research paper on relative strength index

The Relative Strength Index (RSI) to Monitor GDP Variations. Comparing Regions or Countries from a New Perspective

• First Online: 28 June 2022

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• Carlos Maté 7  

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 445))

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The Relative Strength Index (RSI) is one key oscillator in the technical analysis used basically to trade in equity markets such as FOREX or stock markets. However, most of its potential is unknown. This paper reviews the RSI definition to adapt it to the context of quarterly GDP variations in any region or country, showing a detailed example and several applications. It highlights its uses and provides a new insight to compare economies based on this macroeconomic RSI. The extension to other macroeconomics indicators such as inflation or unemployment rates is proposed as well as further research issues.

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Acknowledgements

I would like to thank Leandro Pardo for his friendship and conversations about Statistics and Life. Our lives were linked through Professor Sixto Rios who advised and supervised both on 1980, July 1. Special thanks to the editors Narayanaswamy Balakrishnan, María Ángeles Gil, Nirian Martín, Domingo Morales, and María del Carmen Pardo for their invitation to contribute to this monograph.

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Carlos Maté

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Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada

Narayanaswamy Balakrishnan

Department of Statistics and OR and TM, University of Oviedo, Oviedo, Asturias, Spain

María Ángeles Gil

Department of Financial and Actuarial Economics & Statistics, Complutense University of Madrid, Madrid, Spain

Nirian Martín

Department of Statistics, Mathematics and Informatics, Miguel Hernández University of Elche, Elche, Spain

Domingo Morales

Department of Statistics and Operational Research, Complutense University of Madrid, Madrid, Spain

María del Carmen Pardo

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Maté, C. (2023). The Relative Strength Index (RSI) to Monitor GDP Variations. Comparing Regions or Countries from a New Perspective. In: Balakrishnan, N., Gil, M.Á., Martín, N., Morales, D., Pardo, M.d.C. (eds) Trends in Mathematical, Information and Data Sciences. Studies in Systems, Decision and Control, vol 445. Springer, Cham. https://doi.org/10.1007/978-3-031-04137-2_9

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The Encyclopedia of the Indicator RSI (Relative Strength Index)

Corporate Governance

ISSN : 1472-0701

Article publication date: 5 April 2013

Rudik, N.I. (2013), "The Encyclopedia of the Indicator RSI (Relative Strength Index)", Corporate Governance , Vol. 13 No. 2, pp. 218-219. https://doi.org/10.1108/14720701311316698

Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

Investors and traders use technical analysis to study price behaviour and estimate upcoming price movements of different financial instruments. This type of analysis is generally applied across all segments of the financial market, and is preferred by traders and investors who deal in the futures market and Forex. Technical analysis employs a wide variety of tools, including moving average and trend lining as well as more complex techniques (e.g., Elliott wave principle; Gann trading methods). The relative strength index (RSI) is one of the most popular technical analysis tools today, used by many investors and traders on a daily basis.

There is a great deal of literature about the RSI; however, most authors focus primarily on the graphic analysis of the RSI signals, on levels of support/resistance and on divergence with the base price. The Encyclopedia of the Indicator RSI (Relative Strength Index) takes a different approach, and instead analyses the relationship between the RSI values and the price movement of the underlying asset. In essence, the book examines the RSI overbought/oversold indicators and the price of the asset, and then analyses the relationship between RSI and the asset price changes within a time interval. When the RSI leaves the overbought/oversold area, the underlying asset price change may move counter to the dominant trend originally behind the initial growth or decline of the RSI.

The book describes financial instruments by category and type: commodity futures, metals futures, agricultural futures, Forex, shares index, and spreads and futures for bonds and shares. With the underlying assumption that the price behaviour of different financial instruments varies, the book aims to test the relationship between the price change and the RSI indicator for each financial instrument.

The book is well organised and consists of nine sections. The first section provides a brief description of the RSI indicator and RSI analysis; at the same time, the author discusses the key principles of using the RSI. This level of detail is exacting, and reflects the author's practical experience with the RSI. The book also includes a significant amount of statistical data, charts and graphs. The author's research on each financial instrument is accompanied by concise, user‐friendly tables.

Sections two through nine are dedicated to individual financial instruments. Each section provides a description of the specific financial instrument as well as the structure of using the RSI indicator for each category of financial instrument. This approach allows the reader to better understand and interpret the presented data. The section on futures spread deserves special mention, as the existing literature on futures spread tends not to utilise the RSI indicator to estimate spread price movements. The author suggests a new method of analysing the RSI, which may be used for underlying assets of any type, including using a large sample size, should this amount of data be required by potential investors. In addition, the book contains the most recent data with respect to financial markets.

Despite the technical nature of the subject matter, the book is fairly easy to navigate. The author demonstrates a superb grasp of financial instruments and is successful in presenting the materials in a clear and concise manner. This book will be of considerable interest to traders, investors, and anyone who wishes to study the RSI in more detail.

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Trend identification with the relative strength index (RSI) technical indicator -A conceptual study

2021, Journal of Management Research and Analysis

We all must agree that the word "trend" is now the buzzword of the stock market. As a part of investment strategy and analysis, it is always suggested that the investors should keep an eye on medium-term and short-term changes in addition to longer-term (secular) patterns. Traders and investors use the RSI as a momentum indicator. Overbought and oversold situations are indicated by RSI values between 70 and 30. Over the past two decades, several techniques have been developed to analyze NIFTY 50 data for investment purposes. In this paper, we have estimated the returns by looking at the two trends i.e., 50-50 and 60-40. In addition to this, how to trade and back-test our strategy is also explained. Applying these two RSI strategies to the NIFTY 50 chart revealed that 50-50 offers a higher long-term return, while 60-40 provides a superior short-term return. Finally, the strategies' returns F-statistics and P-values were calculated and analyzed to determine their significance level and acceptability. This is an Open Access (OA) journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

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Trend identification with the relative strength index (RSI) technical indicator –A conceptual study

[ ] Ashok Kumar Panigrahi [ 1 ]

Email: [email protected]

Designation:

Associate Professor

[ ] Kushal Vachhani [ 1 ]

[ ] Suman Kalyan Chaudhury [ 2 ]

Faculty Member

Dept. of Technology Management, Narsee Monjee Institute of Management Studies Dhule, Maharashtra India

Dept. of Business Administration, Berhampur University Brahmapur , Odisha India

We all must agree that the word "trend" is now the buzzword of the stock market. As a part of investment strategy and analysis, it is always suggested that the investors should keep an eye on medium-term and short-term changes in addition to longer-term (secular) patterns. Traders and investors use the RSI as a momentum indicator. Overbought and oversold situations are indicated by RSI values between 70 and 30. Over the past two decades, several techniques have been developed to analyze NIFTY 50 data for investment purposes. In this paper, we have estimated the returns by looking at the two trends i.e., 50-50 and 60-40. In addition to this, how to trade and back-test our strategy is also explained. Applying these two RSI strategies to the NIFTY 50 chart revealed that 50-50 offers a higher long-term return, while 60-40 provides a superior short-term return. Finally, the strategies' returns F-statistics and P-values were calculated and analyzed to determine their significance level and acceptability.

Introduction

Introduction to rsi technical indicator.

The Relative Strength Index (RSI) is a J. Wilder-invented momentum oscillator that estimates price changes by measuring how quickly and in which direction prices move. The RSI may be anything between 0 and 100. According to author Donald J. Wilder, RSI is overbought when it rises over 70, and oversold when it falls below 30. There are several ways to use swinging points, divergences, and crossing the centreline to produce signals. Furthermore, the RSI is often utilized to detect the unfolding trend. It is very important to pay attention to the main trend to guarantee those indicator findings are correctly interpreted. According to Constance Brown, CMT, a well-known market analyst, a reading of the RSI that is much higher than the historical average would indicate a bullish trend, while a reading that is significantly lower than the historical average would signal a bearish trend. 1

Calculation of RSI

To make things simpler, RSI has been broken down into its basic components: RS, Average Gain, and Average Loss. Wilder suggested the 14 periods in his book as the default period lengths. If there are no losses, there are no positive values to reflect them. To get initial estimates of average gain and average loss, simple 14-period averaging is employed:

FAG= Sum of Gains over the past 14 periods / 14

FAL= Sum of Losses over the past 14 periods / 14

Where FAG=first average gain and FAL=first average loss

In the second part of calculations, it is based on the prior averages and the current gain loss:

AG= [(previous Average Gain) x 13 + current Gain] / 14.

AL= [(previous Average Loss) x 13 + current Loss] / 14.

Where, AG=average gain and AL=average loss

Smoothing techniques comparable to those used to build an exponential moving average are utilized in this case. In addition to being more precise as computation time increases, RSI readings also become more consistent. 2

Scope of research

Despite the vast amount of information available about stock trading and investing, new traders and investors often lose money in the stock market owing to a lack of knowledge about trading and investing in stocks using technical indicators. The RSI technical indicator and two strategies for modifying the RSI's default parameters were the subjects of our paper. By presenting knowledge of market trends and by utilizing the RSI indicator, these papers demonstrate how to find particular market trends. These two strategies have also been applied to the NIFTY 50 index chart, and the resulting trend has been studied using two modified RSI strategies mentioned in the paper. 3

Research methodology

Trends and the RSI technical indicator were two of the most significant topics we discussed in this paper. We utilized trading view.com, a website that allows traders and investors to analyze charts and apply technical indicators to them. 4 I gathered all the secondary data from the Yahoo Finance website to determine the NIFTY 50 indexs' closing price. Excel is used to compute RSI readings, and the resulting calculations are generated. Because TradingView.com offers free charting, these new RSI strategies may be used in observational research. We have described how to apply the RSI technical indicator to a chart and then how to analyze a trend using a new RSI technique in the paper that follows. To compute the F-test, we first estimated the return in a particular year of both strategies and then calculated the F- statistical value and P-value in excel.

Literature Review

The currency market served as a platform for Bing Anderson and Shuyun Li to explore market efficiency (2015). If the market is efficient, there will be no profitability for the RSI, which implies that the market is not efficient. Conversely, if the market is not efficient, then it must have profitability, which implies that the market is efficient. While these researchers found that over the last decade when an RSI equal to 30 is used to indicate a buying opportunity and an

RSI of over 70 is used to signal a selling opportunity, RSI does not provide profitable trading but rather results in small losses. According to the paper, they note that the profitability of an indicator diminishes when well-known technical indicators and conventional parameter configurations are used by practitioners. As well, the study's advice was also passed on to practitioners, who were advised to pursue the "unpaved" route, and to academics, who found the study's conclusions to apply to the market efficiency theory. 5

Murtadha Alhilfi (2019) said in his study that one method to assist speculators in making sound trading decisions is to use technical analysis through the RSI. His objective is to show the value of technical analysis by using the RSI in generating speculations, forecasting future market changes, and contributing to the process of making critical decisions by providing suggestions. Using the Relative Strength Index (RSI) enables the Bank of Baghdad to maintain a steady position on the Iraqi Stock Exchange. By offering a proactive suggestion, the RSI helped speculators at the Bank of Baghdad on the Iraqi Stock Exchange. He computed and used RSI analysis to the Bank of Baghdad's stocks and found that RSI is a useful and effective technique for doing technical analysis on the bank's equities. RSI allows traders at the Iraq Stock Exchange's bank of Baghdad to anticipate market trends and forecast future prices. 6

Dr. Yogesh D Mahajan and Dr. Krishnamurthy Inumula (2015) used the RSI AND MACD technical indicators to analyze companies in the information technology, financial, automotive, and fast-moving consumer goods (FMCG) sectors listed on Indian stock exchanges such as the NSE. To increase the effectiveness of the MACD and RSI indicators, they were simulated; the simulations changed the parameters of both indicators. This research demonstrates empirically that both the optimum MACD and optimal RSI indicators are advantageous for creating a successful investing strategy and accepts the concept that optimized MACD and RSI indicators are much more lucrative than the conventional buy-and-hold strategy. The findings indicate that optimizing the MACD and RSI indicators significantly reduced the number of trading sessions. 7

Giner Alor-Hernandez, Rubén Posada-Gomez, Guillermo Cortes-Robles, Alejandro Rodrguez- González, Fernando Guldrs-Iglesias, Ricardo Colomo-Palacios, Juan Miguel Gomez-Berbis, and Enrique Jimenez-Domingo (2010) conducted RSI-based research intending to develop systems capable of investing automatically This stock market simulation was built entirely using RSI financial indicators and heuristic methods since the formula was derived using these techniques. Additionally, the researchers recommended four additional studies that might be conducted based on the current results. 8

Adrian Taran-Morosan (2011) examined the same set of data using both traditional and modified RSI. He also incorporated trading volume in the method's calculating formula. Finally, findings acquired using the indicator's traditional form will be compared to those obtained using the modified version. He found that, in comparison to the original form, his version resulted in a greater advantage when a different, even opposing interpretation was used. And, in the alternative case, it resulted in much larger losses. This implies that the study indicates that short-term trends will persist, at least temporarily. It seems as if the conventional view is incorrect, while the alternative understanding produces beneficial results. Using the RSI version that we suggest yields the best results.

