolescents ( Barber et al., 2005 ; Heider et al., 2006 ). Rohner and Khaleque (2003) argue that children's psychological adjustment is closely linked to their perception of being accepted or rejected by their principal caregivers, and other studies have found that weaker support from parents is associated with higher levels of depression and anxiety among adolescents ( Yap et al., 2014 ).

Similarly, Jaureguizar et al. (2018) found that a low level of perceived parental warmth was linked to high levels of clinical and school maladjustment, and that the weaker the parental control, the greater the clinical maladjustment. These authors also found that young people with negligent mothers and authoritarian fathers had higher levels of clinical maladjustment.

In short, according to the different theories, depression may be due to (1) biological reasons; (2) insecure attachment; (3) lack of reinforcement of previously-reinforced behaviors; (4) negative interpersonal relations and relations with one's environment and the resulting negative consequences; (5) attributions made by individuals about themselves, the world and their future; and (6) sociocultural changes. It is likely that no single theory can fully explain the genesis and persistence of depression, although currently, negative interpersonal relations and relations with one's environment and sociocultural changes (economic, political, and demographic) may explain the observed increase in the prevalence of depression.

Evaluation Instruments

Many different evaluation instruments can be used to measure child and adolescent depression. Tables 2 , 3 outline the ones most commonly used in scientific literature. Table 2 summarizes the main self-administered tests that specifically measure child and adolescent depression, while Table 3 presents tests that measure child and adolescent depression among other aspects (i.e., broader or more general tests). Finally, Table 4 summarizes the main hetero-administered psychometric tests for assessing this pathology.

Table 2 . Self-administered psychometric tests designed specifically for evaluating child and adolescent depression.

Table 3 . Self-administered general psychometric tests which, among other variables, also assess child and adolescent depression.

Table 4 . Hetero-administered psychometric tests for assessing child and adolescent depression.

As shown in the tables above, there are several self-administered instruments that can be used with children from age 6 to 7 onwards, although their duration should be taken into consideration in order to avoid overtiring subjects. While it is clear that an effort has been made to design shorter measures (compare, for example, the 66 items of the CDS with the 16 items of the longest version of the KADS), the duration of the test should not be the only aspect taken into account when selecting an evaluation instrument.

One of the most widely used instruments to measure child depression in the scientific literature is the Children's Depression Inventory-CDI ( Kovacs, 1985 ), which is based on the Beck Depression Inventory-BDI ( Beck and Beamesderfer, 1974 ). Thus, it is based on Beck's cognitive theory of depression. Following this same theoretical line, the Children's Depression Scale-CDS ( Lang and Tisher, 1978 ) was designed, but in this case, this instrument was not created based on another instrument previously designed for adult population (as in the case of the CDI), but instead from its beginnings, it was conceived exclusively to assess child depression. Chorpita et al. (2005) explain that the CDI measures a broader construct of negative affectivity rather than depression as a separate construct, and that it may be useful for screening for trait dimensions or personality features, whereas other instruments, such as the Revised Child Anxiety and Depression Scale-RCADS ( Chorpita et al., 2000 ), measure a specific clinical syndrome.

Table 2 describes many other instruments that are very useful as screening tests for depression and depressive disorder, such as the Center for Epidemiological Studies Depression Scale for Children-CES-DC ( Weissman et al., 1980 ) (based on the Center for Epidemiological Studies Depression Scale for Adults, CES-D; Radloff, 1977 ), the Mood and Feelings Questionnaire-MFQ ( Angold et al., 1995 ), or the Depression Self-Rating Scale for Children-DSRS ( Birleson, 1981 ). This last one, for example, is useful to measure moderate to severe depression in childhood and is based on the operational definition of depressive disorder, that is, a specific affective-behavior pattern that implies an impairment of a child's or adolescent's ability to function effectively in his/her environment ( Birleson, 1981 ).

The cognitive and affective component of depression is the one that is most present in the instruments described in Table 2 . In fact, for example, the Short Mood and Feelings Questionnaire (SMFQ) includes the cognitive and affective items from the original MFQ item pool, in addition to some items related to tiredness, restlessness, and poor concentration ( Angold et al., 1995 ). In the SMFQ, more than half of the items from the MFQ were removed, and even so, high correlations between the MFQ and the SMFQ were found ( Angold and Costello, 1995 ), which may be indicating that the really important items were the cognitive and affective items that were maintained. Reynolds et al. (1985) defended that children could accurately report their cognitive and affective characteristics, so “ if one wishes to know how a child feels, ask the child” ( Reynolds et al., 1985 , p. 524).

Depending on the specific aim of the evaluation or research study, a broader diagnostic measure, such as those outlined in Table 3 , may also provide valuable information. Finally, it is worth noting that only two hetero-administered instruments were found for teachers, with all others being clearly oriented toward the clinical field. In this sense, special emphasis should be placed on the need to develop valid and reliable instruments for teachers, since they may be key agents for detecting symptoms among their students. While it is important to train teachers in this sense, it is also important to provide them with instruments to help them assess their students. The instruments that are currently available have produced very different results as regards their correlation with students' self-reported symptoms, although in general, teachers tend to underestimate their students' depressive symptoms ( Jaureguizar et al., 2017 ).

Child and Adolescent Depression Prevention Programs in the School Environment

Extant scientific literature was reviewed in order to summarize the main depression prevention programs for children and adolescents in school settings. The databases used for conducting the searches were PubMed, PsycINFO, Web of Science, Scopus, Science Direct, and Google Scholar, along with a range of different manuscripts. With the constant key word being depression, the search for information cross-referenced a series of other key words also, namely: “child* OR adolescent*,” “prevent*program,” and “school OR school-based.” Searches were conducted for information published between January 1, 1970 and December 31, 2017.

First, articles were screened (i.e., their titles and abstracts were read and a decision was made regarding their possible interest for the review study). The inclusion criteria were that the study analyzed all the research subjects of the review study (depression, childhood, or adolescence and prevention programs in school settings), that study participants were aged between 6 and 18, that the study was published in a peer-reviewed journal and that it was written in either English or Spanish. Review studies and their references were also analyzed. Studies focusing mainly on psychiatric disorders other than depression were excluded.

Finally, 39 studies were selected for the review, which explored 8 prevention programs that are outlined in Table 5 . In general terms, child depression prevention programs are divided into two main categories: universal programs for the general population, and targeted programs aimed at either the at-risk population or those with a clear diagnosis. Although scientific literature reports that targeted programs obtain better outcomes than universal ones, the latter type nevertheless offer certain advantages, since they reach a larger number of people without the social stigma attached to having been specially selected ( Roberts et al., 2003 ; Huggins et al., 2008 ). Thus, the ideal context for instigating universal child depression prevention programs is the school environment.

Table 5 . School-based child and adolescent depression prevention programs.

Table 5 outlines the most important child depression prevention programs carried out in the school context. They are all cognitive-behavioral programs implemented either by psychologists or teachers with specialist training, consisting of between 8 and 15 sessions. Only a few universal programs designed to prevent the symptoms of depression focus on younger children, since most are targeted mainly at the adolescent population ( Gillham et al., 1995 ; Barrett and Turner, 2001 ; Farrell and Barrett, 2007 ; Essau et al., 2012 ; Gallegos et al., 2013 ; Rooney et al., 2013 ). Indeed, in the present review, only four universal child depression prevention programs were found that were aimed at a younger age group (between 8 and 12): the Penn Resiliency Program, FRIENDS, the Aussie Optimism Program, and FORTIUS (see Table 5 ).

As shown in the table, the results of the various programs outlined are not particularly positive, since on many occasions the effects (if there are any) are not sustained over time or are limited in scope (being dependent on who applies the program or on the sex of the participant, etc.). Nor is the distinction between universal and targeted programs particularly clear as regards their effects, since although targeted programs may initially appear to be more effective, their impact is not found to be sustained in the long term.

Greenberg et al. (2001) argue that researchers should explain whether their prevention programs focus on one or various microsystems (basically family and school), mesosystems or exosystems, etc. (following the model described by Bronfenbrenner, 1979 ), or are centered exclusively on the individual and his or her environment, since this will influence the results reported. These same authors conclude that programs focused exclusively on children and adolescents themselves are less effective than those which aim to “educate” subjects and bring about positive changes in their family and school environments.

As Calear and Christensen (2010) point out in their review, some authors suggest that the fact that some targeted programs are aimed at people with high levels of depressive symptoms entails a broader range of possibilities for change; however, this does not help us understand why these changes are not sustained over time. Thus, further research is required in this field in order to identify what specific components of those programs observed to be effective actually have a positive impact on the level of depressive symptoms, how these programs are developed, who implements them and whether or not their effects are sustained in the short, medium, and long term.

Clinical Treatments for Depression

In order to draft this section, a search was conducted for the most commonly-used therapies with proven efficacy for treating depression. The databases used were PubMed, Web of Science, Science direct, and Google Scholar. The key words used in the search were treatment, depression, child depression, and adolescent depression. A total of 30 bibliographic references were used in the drafting of this summary, including the major contribution made by The American Psychological Association's Society of Clinical Psychology ( American Psychological Association, Society of Clinical Psychology (APA), 2017 ) regarding the most effective psychological methods for treating depression.

Although the World Health Organization (WHO) (2017) claims that prevention programs reduce the risk of suffering from depression, it has yet to be ascertained what type of programs and what contents are the most effective. The WHO also states that there are effective treatments for moderate and severe depression, such as psychological treatments (behavioral activation, cognitive behavioral therapy, and interpersonal psychotherapy) and antidepressant drugs (although it also warns of adverse effects), as well as psychosocial treatments for cases of mild depression. Moreover, a study conducted with adolescents by Foster and Mohler-Kuo (2018) found that the combination of cognitive-behavioral therapy and fluoxetine (antidepressant drug) was more effective than drug therapy alone.

The efficacy of treatment with antidepressants has been called into question for some years now. Iruela et al. (2009) claim that tricyclic antidepressants (imipramine, clomipramine, amitriptyline) are not recommended in childhood and adolescence since no benefits other than the placebo effect have been proven and furthermore, they generate major side effects due to their cardiotoxicity. They are therefore particularly dangerous in cases of attempted suicide. These same authors also advise against the use of monoamine oxidase inhibitors (MAOIs) due to dietary restrictions, interactions with other medication and the lack of clinical trials with sufficiently large groups which guarantee their efficacy. SSRIs or serotonergic antidepressants are the ones that have been most extensively studied in this population. The most effective is fluoxetine, the use of which is recommended in association with cognitive psychotherapy for cases of moderate and severe child depression.

On another hand, Wagner and Ambrosini (2001) analyzed the efficacy of pharmacological treatment in children and adolescents and stated that, at best, antidepressant therapy for depressed youth was moderately effective. Peiró et al. (2005) indicate that there is a great debate about the safety of selective serotonin reuptake inhibitors (SSRIs) in childhood. SSRIs, except for fluoxetine in the United States, have never been authorized by any agency for use in children or adolescents, mainly because of the risk of suicide to which they are associated. In 1991, the Food and Drugs Administration (FDA) claimed that there was insufficient evidence to confirm a causal association between SSRIs and suicide. Vitiello and Ordoñez (2016) conducted a systematic review of the topic and found more than 30 controlled clinical trials in adolescents and a few studies with children. Most studies found no differences between studies that administered drugs and those that used placebo, but they did find fluoxetine to be effective. They noted that antidepressants increased the risk of suicide (suicidal ideation and behaviors) compared to studies that had used placebos. The authors recommend using antidepressants with caution in young people and limiting them to patients with moderate to severe depression, especially when psychosocial interventions are not effective or are not feasible.