Dr. Bhargavi. R, Dr. Srinivas Gumparthi, and Anith. R (2017) evaluated short-term investment performance by computing the 14-day RSI for chosen short-term investment stocks and determining if the 14-day RSI is equal to or greater than the original 14-day RSI. They noticed that investors suffered as a result of portfolio securities being mismanaged. Selecting inappropriate securities may result in investor losses. And to address this issue, they recommended using the RSI tool and incorporating it into the stock-picking process. They discovered that RSI can be utilized to construct portfolios and make short- and long-term investment choices. It predicts the buy and sells signals for a variety of stocks accurately. The P/E ratio is a more accurate indicator of profitability than earnings per share. Their study emphasized the short- and long-term investment potential of the twenty companies. They concluded as a result of their study.

Firuz Kamalov and Ikhlaas Gurrib (2019) use an improved version of the Relative Strength Index (RSI) model to forecast currency pairs where one of the instruments is the US dollar. A new model (AdRSI) was constructed and implemented by taking daily data spanning 2001– 2015 into consideration. When it comes to energy markets, their results show that the risk was considerable; in contrast, the annualized risk for the Chinese yuan was quite low. AdRSI's new model provided an impressive increase in annualized returns, a decrease in the number of transactions, and a significant increase in annualized risk. Concerning reward-to-volatility, the buy-and-hold investment strategy came out on top. 9 , 1

Need of research

When we conducted a literature analysis of many papers, we found that similar types of studies had been conducted on the RSI subject. Various authors have addressed the use of RSI indicators on stock charts and conducted a comparative study. Additionally, the authors utilized other indicators within RSI and conducted a research study. RSI is a momentum indicator that provides insight into market trends. However, no study on the subject of trend analysis using RSI has been performed. As a result, we chose to write a research paper on trend analysis utilizing RSI.

Many traders and investors lose money in the stock market by using technical indicators. When it comes to trading, new traders make one common mistake: they do not follow the market's trend. To put it another way, whenever a trader wants to enter a trade, traders must first determine if the market is trending upward or downward. If there is an uptrend, traders should take a long position, and if there is a downtrend, traders should take a short position. Similarly, when it comes to short-term trends, investors make mistakes as well. By analyzing the NIFTY 50 index chart over the past 20 years, we were able to develop two methods for identifying market trends.

Steps To Add Rsi Indicator On Chart

STEP-1: We have explained both strategies using a weekly time frame so a selection of weekly time frames is necessary.

(Selection of weekly time frame) (https://in.tradingview.com/)

Step-2: In this step, we have to click the indicators section to add RSI to the chart.

(Adding RSI indicator to chart) (https://in.tradingview.com/)

STEP-3: After selection of indicator section in that drop down menu will be shown in that in search section type “RSI”. Then select relative strength index from built-in sections. Then RSI will be added to the chart.

(Searching and selection of RSI indicator in indicator tab) (https://in.tradingview.com/)

After applying all the three steps one can see Figure 4 will appear.

(Chart after applying RSI on the chart) (https://in.tradingview.com/)

(Default RSI on the chart) (https://in.tradingview.com/)

(Default setting of RSI length) (https://in.tradingview.com/)

(Default setting of RSI bands (https://in.tradingview.com/)

(50-50 RSI chart) (https://in.tradingview.com/)

(50-50 strategy settings) (https://in.tradingview.com/)

(uptrend using 50-50 strategy) (https://in.tradingview.com/)

(downtrend using 50-50 strategy) (https://in.tradingview.com/)

(60-40 RSI chart) (https://in.tradingview.com/)

(60-40 settings) (https://in.tradingview.com/)

(uptrend using 60-40 strategy) (https://in.tradingview.com/)

(downtrend using 60-40 strategy) (https://in.tradingview.com/)

Default RSI

To help investors/traders in dealing with a variety of circumstances, one should establish RSI parameters in advance to achieve your analytical goals for the situation. The default RSI period is 14 days. But we may utilize the RSI to detect overbought and oversold conditions for a limited period. Since the RSI rises, it is better at identifying wide market changes. Price changes affect the RSI's range-bound behavior (0-100). The upper/lower bars denote the 70/30 levels accordingly. As seen in Figure 5 below, applying RSI to the chart and figure produces the default view. Figure 6 , Figure 7 show the RSI's default settings.

Strategy-1 (RSI 50-50)

The RSI's default settings include a 14-period length and an upper and lower band of 70, and We will change the parameters in this method and see an example of how to apply this strategy in practice. In this approach, the length will remain constant; the only change will be in the values of the lower and upper bands. Instead of the existing values, the new lower and upper bands will have values of 50 and 50, respectively. We will apply these strategies on weakly time frame of NIFTY 50. We will now learn how to use the 50-50 approach to forecast the direction of a trend. Follow the steps below to get a better understanding of the strategy:

STEP-1: Apply new settings which are upper band=50 and lower band=50. When looking at the RSI chart, one can notice one single line as shown in the Figure 9 . To set up the new preferences, do so as indicated in Figure 10 .

STEP-2: Now analyze the RSI chart which one can find below the candlestick chart. In that chart whenever the value of RSI closes above 50, then we will consider the beginning of an uptrend. And whenever the value of RSI closes below 50, we will consider the beginning of a downtrend. Figure 10 is an example of an uptrend, in which the uptrend starts with candle no.1 when the RSI closes above 50 and terminates with candle no.2 when the RSI value is near or below 50, respectively. Similar to that, we can analyze a downtrend in Figure 11 , in which candle no.1 represents the beginning of the downtrend and candle no.2 represents the end of the downtrend when the RSI value is below 50.

Strategy-2 (RSI 60-40)

Similarly, to the 50-50 strategy, we will maintain the default 14-period length setting in the 60 – 40 approach. Only the parameters for the lower and upper bands will be altered. The upper and lower bands will now be 60 and 40, respectively. In the same manner, as discussed in 50-50 we will apply these strategies in a weakly time frame of NIFTY 50. We'll now examine how to use the 60-40 strategy to forecast the direction of a trend. To get a better understanding of the method, consider the following steps:

STEP-1: Apply the updated settings, which have upper band=60 and lower band=40. In the RSI chart, one can see that there are two lines: the top line with a dashed line represents the upper band 60, and the lower line with a thick line represents the lower band 40, as shown in Figure 12 . To configure the new preferences, follow the steps shown in Figure 13 .

STEP-2: As with the 50-50 strategy, one can find the RSI chart below the candlestick chart. When the RSI value closes above 60, we believe that a new uptrend has started; when the RSI value closes below 40, we consider that a new downtrend has begun. Figure 14 illustrates an uptrend in which the uptrend begins with candle no.1 as the RSI value closes above 60 and ends with candle no.2 as the RSI value closes below or around 60. Similarly, as shown in Figure 15 , a downtrend begins with candle no.1 as the RSI value closes below 40 and ends with candle no.2 as the RSI value closes above or around 40.

How To Trade Using 50-50 And 60-40 Strategy

As previously stated, if the RSI closes above 50 during an uptrend, the trader or investor must enter the trade; however, how long the trader or investor must remain in the trade is determined by the risk-reward ratio and other criteria listed below in this section; similarly, the 60-40 strategy follows the same rules.

When a trader or investor enters a downtrend when the RSI falls below 50, the trader or investor must decide how long to remain in the trade. Likewise, the 60-40 strategy is applicable.

Concerning our findings, we have estimated returns based on historical data, and although looking at the number of returns, it appears that this had an ambitious return, yet it produced that high of a return. When it comes to trading, one must establish a set of trading criteria in advance.

Several specific rules that traders should follow include: controlling one's emotions, not over trading, always accepting profits, managing trade risk (the risk-reward ratio), trusting one's analysis, monitoring one's trades, homering stop losses, and preparing one's trade, time frame for trading, and target

How To Back-Test Any Strategy

Back-testing any strategy may be accomplished by following the procedures outlined below:

Define a specific parameter for testing purposes.

Specify the time frame for testing the approach on the chart.

Historical price charts may be used to find potential trades.

Analyze and record the trade following the specified entry and exit points.

Risk to reward and net return of back-tested data should be evaluated.

To comprehend the findings sections, we must first understand the table of findings, as illustrated in Table 1 , Table 2 . The titles in the table are as follows, and they are the same for both tables:

TREND FROM: This is the date on which an uptrend or downtrend begins.

TREND TO: This column indicates the end of an uptrend or downturn.

TOTAL NO. OF TRENDS: This column indicates the total number of days that the NIFTY 50 has been in a specific trend.

TYPE OF TREND: These indicate the direction of the trend, either upward or downward.

TREND FROM CLOSING PRICE: This is the closing price on the day the trend began.

TREND TO CLOSING PRICE: This is the closing price on the day the trend ended.

RETURN (%): This column indicates the total number of returns generated by a given trend.

Both strategies may be utilized observation ally in nature since they do not need a great deal of computation. To learn this technique, one must do back-testing on any stock or index chart. One must also examine many charts to master this strategy. The steps for doing a back-test on any strategy are detailed above.

In terms of the 50-50 approach's findings, we have discovered that this technique offers the best long-term return. As shown in Table 1 , the larger the duration of the trend, the higher the return. The trend may be down or rising.

We noticed that the 60-40 approach generates a very high rate of return during a short-term trend. As shown in Table 2 , a trend that lasted about two months (approximately 60 days) generated a very high rate of return in the short term.

(50-50 strategy findings) (Authors finding)

(60-40 strategy findings) (authors finding), (50-50 strategy return) (authors finding), ( 60-40 strategy return) (authors finding).

Below shown Table 1 is the formula for the statistical model and Table 2 and Table 3 are actual calculated values for the model.

(Formula for calculating model)

(actual calculated values in excel), (conclusion of f-value and p-value) (authors finding).

Between Groups Degrees of Freedom: DF = k − 1, where k is the number of groups

Within Groups Degrees of Freedom: DF = N − k, where N is the total number of subjects

Total Degrees of Freedom: DF = N — 1

Sum of Squares Between Groups:  S S b = ∑ k   i = 1 n i   ( x i - x ) 2 , where n i  is the number of subjects in the i-th group

Sum of Squares Within Groups: S S w = ∑ k   i = 1 n i - 1 S i 2 , where S i  is the standard deviation of the i-th group

Total Sum of Squares: SSt = SSb + SSw

Mean Square Between Groups: MSb = SSb / (k − 1)

Mean Square Within Groups: MSw = SSw / (N − k)

F-Statistic (or F-ratio): F = MSb / MSw

Now, we'll examine the data implications of our calculated returns for a certain year. Table 3 illustrates the estimated return on a 50-50 strategy over the past two decades, whereas Table 4 illustrates the calculated return on a 60-40 strategy over the same period. The return is computed on the year's last financial day. We performed the F-test and P-value for that return to determine its significance. We examine for significance to determine whether or not the F- a test used is statistically significant. As shown in Table 7 , the F-statistical value and P-value for both methods' data are shown. For analysis purposes, the P-values of the 50-50 and 60-40 strategies' returns use a 0.05 standard significant value. We discovered that both strategies had a P-value higher than the 0.05 standard significance level. The F-test we used on this data set is statistically insignificant and therefore cannot be fitted to any regression model.

With an understanding of the RSI technical indicator and the two RSI strategies, one may trade or invest in stocks and make a profit. Traders lose money because they lack a suitable strategy and trading guidelines to follow while trading. Additionally, the investor may lose money in the stock market by relying on technical indications. In this case, fundamental analysis is critical since the investor may pick companies that are not fundamentally sound and therefore lose money by investing in the incorrect business. In this instance, the technical analysis fails since freshly entering investors are constantly on the lookout for penny stocks that are both volatile and operator-driven. As an investor, one should always adhere to techno funda analysis, which includes both technical and fundamental analysis. Investors should use technical analysis only if the company's fundamentals are strong. In this article, we have explained two methods, one of which generates a high rate of return over the long term and another which generates a high rate of return over the short term. Technical analysis is critical for trading nowadays if the trader maintains it simple and follows all trading principles as outlined in this paper.

Source of Funding

Conflict of interest.

B Anderson S Li An investigation of the relative strength index. Banks and Bank SystemsBanks Bank Syst2015101926

M Alhilfi A Alnoor Role of using the Relative Strength Index in Making Speculation Decision in Stock Applied Research in the Iraq Stock ExchangeInt J Acad Res Accounting20199112335 10.6007/IJARAFMS/v9-i1/5855

Y Mahajan An Empirical Study of Indian Equity Market for Profitable Investment DecisionsAsian J Res Banking Finance201551213 10.5958/2249-7323.2015.00140.6

A R González F G Iglesias R C Palacios J M G Berbis Improving Trading Systems Using the RSI Financial Indicator and Neural NetworksLecture Notes Comput Sci20101503713 10.1007/978-3-642-15037-1_3

A Moroșan The relative strength index was revisited. African journal of business managementAfr J Business Manag20115145855 62 10.5897/AJBM.9000629

R Bhargavi S Gumparthi R Anith Relative strength index for developing effective trading strategies in constructing an optimal portfolioInt J Appl Eng Res20171219892636

I Gurrib F Kamalov The implementation of an adjusted relative strength index model in foreign currency and energy markets of emerging and developed economies, Macroeconomics and Finance in Emerging Market EconomiesMacroeconomics Finance Emerg Mark Econ2019121910523 10.1080/17520843.2019.1574852

Analysis Education | StockCharts.com. (n.d.)2021 https://school.stockcharts.com/doku.php

A Panigrahi M Mistry R Shukla A Gupta A Study on Performance Evaluation of Equity Linked Saving Schemes (ELSS) of Mutual FundsNMIMS J Econ Public Polocy20205121

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Trading Strategy

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Ashok Kumar Panigrahi , Kushal Vachhani , Suman Kalyan Chaudhury

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The association between reactive strength index and reactive strength index modified with approach jump performance

Jernej pleša.

1 Faculty of Health Sciences, University of Primorska, Izola, Slovenia

Žiga Kozinc

2 Andrej Marušič Institute, University of Primorska, Koper, Slovenia

Darjan Smajla

3 InnoRenew CoE, Human Health Department, Izola, Slovenia

Nejc Šarabon

4 S2P, Science to Practice, Ltd., Laboratory for Motor Control and Motor Behavior, Ljubljana, Slovenia

Associated Data

The dataset underlying this study is available at: https://zenodo.org/record/5558333

Jumping performance is one of the key components of volleyball game, thus evaluating jumping ability through different biomechanical variables offers opportunity for performance optimization. The aim of this study was to assess the associations between reactive strength index (RSI), reactive strength index modified (RSI mod ) and approach jump performance in male volleyball players. Forty volleyball players performed drop jump (DJ) form 40 cm high box, bilateral and unilateral countermovement jumps (CMJ) and approach jump. RSI in DJ was calculated as the ratio between jump height and ground contact time, while the RSI in CMJ tasks (RSI mod ) was calculated as ratio between jump height and jump time. Our results indicate that the relationships among different RSI variants and approach jump in volleyball players are moderate to strong (r = 0.42–0.73), with the highest correlations being observed for RSI mod from bilateral CMJ (r = 0.676–0.727). Those observations are in line with the principle of movement specificity, which suggests that the best performance indicator should be the task that best resembles the demands of the sport-specific movements. Further research is needed to reveal more about the potential of implementing these findings for training optimization through monitoring RSI and RSI mod values.

1 Introduction

Vertical jumping is one of the most important physical capabilities for successful volleyball performance [ 1 ]. The higher a player is able to jump, the greater his/her potential for successful performance in offensive and defensive actions [ 2 ]. The monitoring of various performance characteristics of athletes is crucial component in strength and conditioning practice. Approach jump performance is one of the sport-specific tasks in volleyball gameplay [ 3 , 4 ], which warrants exploration of its underlying biomechanical determinants that could be used for training optimization.

Jumping ability is evaluated through different forms (unilateral and bilateral, vertical and horizontal) with the use of different measurement devices [ 5 ]. In volleyball practice, approach jump is usually performed for evaluating athletic-specific performance of volleyball players [ 6 ]. Approach jump is characterized by countermovement with the use of arm movement and presents a combination of a drop jump (DJ) and a countermovement jump (CMJ) [ 5 ]. Players normally use 2- to 3-step approach [ 5 ], with an explosive penultimate step [ 7 ]. Penultimate step is also called the approach phase, which is defined between the last step take-off and the ground contact of both feet, followed by plant phase which lasts from ground contact of both feet to take-off [ 8 ]. Penultimate step could be also presented as a half-drop jump [ 9 ], followed by a countermovement arm swing and an eccentric contraction that exploits the stretch-shortening cycle (SSC) of the activated muscles [ 5 , 10 ]. In push off phase, one leg is usually in front of the other, with foot directed slightly inwards, to emphasize vertical direction of the jump and prevent too much horizontal flight [ 11 , 12 ]. The purpose of approach is to create high horizontal force, which is later transferred into vertical direction to jump as high as possible [ 7 ]. Apporach jump presents the hight at which volleyball player can spike the ball in the attacking action, while the difference between standing reach and jumping reach presents the height of the jump [ 5 ].

With more analytical approach and biomechanical testing, we can evaluate jumping characteristics throughout more complex forms of performance tests. Those tests provide a more detailed insight into the athlete’s neuromuscular capacity and thus offer the opportunity for training optimization. Previous research has identified the reactive strength index (RSI) as a variable that can be used to assess an athlete’s reactive strength [ 13 ]. Reactive strength is the ability to rapidly and efficiently transition from an eccentric to a concentric muscle contraction within a SSC movement [ 14 ]. The SSC is present during many sporting activities, such as sprinting and jumping [ 15 , 16 ]. Activities such as sprinting and jumping largely depend on the ability to develop maximal force in a minimal bout of time [ 17 ]. The RSI is a measure of produced force and the time to develop this force, which is calculated as the ratio between jump height and ground contact time [ 13 ], thereby assessing vertical reactive strength [ 18 ] and may present potentially useful tool for designing individually tailored plyometric training [ 19 ]. Recent studies indicated that modified version of RSI (RSI mod ), obtained from counter-movement jump (CMJ) metrics, may provide an alternative method for assessing RSI during several different plyometric exercises [ 20 ]. Calculation of RSI mod is similar to that of RSI, with groud contact time (DJ) being replaced with the time to takeoff (CMJ). Similar to RSI [ 21 ], the RSI mod is considered a reliable measure and was reported to discriminated between different groups of athletes [ 22 ]. The RSI in DJ is considered to represent fast SSC ability (ground contact < 250 ms) [ 23 ], whereas the RSI mod represents slow SSC ability. Therefore, both RSI and RSI mod could present useful method for evaluation of jumping characteristics of volleyball players.

The purpose of this study was to examine the relationship between RSI and RSI mod (from both bilateral and unilateral CMJ) in different tasks with approach jump performance in volleyball players. Approach jump performance is one of the key components for successful volleyball performance [ 3 , 4 ], thus its association with RSI could present potentially useful tool to guide training-related decision making for improving jumping performance. We hypothesized that all RSI outcomes will be positively related to approach jump height.

2.1 Subjects

For this study, we recruited 40 male volleyball players (age: 20.3 ± 3.3 years; body height: 187.4 ± 7.75 cm; body mass: 79.2 ± 8.6 kg). All the players have been competing in 1 st or 2 nd division of the national league. They reported to be involved in regular training for 10.9 ± 4.1 years, to attend 5.7 ± 1.2 training sessions per week and to regularly perform full body resistance exercises at least twice a week. The exclusion criteria were the presence of musculoskeletal injuries in the previous 6 months. The participants were informed about the experimental procedures and were required to sign an informed consent before participating in the experiment. For underage participants, their parents or legal guardians signed the consent on their behalf. The experiment was approved by Republic of Slovenia National Medical Ethics Committee (approval no. 0120–99/2018/5) and was conducted in accordance to the latest revision of the Declaration of Helsinki.

2.2 Study design

This was a cross-sectional study, with all measurements conducted in a single visit. The participants had been performing bilateral and unilateral jumps as part of their regular training and assessments. The participants performed a warm-up consisting of 10 min of self-pace jogging, 5 min of dynamic stretching and 5 min of bodyweight resistance exercises (squats, lunges, push-ups) and 3 min of activation exercises (vertical jumps and short-distance sprints). Then, they completed assessments of vertical jumps on a force plate (DJ, bilateral CMJ and unilateral CMJ) and volleyball specific performance test (approach jump). The order of the tasks was randomized across participants. For all tasks, three trials were performed, and the average of the three trials was taken for further analysis.

2.3 Assessment of drop jump and countermovement jump tests

DJs and CMJs were performed on a piezoelectric force plate (Kistler, model 9260AA6, Winterthur, Switzerland). Ground reaction force data were recorded at sampling rate of 1000 Hz. The signals were automatically processed by the manufacturer’s software (MARS, Kistler, Winterthur, Switzerland) by a moving average filter with a 5 ms window. Participants performed three warm-up trials for each jumping task. Each task was performed three times, with a 60-s rest between trials. The hands were placed on the hips at all times. For the DJ, the participants stood on a solid 40 cm high box, which was shown to reflect the highest and most reliable RSI in the population of professional basketball players [ 24 ]. The participants stepped off the box and performed a vertical jump immediately after the landing. They were instructed to achieve maximal jump height whilst minimizing the ground contact time. When performing the DJ participants maintained upright posture. The jump height was calculated based on take-off velocity. Contact times were also taken for the analysis, and subsequently, the RSI (RSI DJ ) was calculated as the ratio between the jump height and the contact time. Ground contact time was defined as the time during which the force signal was > 10 N.

When performing CMJ, the participants were instructed to start from the standing position and use an explosive countermovement to a self-selected depth and to jump as high as possible. Self-selected depth for performing CMJ was chosen as it was shown to be superior for jump height and RSI mod values [ 25 ]. For the unilateral CMJ, the non-tested leg was slightly flexed at the knee and was not allowed to touch the tested leg. Performing the swing with the non-tested leg was not allowed. Participants performed three repetitions for each leg in an alternating order, with 1-minute breaks between the repetitions. The jump height was calculated based on take-off velocity. RSI was calculated by dividing the jump height with the time to take off. Time to take off was determined as the time between the countermovement initiation (defined as the decrease in force signal larger than 3 standard deviations of the baseline signal) and the take-off (defined as the first instant of force < 10 N), which was shown to be reliable method to determine the take-of instant [ 26 ].

2.4 Assessment of volleyball specific approach jump

Basketball board with measurement tape was used to record approach jump heights. Before jumping attempts, participants chalked their fingertips for more precise detection of the jumping reach. Jumping height was calculated as a difference between standing reach and jumping reach. All the participants were experienced volleyball players, so the only instruction was to jump as high as possible, by utilizing a normal spike approach. All the participants were experienced volleyball players, so further standardization could have negative impact on jumping performance. Each participant performed two warm-up trials at submaximal effort and three testing attempts, with 1-min breaks in between. Measurements were read to the nearest centimeter.

2.5 Statistical analysis

The data were analyzed with SPSS (version 25.0, SPSS Inc., Chicago, USA). Descriptive statistics are reported as mean ± standard deviation, minimum and maximum values. The normality of the data distribution was checked with Shapiro-Wilk tests. Trial-to-trial reliability was assessed with two way random, single measures, absolute agreement model for calculating intra-class correlation coefficient (ICC) and typical error, expressed relative to the mean (coefficient of variation; CV). Correlations between different RSI outcomes and approach jump performance were assessed with Pearson’s correlation coefficients and interpreted as negligible (< 0.1), weak (0.1–0.4), moderate (0.4–0.7), strong (0.7–0.9) and very strong (> 0.9) [ 27 ]. The threshold for statistical significance was set at p < 0.05.

The descriptive statistics for all variables are presented in Table 1 . The correlations among RSI variables and approach jump performance are presented in Table 2 . The approach jump showed excellent reliability (ICC = 0.99; CV = 2.45%). All jump height outcomes also showed excellent reliability (ICC = 0.93–0.96; CV = 4.7–6.5%). The RSI and all RSI mod outcomes had excellent relative reliability (ICC = 0.91–0.93). RSI and bilateral RSI mod also had acceptable absolute reliability (CV = 6.5 and 6.8%), while the absolute reliability for the unilateral RSI mod was on the border of acceptable threshold (CV = 9.6% for the preferred leg and 10.2% for the non-preferred leg).

SD–standard deviation; DJ–drop jump; RSI–reactive strength index; CMJ–countermovement jump; BL–bilateral, D–dominant; ND–non dominant.