As regards the effectiveness of psychodynamic treatments, Luyten and Blatt (2012) advocate the inclusion of psychoanalytic therapy in the treatment of child, adolescent and adult depression. After conducting a review of both the theoretical assumptions of psychodynamic treatments of depression and the evidence supporting the efficacy of these interventions, these authors concluded that brief psychoanalytic therapy (BPT) is as effective in treating depression as other active psychotherapeutic treatments or pharmacotherapy, and its effects tend to be maintained in the longer term. They also observed that the combination of BPT and medication obtained better results than medication alone. Longer-term psychoanalytic treatment (LTPT) was found to be effective for patients suffering from chronic depression and co-morbid personality problems. Together, the authors argue, these findings justify the inclusion of psychoanalytic therapy as a first-line treatment in adult, child, and adolescent depression.

In a qualitative study carried out by Brown (2018) on parents' expectations regarding the recovery of their depressed children, a direct relationship was observed between said expectations and type of attachment. Parents who remained more passive and expected expert helpers to fix their child experienced reduced hope months after finishing the program. However, when parents changed their interactions with their child and adopted more positive expectations regarding their cure, they felt a more sustained sense of hope. Moreover, when parents themselves participated in therapy sessions, as part of their child's treatment, they felt greater hope and effectiveness in contributing to their child's recovery.

The American Psychological Association's Society of Clinical Psychology [ American Psychological Association, Society of Clinical Psychology (APA), 2017 ] has published a list of psychological treatments that have been tested with the most scientific rigor and which, moreover, have been found to be most effective in treating depression. These treatments are as follows:

– Self-Management/Self-Control Therapy ( Kanfer, 1970 ). Depression is due to selective attention to negative events and immediate consequences of events, inaccurate attributions of responsibility for events, insufficient self-reinforcement, and excessive self-punishment. During therapy, the patient is provided with information about depression and taught skills they can use in their everyday life. This 10-session program can be delivered either in group or individual formats, at any age.

– Cognitive Therapy ( Beck, 1987 ). Individuals suffering from depression are taught cognitive and behavioral skills to help them develop more positive beliefs about themselves, others, and the world. Méndez (1998) argues that therapists working with depressed children should pursue three changes: (1) Learn to value their own feelings; (2) Replace behaviors which generate negative feelings with more appropriate behaviors; and (3) Modify distorted thoughts and inaccurate reasoning. The number of sessions varies between 8 and 16 in patients with mild symptoms. Those with more severe symptoms show improvement after 16 sessions.

– Interpersonal Therapy ( Klerman et al., 1984 ). García and Palazón (2010) identified four typical focal points for tension in depression, related to loss (complicated mourning), conflicts (interpersonal disputes), change (life transitions), and deficits in relations with others (interpersonal deficits), which generate and maintain a depressive state. It uses certain behavioral strategies such as problem solving and social skills training and lasts between 12 and 16 sessions in the most severe cases, and between 3 and 8 sessions in milder cases.

– Cognitive Behavioral Analysis System of Psychotherapy ( McCullough, 2000 ). This therapy combines components of cognitive, behavioral, interpersonal, and psychodynamic therapies. According to McCullough (2003) , it is the only therapy developed specifically to treat chronic depression. Patients undergoing this therapy generate more empathic behaviors and identify, change and heal interpersonal patterns related to depression. Patients are recommended to combine the therapy with a regime of antidepressant medication.

– Behavior Therapy/Behavioral Activation (BA) ( Martell et al., 2013 ). Depression prompts sufferers to disengage from their routines and become increasingly isolated. Over time, this isolation exacerbates their depressive symptoms. Depressed individuals lose opportunities to be positively reinforced through pleasant experiences or social activities. The therapy aims to increase patients' chances of being positively reinforced by increasing their activity levels and improving their social relations. The therapy usually lasts between 20 and 24 sessions, with the brief version consisting of between 8 and 15 sessions.

– Problem-Solving Therapy ( Nezu et al., 2013 ). The aim is to enhance patients' personal adjustment to their problems and stress using affective, cognitive, and behavioral strategies. The therapy usually comprises around 12 sessions, although substantial changes are generally observed from the fourth session onwards. This therapy is widely used in primary care. It is an adaptation that is easy to apply in general medicine by personnel working in those contexts, and can be completed in around 6 weeks ( Areán, 2000 ).

The treatments that, according to the American Psychological Association, Society of Clinical Psychology (APA) (2017) , have modest research support and could be used with children are as follows:

– Rational Emotive Behavioral Therapy ( Ellis, 1994 ). This short-term, present-focused therapy works on changing the thinking which contributes to emotional and behavioral problems using an active-directive, philosophical and empirical intervention model. Using the A-B-C model (A: events observed by the individual; B: Individual's interpretation of the observed event; C: Emotional consequences of the interpretations made), the aim is to bring about the cognitive restructuring of erroneous thoughts, so as to replace them with more rational ones. The most commonly used techniques are cognitive, behavioral, and emotional.

– Self-System Therapy ( Higgins, 1997 ). Depression occurs as the result of the individual's chronic failure to achieve their established goals. During therapy, patients review their situation, analyze their beliefs and, on the basis of the results, alter their regulation style and move toward a new vision of themselves. Therapy generally consists of between 20 and 25 sessions.

– Short-Term Psychodynamic Therapy ( Hilsenroth et al., 2003 ). The aim of this therapy is to help patients understand that past experiences influence current functioning, and to analyze affect and the expression of emotion. The therapy focuses on the therapeutic relationship, the facilitation of insight, the avoidance of uncomfortable topics and the identification of core conflictual relationship themes. It is usually combined with pharmacological treatment to alleviate depressive episodes.

– Emotion-Focused Therapy (emotion regulation therapy or Greenberg's experiential therapy) ( Greenberg, 2004 ). According to Greenberg et al. (2015) , this therapy combines elements of client-based practices ( Rogers, 1961 ), Gestalt therapy ( Perls et al., 1951 ), the theory of emotions and a dialectic-constructivist meta-theory. The aim is to create a safe environment in which the individual's anxiety is reduced, thereby enabling them to confront difficult emotions, raising their awareness of said emotions, exploring their emotional experiences in more depth and identifying maladaptive emotional responses. The therapy is delivered in 8–20 sessions.

– Acceptance and Commitment Therapy ( Hayes, 2005 ). This theory has become increasingly popular over recent years and is the contextual or third-generation therapy that is supported by the largest body of empirical evidence. It is based on a realization of the importance of human language in experience and behavior and aims to change the relationship individuals have with depression and their own thoughts, feelings, memories, and physical sensations that are feared or avoided. Strategies are used to teach patients to decrease avoidance and negative cognitions, and to increase focus on the present. The aim is not to modify the content of the patient's thoughts, but rather to teach them how to change the way they analyze them, since any attempt to correct thoughts may, paradoxically, only serve to intensify them ( Hayes, 2005 ).

Ferdon and Kaslow (2008) , for their part, in a theoretical review of the treatment of depression in children and adolescents, concluded that the cognitive-behavioral-therapy-based specific programs of the Penn Prevention program meet the criteria to conduct effective interventions in children with depression. In adolescent depression, the cognitive-behavioral therapy and the Interpersonal Therapy–Adolescent seem to have a well-established efficacy. Weersing et al. (2017) , in this same line, state that, although the efficacy of treatments in children is rather weak, cognitive-behavioral therapy is probably the most effective therapy. They also confirm that, in depressed adolescents, cognitive behavioral therapy, and interpersonal psychotherapy are appropriate interventions.

There are other studies also which focus on treatments for depression in childhood. For example, Crowe and McKay (2017) carried out a meta-analysis of the effects of Cognitive Behavioral Therapy (CBT) on children suffering from anxiety and depression, concluding that CBT can be considered an effective treatment for child depression. According to these authors, the majority of protocols for children have been adapted from protocols for adults, and the most common techniques are psychoeducation, self-monitoring, identification of emotions, problem solving, coping skills, and reward plans. Similarly, cognitive strategies include the identification of cognitive errors, also known as cognitive restructuring. In another meta-analysis conducted to analyze the efficacy and acceptability of CBT in cases of child depression, Yang et al. (2017) observed that, in comparison with the control groups that did not receive treatment, the experimental groups showed significant improvement, although they also pointed out that the relevance of this finding was limited due to the small size of the trial groups.

Another study carried out in Saudi Arabia concluded that student counseling in schools may help combat and directly reduce anxiety and depression levels among Saudi children and adolescents ( Alotaibi, 2015 ).

Family-based treatment may also be effective in treating the interpersonal problems and symptoms observed among depressed children. The data indicate that the characteristics of the family environment predict recovery from persistent depression among depressed children ( Tompson et al., 2016 ). In this sense, Tompson et al. (2017) compared the effects of a family-focused treatment for child depression (TCF-DI) with those of individual supportive psychotherapy among children aged 7–14 with depressive disorders. The results revealed that incorporating the family into the therapy resulted in a significant improvement in depressive symptoms, global response, functioning, and social adjustment.

To conclude this section, it can be stated that treatment for depression should be multifactorial and should bear in mind the personal characteristics of the patient, their coping strategy for problems, the type of relationship they have with themselves and the type of relationship they establish with their environment (friends, school, family, etc.). Thus, in order for the individual to attain the highest possible level of psychological wellbeing, attention should focus on both these and other related aspects.

Conclusions

The present review aims to shed some light on the complex and broad-ranging field of child and adolescent depression, starting with a review of the construct itself and its explanatory theories, before continuing on to analyze existing evaluation instruments, the main prevention programs currently being implemented and the various treatments currently being applied. All these aspects are intrinsically linked: how the concept is defined depends on the explanatory variables upon which said definition is based, and this in turn influences how we measure it and the variables we define as being key elements for its prevention and treatment.

It is interesting to note the low level of specificity of both the construct itself and the explanatory theories offered by child and adolescent psychology, which suggest that child depression can be understood on the basis of the adult version of the pathology. This may well be a basic error in our approach to depression among younger age groups. The fact that universal prevention programs specifically designed for children are obtaining only modest results may indicate that we have perhaps failed to correctly identify the key variables involved in the genesis and maintenance of child and adolescent depression.

The review of current child and adolescent depression prevention programs revealed that the vast majority coincide in adopting a cognitive-behavioral approach, with contents including social skills and problem solving training, emotional education, cognitive restructuring, and strategies for coping with anxiety. These contents are probably included because they are important elements in the treatment of depression, as shown in this review. But if their inclusion is important and effective in the treatment of depression, why do they not seem to be so effective in preventing this pathology? There are probably many factors linked to prevention programs which, in one way or another, influence their efficacy: who implements the program and what prior training they receive; the characteristics of the target group; group dynamics; how sessions are run; how the program is evaluated; and if the proposed goals are really attained (e.g., training in social skills may be key, but perhaps we are not training students correctly). Moreover, in universal prevention programs carried out in schools, the intervention focuses on students themselves rather than adopting a more holistic approach, as recommended by certain authors such as Greenberg et al. (2001) . But, if we accept that depression is multifactorial and that risk and protection factors may be found not only in the school environment but also in the family and social contexts, should prevention not also be multifactorial?

There is therefore still much work to be done in order to fully understand child and adolescent depression and its causes, and so design more effective evaluation instruments and prevention and treatment programs. Given the important social and health implications of this disorder, we need to make a concerted effort to further our research in this field.

Author Contributions

MG designed the study and wrote the protocol. EB and JJ conducted literature review and provided summaries of previous research studies, and wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.

The Research Project was sponsored by the Alicia Koplowitz Foundation, with grant number FP15/62.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: depression, adolescent, child, instruments, prevention, treatment

Citation: Bernaras E, Jaureguizar J and Garaigordobil M (2019) Child and Adolescent Depression: A Review of Theories, Evaluation Instruments, Prevention Programs, and Treatments. Front. Psychol. 10:543. doi: 10.3389/fpsyg.2019.00543

Received: 13 March 2018; Accepted: 25 February 2019; Published: 20 March 2019.

Reviewed by:

Copyright © 2019 Bernaras, Jaureguizar and Garaigordobil. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Joana Jaureguizar, [email protected]

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Major Depressive Disorder in Children: A Case Study

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Depression can affect any of us, at any age or stage in our lives and can be triggered by a number of factors or events. Children are no exception to this and can suffer from depression in the same way as adults do. Feelings of hopelessness, anxiety, sadness and worthlessness can make children feel isolated, and it is important that they receive the help and support that they need.

Table of Contents

Behavioural Changes

Jane and Rob took their nine-year-old son Alex to see a psychiatrist when they became concerned about his behaviour during their divorce.

Alex had become irritable and developed behavioural difficulties, and his parents were very concerned about him, and how his behaviour would impact on his social and school life, as well as his life at home.

Although Jane and Rob were in the middle of a divorce, they had reached an amicable situation, and were both concerned about their son. Alex’s parents described him as a bright, pleasant and easygoing child who loved school, but when his parents separated, Alex began defying teachers and got involved in confrontations with other children.

Sleeping and Eating Difficulties

His work began to suffer, and he started having trouble sleeping, often waking up sometimes as much as four times in the night. He also became really fussy about what he ate, stopped playing football with his club, and lost interest in all his after school activities. For a previously outgoing, sociable and sports mad young boy, this behaviour was out of character and very worrying for Jane and Rob.

Medication Helped

After two months of therapy and help, Alex’s therapist recommended that he should be evaluated to see if a course of medication would help. The therapist came to this decision because Alex began to say things like “I wish I’d never been born,” “I’m stupid,” and “I hate myself.”

He also complained of stomach aches and headaches, which caused him to miss school. Alex’s GP found no cause for the physical complaints, but it transpired that two close relatives had suffered from depressive disorders.

When the therapist spoke to Alex, he was reluctant to answer too many questions, avoided eye contact, and appeared lethargic. He said his mood was about three out of 10, with 10 being the best he’d ever felt.

He said he had a death wish, but no true suicidal plan. He didn’t admit to a current desire for self-harming, but he had cut his wrists about two months before. The psychiatrist recommended continued individual and family therapy, and Alex was prescribed medication to help him sleep and enhance his mood.

Improvements and a Happier Child

At his six-week visit, Alex said his mood had improved to about five out of 10. He was sleeping better, and his parents noticed an improvement in their son’s mood and attitude, and he was also happy to go to school. The dose of his medication was increased and after 12 weeks, Alex rated his mood at eight out of 10. His school work was back on track, he was sleeping well and beginning to see his friends again. Alex was also planning to take part in a school residential.

Alex will see his psychiatrist every three to four months for the next 12 months.

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• Volume 32, Issue 6
• Very early family-based intervention for anxiety: two case studies with toddlers
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• http://orcid.org/0000-0001-5603-6959 Dina R Hirshfeld-Becker 1 , 2 ,
• Aude Henin 1 , 2 ,
• Stephanie J Rapoport 1 ,
• Timothy E Wilens 2 , 3 and
• Alice S Carter 4
• 1 Child CBT Program, Department of Psychiatry , Massachusetts General Hospital , Boston , Massachusetts , USA
• 2 Department of Psychiatry , Harvard Medical School , Boston , Massachusetts , USA
• 3 Division of Child and Adolescent Psychiatry, Department of Psychiatry , Massachusetts General Hospital , Boston , Massachusetts , USA
• 4 Department of Psychology , University of Massachusetts Boston , Boston , Massachusetts , USA
• Correspondence to Dr Dina R Hirshfeld-Becker; dhirshfeld{at}partners.org

Anxiety disorders represent the most common category of psychiatric disorder in children and adolescents and contribute to distress, impairment and dysfunction. Anxiety disorders or their temperamental precursors are often evident in early childhood, and anxiety can impair functioning, even during preschool age and in toddlerhood. A growing number of investigators have shown that anxiety in preschoolers can be treated efficaciously using cognitive–behavioural therapy (CBT) administered either by training the parents to apply CBT strategies with their children or through direct intervention with parents and children. To date, most investigators have drawn the line at offering direct CBT to children under the age of 4. However, since toddlers can also present with impairing symptoms, and since behaviour strategies can be applied in older preschoolers with poor language ability successfully, it ought to be possible to apply CBT for anxiety to younger children as well. We therefore present two cases of very young children with impairing anxiety (ages 26 and 35 months) and illustrate the combination of parent-only and parent–child CBT sessions that comprised their treatment. The treatment was well tolerated by parents and children and showed promise for reducing anxiety symptoms and improving coping skills.

• childhood anxiety disorders
• preschoolers
• cognitive behavioural therapy

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Introduction

Anxiety disorders affect as many as 30% of children and adolescents and contribute to social and academic dysfunction. These disorders or their temperamental precursors 1 are often evident in early childhood, with 10% of children ages 2–5 already exhibiting anxiety disorders. 2 Anxiety symptoms in toddlerhood 3 and preschool age 4 show moderate persistence and map on to the corresponding Diagnostic and Statistic Manual anxiety disorders. 5 6 Well-meaning parents, particularly those with anxiety disorders themselves, may respond to a child’s distress around separating from parents or being around unfamiliar children by decreasing the child’s exposure to these situations, for example, by not having the child start preschool or by not leaving the child with a childcare provider to go to work or socialise. In the short term, such responses may impair concurrent family function, strain the parent–child relationship, and reduce the child’s opportunity for increased autonomy, learning and social development. 7 These avoidant strategies may initiate a trajectory where the child takes part in fewer and fewer activities, leading to social and academic dysfunction. 8

Members of our research team began championing the idea of early intervention with young anxious children over two decades ago, with the aim of teaching children and their parents cognitive–behavioural strategies to manage anxiety before their symptoms became too debilitating. 8 Although cognitive–behavioural therapy (CBT) has since emerged as the psychosocial treatment of choice for treating and preventing anxiety, 9 10 at that time, most protocols that had been empirically tested were aimed at children ages 7 through early adolescence, with only a few enrolling children as young as age 6. 11 We developed and tested a parent–child CBT intervention (called ‘Being Brave’) and reported efficacy in children as young as 4 years. 12 13 The treatment involved teaching parents about fostering adaptive coping and implementing graduated exposures to feared situations, and modelling how to teach children basic coping skills and conduct exposures with reinforcement. In parallel, a growing number of investigators confirmed that anxiety in preschoolers could be treated efficaciously using CBT administered either by training parents to apply CBT strategies with their children or through direct intervention with children. 14 15 Early family-based intervention using cognitive–behavioural strategies was shown to reduce rates of later anxiety and to attenuate the onset of depression in adolescence in girls. 16

The question remains as to whether early intervention can be extended even younger. With few exceptions, 17 18 most investigators do not offer direct CBT for anxiety to children under age 3 or 4, 15 and none to our knowledge have treated anxiety disorders with CBT in children under age 2.7. 15 However, we reasoned that since toddlers can also present with impairing symptoms, and since behaviour strategies can be feasibly applied even in preschoolers with poor language ability, 19 it ought to be possible to apply family-based CBT for anxiety to toddlers as well. We therefore present two cases of anxious children, ages 26 and 35 months, treated with parent and child CBT.

Recruitment

Parents of children ages 21–35 months were recruited for a pilot intervention study (a maximum of three cases) using advertisements to the community. To be included, children had to be rated by a parent as above a standard deviation on the Early Childhood Behavior Questionnaire Fear or Shyness Scale 20 and could not have global developmental delays, autism spectrum disorder or a primary psychiatric disorder other than anxiety.

Children were evaluated for behavioural inhibition using a 45 min observational protocol. 21 Parents completed a structured diagnostic interview about the child (Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime) that has been used with parents of children as young as 2 years; 22 23 an adapted Coping Questionnaire, 24 in which parents assessed the child’s ability to cope with their six most feared situations; and questionnaires assessing child symptoms (Child Behavior Checklist 1-1/2-5 (CBCL), 25 subscales from the Infant Toddler Social Emotional Assessment (ITSEA) 26 ), family function (Family Life Impairment Scale 27 ) and parental stress (Depression Anxiety Stress Scale 28 ). These assessments were repeated following the intervention, with the exception of the behavioural observation for the child initially rated ‘not inhibited’. The clinician rated the global severity of the child’s anxiety on a 7-point severity scale (Clinician Global Impression of Anxiety 29 ) at baseline and rated global severity and improvement of anxiety postintervention. Participant engagement in session and adherence to between-session assignments were rated by the clinician at each visit, and parents completed a post-treatment questionnaire rating the intervention.

Children were treated by the first author, a licensed child psychologist, using the ‘Being Brave’ programme. 13 It includes six parent-only sessions, eight or more parent–child sessions and a final parent-only session on relapse prevention. An accompanying parent workbook reinforces the information presented. Parent-only sessions focus on factors maintaining anxiety; monitoring the child’s anxious responses and their antecedents and consequences; restructuring parents’ anxious thoughts; identifying helpful/unhelpful responses to child anxiety; modelling adaptive coping; playing with the child in a non-directive way; protecting the child from danger rather than anxiety; using praise to reinforce adaptive coping; and planning and implementing graduated exposure. Child–parent sessions teach the child basic coping skills; and focus on planning, rehearsing and performing exposure exercises, often introduced as games, with immediate reinforcement. All parent–child sessions were preserved from the original protocol, but two sessions teaching the child about the CBT model, relaxation and coping plans were omitted, as were two sessions in which the (older) child does a summary project and celebrates gains. Up to six child–parent sessions focusing on exposure practice were included.

In the cases that follow, identifying details are disguised to protect participants’ privacy. Parents of both children provided written consent for the publication of de-identified case reports.

Background information

‘J’ was a 35-month-old girl, the third of three children of married parents. She had congenital medical problems requiring multiple surgeries, and she continued to undergo regular follow-up procedures. J met the criteria for separation anxiety disorder with marked severity, mild social phobia and mild specific phobia. Although she was able to attend her familiar day care if handed directly to a teacher and attend a gymnastics class with a friend while her mother waited in the hall, J showed great distress if apart from her mother at home. If her mother left her sight (eg, to use the bathroom), J would sob, cry and try to open the door to get in. If her mother went out and left her with a family member, J would fuss, cry and try to come along, and would continually ask to video-call her, so her mother would cut her outings short. J also had fears of doctors’ visits, of riding in the car seat, and of walking independently up and down a staircase at home. She would approach new children only with assistance from her mother, and she was afraid to take part in gymnastics performances.

J also had some mood symptoms possibly related to her medical issues. She would intermittently have days when she was much more clingy, had uncharacteristically low energy, would want to be held, and would say ‘ow, ow’ if put down to stand. She also had difficulty staying asleep and would periodically wake up with respiratory difficulties.

‘K’ was a 26-month-old boy, the only child of married parents. He met the criteria for moderate separation anxiety disorder. Although able to go to a day care he had been attending since infancy, he showed distress at drop-off particularly at the start of each week, crying for 15 min. He feared being apart from his mother in the house: he could not tolerate his mother leaving the room even to change clothes and would cry if his mother left the playroom while K played with his father. He would get distressed if his father took him on outings without his mother. He could not be dropped off at a childcare centre at his parents’ gym, leading to their avoiding exercise. He slept in his own crib, rocked to sleep by a parent, but would wake in a panic (alert but distressed) two to three times per month, crying for over an hour until his parents took him into their bed. K also was very particular about where objects were placed in the playroom and would fuss if they were put in the wrong place. He got anxious about deviations in routine (eg, taking a different path on a walk) and had trouble throwing things away (eg, used Band-Aids).

Intervention Feasibility and Outcomes

To demonstrate feasibility, the application of the treatment protocol with both participants is summarised in table 1 . Both participants completed the treatment, in 11 and 10 sessions, respectively. For each, session engagement was rated ‘moderately’ or ‘completely engaged’ at all but one session, and homework adherence was rated as ‘moderate work’ to ‘did everything assigned’ at all but one session.

• View inline

Application of treatment protocol with both participants

The quantitative results of the treatment are presented in table 2 . Both children were rated by the clinician as having shown ‘much improvement’ (Clinician Global Impression of Anxiety-Improvement 1 or 2), and both showed changes in quantitative measures of anxiety and family function. In both families, parents rated their satisfaction with the treatment as ‘extremely satisfied’, and felt that they would ‘definitely’ recommend the intervention to a friend. They rated all strategies introduced in the intervention as ‘very-’ or ‘moderately helpful’ and rated the change in their ability to help their child handle anxiety as ‘moderately-’ to ‘very much improved’.