* p < 0.05;

** p < 0,01; DJ–drop jump; RSI–reactive strength index; CMJ–countermovement jump; BL–bilateral, D–dominant; ND–non dominant.

Approach jump was in moderate correlations with DJ height (r = 0.423; p < 0.05) and RSI (r = 0.436; p < 0.001). In bilateral CMJ, jump height (r = 0.727; p < 0.001) and RSI mod (r = 0.676); p < 0.001) showed high correlations, while jump time showed weak negative correlation (r = -0.331; p < 0.05) with approach jump performance. The negative correlation means that the subjects with shorter jump times jumped higher in approach jump test. In terms of unilateral CMJs (both in dominant and non-dominant side) moderate to high correlations between jump height and RSI mod with approach jump were shown (r = 0.579–0.733; all p < 0.001). Jump time in unilateral CMJs and contact time in DJ were not significantly associated with approach jump performance (p > 0.05). In addition, the RSI was in moderate correlation with all RSI mod variants (r = 0.57–0.70; p < 0.01). Moreover, RSI mod variants were in moderate to high correlation among themselves (r = 0.68–0.78; p < 0.01).

4 Discussion

The purpose of this study was to examine the association between RSI and RSI mod with volleyball specific approach jump performance. Our results show that approach jump was a) moderately associated with DJ height and RSI b) moderately to strongly associated with jump height and RSI mod in bilateral CMJ, as well as jump height and RSI mod in both dominant and non-dominant unilateral CMJ. Moreover, the relative reliability of the RSI and bilateral RSI mod were excellent, while the absolute reliability of RSI and bilateral RSI mod were acceptable and in line with previous studies [ 13 , 21 ]. On the other hand, the absolute reliability of the unilateral RSI mod was on the border of the acceptable treshold. These results suggest that RSI mod could be preferable to RSI when trying to monitor performance and training adaptations in approach jump performance Bilateral variant is suggested to be used in practice due to better absolute reliability.

To our knowledge, this is the first study to date that examined the association between different RSI variants with volleyball specific athletic performance. Our results indicate that the relationships among different RSI variants and approach jump in volleyball players are moderate to strong. Those results are in line with studies reporting associations between approach jump height and CMJ height without arm swing [ 8 ] and CMJ with arm swing [ 28 ]. Furthermore, a recent systematic review with meta-analysis showed moderate associations between RSI in DJ and independent measures of physical and sporting performance, while the strength of these relationships varied based on the task and physical quality assessed [ 29 ]. However, it should be mentioned, that there are some differences in jump characteristics between DJ and CMJ. While in DJ ankle strength and stiffness are main determinants for performance [ 30 ], higher contribution of the knee joints is typical for the CMJ [ 31 ]. Approach jump is a combination of DJ and CMJ [ 5 ], thus positive correlations between approach jump height and both RSI and RSI mod were expected. Furthermore, we observed the highest correlations between bilateral CMJ height and bilateral RSI mod with approach jump height, which is in line with the principle of movement specificity. It is suggested that the best performance indicator should be the task that best resembles the demands of the sport-specific movement task (e.g., unilateral or bilateral actions, horizontally or vertically oriented task). Approach jump is vertically oriented, performed in bilateral circumstances, similar to the characteristics of CMJ.

Higher correlations between approach jump and RSI mod, compared to its correlation with RSI, could be also explained by the specificity of the SSC type. In brief, SSC actions can be roughly classified two different types, fast SSC (contact time < 250 ms) [ 23 ], and slow SSC, where the time of descent and transition to ascent is much longer [ 32 ]. DJ is performed with the use of fast SSC, while slow SSC is present in exercises such as CMJ [ 18 ]. Approach jump characteristics based on the ground contact time and time of downward and upward phase, also reveals the use of slow SSC [ 8 , 33 , 34 ]. Performance enhancement in slow SSC activities may be primarily due to the slow eccentric phase allowing an increased time to develop force [ 16 ], while in fast SSC, the underlying mechanisms are based on increased excitability of proprioceptors such as Golgi-tendon organ and muscle spindle [ 35 ]. This hypothesis may have implications for volleyball athletic performance training. Different exercises or the manner in which exercises are performed may elicit different mechanisms of SSC action. Moreover, many studies reported the importance of horizontal velocity in the approach phase for jumping performance [ 8 , 28 , 36 ], thus it would be interesting to check the associations between RSI in horizontal direction and approach jump performance. With all of the above in mind, it has to be noted that although RSI outcomes appear to be related to approach jump performance, high correlations between approach jump height and CMJ as well as DJ heights, which means that the RSI offer little additional information. This is probably because approach jump is not a time-restricted task, which means that athletes can take a little longer to perform it (i.e., spend more time on the ground) without compromising the score. Perhaps different results would be observed if we used time-restricted tasks or tasks wherein the performance is defined by time to completion (i.e. sprint). As noted above, RSI in DJ has been shown to be related to several performance proxies [ 29 ]. However, further studies should examine independent contributions of RSI and RSI mod to explaining performance in addition to DJ or CMJ height alone in explaining performance.

A common modality to enhance SSC capabilities is plyometric training. Characteristic of plyometric training are quick, powerful movements using a pre-stretch or countermovement that involves SSC [ 37 ]. The literature shows that RSI may present potentially useful tool for designing individually-tailored plyometric training [ 18 , 19 ]. To prescribe plyometric training, the optimal drop height for DJs is suggested to be based on the highest RSI values [ 38 ]. The study of Ramirez-Campillo et al. [ 19 ] confirmed that statement on sample of young football players, where the group of athletes that performed DJs at highest RSI output exhibit greater performance benefit than the group of athletes performing DJs at the fixed height. Moreover, an intervention study on volleyball players showed that 6-weeks of plyometric training improves jumping ability of volleyball players [ 39 ]. Additionally, studies have suggested that RSI mod in bilateral CMJ can be used as a measure of explosiveness in volleyball players [ 40 ] and could be used to determine the need of incorporating ballistic-type exercises (i.e., plyometric exercises, weightlifting movements) into an athlete’s training program [ 41 ]. Based on the results of this study RSI and RSI mod could potentially present addition insight into neuromuscular characteristics that could be further manipulated with training. For example, for the participants with low RSI values, one of the missing links for better approach jump performance may be bad efficiency of fast stretch shortening cycle. On the other hand, if the athlete has low values of RSI mod this mean low jump height or slow transition from the eccentric to concentric part of the movement. In practice, this would mean that participants with low CMJ height could be directed towards power training, while the participants with slow countermovement transition could be directed towards training improving intermuscular coordination (e.g. rhythmic squats, jumps emphasizing fast transition from countermovement, depth jumps, etc.). Based on the results of this study, RSI and RSI mod could be used as a supplementary part of the training for improving approach jump performance. Nevertheless, it has to be stressed that this metrics should not be used for primary testing of volleyball players, but rather be used as a supplementary diagnostic tool, preferably utilized at the beginning of the season to get a better insight into each individual player.

Some limitations of the study must be acknowledged. The study was conducted on a sample of well-trained male volleyball players. The performance test used in this study covered only a limited aspect of volleyball athletic performance. Referring to RSI, previous studies have found significant differences in RSI among sports and between sexes [ 41 ], thus, our results cannot be generalized to other sports and females. Moreover, only DJ task from 40 cm height was included in the study. While some studies reported no differences in RSI computed from DJs of varying heights [ 42 ], others suggest that optimal DJ height exists that maximizes RSI [ 19 ]. Thus, future studies should consider including multiple DJ with different heights. Finally, the cross-sectional design precludes establishing any causal relationships, thus, further prospective and experimental research is needed to corroborate our results.

5 Conclusion

In this study, we found that approach jump performance seems to be associated by both, RSI and RSI mod , while the RSI mod exhibit higher correlations with approach jump, thus present preferable method when trying to monitor performance and training adaptations in approach jump performance. Results of this study are in line with the principle of movement specificity, which suggests that the best performance indicator should be the task that best resemble the demands of the sport-specific movements. The literature suggests, that RSI could be used as a tool for designing individually tailored plyometric training, while RSI mod could be used to determine the need of incorporating ballistic-type exercises into training program. Bilateral over unilateral RSI mod is to be preferred for now, as the latter showed poorer reliability, but similar association to approach jump performance compared to the bilateral variant. It has to be noted that RSI outcomes might not add significant additional information (in terms of explaining performance) to DJ and CMJ height alone.

Funding Statement

The authors received part of the salary through the Slovenian Research Agency through the programme ‘Kinesiology of monostructural, polystructural and conventional sports’ [P5-0147 (B)] and the project TELASI-PREVENT [L5-1845] (Body asymmetries as a risk factor in musculoskeletal injury development: studying aetiological mechanisms and designing corrective interventions for primary and tertiary preventive care). The Agency had no role in conceptualization of the study, analysis of the data, manuscript preparation or any other activities leading to the creation of this article. There was no additional external funding received for this study.

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Steering Committee Co-Directors

Ray Perrault

Steering committee members.

Erik Brynjolfsson

John Etchemendy

Katrina Ligett

Terah Lyons

James Manyika

Juan Carlos Niebles

Vanessa Parli

Yoav Shoham

Russell Wald

Staff members.

Loredana Fattorini

Nestor Maslej

Letter from the co-directors.

AI has moved into its era of deployment; throughout 2022 and the beginning of 2023, new large-scale AI models have been released every month. These models, such as ChatGPT, Stable Diffusion, Whisper, and DALL-E 2, are capable of an increasingly broad range of tasks, from text manipulation and analysis, to image generation, to unprecedentedly good speech recognition. These systems demonstrate capabilities in question answering, and the generation of text, image, and code unimagined a decade ago, and they outperform the state of the art on many benchmarks, old and new. However, they are prone to hallucination, routinely biased, and can be tricked into serving nefarious aims, highlighting the complicated ethical challenges associated with their deployment.

Although 2022 was the first year in a decade where private AI investment decreased, AI is still a topic of great interest to policymakers, industry leaders, researchers, and the public. Policymakers are talking about AI more than ever before. Industry leaders that have integrated AI into their businesses are seeing tangible cost and revenue benefits. The number of AI publications and collaborations continues to increase. And the public is forming sharper opinions about AI and which elements they like or dislike.

AI will continue to improve and, as such, become a greater part of all our lives. Given the increased presence of this technology and its potential for massive disruption, we should all begin thinking more critically about how exactly we want AI to be developed and deployed. We should also ask questions about who is deploying it—as our analysis shows, AI is increasingly defined by the actions of a small set of private sector actors, rather than a broader range of societal actors. This year’s AI Index paints a picture of where we are so far with AI, in order to highlight what might await us in the future.

- Jack Clark and Ray Perrault

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This paper is in the following e-collection/theme issue:

Published on 11.4.2024 in Vol 26 (2024)

This is a member publication of Imperial College London (Jisc)

Regulatory Standards and Guidance for the Use of Health Apps for Self-Management in Sub-Saharan Africa: Scoping Review

Authors of this article:

• Benard Ayaka Bene 1, 2 , MBBS, MPH   ; 
• Sunny Ibeneme 3 , MD, PhD   ; 
• Kayode Philip Fadahunsi 1 , MBBS, MPH   ; 
• Bala Isa Harri 4 , MBBS, MPH, MSc   ; 
• Nkiruka Ukor 5 , MSc   ; 
• Nikolaos Mastellos 1 , BSc, PhD   ; 
• Azeem Majeed 1 , MD   ; 
• Josip Car 1, 6 , MSc, MD, PhD  

1 Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom

2 Department of Public Health, Federal Ministry of Health, Abuja, Nigeria

3 Digital Health Specialist, UNICEF East Asia Pacific Regional Office, Bangkok, Thailand

4 Department of Health Planning, Research and Statistics, Federal Ministry of Health, Abuja, Nigeria

5 Strategic Health Information Cluster, World Health Organization, Abuja, Nigeria

6 School of Life Course & Population Sciences, King’s College London, London, United Kingdom

Corresponding Author:

Benard Ayaka Bene, MBBS, MPH

Department of Primary Care and Public Health

School of Public Health

Imperial College London

The Reynolds Building

St Dunstan’s Road

London, W6 8RP

United Kingdom

Phone: 44 7598439185

Email: [email protected]

Background: Health apps are increasingly recognized as crucial tools for enhancing health care delivery. Many countries, particularly those in sub-Saharan Africa, can substantially benefit from using health apps to support self-management and thus help to achieve universal health coverage and the third sustainable development goal. However, most health apps published in app stores are of unknown or poor quality, which poses a risk to patient safety. Regulatory standards and guidance can help address this risk and promote patient safety.

Objective: This review aims to assess the regulatory standards and guidance for health apps supporting evidence-based best practices in sub-Saharan Africa with a focus on self-management.