Quantitative changes in diagnoses, coping ability, symptoms and family function in both participants

These pilot cases demonstrate the feasibility and acceptability of parent–child CBT for toddlers with anxiety disorders. The two participating families completed the treatment protocol and were consistently engaged with in-session exercises and adherent to between-session skills practice. The cases demonstrate that basic coping skills and exposure practice can be conducted with toddlers.

Although efficacy cannot be determined from uncontrolled case studies, the cases did show promising preliminary results. Both children showed a decrease in number of anxiety disorders, both were rated by the clinician (and parents) as either ‘moderately-’ or ‘much improved’ in their overall anxiety, and both showed increases in their parent-rated ability to cope with their most feared situations. Participant 2 improved on all symptom measures as well. Most significantly, his ITSEA general anxiety, separation distress, inhibition to novelty, negative emotionality, compliance and social relatedness scores and his CBCL total score, internalising score and somatic complaints scale score normalised from clinical to non-clinical range. Participant 1 had a more complicated clinical presentation, and whereas her diagnoses and coping scores improved, her parent-rated symptom scores were more mixed, perhaps related to medical problems which impacted sleep. Beyond changes in the children’s behaviour, family life impairment was reduced for both families, and parental stress was decreased out of clinical range for participant 1. Notably, both children also showed gains in areas of competence, including prosocial peer relations and mastery motivation.

This work extends previous research demonstrating that very young children experience impairing levels of anxiety that are amenable to CBT. Previous studies have found that CBT is as efficacious with older preschool-age children with anxiety disorders as it is with school-aged youth, 14 15 with approximately two-thirds of treated youth demonstrating clinically significant improvement. There is increasing recognition that anxiety disorders start early in childhood, and that there are significant advantages to intervening proximally to their onset, before anxiety symptoms crystallise and impairment accumulates. For example, one study of 1375 consecutive referrals (mean age 10.7) to a paediatric psychopharmacology clinic found that the median age of onset of a child’s first anxiety disorder was 4 years. 30 Children seeking treatment for anxiety often present in middle childhood, for symptoms which began much earlier, exposing the child and family to undue stress for years. By teaching parents and very young children skills to manage anxiety, we hope to give families important tools to navigate the developmental transitions inherent in this age range, and to help children develop a sense of mastery during a critical developmental period. Of course, a larger controlled trial is needed to further evaluate this intervention and its efficacy over time.

Assessing and treating toddlers require a developmentally informed approach. Anxiety and other symptoms may present differently in younger children, and because of limited language and cognitive abstraction capabilities toddlers are not as able to describe their fears and worries. Because some forms of anxiety (eg, separation anxiety, stranger anxiety) are normative, determination of clinically significant levels of anxiety requires an understanding of typical development in toddlerhood and the ability to conduct a detailed assessment with parents and the child using measures normed for this age group (such as the ITSEA and CBCL 1-1/2-5). Similarly, implementing CBT with toddlers and preschoolers requires age-appropriate modifications of empirically supported techniques. The adaptations we used included increased parental involvement in planning exposures, decreased focus on child cognitive restructuring (beyond framing the practice as ‘being brave’ and redirecting the child’s attention to rewarding aspects of the situation), and adaptations to exposure exercises to maximise child participation and motivation (practising at times when the child was rested and not irritable, incorporation of games and reinforcers, and allowing the child maximal choice about when/how to carry out the exposure). The cases we presented demonstrate that existing interventions can be effectively adapted and implemented with children as young as 2 years of age. By sharing the information gleaned from our research, we hope to inform providers who may be less familiar with treating children in this age range and increase their confidence in intervening with very young children.

Acknowledgments

The authors acknowledge Jordan Holmen for assistance with data checking.

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Dina Hirshfeld-Becker earned her undergraduate degree from Harvard and her doctorate in clinical psychology from Boston University, and completed post-doctoral training at Massachusetts General Hospital. Dr Hirshfeld-Becker is currently co-founder and co-director of the Child Cognitive Behavioral Therapy (CBT) Program in the Department of Psychiatry at MGH and an associate professor of psychology in the Department of Psychiatry at Harvard Medical School. The Child CBT Program offers short-term empirically supported CBT with youths ages 3-24, research in novel treatment adaptations, and clinical training in CBT, including on-line training courses. She pioneered the development and empirical evaluation of one of the first manualized cognitive-behavioral intervention protocols for anxiety in 4- to 7-year-old children, the “Being Brave” program, and has been exploring its use with children with autism spectrum disorder and with younger toddlers and their parents. Dr Hirshfeld-Becker has published numerous articles, reviews, and chapters. Her main research interests include the etiology, development, and treatment of childhood psychiatric disorders, particularly anxiety disorders, and in the study of early risk factors for these disorders.

Contributors DRHB designed the study with input from ASC, AH and TEW. DRHB developed the intervention and treated the cases, and DRHB, SJR and AH collected, scored, analysed and tabulated the data. DRHB wrote the first draft of the manuscript, SJR drafted parts of the Results section, and AH made significant additions to the Discussion section. AH, ASC and TEW revised the manuscript critically for important intellectual content. DRHB incorporated all of their edits and finalised the document. All authors approved the final version and are accountable for ensuring accuracy and integrity of the work.

Funding This work was supported by a private philanthropic donation by Mrs. Eleanor Spencer.

Competing interests DRHB and AH receive or have received research funding from the National Institutes of Health (NIH). ASC reports receipt of royalties from MAPI Research Trust on the sale of the ITSEA, one of the instruments included in the manuscript. TEW receives or has received grant support from the NIH (NIDA), and is or has been a consultant for Alcobra, Neurovance/Otsuka, Ironshore and KemPharm. TEW has published a book, Straight Talk About Psychiatric Medications for Kids (Guilford Press); and co/edited books: ADHD in Adults and Children (Cambridge University Press), Massachusetts General Hospital Comprehensive Clinical Psychiatry (Elsevier), and Massachusetts General Hospital Psychopharmacology and Neurotherapeutics (Elsevier). TEW is co/owner of a copyrighted diagnostic questionnaire (Before School Functioning Questionnaire), and has a licensing agreement with Ironshore (BSFQ Questionnaire). TEW is Chief of the Division of Child and Adolescent Psychiatry, and (Co)Director of the Center for Addiction Medicine at Massachusetts General Hospital. He serves as a clinical consultant to the US National Football League (ERM Associates), US Minor/Major League Baseball, Phoenix House/Gavin Foundation and Bay Cove Human Services.

Patient consent for publication Parental/guardian consent obtained.

Ethics approval All procedures were approved by our hospital’s institutional review board (Partners Human Research Committee, 2018P000376), and parents provided informed consent for themselves and their child.

Provenance and peer review Not commissioned; externally peer reviewed.

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• Research article
• Open access
• Published: 22 April 2024

Impact of COVID-19 pandemic on depression incidence and healthcare service use among patients with depression: an interrupted time-series analysis from a 9-year population-based study

• Vivien Kin Yi Chan 1   na1 ,
• Yi Chai 1 , 2   na1 ,
• Sandra Sau Man Chan 3 ,
• Hao Luo 4 ,
• Mark Jit 5 , 7 ,
• Martin Knapp 4 , 6 ,
• David Makram Bishai 7 ,
• Michael Yuxuan Ni 7 , 8 , 9 ,
• Ian Chi Kei Wong 1 , 10 , 11 , 13 &
• Xue Li   ORCID: orcid.org/0000-0003-4836-7808 1 , 10 , 12 , 13  

BMC Medicine volume  22 , Article number:  169 ( 2024 ) Cite this article

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Most studies on the impact of the COVID-19 pandemic on depression burden focused on the earlier pandemic phase specific to lockdowns, but the longer-term impact of the pandemic is less well-studied. In this population-based cohort study, we examined the short-term and long-term impacts of COVID-19 on depression incidence and healthcare service use among patients with depression.

Using the territory-wide electronic medical records in Hong Kong, we identified all patients aged ≥ 10 years with new diagnoses of depression from 2014 to 2022. We performed an interrupted time-series (ITS) analysis to examine changes in incidence of medically attended depression before and during the pandemic. We then divided all patients into nine cohorts based on year of depression incidence and studied their initial and ongoing service use patterns until the end of 2022. We applied generalized linear modeling to compare the rates of healthcare service use in the year of diagnosis between patients newly diagnosed before and during the pandemic. A separate ITS analysis explored the pandemic impact on the ongoing service use among prevalent patients with depression.

We found an immediate increase in depression incidence (RR = 1.21, 95% CI: 1.10–1.33, p  < 0.001) in the population after the pandemic began with non-significant slope change, suggesting a sustained effect until the end of 2022. Subgroup analysis showed that the increases in incidence were significant among adults and the older population, but not adolescents. Depression patients newly diagnosed during the pandemic used 11% fewer resources than the pre-pandemic patients in the first diagnosis year. Pre-existing depression patients also had an immediate decrease of 16% in overall all-cause service use since the pandemic, with a positive slope change indicating a gradual rebound over a 3-year period.

Conclusions

During the pandemic, service provision for depression was suboptimal in the face of increased demand generated by the increasing depression incidence during the COVID-19 pandemic. Our findings indicate the need to improve mental health resource planning preparedness for future public health crises.

Peer Review reports

The COVID-19 pandemic that began in 2020 has resulted in an unprecedented public health crisis, with 771 million confirmed cases and over 6 million deaths across the globe as of September 2023 [ 1 ]. To curb the spread and reduce the mortality of SARS-CoV-2 infections, governments worldwide enacted stringent measures to contain its spread, including social mobility restrictions, mask-wearing, massive screenings, and lockdowns. Despite their effectiveness in limiting viral spread, these measures may have created a macro-environment of fear, social exclusion of individuals who contracted the virus, and reduced community cohesion [ 2 , 3 , 4 ]. The pandemic and the ensuing measures also led to economic disruption and created financial hardship for millions of families [ 4 , 5 ]. The combined pandemic stresses may have exacerbated the risk factors for mental health conditions including depression. Among patients with pre-existing depression, the government effort re-prioritized for outbreak control may have also led to disrupted non-emergency services and unmet care need in mental health [ 6 ].

A meta-analysis estimated an additional 53 million cases of depression and a 27.6% increase in its global prevalence in 2020 due to COVID-19-related illnesses and reduced mobility [ 7 ], which affected individuals across age groups [ 8 , 9 , 10 ]. In Hong Kong, a survey showed a consistent mental health crisis with a two-fold increase in depression symptoms and a 28.3% rise in the stress level even during the well-managed small-scale outbreaks [ 11 ]. Conversely, other studies reported that the pandemic reduced the risk of depression and self-harm because of the emotional security provided by timely government intervention, but these findings were confounded by increased barriers to seek medical help [ 12 , 13 , 14 ]. In the emergency phase of the pandemic, it was reported that lockdowns significantly reduced healthcare service use for both outpatient and inpatient services [ 15 , 16 , 17 ]. Studies also found an elevated risk of depression relapse and use of antidepressants [ 18 , 19 ].

Literature exploring pandemic impact on depression has mostly focused on the earlier phase of the pandemic (2020–2021) when short-term lockdown orders were in place. There are fewer studies and more mixed results for the post-emergency phase. Hong Kong followed the “dynamic zero-COVID policy” of China with strict border control, contact tracing, and quarantine before cases spread until the end of 2022 and so recorded a low number of SARS-CoV-2 cases for most of the time before a major Omicron outbreak [ 20 ]. It did not experience full lockdown, although stringent infection control and social measures were deployed for an entire 3-year-long period. This context thus enables us to evaluate the longer-term pandemic impact apart from a focus on lockdowns. In the late pandemic period, it is also useful to understand any potential decline in depression incidence and rebound in health service utilization. Using interrupted time series (ITS) analysis with a cohort study, we examined the changes in depression incidence and healthcare service use due to the pandemic, aiming to measure both the short-term (immediately after pandemic onset) and long-term (3 years since the outbreak) impacts on the burden of depression. We aimed to facilitate better preparedness in mental health resource planning for future public health crises.

Data source

We analyzed the Clinical Data Analysis and Reporting System (CDARS), the territory-wide routine electronic medical record (EMR) developed by the Hospital Authority, which manages all public healthcare services in Hong Kong and provides publicly funded healthcare services to all eligible residents (> 7.6 million). CDARS covers real-time anonymized patient-level data, including demographics, deaths, attendances, and all-cause diagnoses coded based on the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), since 1993 across outpatient, inpatient, and emergency settings for research and auditing purposes in the public sector. The quality and accuracy of CDARS have been demonstrated in population-based studies on COVID-19 [ 21 , 22 ] and depression [ 23 , 24 ]. In Hong Kong, the public healthcare is heavily subsidized at a highly affordable price, while the private sector is financed mainly by non-compulsory medical insurance and out-of-pocket payments. The Hospital Authority thus manages 76% of chronic medical conditions including mental health illnesses despite a dual-track public and private system [ 25 ].

Study design and participants

This study consisted of both a quasi-experimental design with ITS analyses and a population-based retrospective study. We first identified all patients who received new clinical diagnoses of major depressive disorder or dysthymia (ICD-9-CM codes: 296.2, 300.4, 311) between January 2014 and December 2022. Patients aged below 10 were excluded to avoid confusion with maternal depression in the coding system. We performed an ITS analysis to evaluate changes in medically attended depression incidence during 36 quarters of data observations. The data cut point was the first quarter of 2020, leaving 24 quarters as pre-cut points and 12 quarters as post-cut points. ITS analysis is a valuable tool to assess the impact of population-level interventions or major macro-environmental changes and widely used in various health policy assessments [ 26 ]. Since patients who received incident diagnoses in different years could have different disease durations and care needs, we divided all patients into nine “incident cohorts” (2014 to 2022 cohorts) based on year of depression incidence. All patients were followed up until the end of 2022 for their service use patterns across outpatient, inpatient, and emergency settings.

An exploratory trend analysis showed that use of healthcare resources was the greatest at the beginning of the disease course before stabilizing. Recognizing this feature, we separately investigated the pandemic impact on the (1) initial and (2) ongoing healthcare service use. Respectively, we compared the rates of healthcare service use during the first calendar year following diagnosis, which potentially represents the most care-demanding phase, among patients newly diagnosed during the pandemic (2020 to 2022, the exposure groups) with those diagnosed before the pandemic (2014 to 2019, the reference groups) using a generalized linear model. To study the ongoing resource utilization among the relatively stable prevalent patients, defined as having a disease duration for at least 3 years by the start of the pandemic (i.e., represented by all patients in the 2014–2016 cohorts), we conducted another ITS analysis to compare their rates of service use before and during the pandemic until the end of 2022. The data points before the third calendar year of diagnosis were excluded in the analysis. The linkage between the three parts of analyses is illustrated in Additional file 1 : Figure S1.

Exposure and outcomes of interest

Our study defined the exposure as the macro-environment with the implementation of containment measures in response to the pandemic. Based on the COVID-19 Stringency Index by the Oxford COVID-19 Government Response Tracker, the Hong Kong government introduced relevant policies since January 2020 and announced the lifting of most mandates by December 2022 [ 27 ]. With quarterly data, we operationally defined the exposure period starting from the first quarter of 2020 until December 2022 (the intervention period). The reference period (the pre-pandemic period) was between the first quarter of 2014 and the last quarter of 2019.

The first outcome of interest was quarterly incidence of medically attended depression, defined as the number of patients who received depression diagnosis in the current quarter but without history of depression divided by the local eligible population, with age standardization using 5-year age bands based on the 2021 mid-year population. The second outcome was quarterly or yearly rates of attendance episodes or bed-days by incident cohort and service setting, defined by the total visit episodes or bed-days in the current period divided by the number of patients with depression whose observation period (from their first diagnosis to death or end of study) fell within the same period. We further stratified the outpatient attendance into “all-cause” (all outpatient services) and “psychiatric-related” (psychiatric specialist clinic, day hospital, and community nursing) use. Stratified data were unavailable in the inpatient and emergency settings.

Statistical analysis

In the ITS analyses, we applied segmented quasi-Poisson regression models since the data showed signs of overdispersion [ 28 ]. We included a continuous time variable in quarters, a binary indicator for the pandemic period (the exposure period) to represent level change (immediate effect) and the interaction of the two to measure slope change (gradual effect) [ 29 ], offsetting the logarithm of the local population or patients with depression. We adjusted the quarters of the data points to account for seasonality. Residual plots, autocorrelation function, and partial autocorrelation function suggested very little evidence of autocorrelation [ 28 , 30 ]. We then used Newey-West method to obtain robust standard errors and address autocorrelation up to the largest lag [ 31 , 32 ]. In the comparison of the initial healthcare service use between patients newly diagnosed during and before the pandemic, we fitted the rates of service use in the year of diagnosis between cohorts using a generalized linear model with negative binomial log link function. The model adjusted for a binary indicator of whether the diagnosis year occurred before or during the pandemic (the exposure period) and offset the logarithm of incident patients with depression in each cohort. In all analyses, we excluded data points related to major local social movements in 2014 and 2019 to address confounding due to changes in socio-political environment [ 33 , 34 , 35 ].

Subgroup and sensitivity analyses

In the ITS analysis to evaluate changes in depression incidence, we further stratified the analysis into three age groups: adolescents (10–24), adults (25–64), and the older population (65 +) to explore whether these population subgroups were differentially susceptible to a new depression diagnosis as a result of the pandemic.

During the first quarter of 2022, there was an unprecedented abrupt increase of SARS-CoV-2 cases due to the Omicron variant, marking the start of “fifth-wave outbreak” in Hong Kong [ 20 ]. In contrast to the earlier waves of smaller-scale outbreaks (below 13,000 cumulative cases before 2022), the public healthcare services were overwhelmed at the beginning of this wave, which possibly strained diagnostic capacity and caused the number of depression diagnoses to be lower than usual. We therefore performed sensitivity analyses for the ITS analyses for depression incidence and healthcare service use by adjusting a variable indicating the relevant quarter to validate the results. In addition, since outpatient service reception may be subject to long waiting time, we conducted an additional sensitivity analysis with a 6-month lag for the pandemic period by adding a binary indicator for the transition period and re-defining the pandemic to start from the third quarter of 2020. Lastly, we also performed sensitivity analyses for the pandemic impact on ongoing healthcare resource utilization by changing the defined disease duration of 3 years as stable patients into 2 years.

All data were analyzed using R version 4.0.3 and cross-validated by two investigators.

Over the 9-year study period, we identified 85,111 patients with new depression diagnosis, who generated 4,433,558 attendance or admission episodes across all diagnosis settings and 1,327,424 inpatient bed-days. For these patients, the mean age was 48.6 (SD:19.8) with 71.6% being female. Detailed demographic characteristics of the patients diagnosed in each year are summarized in Additional file 2 : Table S1.

Incidence of medically attended depression

Figure  1 illustrates the trends of the observed and model-implied quarterly incidence of medically attended depression between 2014 and 2022. The average quarterly incidence rates were 3.44 and 3.59 per 10,000 population before and during the pandemic (Additional file 2 : Table S2), respectively. After adjusting for major social movements, ITS analysis showed a small but marginally significant decline in the population incidence in the pre-pandemic period (risk ratio, RR = 0.995, 95% CI: 0.99–1.00, p  = 0.042). Since the pandemic, however, there was a significant immediate increase in incidence indicated by level change (RR = 1.21, 95% CI: 1.10–1.33, p  < 0.001), with a non-significant slope change (Fig.  1 A).

Interrupted time series analysis plot of pandemic impact on depression incidence

Stratifying by age groups, ITS analysis showed a slow but significant decline in incidence in the pre-pandemic period among adults and the older population (RR = 0.99, 95% CI: 0.99–0.99) but a significant increase over the time among adolescents (RR = 1.04, 95% CI: 1.04–1.05) before the pandemic. Since the pandemic, we found significant level increases indicating immediate effects of the pandemic among adults (RR = 1.19, 95% CI: 1.09–1.29) and the older population (RR = 1.33, 95% CI: 1.29–1.38, all p  < 0.001), but not adolescents. The slope changes remained non-significant in all subgroups (Fig.  1 B–D).

In the sensitivity analysis which accounted for the fifth-wave outbreak, we found a similar level change (RR = 1.20, 95% CI: 1.10–1.32, p  < 0.001) as the main analysis, with a significant but slowly declining pre-pandemic trend (RR = 0.995, 95% CI: 0.990–0.999, p  = 0.039). Using a 6-month transition window showed a consistent level change (RR = 1.28, 95% CI: 1.22–1.34, p  < 0.001) and pre-pandemic trend (RR = 0.995, 95% CI: 0.994–0.996, p  < 0.001). The slope changes in both sensitivity analyses remained non-significant.

Healthcare service use

In each incident cohort, the patterns followed the natural disease history such that the greatest service demand consistently occurred within the first 2 years of a depression diagnosis, followed by gradual decline subsequently (Fig.  2 ). During the pandemic, service utilization appeared to decrease further across all diagnosis settings except for inpatient bed-days. All counts and rates of healthcare service use are listed in Additional file 2 : Tables S3–S12.

Trend of healthcare resource utilization from 2014 to 2022

Pandemic impact on initial healthcare service use

Table 1 details the rates of healthcare service use in the year of diagnosis stratified by incident cohort and the regression results across diagnosis settings. Annual rates of overall all-cause visits per patient in the year of diagnosis were 10.5 to 10.8 episodes among patients diagnosed between 2015 and 2018, in contrast to 9.0 to 10.2 episodes among those diagnosed between 2020 and 2022. Adjusting for major social movements, the negative binomial model showed that the pandemic was associated with significantly reduced utilization in inpatient bed-days (RR = 0.78, 95% CI: 0.70–0.85), outpatient all-cause visits (RR = 0.89, 95% CI: 0.85–0.93), outpatient psychiatric visits (RR = 0.82, 95% CI: 0.76–0.88), and overall all-cause visits (RR = 0.89, 95% CI: 0.85–0.94, all p  < 0.001). Being diagnosed during the pandemic was not significantly associated with changes in rates of emergency and inpatient admission episodes.

Pandemic impact on ongoing healthcare service use

For the combined 2014–2016 cohorts, the mean rate of overall all-cause visits counting from their third year of diagnosis was 3.38 episodes per patient in the pre-pandemic period, which dropped to 2.25 episodes per patient in the pandemic period. Adjusting for social movements, the ITS analysis showed significant decreases in the original trends of ongoing service use in all diagnosis settings (RRs ranged from 0.96 to 0.99, all p  < 0.01) before the pandemic (Table  2 and Fig.  3 ). When the pandemic began, there were immediate decreases in service use indicated by significant level changes in inpatient admission episodes (RR = 0.91, 95% CI: 0.83–0.99, p  = 0.024), inpatient bed-days (RR = 0.87, 95% CI: 0.78–0.96, p  = 0.017), outpatient all-cause visits (RR = 0.83, 95% CI: 0.76–0.91, p  < 0.001), outpatient psychiatric visits (RR = 0.77, 95% CI: 0.74–0.83, p  < 0.001), and overall all-cause visits (RR = 0.84, 95% CI: 0.76–0.92, p  < 0.001), but not emergency visits. Regarding gradual effects, there were significant but small slope changes during the pandemic across all diagnosis settings except inpatient bed-days, with RRs ranging from 1.02 to 1.03, indicating a gradual rebound over time (Table  2 and Fig.  3 ).

Impact of the pandemic on the ongoing healthcare resource utilization among the 2014–2016 cohorts

In the sensitivity analyses accounting for the fifth-wave outbreak and changing definition of disease duration prior to the pandemic, effect sizes were largely consistent with those in the main analysis (Additional file 2 : Tables S13–S14).