Methods: A methodological framework for scoping reviews was applied. A search strategy was built and applied across the following databases, gray literature sources, and institutional websites: PubMed, Scopus, World Health Organization (WHO) African Index Medicus, OpenGrey, WHO Regional Office for Africa Library, ICTworks, WHO Directory of eHealth policies, HIS Strengthening Resource Center, International Telecommunication Union, Ministry of Health websites, and Google. The search covered the period between January 2005 and January 2024. The findings were analyzed using a deductive descriptive content analysis. The policy analysis framework was adapted and used to organize the findings. The Reporting Items for Stakeholder Analysis tool guided the identification and mapping of key stakeholders based on their roles in regulating health apps for self-management.

Results: The study included 49 documents from 31 sub-Saharan African countries. While all the documents were relevant for stakeholder identification and mapping, only 3 regulatory standards and guidance contained relevant information on regulation of health apps. These standards and guidance primarily aimed to build mutual trust; promote integration, inclusion, and equitable access to services; and address implementation issues and poor coordination. They provided guidance on systems quality, software acquisition and maintenance, security measures, data exchange, interoperability and integration, involvement of relevant stakeholders, and equitable access to services. To enhance implementation, the standards highlight that legal authority, coordination of activities, building capacity, and monitoring and evaluation are required. A number of stakeholders, including governments, regulatory bodies, funders, intergovernmental and nongovernmental organizations, academia, and the health care community, were identified to play key roles in regulating health apps.

Conclusions: Health apps have huge potential to support self-management in sub-Saharan Africa, but the lack of regulatory standards and guidance constitutes a major barrier. Hence, for these apps to be safely and effectively integrated into health care, more attention should be given to regulation. Learning from countries with effective regulations can help sub-Saharan Africa build a more robust and responsive regulatory system, ensuring the safe and beneficial use of health apps across the region.

International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2018-025714

Introduction

Health apps are the most widely used digital health products globally [ 1 , 2 ]. Harnessing the potential of health apps creates a huge opportunity in providing support for health care delivery, including patient communication, patient education, and decision support for self-management [ 3 - 8 ]. Health apps can be an effective tool to strengthen health systems worldwide, especially in low- and middle-income countries including those in sub-Saharan Africa [ 4 , 5 , 9 ]. As a result, the attainment of universal health coverage (UHC) and sustainable development goal (SDG) 3, good health and well-being, can be accelerated [ 8 , 10 ].

Many health apps fall below the expected quality threshold [ 11 ]. Several studies have found that widely used health apps are often technically unreliable and clinically unsafe [ 12 - 14 ] and do not comply with ethical standards and the principles of confidentiality of information and data privacy [ 15 , 16 ]. In addition, many commercially available health apps were not developed using interoperability standards that are widely accepted in sub-Saharan Africa (eg, Fast Healthcare Interoperability Resources [FHIR]) [ 17 - 20 ]. Consequently, it becomes difficult to integrate these apps into a clinical workflow.

Hence, regulation through robust mechanisms is crucial to enhance the development, implementation, and adoption of health apps. Regulatory standards and guidance are essential for the safety of patients as they ensure quality assurance of any new technology in health care and contribute to building mutual trust while promoting the optimal use of the technology [ 21 - 23 ]. Therefore, to ensure that health apps that are used to support the self-management of patients are technically reliable and clinically safe, interoperable across systems, and compliant with the principles of confidentiality of information and data privacy, there is a need for effective regulatory standards. Furthermore, effective regulation can help ensure that health apps for self-management are culturally functional and competent and are accessible to those who need them regardless of gender, ethnicity, geographical location, or financial status [ 24 - 31 ].

Since 2005, there have been ongoing efforts to strengthen digital health governance at both the national and international levels [ 32 , 33 ]. In 2018, the World Health Organization (WHO) member states renewed their commitment to using digital health technologies (DHTs) to advance UHC and SDG 3 [ 33 ]. However, to date, the extent to which the use of health apps for self-management is regulated across countries within the WHO African Region (also known as sub-Saharan Africa) remains unclear. Therefore, this review was conducted to identify available regulatory standards and guidance and assess the extent to which they regulate health apps for self-management in sub-Saharan Africa. The review also mapped out the key stakeholders and their roles in regulating health apps for self-management across sub-Saharan Africa.

Review Questions

The review attempted to answer the following questions: (1) What regulatory standards and guidance are available for regulating health apps for self-management across sub-Saharan Africa? (2) To what extent do regulatory standards and guidance regulate health apps for self-management in terms of what aspects are regulated; why, how, and for whom; and what aspects are not regulated? (3) Who are the key stakeholders and what are their roles in regulating health apps for self-management?

Study Design

The process of this scoping review followed the methodological framework for conducting a scoping study originally described by Arksey and O’Malley [ 34 ] and the updated methodological guidance for conducting a Joanna Briggs Institute scoping review [ 34 - 37 ]. The reporting of the review was guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist [ 38 ]. A completed PRISMA-ScR checklist is provided in Multimedia Appendix 1 . The protocol of this scoping review was published in BMJ Open [ 30 ].

Identifying Relevant Documents

Two reviewers (BAB and SI) developed the search strategy with the assistance of a librarian and in consultation with other research team members (KPF, BIH, NU, NM, AM, and JC). The following key terms were included: policy, legislation, strategy, regulation, standard, criterion, framework, guidance, guideline, digital health, eHealth, app, WHO African Region, and sub-Saharan Africa, and the names of all sub-Saharan African countries.

Owing to the absence of regulatory standards and guidance in scientific databases, the search focus was narrowed down to gray literature sources and institutional websites, including OpenGrey, WHO Regional Office for Africa (AFRO) Library, repositories for digital health policies (ICTworks, WHO’s Directory of eHealth Policies, and Health Information System Strengthening Resource Center), as well as the websites of WHO, International Telecommunication Union (ITU), and Ministries of Health (MOHs). The only scientific databases searched were PubMed, Scopus, and WHO AIM. PubMed was not included in the protocol. We also conducted a systematic search on Google. We used truncation to increase the yield of the results. The search strategy was then applied across PubMed, Scopus, and WHO AIM databases using Boolean terms (mainly OR and AND ) to combine search results. Gray literature sources and institutional websites were searched using phrases containing ≥2 keywords such as “eHealth regulation,” “digital health regulatory standard,” “eHealth regulatory standard,” “digital health regulation,” “digital health policy,” “eHealth policy,” “digital health strategy,” and “eHealth strategy.” For Google search, we added the names of the country to the phrases (eg, “digital health regulation Nigeria”). The reference lists of the included documents were also searched, and key individuals at the MOHs, WHO Country Offices, and the WHO AFRO were contacted for related documents. When our search was conducted, the WHO Directory of eHealth policies website was unavailable, and the WHO AFRO Library was undergoing reconstruction. The search strategies for PubMed, Scopus, and WHO AIM are provided in Multimedia Appendix 2 . The search was conducted between 2005 and January 2024.

Study Selection

The search results obtained from PubMed, Scopus, and WHO AIM were imported into Mendeley (Elsevier) [ 39 ] to remove duplicates. The search conducted on OpenGrey did not yield any results, whereas relevant records obtained from institutional websites, repositories, and Google were downloaded as PDF copies and uploaded to Mendeley. After removing duplicates, the remaining results were imported into Covidence (Veritas Health Innovation) [ 40 ] for screening. Two reviewers (BAB and SI) applied the predefined eligibility criteria ( Textbox 1 ) to screen the documents in 2 stages (title and abstract or executive summary). All discrepancies were discussed until the reviewers reached agreement.

Inclusion criteria

• Type of document: Regulatory standards, guidance, policies, strategies, and committee or government reports that address regulatory issues related to the use of health apps for self-management
• Location: Documents developed and implemented in countries within sub-Saharan Africa
• Date of publication: Documents developed since 2005; the global efforts toward promoting standards to minimize variability and potential harms that could arise from poorly regulated use of digital health began in 2005 [ 33 ]
• Language: Documents written in English language and other official languages of sub-Saharan African countries (Portuguese and French)

Exclusion criteria

• Type of document: Standards, guidance, policies, strategies, and reports not related to regulation of health apps
• Location: Documents from countries outside sub-Saharan Africa
• Date of publication: Documents developed before 2005
• Language: None

Data Charting (Extraction)

Two reviewers (BAB and SI), in consultation with the other members of the research team, developed the data extraction forms using an iterative process that included piloting data extraction and refinement until a consensus was reached.

We proposed in the study protocol [ 30 ] that data extraction would be conducted by the 2 reviewers independently. However, owing to the approach adopted for data extraction (deductive qualitative content analysis), 1 reviewer, rather than 2, initially extracted data from the included documents, and any concerns were discussed with a second reviewer [ 41 ]. Unresolved issues were then discussed and resolved with a third reviewer in a steering group meeting.

Collating, Summarizing, and Reporting Results

To address the research questions (particularly question 2), we adopted a deductive descriptive qualitative content analysis method to analyze and report the key findings. The policy analysis framework by Walt and Gilson [ 42 ] was adapted and applied to ensure that there was a consistent way of organizing the key findings: (1) Content (which aspects are regulated and which aspects are not?)—these are the components that directly or indirectly address regulatory issues related to the use of health apps for self-management, including areas that have not been addressed. (2) Context (why are those aspects regulated?)—this characterizes the rationale indicated for addressing regulatory issues related to the use of health apps for self-management. (3) Process (how are the regulatory standards developed and implemented?)—this describes the methods or approaches used to develop and implement regulatory standards. (4) Actors (who are the regulatory standards targeted toward?)—these are the key actors targeted by the standards.

Using a deductive descriptive qualitative content analysis approach, we examined each included document to systematically identify texts for concepts, patterns, and other relevant information. We then categorized them under content, context, process, or actors in relation to regulating health apps for self-management. The findings under content and context were further organized based on 4 predefined regulatory categories or themes as documented in the literature, namely (1) technical and clinical safety [ 12 - 14 ], (2) data protection and security [ 15 , 16 ], (3) standards and interoperability [ 28 , 31 ], and (4) inclusion and equitable access [ 24 - 29 ].

To address the third research question, the Reporting Items for Stakeholder Analysis (RISA) tool [ 41 ] was used as a guide to group key stakeholders based on role categorization as recognized globally by the WHO, the ITU, and UNESCO [ 32 , 33 , 43 ].

Ethical Considerations

Primary data were not collected in this study. Therefore, no ethics approval was required.

Search Results

A total of 2900 records were obtained after removing duplicates. Although the literature search was conducted in English, the search also yielded documents written in French and Portuguese from the ICTworks repository [ 44 ]. Following the initial screening of the title and abstract (or executive summaries), 73 documents were retrieved for full-text assessment. After applying the inclusion criteria for the full-text assessment, 49 documents were found eligible for inclusion in the review.

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram [ 45 ] showing the study selection process is presented in Figure 1 .

Types of Documents

On the basis of the inclusion criteria, 3 categories of documents were considered for this review, namely “stand-alone regulatory standards and guidance that potentially regulate health apps for self-management,” “national policies and strategies on digital health,” and “other national documents that relate to the regulation of health apps for self-management.” Table 1 presents the types of documents obtained for each country within sub-Saharan Africa.

Characteristics of the Included Documents

Stand-alone regulatory standards and guidance.

We identified and included 6 stand-alone regulatory standards [ 18 , 19 , 46 - 49 ] from 3 countries (Ethiopia, Kenya, and Nigeria). All 6 documents were written in English. The years of development ranged between 2013 and 2021, as indicated in Multimedia Appendix 3 . The years of implementation were not specifically stated.

Although none of the included regulatory standards were exclusively developed to regulate health apps for self-management, 3 of them (Kenya Standards and Guidelines for mHealth Systems [ 18 ], Kenya Standards and Guidelines for E-Health Systems Interoperability [ 47 ], and Health Sector Information and Communications Technology Standards and Guidelines [ 48 ]) provided concept and information relevant to the regulation of health apps and were included in the qualitative content analysis. The Kenya Standards and Guidelines for mHealth Systems [ 18 ] provides standards and guidelines on the design, development, and implementation of mobile health (mHealth) solutions to ensure they are interoperable, scalable, and sustainable. The Kenya Standards and Guidelines for E-Health Systems Interoperability [ 47 ] outlines the principles, requirements, and standards for eHealth systems interoperability in Kenya. The Health Sector Information and Communications Technology Standards and Guidelines [ 48 ] provide guidance and a consistent approach across the health sector in Kenya for establishing, acquiring, and maintaining current and future information systems and information and communications technology (ICT) infrastructure that foster interoperability across systems. These 3 documents are a good combination of regulatory standards and guidance that provide content and context relevant to the regulation of health apps in sub-Saharan Africa.

The remaining 3 standards (standard for electronic health record [EHR] system in Ethiopia [ 19 ], standards and guidelines for electronic medical record systems in Kenya [ 46 ], and the health information exchange standard operating procedure and guideline [ 49 ]) were exclusively developed for EHRs or electronic medical records. However, they contain information relevant for mapping stakeholders with potential roles in regulating health apps for supporting self-management.

National Policies and Strategies on Digital Health

This review includes 35 national policies and strategies that are related to digital health (potentially covering health apps) [ 50 - 84 ] from 31 countries written in English, French, and Portuguese (Benin, Botswana, Burkina Faso, Burundi, Cameroon, Comoros, Côte d’Ivoire [Ivory Coast], Democratic Republic of the Congo, Eswatini, Ethiopia, Gabon, Ghana, Kenya, Liberia, Madagascar, Malawi, Mali, Mauritius, Mozambique, Namibia, Niger, Nigeria, Rwanda, Senegal, Sierra Leone, South Africa, Tanzania, Togo, Uganda, Zambia, and Zimbabwe). Although the literature search was conducted in English, it also yielded documents written in French and Portuguese from the ICTworks repository. The years of development and implementation range between 2005 and 2030. Policies and strategies written in French and Portuguese were translated into English using Google Translate. Documents labeled as national development plans, strategic plans, and strategic development plans were considered as national strategies.

National policies and strategies do not offer specific standards or guidance, but rather outline the country’s vision, policy directions, and strategies for using digital technologies in health care. They provide useful information for identifying digital health stakeholders who can play a role in regulating health apps for self-management. For example, Nigeria has a separate National Digital Health Policy [ 72 ] and a National Digital Health Strategy [ 71 ]. Both documents were developed by building on the lessons learned from the end-term evaluation of the previous National Health ICT Strategic Framework [ 85 ]. They describe Nigeria’s renewed vision, mission, goals, objectives, and strategies for the development and implementation of digital health with the aim to improve the quality, efficiency, and effectiveness of health service delivery and health outcomes.

It is worth noting that for countries with >1 policy or strategy, we included only the most recent versions. For instance, as mentioned earlier, Nigeria now has both a national digital health policy and a national digital health strategy. These 2 documents supersede and thus replace the old National Health ICT Strategic Framework [ 86 ]. Details of included documents are presented in Multimedia Appendix 3 .

Other Related National Documents

We included 8 other documents [ 20 , 85 , 87 - 92 ] from 6 countries (Ethiopia, Kenya, Liberia, Nigeria, South Africa, and Tanzania) that did not fall under either stand-alone regulatory standards and guidance or national policies and strategies. These were mostly frameworks, road maps, and reports that potentially provide information relevant to the use of health apps. The years of development and implementation range from 2016 to 2025. These documents do not provide standards or guidance, but they contain information that can help map the digital health stakeholders that potentially play a role in regulating health apps for self-management. When multiple versions of a document exist, only the latest version was taken into consideration. Multimedia Appendix 3 provides details of the included documents.

Content: Aspects That Are Regulated and Aspects That Are Not

Technical and clinical safety.

Technical and clinical safety standards are required to prevent or minimize the harm that may arise from the use of the health ICT systems (including mHealth systems) as well as to improve the health outcomes and user satisfaction. As shown in Figure 2 , two subthemes were generated from included standards [ 18 , 47 , 48 ] as content under technical and clinical safety: v(1) guidance on system quality and (2) guidance on software or app development, acquisition, support, and maintenance.

Notably, 2 of the included standards [ 18 , 47 ] provide guidance on system quality to ensure the quality, security, reliability, performance, and maintenance of eHealth and mHealth systems. The Kenya Standards and Guidelines for E-Health Systems Interoperability [ 47 ] recommend the implementation of a data quality protocol to ensure that the data collection, collation, analysis, interpretation, dissemination, and use are managed in accordance with the quality standards. Similarly, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] recommends the inclusion of the following requirements in the technical manual: (1) minimum hardware requirements that should incorporate the preferred hardware architecture, (2) minimum software requirements that should include the minimum version of the underlying operating system as well as acceptable versions of related software, and (3) a detailed list of software dependencies (external libraries) necessary for the system to function properly.

The included standards [ 18 , 48 ] cover guidance on software or app development, acquisition, support, and maintenance, which aim to ensure the efficiency and effectiveness of eHealth and mHealth systems. The Kenya Standards and Guidelines for mHealth Systems [ 18 ] recommends a technical manual to provide a detailed description of the system’s installation and maintenance processes for system administrators and implementers; a developer’s guide for software developers and programmers to provide them with an overview of the system, description of the software design methodologies, description of the system architecture, and technical design diagrams; and a user manual to aid users in understanding how the system works and how each feature operates; in addition, the technical manual contains instructions for operating the software; entering and updating data; and generating, saving, and printing reports.

Although the contents generated here provide guidance that is relevant to health apps, they are not specific to health apps. Moreover, there are no clear measures to enable individuals or organizations that use health apps to manage clinical risk appropriately.

Data Protection and Security

Data protection and security are crucial aspects of managing patient information, thus ensuring the confidentiality, integrity, and availability of data as well as the rights and interests of the patient. Two subthemes related to data protection and security are (1) security measures for adequate protection of patients’ digital records and (2) guidance on data exchange.

The included standards [ 18 , 48 ] provide security measures for eHealth or mHealth systems to ensure the adequate protection of digitally accessible patient records. These measures include authentication, accountability, identification, authorization, integrity, confidentiality, availability, security, administration, and audit. This will help to achieve confidentiality, integrity, availability, and nonrepudiation of patient data or health records. Additional levels of security such as data encryption are required when there is a need to store sensitive information on removable devices or media or outside the MOH premises.

The Kenya Standards and Guidelines for mHealth Systems [ 18 ] provide the following guidance on data exchange to ensure privacy: (1) anonymize client data as much as possible before they can be shared; (2) where possible, use pseudonyms for the client data before they can be shared; (3) aggregate client data before they can be shared to reduce possibilities of tracing the data back to the client; and (4) minimize data so that access is available only to the data set required for that particular use. With regard to privacy rules, the Kenya Standards and Guidelines for E-Health Systems Interoperability [ 47 ] propose that a notice of privacy practices should be given to patients describing how their information may be used or shared while also specifying their legal rights.

Standards and Interoperability

Standards and interoperability are essential concepts in the field of IT, especially for systems that need to communicate and exchange data, as seen in the use of health apps for self-management. Two subthemes related to standards and interoperability are (1) interoperability as a basic requirement and (2) minimum standards to enable integration.

All the regulatory standards [ 18 , 47 , 48 ] highlight the importance of having interoperability as a basic requirement when selecting software products or services for use within the health system. This facilitates interaction across systems. For instance, to facilitate seamless interaction between mHealth systems and primary information systems for data capture, reporting, and decision support in various domains of the health system, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] recommends the incorporation of at least 3 types of interoperability, namely, technical interoperability, semantic interoperability, and process interoperability.

Furthermore, 2 regulatory standards [ 18 , 47 ] proposed minimum interoperability standards to enable the integration of services and data exchange between various systems in health care. For instance, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] suggests standards (for interoperability) for mHealth systems that are consistent with the recommendations in internationally accepted standards. They include the following: (1) clinical messaging—ensuring mHealth systems conform to Health Level 7 (HL7) version 3 standards and corresponding implementation guideline; (2) clinical terminology—ensuring terminologies and classifications for clinical concepts (eg, International Classification of Diseases, tenth revision—for diseases; Systemized Nomenclature of Medicine—for clinical data coding; Logical Observation Identifiers Names and Codes—for laboratories; and RxNorm—for Pharmacies); (3) the mHealth system must use the latest versions of international standards, such as HL7 Clinical Document Architecture for electronic sharing of clinical documents; (4) concepts—mHealth systems will use the idea of “concepts” so that information can be transmitted between systems without losing meaning or context, and HL7 Reference Implementation Model or other appropriate standards are recommended for implementing concepts; (5) architecture—to develop mHealth systems, developers should define the system architecture that should include data elements and business logic. Furthermore, to define how mHealth systems interact with other systems, developers of mHealth solutions must provide application programming interfaces. FHIR is the preferred application programming interface interoperability standard.

Inclusion and Equitable Access

Inclusion and equitable access are essential principles to ensure that health apps are culturally appropriate and relevant and accessible to everyone, regardless of gender, ethnicity, location, or economic status.

All the included regulatory standards [ 18 , 47 , 48 ] indicate that they were developed based on a combination of participatory and consultative approaches involving multiple actors or stakeholders, thus promoting inclusion. However, there are no specific measures or guidance to ensure adequate engagement and representation of all the relevant stakeholders and to sustain that engagement.

The Kenya Standards and Guidelines for mHealth Systems [ 18 ] proposes the following systems attributes to ensure equitable access to mHealth services at all times and from anywhere: (1) allocation of adequate storage and bandwidth capacity; (2) fast response time; (3) fast recovery capabilities; (4) performance monitoring; (5) business continuity processes, for example, backups; and (6) redundant sites and links. Furthermore, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] prescribes the following metrics for measuring system availability: (1) downtime per year, (2) mean time between failure, (3) mean time to repair, and (4) failure in time.

Although the abovementioned systems attributes and metrics for measuring system availability are important, the included standards do not offer any concrete guidance or model for achieving a sustainable funding mechanism for health apps to ensure that they are readily available and accessible to those who need them.

Context: Reasons Why Those Aspects Are Regulated

The 3 standards [ 18 , 47 , 48 ] were developed to address unsafe, isolated, and inconsistent implementation. The Health Sector ICT Standards and Guidelines [ 48 ] suggest that although there has been a lot of ICT investment in the health sector leading to improvement in service delivery and information exchange, there remains the challenge of inconsistency in ICT implementation and harmonization of the health sector system requirements. Hence, there is a need to adopt global best practices for software development, acquisition, support, and maintenance by the MOH. In addition, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] indicates that standards and guidelines are necessary to ensure a consistent approach to the development of ICT systems. Similarly, the Kenya Standards and Guidelines for E-Health Systems Interoperability [ 47 ] recognize the need to ensure that the processes of collecting, collating, analyzing, interpreting, disseminating, and using data are consistent with data quality standards.

To build mutual trust and maximize the benefits of eHealth information exchange, the Kenya Standards and Guidelines for E-Health Systems Interoperability [ 47 ] reiterate that as health data are constantly being exchanged across health information systems, robust security standards are required to maintain their integrity and confidentiality. This will build the trust of service users and consequently help to maximize the benefits of eHealth information exchange such as in self-management.

Two of the included regulatory standards [ 47 , 48 ] indicate that the context for standards and interoperability was (1) to address poor coordination, duplication of efforts, and inefficient use of resources and (2) to promote the integration of ICT systems.

The Kenya Standards and Guidelines for E-Health Systems Interoperability [ 47 ] acknowledge that the absence of interoperability standards over the years has led to the duplication of efforts and the inefficient use of ICT resources in health care. Now that ICT has become increasingly relevant in improving efficiency in health service delivery, the Kenya MOH recognizes the need to adopt a standardized approach, hence the development of interoperability standards for eHealth systems. In addition, the Health Sector ICT Standards and Guidelines [ 48 ] emphasize the relevance of interoperability as a requirement for addressing the inconsistency in implementing ICT in the health sector.

The Health Sector ICT Standards and Guidelines [ 48 ] consider “integration of ICT systems” as one of its key guiding principles, acknowledging the lack of information systems integration as a challenge experienced by ICT services across Kenya.

The contexts for inclusion and equitable access as generated from included standards [ 18 , 47 , 48 ] were (1) to promote inclusion and (2) to promote equitable access to services.

To promote inclusion, the standards [ 18 , 47 , 48 ] highlight the importance of involving and engaging multiple actors and stakeholders during the development process. However, no emphasis was placed on the need to sustain stakeholder engagement during the implementation process.

Pertaining to equitable access, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] acknowledges that the public health care system is largely unavailable to most of the population in many developing countries because of geographical location, resource constraints, inefficiencies, and lack of awareness. Hence, it recognizes the importance of ensuring that mHealth services are always accessible by users and from anywhere as well as the need to put in place mechanisms to make this happen.

Process: How the Regulations Are Developed and Implemented

Two themes were generated from the included standards: development and implementation processes [ 18 , 47 , 48 ].