Using a 9-year population-based study with a quasi-experimental design, we present the immediate and long-term impacts of 3 years of the pandemic on depression burden. We found a 21% immediate increase in incidence of medically attended depression, with 19% and 33% increases among adults and the older population during the 3-year period. There was no significant slope change during the pandemic, indicating a sustained effect towards the end of 2022. Though the pandemic did not affect incidence among adolescents, the incidence had been rising significantly in this subgroup over time even before the pandemic. Despite the increasing overall incidence, patients newly diagnosed during the pandemic used 11% fewer resources in their year of diagnosis than the pre-pandemic patients. Patients with pre-existing depression also had an immediate decrease by 16% in overall all-cause visits, with a positive slope change which suggests a gradual rebound over 3 years.

Rising incidence of medically attended depression

Our findings are largely consistent with the previous literature that has reported an increased prevalence of depressive mood during the pandemic [ 7 , 8 , 9 , 10 , 11 ]. However, the results from EMR-based studies that focused on clinically confirmed incident diagnoses were mixed. A cohort study based on the UK Biobank reported a 2.0- to 3.1-fold increase in new diagnoses of depressive or anxiety disorders compared to the pre-pandemic period, especially in the first 6 months of the pandemic [ 36 ]. Another Israeli time-series analysis observed a 36% increase in depression incidence among youth [ 37 ]. Conversely, population-based time-series and cohort studies in the UK found a 28% to 43% decline in recorded depression incidence with a gradual return towards pre-pandemic rates [ 38 , 39 ]. One explanation for such discrepancies is service disruption during lockdowns that led to under-diagnoses in primary care systems. Alternatively, the nature of social measures may have contributed to the trends differently. Costa-Font et al. highlighted that a “preventive lockdown” when there was low mortality appeared to increase depressive symptoms, but it was the opposite when lockdowns were in a high-mortality context [ 40 ]. This echoes with our findings in Hong Kong, where control measures were mostly preventive following the “dynamic zero-COVID” approach while maintaining low case load most of the time.

In our subgroup analysis, we found that adults and the older population were prone to developing depression due to the pandemic, but adolescents were not. However, prior studies tend to report consistent risks across age groups: adults were likely to suffer from job insecurity and increased caregiver responsibilities, older adults were susceptible to prolonged isolation, fear of illness, and grief of losing the loved ones, while adolescents faced school closures, reduced peer interactions, and outdoor activities [ 37 , 41 , 42 , 43 , 44 ]. Between 2014 and 2019, we found the incidence among Hong Kong adolescents was already increasing, with rates doubling within 5 years and overtaking the incidence among adults and the older population. This pre-existing rising trend might explain why the pandemic, despite being an additional risk factor, did not have as comparable impact as in other age groups due to a potential diminishing marginal effect. The earlier rise in adolescent depression may have stemmed from existing contextual forces including social unrest and other unknown stressors [ 35 ]. Our findings suggest that resources for depression care among adults and the older population are needed to prepare for future pandemic threats. However, policymakers should be aware of the worrying mental health situation in adolescents. As the rising incidence was minimally linked to the pandemic in this subgroup, it implies that the mental health crisis could persist in the future regardless of the pandemic. Further investigation is needed to confirm the stressors behind the recent trend and ways to reverse the deterioration in adolescent mental health.

Declining use of healthcare resources

Given the increased demand for depression care during the pandemic, evaluating the pattern in healthcare service use in this critical period is important to identify potential unmet care needs, optimize strategies of service provision, and strengthen the preparedness for future pandemics. Despite the rising incidence, we found that the pandemic substantially reduced the use of inpatient and outpatient services among both newly diagnosed and pre-existing patients. This is consistent with the previous studies in South Africa, South Korea, the United States, and the UK, which estimated 15% to 51% reductions in healthcare resource utilization depending on diagnosis settings [ 15 , 17 , 45 , 46 ]. Most of them were conducted during the early phase of the pandemic with a focus on lockdowns. This may explain the generally greater decline in service use compared with our observations for Hong Kong. Among the pre-existing patients, the reductions in service use were unlikely to represent an immediate improvement in depression outcomes but rather the limited capacity of the system even without mobility restriction to access. This also affected the care delivery for the rising number of new patients during the pandemic, who need the greatest care in the first years of diagnosis but accessed less care than historical controls. The findings therefore revealed a suboptimal service provision in response to the extra care demand generated by the pandemic.

In our study, the service types most impacted by the pandemic were the inpatient bed-days for newly diagnosed patients and outpatient psychiatric visits for pre-existing patients. This is consistent with the observation that most inpatient care occurred at the beginning of the disease course, while outpatient follow-ups became more common as patients stabilized. During the pandemic, however, inpatient resources were reserved for outbreak control, leaving the new patients with inadequate service access. Among pre-existing patients, reluctance to visit clinics owing to fear of getting infected may have discouraged them from attending regular appointments [ 47 ]. Video consultations for SARS-CoV-2 infected cases have been initiated since July 2022, which led to 214,900 consultations for quarantined patients [ 48 ]. “Tele-psychiatry” in the post-pandemic era is worth investigation for its feasibility and effectiveness in extending continuity of care, as it enables follow-ups after hospital discharge and ensures ongoing patient access even without physical attendance.

Strengths and limitations

One of the major strengths of our study is the use of territory-wide longitudinal data with a large sample size, which allowed a quasi-experimental study design. This enabled us to investigate the population-level impact of the pandemic and validate prior findings from smaller community-based studies. The context of Hong Kong also enabled us to study the longer-term impact of the entire pandemic apart from a focus on lockdowns. When studying healthcare service use, our study differed from previous studies by separating patients into nine incident cohorts before analyzing their rates of service use during the follow-up. This allowed us to differentiate the pandemic impact more clearly on new and pre-existing patients, unlike most of the previous studies.

There are also limitations to our study. Firstly, patients’ decision to seek treatment mediates whether their condition is recorded. Systematic differences between age groups in the propensity to seek treatment during different periods rather than differences in the underlying population-level burden may have driven the trends before and after 2020. Secondly, we were unable to stratify the patterns of service use into all-cause and psychiatric-related use in the emergency and inpatient settings since such information was not available in the raw data. Thirdly, though the public sector provides the majority of local healthcare services, patients may have sought help from private doctors especially when the public healthcare system was overwhelmed at the start of the fifth-wave outbreak, possibly leading to underestimated incidence and healthcare service use. Patients who were diagnosed in private clinics before seeking care in the public sector may also be labeled as incident cases later than actual diagnosis date. We therefore performed sensitivity analyses but found no change in the conclusion. Lastly, the findings represent the mixed overall effect of the pandemic macro-environment, but the current time-series study was unable to disentangle the effects of specific contributing factors.

Using ITS analyses from a 9-year cohort study, we found a persistent increase in incidence of medically attended depression over the pandemic period in the overall population, adults, and the older population. However, patients newly diagnosed during the pandemic used fewer resources in their first year of diagnosis than pre-pandemic patients. Pre-existing patients also had immediate decreases in healthcare service use following the pandemic in all diagnosis settings, with a gradual rebound over 3 years. Our findings highlight the need to improve the preparedness in mental health resource planning for future public health crises.

Availability of data and materials

We are unable to directly share the data used in this study since the data custodian, the Hong Kong Hospital Authority who manages the Clinical Data Analysis and Reporting System (CDARS), has not given permission. However, CDARS data can be accessed via the Hospital Authority Data Sharing Portal for research purpose. The relevant information can be found online ( https://www3.ha.org.hk/data ).

Abbreviations

Clinical Data Analysis and Reporting System

• Electronic medical records

Interrupted time-series

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Acknowledgements

We thank Ms. Qiwen Fang and Ms. Yin Zhang for assistance in data retrieval; Dr. Deliang Yang and Ms. Jin Lee for statistical advice and support; we also thank Ms. Lisa Lam for English proofreading.

The study was jointly supported by the Collaborative Research Fund (ACESO, C7154-20GF), the Research Impact Fund (SCAN-2030, R7007-22) granted by the Research Grant Council, University Grants Committee, and the Health and Medical Research Fund (COVID19F04; COVID19F11) granted by the Health Bureau, The Government of the Hong Kong Special Administrative Region, and the Laboratory of Data Discovery for Health (D 2 4H) funded by the Innovation and Technology Commission for data during the pandemic, modeling depression burden between 2014 and 2022. The funders had no active role in the design and conduct of the work and in the analysis, interpretation, and preparation of study reports.

Author information

Vivien Kin Yi Chan and Yi Chai are co-first authors with equal contribution.

Authors and Affiliations

Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

Vivien Kin Yi Chan, Yi Chai, Ian Chi Kei Wong & Xue Li

The Hong Kong Jockey Club Centre for Suicide Research and Prevention, The University of Hong Kong, Hong Kong SAR, China

Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China

Sandra Sau Man Chan

Department of Social Work and Social Administration, Faculty of Social Sciences, The University of Hong Kong, Hong Kong SAR, China

Hao Luo & Martin Knapp

Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK

Care Policy and Evaluation Centre, Department of Health Policy, London School of Economics and Political Science, London, UK

Martin Knapp

School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

Mark Jit, David Makram Bishai & Michael Yuxuan Ni

The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China

Michael Yuxuan Ni

Urban Systems Institute, The University of Hong Kong, Hong Kong SAR, China

Laboratory of Data Discovery for Health (D24H), Hong Kong SAR, China

Ian Chi Kei Wong & Xue Li

School of Pharmacy, Aston University, London, UK

Ian Chi Kei Wong

Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

Advanced Data Analytics for Medical Science (ADAMS) Limited, Hong Kong SAR, China

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Contributions

X Li and ICK Wong conceived the study idea and study design. VKY Chan and Y Chai gathered the data and performed data analyses. All authors provided clinical, statistical, and epidemiological advice and interpreted the results. VKY Chan and X Li wrote and revised the drafts with all authors’ critical comments and revisions. All authors agree to be accountable for all aspects of the work. X Li and ICK Wong obtained the funding and supervised the study conduct. The corresponding authors confirm that all co-authors meet authorship criteria. All authors read and approved the final manuscript.

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Martin Knapp: @knappem

Hao Luo: @HaoLuo429

Ian Chi Kei Wong: @Ian_HKU

Xue Li: @snowly12191

HKU Pharmacy: @HkuPharm

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Correspondence to Ian Chi Kei Wong or Xue Li .

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This study received ethics approval from the Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong Western Cluster (UW 20-218). Informed consent has been waived as the study utilized de-identified data.

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Competing interests

X Li received research grants from the Hong Kong Health and Medical Research Fund (HMRF, HMRF Fellowship Scheme, HKSAR), Research Grants Council Early Career Scheme (RGC/ECS, HKSAR), Janssen, and Pfizer; internal funding from the University of Hong Kong; and consultancy fees from Merck Sharp & Dohme and Pfizer; she is also a non-executive director of Advanced Data Analytics for Medical Science (ADAMS) Limited Hong Kong; all are unrelated to this work. ICK Wong received research funding outside the submitted work from Amgen, Bristol-Myers Squibb, Pfizer, Janssen, Bayer, GSK, Novartis, Takeda, the Hong Kong Research Grants Council, the Hong Kong Health and Medical Research Fund, National Institute for Health Research in England, European Commission, National Health and Medical Research Council in Australia, and the European Union’s Seventh Framework Programme for research and technological development. He has also received consulting fees from IQVIA, the WHO, and expert testimony for Appeal Court in Hong Kong over the past 3 years. He is an advisory member of Pharmacy and Poisons Board, Expert Committee on Clinical Events Assessment Following COVID-19 Immunization, and the Advisory Panel on COVID-19 Vaccines of the Hong Kong Government. He is also a non-executive director of Jacobson Medical Hong Kong, Advanced Data Analytics for Medical Science (ADAMS) Limited, and OCUS Innovation Limited (Hong Kong, Ireland, and UK), and the founder and a director of Therakind Limited (UK). Other authors declared no competing interests related to this study.