Development Process

All the included standards [ 18 , 47 , 48 ] indicate that they were developed through a participatory process and in consultation with a range of subject experts and interest groups. In addition, the standards [ 18 , 47 , 48 ] adopted a multisectoral approach to engage health-related stakeholders from government ministries or agencies and development partners and a range of subject experts and interest groups. It has also been reported that these standards [ 18 , 47 , 48 ] were developed based on international best practices and with reference to international standards. However, there is no indication that a stakeholder engagement strategy was adopted to sustain the engagement of stakeholders through the entire development and implementation process.

Implementation Process

The 3 regulatory standards [ 18 , 47 , 48 ] identify the key requirements to ensure effective implementation of IT services in the health sector. These are (1) legal authority, (2) coordination, (3) building capacity, and (4) monitoring and evaluation.

The included standards [ 18 , 47 , 48 ] were established based on the legal provisions enshrined in the health and other related acts and laws of Kenya as well as the relevant policies and strategies. Hence, it is expected that their implementation will comply with and be backed by those legal provisions. For example, the Health Sector ICT Standards and Guidelines [ 48 ] indicate that its implementation will be supported by the authority from the Kenya Communications Act 2009, E-Government Strategy, and National ICT Policy. Similarly, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] asserts that it will be implemented by complying with existing and relevant national policies, legal frameworks, strategies, and standards, including the Health Information Policy, ICT Standards, and System Interoperability Principles.

The included standards [ 18 , 47 , 48 ] report that the implementation of regulations will require robust coordination mechanisms. For instance, the Health Sector ICT Standards and Guidelines [ 48 ] indicate that, as the Ministry’s ICT resource manager, the principal secretary (also the head of ICT), in collaboration with the ICT Governance Committee, is responsible for coordinating the implementation of the standard. The ICT Governance Committee comprises representatives from the heads of departments and ICT development partners in the health sector. The committee’s responsibilities include overseeing, enforcing, and reviewing standards as well as initiating ICT projects.

The Health Sector ICT Standards and Guidelines [ 48 ] highlight the need for capacity building or training of the MOH staff and stakeholders who are the primary users of the Ministry’s ICT services. This will enhance their capacity to implement the guidelines provided in the document in line with the ministry’s human resource development policies, regulations, and rules. However, it is acknowledged that building capacity for health ICT is a challenge given that there is low adoption of ICT among health providers, and ICT is not routinely included in the course content of most training programs. The Kenya Standards and Guidelines for mHealth Systems [ 18 ] listed the “number of mHealth practitioners trained on the standards and guidelines” as one of the indicators for monitoring and evaluating mHealth interventions.

The Health Sector ICT Standards and Guidelines [ 48 ] assert that monitoring and evaluation is an essential role of the MOH to ensure efficiency, accountability, and transparency throughout the implementation period. It further stresses that all those who use the Ministry’s ICT services are required to adhere to the provisions in the standard as the MOH will carry out quarterly monitoring exercises on the use of the standard to ensure compliance based on clear indicators. Furthermore, the ICT Governance Committee will periodically review and amend the standard to keep it relevant and effective. Similarly, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] establishes the following key indicators for effectively monitoring and evaluating the implementation of the standards and guidelines: (1) the number of counties in which the MOH has disseminated the standards and guidelines, (2) the number of counties successfully implementing the standards and guidelines, (3) the number of mHealth practitioners trained on the standards and guidelines, (4) the number of mHealth practitioners accessing the standards and guidelines, (5) the number of mHealth practitioners who correctly understand the standards and guidelines, (6) the number of stakeholders who adhere to the standards and guidelines, (7) the number of mHealth systems that follow the required development steps, and (8) the number of mHealth practitioners who have implemented their systems by using the standards and guidelines. In addition, the Kenya Standards and Guidelines for mHealth Systems [ 18 ] indicates that the outlined standards will be reviewed every 3 years to ensure they are up to date with new changes including the changes in policies and systems upgrades.

Although all the abovementioned indicators are relevant, the implementation process is not explicit on the approach for regulating health apps and ensuring compliance with regulatory standards and guidance.

Actors: Those the Regulations Are Targeted at

The included standards [ 18 , 47 , 48 ] identified 2 main groups of actors for whom the regulations and guidance were targeted. They included (1) those who provide digital health services and (2) those who use the ICT infrastructure of the MOH.

Two of the standards [ 47 , 48 ] indicated that the regulations should be implemented by all individuals and organizations that provide ICT-related health care services to the public. Similarly, the Health Sector ICT Standards and Guidelines [ 48 ] state that all those who access or use the MOH ICT infrastructure are expected to adhere to the guidelines outlined in the document.

Mapping of Stakeholders

To address the third research question, we conducted a stakeholder mapping guided by the RISA tool [ 41 ].

A total of 11 categories of key stakeholders were identified from all 49 included documents (6 stand-alone regulatory standards and guidance, 35 national policies or strategies, and 8 other related documents). These categories are consistent with the digital health stakeholders recognized by the WHO, ITU, and UNESCO [ 32 , 33 , 43 ]. Table 2 presents the mapping of stakeholders according to their role categorization. A more detailed table with a potential role description with regard to regulating health apps for self-management is presented in Multimedia Appendix 4 .

a WHO: World Health Organization.

This paper presents the findings of a scoping review of regulatory standards and guidance for the use of health apps for self-management in sub-Saharan Africa. To the best of our knowledge, this is the first study that attempted to identify and assess the extent to which regulatory standards and guidance regulate and guide the use of health apps for self-management in sub-Saharan Africa as well as map out the key stakeholders and their potential roles.

Our findings reveal that only 1 country (Kenya) in sub-Saharan Africa currently has national regulatory standards that could potentially regulate the use of health apps for self-management. The included standards failed to adequately address adequate attention to inclusion and equitable access. This is concerning given the growing need to promote the adoption of culturally appropriate and relevant health apps and to ensure that they are available to those who need them regardless of gender, ethnicity, geographical location, or financial status [ 24 - 29 ]. Consequently, this review provides insights into the regulation of health apps for self-management in sub-Saharan Africa, which needs to be given more attention if the potential of these apps is to be harnessed in the region.

Principal Findings

We identified 49 documents from 31 countries in sub-Saharan Africa. Although none of the included standards provided a specific set of regulations on health apps for self-management, we identified 3 standards [ 18 , 47 , 48 ] that provided relevant information regarding the regulation of health apps. The included national policies and strategies, in contrast, only outline the goals and commitments made by national governments to promote the adoption of digital technologies in the health sector and the plans and paths set forth to achieve these goals. However, the information they provided was relevant for identifying and mapping digital health stakeholders who potentially have vital roles in regulating the use of health apps for self-management.

The policy analysis framework (content, context, process, and actors) [ 42 ] was adapted and applied to organize the key findings. The content covered the following areas: guidance on systems quality; guidance on software and app development, acquisition, support, and maintenance; security measures for adequate protection of patients’ digital records; guidance on data exchange; interoperability as a basic requirement; minimum standards to enable integration; involvement and engagement of relevant stakeholders; and system attributes for equitable access to services. Meanwhile, the context was to address unsafe, isolated, and inconsistent implementation; to build mutual trust and maximize the benefits of eHealth information exchange; to address poor coordination, duplication of efforts, and inefficient use of resources; to promote the integration of ICT systems; and to promote inclusion and equitable access to services. The process involved the development process (which covers participatory and consultative processes and multisectoral approach, with reference to international standards and best practices) and the implementation process (which covers legal authority, coordination, capacity building, and monitoring and evaluation). The targeted actors were those who provided digital health services and those who used the ICT infrastructure of the MOH.

Furthermore, key stakeholders with potential roles in regulating health apps for self-management were identified. They include the government, regulatory bodies, funders, intergovernmental and nongovernmental organizations, academia, and the health care community.

Implications of the Study Findings for Practice

Regulatory standards and guidance act as a bridge between technological innovation and its safe and effective use in health care. They ensure that while technology continues to advance, the safety and trust of patients are never compromised. Among the plethora of health apps on the market, the over-the-counter, nonregulated apps such as wellness and fitness apps are the most mainstream [ 93 - 95 ]. On the other side of the spectrum, there are regulated health apps that are classified under medical devices or software as medical device products [ 94 , 95 ]. Some of these are prescription-only apps, such as digital therapeutics (DTx) apps for managing substance dependence [ 95 , 96 ].

Although some high-income countries have made significant strides in ensuring the safety, effectiveness, and accessibility of health apps, the journey has indeed not been without challenges and hurdles. Sub-Saharan Africa, although dealing with its own unique set of challenges, has the opportunity to learn from the experiences of these high-income countries. This could potentially allow the region to bypass some of the hurdles encountered by high-income countries in their journeys.

Technical and clinical safety are essential requirements that health apps must meet before they can be considered for use for self-management to minimize the risk of harm to patients. It is well documented that health apps that function poorly pose a serious threat to the safety of patients. An example illustrating how health apps used for self-management can threaten patient safety is evident in a study [ 12 ]. This study [ 12 ] revealed that widely used health apps designed to calculate and estimate insulin doses could endanger patients by providing incorrect or inappropriate dose recommendations. Similarly, 2 successive studies that assessed the contents and tools of apps for asthma discovered that none of the apps in the first study offered comprehensive information or adequate tools for asthma self-management, whereas the follow-up study, which was conducted 2 years later, showed a 2-fold increase in the number of asthma apps, yet there was no improvement in the content and tools offered by the newer apps. In fact, many apps recommended self-management procedures that were not supported by evidence [ 13 , 14 ]. Accordingly, some health apps that support the self-management of long-term conditions do not adhere to evidence-based guidelines and are unresponsive to the evolving health needs of patients.

Although the context of included regulatory standards with regard to technical and clinical safety was to address unsafe, isolated, and inconsistent implementation, the guidance provided by these regulatory standards is not specific to health apps, and they do not provide appropriate guidance and standards for health organizations and other key stakeholders to establish a framework for managing the clinical risks associated with deploying and implementing self-management health apps. Considering the rapid advancements in digital health (including artificial intelligence [AI] or machine learning and big data), health apps will increasingly play a crucial role in supporting self-management through digitally enabled care pathways that will improve personalized care and health outcomes [ 97 , 98 ]. Therefore, it is imperative to ensure the technical reliability and clinical safety of health apps for self-management through robust regulatory standards and guidance. For instance, a guide on the criteria for health app assessment, developed by the UK government, includes technical stability and clinical safety as criteria for deciding whether health apps should be considered for use in the National Health Service (NHS) [ 99 ]. In addition, medical device apps are required to conform to the NHS clinical risk management standards as part of the clinical safety requirements [ 99 , 100 ]. In the event of any concerns regarding the safety of a medical device app, the Yellow Card reporting system can be used by a responsible clinical safety officer or any other individual to notify the Medicines and Healthcare products Regulatory Agency (MHRA) [ 101 , 102 ].

To adequately manage patient information when health apps are used for self-management, data protection and security standards and guidance are required. They guarantee that data are kept and handled safely and responsibly within the provisions of the law and that patients’ rights and interests are respected.

There have been ongoing concerns about compliance with ethical standards, the principles of confidentiality of information, and data privacy. For example, an assessment of apps that had previously been endorsed by the former UK NHS Apps Library revealed substantial gaps in compliance with data protection principles regarding the collection, storage, and transmission of personal information. This has raised a fundamental concern about the credibility of developer disclosures and whether these disclosures can be trusted by certification programs [ 15 ]. A study assessed the privacy practices of the 36 most popular apps for depression and smoking cessation for Android and iOS in the United States and Australia [ 16 ]. The findings revealed that although only 69% (25/36) of the apps included a privacy policy, 92% (33/36) of the apps shared data with a third party, and only 92% (23/25 with privacy policy) of the apps disclosed sharing data with a third party in their policy. Although 81% (29/36) of the apps shared data with Google and Facebook for the purposes of advertising, marketing, or analytics, only 43% (12/28) of the apps that shared data with Google and 50% (6/12) of the apps that shared data with Facebook disclosed this in their policy [ 16 ].

In this regard, health app developers and providers in the United Kingdom are required to conduct a data protection risk assessment before they launch or update their apps to ensure compliance with the United Kingdom General Data Protection Regulation (GDPR) and other relevant regulations, including the Data Protection Act 2018 [ 103 ]. By conducting a data protection risk assessment, health app developers and providers can demonstrate that they are accountable; they respect the privacy and dignity of their users; and that they deliver safe, effective, and ethical solutions [ 104 ].

Health apps are expected to play an increasingly important role in supporting self-management. However, this ambition can only be achieved if citizens trust that these apps are collecting and analyzing data safely and in accordance with robust regulatory standards and guidance. It is also crucial that these apps provide reliable information that clinicians can act on [ 98 ]. The context of the standards included in this study regarding data protection and security was to build mutual trust and maximize the benefits of eHealth information exchange. Trust is a key factor in the successful adoption and use of health apps, and transparency in data handling and clinical decision-making is essential to build and maintain that trust. This is also paramount for the widespread acceptance and impact of health apps on health care outcomes in sub-Saharan Africa.