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Supplementary Information

Additional file 1: figure s1..

Study schema to illustrate the linkage between analyses.

Additional file 2: Table S1.

Age and sex distribution of patients newly diagnosed with depression between 2014 and 2022. Table S2. Quarterly age-standardized incidence and counts of patients newly diagnosed with depression between 2014 to 2022. Table S3. Quarterly counts of accident & emergency visit among incident cohorts between 2014 and 2022. Table S4. Quarterly counts of inpatient admission among incident cohorts between 2014 and 2022. Table S5. Quarterly counts of inpatient stay among incident cohorts between 2014 and 2022. Table S6. Quarterly counts of outpatient all-cause visit among incident cohorts between 2014 and 2022. Table S7. Quarterly counts of outpatient psychiatric-related visit among incident cohorts between 2014 and 2022. Table S8. Quarterly rates of accident & emergency visit among incident cohorts between 2014 and 2022. Table S9. Quarterly rates of inpatient admission among incident cohorts between 2014 and 2022. Table S10. Quarterly rates of inpatient stay among incident cohorts between 2014 and 2022. Table S11. Quarterly rates of outpatient all-cause visit among incident cohorts between 2014 and 2022. Table S12. Quarterly rates of outpatient psychiatric-related visit among incident cohorts between 2014 and 2022. Table S13. Sensitivity analysis results of ITS analysis of pandemic impact on the ongoing healthcare resource utilization among the 2014-2016 cohorts by adjusting for the fifth-wave outbreak. Table S14. Sensitivity analysis results of ITS analysis of pandemic impact on the ongoing healthcare resource utilization among the 2014-2017 cohorts (changing the defined disease duration prior to the pandemic from 3 years to 2 years).

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Chan, V.K.Y., Chai, Y., Chan, S.S.M. et al. Impact of COVID-19 pandemic on depression incidence and healthcare service use among patients with depression: an interrupted time-series analysis from a 9-year population-based study. BMC Med 22 , 169 (2024). https://doi.org/10.1186/s12916-024-03386-z

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Positive experiences are associated with improved mental health among teenagers, leading to a decreased risk of depression and anxiety, a new study has revealed. Conversely, adverse experiences could heighten the risk of depression, anxiety, and other significant health concerns.

The study headed by Hasina Samji from Simon Fraser University, Canada, made the conclusions after surveying more than 8,800 students from January to March 2022 during the fifth wave of the pandemic, a time that included the highest number of daily COVID-19 case counts.

The participants were Grade 11 students in British Columbia schools. They were asked to recollect their number of positive and adverse experiences till the age of 18. Additionally, the students were asked to assess the severity of their depression and anxiety symptoms and rate their overall mental well-being and life satisfaction.

The results showed that adults who experienced four or more adverse childhood experiences are four times more likely to experience depression and low life satisfaction. They are three times more at risk of anxiety and 30 times more likely to attempt suicide than people with no adverse childhood experiences.

"Adolescents with no adverse childhood experiences (ACE) had significantly better mental health and well-being than those with one or more ACE. Having six or more positive childhood experiences (PCE) was associated with better mental health and well-being in adolescents with and without ACEs. PCEs significantly moderated the association between ACEs and depression. Effect sizes were larger for PCEs than ACEs in relation to depression, mental well-being, and life satisfaction," the researchers wrote in the study published in the journal Child Abuse & Neglect.

"We can't prevent adversity for all young people. We know adversity leads to so many poor outcomes across a whole host of domains, whether it's infectious diseases, or substance use, or obesity, or cardiac disease. When you look at people who have been exposed to four or more adverse childhood experiences, versus fewer or zero adverse experiences—they are at higher risk for almost every poor health outcome," Samji said.

"There is an urgent need to "bring back the village" post-pandemic to support teens and foster a sense of community belonging for young people. As a health-care system, we're often very reactive. Young people tell us that we wait for them to be in crisis before we provide the supports that they need. I really wanted to go upstream and think about what kind of individual level supports, but also structural and systemic supports can we provide earlier," Samji added.

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New Study Finds Physical Fitness Can Improve Mental Health in Children and Young Adults

Researchers in Taiwan tracked children's performance in sporting activities like running, sit-ups and jumping to study how it impacted their mental health diagnoses over time

Charlotte Phillipp is a Weekend Writer-Reporter at PEOPLE. She has been working at PEOPLE since 2024, and was previously an entertainment reporter at The Messenger.

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A new study out of Taiwan has found that children and adolescents who are more physically active have lower rates of mental health disorders .

The study, published in the journal JAMA Pediatrics on Monday, April 29, used anonymous data from the Taiwan National Student Fitness Tests, which measures students' physical fitness activities in school, and compared it with the National Insurance Research Databases, which compiles information about patients' diagnosis and other medical information.

Using data spanning back to 2009 and ending in 2019, researchers studied the data of students aged 10 to 11 years old, following up for at least 3 years to see the progression of their physical fitness in school compared to their mental health diagnosis, especially concerning anxiety disorders, depressive disorders and ADHD/ADD.

The study split the types of physical fitness into several groups, These included cardio fitness, which was measured by each student's performance in an 800-meter (about one mile) run, muscular endurance, measured by how many sit-ups a student could do, muscular power, measured by how far each student's standing jump was, and flexibility, measured by a sit-and-reach test.

A decreased risk of mental health was linked to better performance in each one of the types of fitness, the study found. Cardio fitness — marked by a 30-second faster half-mile — was associated with lower risks of anxiety, depression and ADHD in female students, and lower risks of anxiety and ADHD in male students.

Better muscular endurance, quantified by the study as 5 more sit-ups per minute, was linked to a lower risk of depression and ADHD in girls as well as lower anxiety and ADHD risks in boys. Better muscular performance, meaning almost 8-inch longer standing jumps was associated with lower risks of anxiety and ADHD in girls and reduced anxiety, depression and ADHD in boys.

Researchers also found better performance in each of the fitness activities could be "dose-dependent," meaning that fitness could serve as a preventative measure for mental health disorders.

"This study highlights the potential protective role of cardiorespiratory fitness, muscular endurance and muscular power in preventing the onset of mental disorders," researchers wrote in the study.

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Exercise and mental health and long been linked by scientists, with many experts advocating for kids to become physically active in the wake of the COVID-19 pandemic.

"Physical activity has a small but significant effect on the mental health of children and adolescents ages 6 to 18," the American Psychological Association wrote in April 2020, citing other research that also linked children's long-term mental health to exercise.

"The finding underscores the need for further research into targeted physical fitness programs," the study's authors wrote, noting that these programs could "hold significant potential as primary preventative interventions against mental disorders in children and adolescents."

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• Assessing quality of direct-to-consumer telemedicine in China: a cross-sectional study using unannounced standardised patients
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• Zhen Zeng 1 ,
• Dong (Roman) Xu 2 ,
• Yiyuan Cai 3 ,
• http://orcid.org/0000-0002-7943-4041 Wenjie Gong 1 , 4 , 5
• 1 HER Team and Department of Maternal and Child Health, Xiangya School of Public Health , Central South University , Changsha , China
• 2 SMU Institute for Global Health (SIGHT), School of Health Management and Dermatology Hospital , Southern Medical University (SMU) , Guangzhou , China
• 3 Department of Epidemiology and Health Statistics, School of Public Health , Guizhou Medical University , Guiyang , China
• 4 Institute of Applied Health Research , University of Birmingham , Birmingham B15 2TT , UK
• 5 Department of Psychiatry , University of Rochester , Rochester , New York , USA
• Correspondence to Professor Wenjie Gong, HER Team and Department of Maternal and Child Health, Xiangya School of Public Health, Central South University, Changsha, Hunan, 410078, China; gongwenjie{at}csu.edu.cn

Direct-to-onsumer telemedicine (DTCT) has become popular as an alternative to traditional care. However, uncertainties about the potential risks associated with the lack of comprehensive quality evaluation could influence its long-term development. This study aimed to assess the quality of care provided by DTCT platforms in China using unannounced standardised patients (USP) between July 2021 and January 2022. The study assessed consultation services on both hospital and enterprise-sponsored platforms using the Institute of Medicine quality framework. It employed 10 USP cases, covering conditions such as diabetes, asthma, common cold, gastritis, angina, low back pain, child diarrhoea, child dermatitis, stress urinary incontinence and postpartum depression. Descriptive and regression analyses were employed to examine platform characteristics and compare quality across platform types. The results showed that of 170 USP visits across 107 different telemedicine platforms, enterprise-sponsored platforms achieved a 100% success in access, while hospital-sponsored platforms had a success rate of only 47.5% (56/118). Analysis highlighted a low overall correct diagnosis rate of 45% and inadequate adherence to clinical guidelines across all platforms. Notably, enterprise-sponsored platforms outperformed in accessibility, response time and case management compared with hospital-sponsored platforms. This study highlights the suboptimal quality of DTCT platforms in China, particularly for hospital-sponsored platforms. To further enhance DTCT services, future studies should compare DTCT and in-person care, aiming to identify gaps and potential risks associated with using DTCT as alternatives or supplements to traditional care. The potential of future development in enhancing DTCT services may involve exploring the integration of hospital resources with the technology and market capabilities of enterprise-sponsored platforms.

• Health services research
• Quality measurement
• Performance measures
• Patient-centred care

https://doi.org/10.1136/bmjqs-2024-017072

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Introduction

Direct-to-consumer telemedicine (DTCT) signifies a revolutionary global healthcare delivery model. It involves patients independently initiating medical services remotely, engaging directly with healthcare providers through text messaging or video/phone calls. By bypassing traditional intermediaries like referral clinicians or facilitators, DTCT empowers patients to access medical care swiftly and efficiently. 1 In China, DTCT is burgeoning, boasting over 1700 registered platforms, 2 each serving as an individual website or application for DTCT services. These platforms are categorised into two main types: hospital sponsored and enterprise sponsored. Hospital-sponsored platforms, associated with single physical hospitals, primarily use in-house medical staff and offer streamlined functions due to resource limitations. In contrast, enterprise-sponsored platforms, supported by larger corporations, provide access to a wider network of licensed physicians and offer a diverse range of functions with sophisticated user interfaces. 3 Despite enhanced accessibility and convenience compared with in-person care, DTCT faces quality challenges, such as communication difficulties and antibiotic misuse. 4 5 However, research on DTCT quality remains limited, especially in the context of China. To address this gap, our study employs unannounced standardised patients (USPs)—individuals trained and validated to portray specific medical conditions in a consistent and standardised manner 6 7 —to assess DTCT quality in China across different platform types based on the Institute of Medicine (IOM) quality framework.

This cross-sectional study examined both types of DTCT platforms that offered Chinese language services. The study was conducted between July 2021 and January 2022. Prior informed consent was waived due to minimal risk, and all analyses were performed on fully deidentified aggregated data. 8

To assess consultation service quality, we employed 10 different USP cases, each representing a specific medical condition (details in online supplemental eMethods and online supplemental example of a USP case ). Following thorough training and assessment, we selected 15 qualified USPs from the initial pool of 25 candidates. Each case was assigned at least one USP. As USPs’ initial requests for physician consultations could be denied for various reasons, mirroring real-world scenarios, each case made consultation requests until they completed at least five consultations on each platform type. The USPs captured screenshots and recorded the consultation process, including any failed attempts and reasons for failure. We evaluated the access success rate and assessed consultation quality using the IOM quality framework 9 ( table 1 ).

Supplemental material

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Quality outcome indicators

We conducted descriptive and regression analyses to evaluate platform characteristics and quality outcomes. Regression analyses compared quality differences using ordinary least squares and logistic regressions, with hospital-sponsored platforms as the benchmark and controlling for patient case fixed effects. Adjusted differences and 95% CIs were reported, adjusted for platform-level clustering. Statistical significance was set at α=0.05. Stata SE (V.16.0) was used for all analyses.

Our study involved 170 visits, with 52 visits on 10 enterprise-sponsored platforms and 118 visits on 97 hospital-sponsored platforms (summarised in online supplemental eTable 1 ). The overall access rate was 63.5% (108/170). Enterprise-sponsored platforms achieved a 100% access rate (52/52), significantly higher than hospital-sponsored ones (56/118, 47.5%) (p<0.001). Common reasons for unsuccessful consultations included incomplete functions, like platforms claiming to offer DTCT services but lacking an accessible feature for initiating online consultations with physicians (25/62, 40.3%), and no response (13/62, 21.0%).

Of 108 successful consultations, 49 consultations (45%) received a correct diagnosis, while adherence to published guidelines was low for consultation (15%) and management decisions (31%). On average, physicians took 3 hours and 47 min to respond, with the total interaction time spanning 12 hours and 19 min. After controlling for disease case fixed effects and adjusting SEs for clustering at platform level, enterprise-sponsored platforms had higher rates of completed management decisions, shorter response times and higher costs ( table 2 ).

Comparison on main quality outcomes between platform types for successful consultations

In this study, we rigorously evaluated the quality of care across two types of DTCT platforms in China using USPs. With 108 successful visits out of 170 attempts, we found a diagnostic accuracy of approximately 45%, along with a decline in completion rates for recommended management decisions to 31%. This may be linked to the limited inquiries during USP encounters, with clinicians asking only about 15% of recommended consultation questions per visit. Besides traditional quality metrics, the timeliness of DTCT services is concerning, with a response time of 3 hours and 47 min and an overall interaction time of 12 hours and 19 min. In China, DTCT predominantly operates asynchronously, leading to these extended durations. Despite offering a more flexible alternative to in-person counselling by eliminating the need for travel, prolonged waiting times may still impact user satisfaction and the perceived effectiveness of DTCT platforms. Future research should prioritise enhancing the timeliness of DTCT services to ensure prompt access and timely interactions. The patient-centredness score averaging 2.4, indicating a medium to low level of patient-centred care, 10 is potentially influenced by less satisfactory outcomes discussed earlier in terms of effectiveness, safety and timeliness. These findings raise concerns about how effective DTCT services are. Further evaluation, including a direct comparison with in-person care, is needed for a clearer understanding of their quality. This can guide improvement measures, especially when DTCT services act as alternatives or supplements to traditional in-person care.

Notably, enterprise-sponsored platforms achieved 100% access success, surpassing hospital-sponsored ones at 47.5%. They exhibited superior performance in response times and completion rates for management decisions. Despite recent growth and policy support, 3 hospital-sponsored platforms seem to be in early developmental stages, potentially limiting medical resource accessibility. These findings challenge a marketing survey suggesting a preference for hospital-sponsored platforms, 11 emphasising higher access denial risks and less timely responses for consumers on these platforms.

This study was limited by the use of a uniform USP for each case. Using standardised scenarios with different USPs potentially allows for a comprehensive assessment of equity. However, due to constraints imposed by scripted scenarios in our study, this aspect was not explored.

Our study highlights the suboptimal quality of DTCT in China, specifically disparities between hospital-sponsored and enterprise-sponsored platforms. These findings likely echo broader challenges and principles inherent in DTCT globally. As DTCT gains momentum after COVID-19, future research becomes critical to effectively address these issues.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by Xiangya School of Public Health (IRB No XYGW-2021-37). Prior informed consent was waived due to minimal risk and no individually identifiable information on physicians.

Acknowledgments

We sincerely thank Xiaohui Wang, Yaolong Chen, Yun Lu, Xiaojing Fan, Zhongliang Zhou, Jay Pan, and Chengxiang Tang for their unwavering leadership in development and management the SP cases. We also apperciate Lu Liu, Chunping Li, and Huanyu Hu for their their diligent efforts as project assistants, as well as all the standardized patients and study coordinators for their hard work.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

Contributors WG conceived the study. ZZ coordinated the daily implementation of this study under the supervision of DRX, YC and WG. ZZ carried out data analysis and composed the initial manuscript draft, receiving guidance from WG and DRX. All authors contributed to critical review of the manuscript and approved the final draft.

Funding This study was funded by China Medical Board (20-368), Swiss Agency for Development and Cooperation (81067392) and the National Natural Science Foundation of China (82273643).

Competing interests None declared.

Provenance and peer review Not commissioned; internally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Reproductive rights in America

What's at stake as the supreme court hears idaho case about abortion in emergencies.

Selena Simmons-Duffin

The Supreme Court will hear another case about abortion rights on Wednesday. Protestors gathered outside the court last month when the case before the justices involved abortion pills. Tom Brenner for The Washington Post/Getty Images hide caption

The Supreme Court will hear another case about abortion rights on Wednesday. Protestors gathered outside the court last month when the case before the justices involved abortion pills.

In Idaho, when a pregnant patient has complications, abortion is only legal to prevent the woman's death. But a federal law known as EMTALA requires doctors to provide "stabilizing treatment" to patients in the emergency department.

The Biden administration sees that as a direct conflict, which is why the abortion issue is back – yet again – before the Supreme Court on Wednesday.

The case began just a few weeks after the justices overturned Roe v. Wade in 2022, when the federal Justice Department sued Idaho , arguing that the court should declare that "Idaho's law is invalid" when it comes to emergency abortions because the federal emergency care law preempts the state's abortion ban. So far, a district court agreed with the Biden administration, an appeals court panel agreed with Idaho, and the Supreme Court allowed the strict ban to take effect in January when it agreed to hear the case.

Supreme Court allows Idaho abortion ban to be enacted, first such ruling since Dobbs

The case, known as Moyle v. United States (Mike Moyle is the speaker of the Idaho House), has major implications on everything from what emergency care is available in states with abortion bans to how hospitals operate in Idaho. Here's a summary of what's at stake.

1. Idaho physicians warn patients are being harmed

Under Idaho's abortion law , the medical exception only applies when a doctor judges that "the abortion was necessary to prevent the death of the pregnant woman." (There is also an exception to the Idaho abortion ban in cases of rape or incest, only in the first trimester of the pregnancy, if the person files a police report.)

In a filing with the court , a group of 678 physicians in Idaho described cases in which women facing serious pregnancy complications were either sent home from the hospital or had to be transferred out of state for care. "It's been just a few months now that Idaho's law has been in effect – six patients with medical emergencies have already been transferred out of state for [pregnancy] termination," Dr. Jim Souza, chief physician executive of St. Luke's Health System in Idaho, told reporters on a press call last week.

Those delays and transfers can have consequences. For example, Dr. Emily Corrigan described a patient in court filings whose water broke too early, which put her at risk of infection. After two weeks of being dismissed while trying to get care, the patient went to Corrigan's hospital – by that time, she showed signs of infection and had lost so much blood she needed a transfusion. Corrigan added that without receiving an abortion, the patient could have needed a limb amputation or a hysterectomy – in other words, even if she didn't die, she could have faced life-long consequences to her health.

Attorneys for Idaho defend its abortion law, arguing that "every circumstance described by the administration's declarations involved life-threatening circumstances under which Idaho law would allow an abortion."

Ryan Bangert, senior attorney for the Christian legal powerhouse Alliance Defending Freedom, which is providing pro-bono assistance to the state of Idaho, says that "Idaho law does allow for physicians to make those difficult decisions when it's necessary to perform an abortion to save the life of the mother," without waiting for patients to become sicker and sicker.

Still, Dr. Sara Thomson, an OB-GYN in Boise, says difficult calls in the hospital are not hypothetical or even rare. "In my group, we're seeing this happen about every month or every other month where this state law complicates our care," she says. Four patients have sued the state in a separate case arguing that the narrow medical exception harmed them.

"As far as we know, we haven't had a woman die as a consequence of this law, but that is really on the top of our worry list of things that could happen because we know that if we watch as death is approaching and we don't intervene quickly enough, when we decide finally that we're going to intervene to save her life, it may be too late," she says.

2. Hospitals are closing units and struggling to recruit doctors

Labor and delivery departments are expensive for hospitals to operate. Idaho already had a shortage of providers, including OB-GYNS. Hospital administrators now say the Idaho abortion law has led to an exodus of maternal care providers from the state, which has a population of 2 million people.

Three rural hospitals in Idaho have closed their labor-and-delivery units since the abortion law took effect. "We are seeing the expansion of what's called obstetrical deserts here in Idaho," said Brian Whitlock, president and CEO of the Idaho Hospital Association.

Since Idaho's abortion law took effect, nearly one in four OB-GYNs have left the state or retired, according to a report from the Idaho Physician Well-Being Action Collaborative. The report finds the loss of doctors who specialize in high-risk pregnancies is even more extreme – five of nine full time maternal-fetal medicine specialists have left Idaho.

Administrators say they aren't able to recruit new providers to fill those positions. "Since [the abortion law's] enactment, St. Luke's has had markedly fewer applicants for open physician positions, particularly in obstetrics. And several out-of-state candidates have withdrawn their applications upon learning of the challenges of practicing in Idaho, citing [the law's] enactment and fear of criminal penalties," reads an amicus brief from St. Luke's health system in support of the federal government.

"Prior to the abortion decision, we already ranked 50th in number of physicians per capita – we were already a strained state," says Thomson, the doctor in Boise. She's experienced the loss of OB-GYN colleagues first hand. "I had a partner retire right as the laws were changing and her position has remained open – unfilled now for almost two years – so my own personal group has been short-staffed," she says.

ADF's Bangert says he's skeptical of the assertion that the abortion law is responsible for this exodus of doctors from Idaho. "I would be very surprised if Idaho's abortion law is the sole or singular cause of any physician shortage," he says. "I'm very suspicious of any claims of causality."

3. Justices could weigh in on fetal "personhood"

The state of Idaho's brief argues that EMTALA actually requires hospitals "to protect and care for an 'unborn child,'" an argument echoed in friend-of-the-court briefs from the U.S. Conference of Catholic Bishops and a group of states from Indiana to Wyoming that also have restrictive abortion laws. They argue that abortion can't be seen as a stabilizing treatment if one patient dies as a result.

Thomson is also Catholic, and she says the idea that, in an emergency, she is treating two patients – the fetus and the mother – doesn't account for clinical reality. "Of course, as obstetricians we have a passion for caring for both the mother and the baby, but there are clinical situations where the mom's health or life is in jeopardy, and no matter what we do, the baby is going to be lost," she says.

The Idaho abortion law uses the term "unborn child" as opposed to the words "embryo" or "fetus" – language that implies the fetus has the same rights as other people.

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The science of ivf: what to know about alabama's 'extrauterine children' ruling.

Mary Ziegler , a legal historian at University of California - Davis, who is writing a book on fetal personhood, describes it as the "North Star" of the anti-abortion rights movement. She says this case will be the first time the Supreme Court justices will be considering a statute that uses that language.

"I think we may get clues about the future of bigger conflicts about fetal personhood," she explains, depending on how the justices respond to this idea. "Not just in the context of this statute or emergency medical scenarios, but in the context of the Constitution."

ADF has dismissed the idea that this case is an attempt to expand fetal rights. "This case is, at root, a question about whether or not the federal government can affect a hostile takeover of the practice of medicine in all 50 states by misinterpreting a long-standing federal statute to contain a hidden nationwide abortion mandate," Bangert says.

4. The election looms large

Ziegler suspects the justices will allow Idaho's abortion law to remain as is. "The Supreme Court has let Idaho's law go into effect, which suggests that the court is not convinced by the Biden administration's arguments, at least at this point," she notes.

Trump backed a federal abortion ban as president. Now, he says he wouldn't sign one

Whatever the decision, it will put abortion squarely back in the national spotlight a few months before the November election. "It's a reminder on the political side of things, that Biden and Trump don't really control the terms of the debate on this very important issue," Zielger observes. "They're going to be things put on everybody's radar by other actors, including the Supreme Court."

The justices will hear arguments in the case on Wednesday morning. A decision is expected by late June or early July.

Correction April 23, 2024

An earlier version of this story did not mention the rape and incest exception to Idaho's abortion ban. A person who reports rape or incest to police can end a pregnancy in Idaho in the first trimester.

• Abortion rights
• Supreme Court