We acknowledge the existence of numerous national laws related to data protection and security outside the health sector. Hence, guidelines that link these legislations together must be provided to ensure compliance with all relevant laws and guidance when using patient data. An example of how to achieve this is the United Kingdome’s guide to good practice for digital and data-driven health technologies that provides guidelines on how to abide by the laws and principles that govern data security and protection in the United Kingdom, including the GDPR, Data Protection Act 2018, and Caldicott Principles [ 105 ].

Standards and interoperability are essential for effectively developing, deploying, and implementing health apps to support self-management in sub-Saharan Africa. Interoperability is the ability of different systems, devices, or applications to communicate and exchange data with each other in a coordinated manner, thus providing timely and seamless portable information across organizational, regional, and national boundaries and optimizing both individual and population health [ 106 ]. In the same vein, standards enable interoperability between systems or devices through a common language and a common set of expectations [ 106 ].

Interoperability is crucial in improving the quality, safety, and efficiency of care delivery as well as empowering patients and providers with access to relevant and timely information [ 99 ]. One of the most widely used and accepted interoperability standards for health care data exchange is FHIR [ 106 , 107 ]. FHIR is a global industry standard developed by HL7 International. FHIR is designed to be quick to learn and implement and to support a variety of use cases, including self-management [ 108 ]. By using apps that are based on an FHIR standard, patients can benefit from data analytics that show how their health data relate to their chronic conditions or wellness goals [ 109 ]. They could also access all their health information from one place, even if they visit different health professionals who use different electronic medical records or EHR, thus promoting integrated care [ 28 , 31 , 33 , 109 - 115 ]. As a result, patient care can easily be coordinated.

The context of the included regulatory standards with regard to standards and interoperability was to address poor coordination, duplication of efforts, and inefficient use of resources and to promote the integration of ICT systems. However, in sub-Saharan Africa, there are many challenges and barriers to the adoption and implementation of interoperability standards, such as the lack of awareness or knowledge of the benefits and requirements of interoperability standards among stakeholders; lack of incentives or regulations to encourage or enforce the adoption of interoperability standards by app developers and vendors; lack of resources or capacity to implement interoperability standards, including technical expertise, infrastructure, funding, or governance; and lack of alignment or coordination among the different actors and initiatives involved in developing, deploying, and implementing the digital health interventions [ 30 , 116 - 119 ]. To address these challenges, some possible solutions may include raising awareness and education on the importance and value of interoperability standards for health apps among all relevant actors; developing and implementing policies and guidelines that promote or mandate the use of interoperability standards by app developers and vendors; providing technical assistance and support for app developers and vendors to adopt and implement interoperability standards, such as tools, frameworks, testing, certification, or accreditation; and establishing and strengthening collaboration and coordination among the different stakeholders and initiatives involved in health app development, deployment, and implementation in sub-Saharan Africa. In addition, the Digital Health Platform Handbook, a toolkit developed by the collaborative efforts of the WHO and ITU [ 120 ], can help countries in sub-Saharan Africa to develop and implement digital health platforms as the underlying infrastructure for interoperable and integrated national digital health systems. The digital health platform is a system-wide approach to developing digital health solutions with the aim to overcome the problems of siloed, vertical, and isolated applications and systems that hamper data management, innovation, efficiency, and impact in the health sector.

Inclusion and equitable access are crucial to ensuring that health apps and related services are culturally appropriate and relevant as well as accessible to all who need them, regardless of gender, ethnicity, geographical location, ability, or financial status [ 24 - 29 ]. This is the key to promoting a “sense of belonging” and “ownership” and thus underscoring the importance of stakeholder mapping and involvement or engagement through the development and implementation process [ 22 ].

In this study, the included regulatory standards demonstrate the importance of inclusion by adopting both a participatory and consultative approach involving multiple stakeholders from different sectors. However, the standards do not provide clear guidance to ensure the adequate participation and sustained engagement of all relevant stakeholders. The lack of concise guidance to ensure the adequate participation and engagement of all relevant stakeholders, especially the susceptible and disadvantaged groups, can increase the risk of tokenistic tendencies, which can undermine the cultural appropriateness of health apps [ 25 , 121 ]. Some susceptible groups, such as women and people with low socioeconomic status, may face additional barriers to accessing and using health apps, such as lack of digital literacy, privacy concerns, cultural norms, or stigma [ 25 ]. Similarly, the cost of developing, maintaining, and updating health apps may not be covered by public or private health insurance schemes, which could limit their affordability and availability for low-income or uninsured populations [ 95 ]. However, there is no specific guidance or model for an effective funding mechanism for health apps in the included regulatory standards.

To address these challenges and ensure equitable access to health apps for self-management in sub-Saharan Africa, possible measures may include developing policies and regulations that support integrating health app interventions into existing health systems and financing mechanisms and engaging with stakeholders from different sectors and backgrounds (including health professionals, patients, communities, governments, civil society, academia, and industry) to co-develop and co-implement frameworks or models that promote the use of health apps for self-management in ways that are responsive to the local context and needs. Moreover, establishing regulations that provide appropriate financing or reimbursement options will reduce the risk of developers of good quality health apps turning to data mining for revenue, thus increasing privacy concerns [ 95 ]. For instance, in Germany, the reimbursement of health apps classified as medical devices (Digitale Gesundheitsanwendungen) was introduced in 2021 under the statutory health insurance [ 122 , 123 ]. When a medical device is prescribed by a physician or a physiotherapist, the manufacturer must submit an application to the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte) for approval [ 123 ]. The Federal Association of the Statutory Health Insurance Funds (Spitzenverband Bund der Krankenkassen) determines and negotiates the reimbursement thresholds following approval. However, the manufacturer must demonstrate that the app is safe, functional, and of good quality; complies with data protection requirements; and benefits patient care [ 123 ].

The process of regulating health apps essentially involves the development and implementation of regulatory standards and guidance. According to our study, the development process comprises a participatory and consultative process, a multisectoral approach, and a reference to international standards and best practices. In contrast, the implementation process is ongoing and requires appropriate legal authority, coordination, capacity building, and monitoring and evaluation.

We recognize that health apps can be accessed and used by patients from different parts of the world, and this means that countries need to carefully consider whether health apps that are accessed and used by their citizens meet the national or regional legal and ethical requirements, including their cultural and linguistic needs [ 23 ]. For countries in sub-Saharan Africa, a cross-border or regional collaboration between national legal authorities through the coordination of agencies such as the African Medicines Regulatory Harmonization (AMRH) may help to ensure that health apps built for the region are safe, effective, and user-friendly for everyone, considering the contextual differences of the countries [ 23 ]. For instance, all medical device companies that want to sell their products in the European market must obtain a Conformité Européenne (CE) mark for their devices, which indicates that they meet the legal requirements and can be freely circulated within the European Union [ 124 ]. Although the European Union member states regulate medical devices, the European Medicines Agency is involved in the regulatory process.

The regulation of health apps is extremely complex and involves a wide range of stakeholders. Therefore, a robust coordination mechanism is essential to reduce the risk of fragmentation and duplication of efforts and to promote the efficient use of resources. Most countries in sub-Saharan Africa have units in health ministries that coordinate and oversee the regulation of medical products. These units should be autonomous, full-fledged departments with legal authority (boards or commissions) to ensure independent, transparent, and accountable decision-making, but this is often not the case [ 125 ]. These units are recognized by the national authorities as regulators (eg, the National Medicines Regulatory Authority [NMRA]) [ 126 ]. Such organizational structures hinder the effectiveness of the national regulatory authorities in fulfilling their mandate and prevent the establishment of quality management systems to ensure transparent and accountable decision-making [ 125 ].

Furthermore, Essén et al [ 23 ] analyzed health app policy or regulation in 9 high-income countries (Sweden, Norway, Denmark, Netherlands, Belgium, Germany, England, the United States, and Singapore) and found that most of these countries adopted centralized approaches to app evaluation. Although centralized approaches might have advantages over self-evaluation, they may create bottlenecks and limit the availability of high-quality health apps for users. As suggested by Essén et al [ 23 ], a decentralized approach, such as the accreditation of evaluation agencies, maybe a worthwhile solution. However, this will require adequate coordination to ensure the consistency and reliability of the evaluation criteria and methods across different agencies as well as the transparency and accountability of the accreditation process. A possible way to achieve this is to adopt a common framework that can guide the evaluation and accreditation of health apps.

Similarly, the postmarket surveillance (PMS) system, which is a new regulation for medical devices in Europe, is a process of collecting and analyzing data on medical devices after they have been launched into the market to ensure their safety and performance and to identify any problems or need for improvements [ 127 , 128 ]. The PMS system is important because premarket data, which are obtained from testing a medical device before it is launched, have limitations in capturing the long-term performance and risks of the device [ 128 ]. Currently, the PMS system does not cover fitness and wellness apps, which are commonly used in self-management. Hence, Yu [ 93 ] proposed that the PMS system should also be applied to DHTs, such as fitness and wellness apps. They argue that the postmarket data would help regulators periodically review and adjust the regulatory standards for these groups of health apps based on their risks and benefits.

Drawing on the experience of the United Kingdom, it can be clearly demonstrated that the regulation of health apps is a complex, a multifaceted, and an evolving process that involves different regulators and criteria depending on the nature and function of the app. For instance, a centralized NHS Apps Library was launched as a beta site in April 2017 to provide patients with a collection of trusted and easy-to-use digital health tools [ 129 ]. The library provided access to a range of health apps that were reviewed and approved by the NHS, including apps that could help patients manage conditions such as diabetes, mental health, and chronic obstructive pulmonary disease [ 130 ]. However, the library was closed in December 2021 [ 131 ]. Although no reason for the closure was provided on the website, it is likely because of persistent concerns regarding the safety of patients and data privacy involving multiple apps including those listed in the library [ 12 , 14 - 16 , 131 , 132 ]. The NHS App was introduced in January 2019 before the closure of the NHS Apps Library to serve as the gateway for accessing NHS services including ordering repeat prescriptions and booking or managing appointments [ 133 ].

Furthermore, the United Kingdom Health Security Agency, formerly known as Public Health England, issued a guidance on criteria for health app assessment in October 2017 [ 99 ]. The purpose of this guidance was to ensure that all health apps built for the UK population work well and provide clear information about their functions, benefits, and intended outcomes for patients and health care professionals. On the basis of this guidance, those intending to build an app are required to conform to certain regulations before being considered for the app assessment process. The 2 main regulations are the medical device regulation and the Care Quality Commission (CQC) registration. Apps that are considered as medical devices must register with the MHRA and have a CE mark. Apps providing health or social care that fit into 1 of 14 regulated activities are required to register with the CQC before they can be assessed [ 134 ]. CQC is an independent regulator of health and social care services in England.

Similarly, the Organisation for the Review of Care and Health Apps (ORCHA) is a UK-based organization that independently evaluates and distributes health apps. It provides services such as app review, accreditation, curation, and recommendation within the United Kingdom and across the world [ 135 ]. ORCHA also enables organizations (including the NHS) to build a decentralized web-based digital health library of consumer-friendly over-the-counter apps [ 135 - 137 ]. These apps are continuously assessed by ORCHA against the standards and regulations in clinical and professional assurance, data quality and privacy, and usability and accessibility [ 137 ].

In addition, the Digital Technology Assessment Criteria (DTAC) were introduced in beta in October 2020, and its first official version was subsequently launched in February 2021 [ 138 ]. The DTAC plays a crucial role in ensuring that digital health tools meet the necessary standards in areas such as clinical safety, data protection, technical security, interoperability, usability, and accessibility. By serving as the national baseline criteria for DHTs in the NHS and social care, it provides a valuable framework for health care organizations during procurement. It also offers guidance for developers on the expectations for their digital technologies within the NHS and social care. This is an example of how a harmonized framework can help ensure the quality and safety of DHTs, including health apps.

In addition, the National Institute for Health and Care Excellence Evidence Standards Framework is a set of evidence standards for a wide range of DHTs designed to help evaluators and decision makers in the health care system to consistently identify DHTs that are likely to offer benefits to the users and the health care system [ 139 ]. The Evidence Standards Framework was first published in March 2019 and is ideally used before DHTs (including health apps) are considered for commissioning or procurement by the NHS [ 140 ]. It is a crucial tool for ensuring that DHTs are clinically effective and offer value to the health and care system in the United Kingdom. In August 2022, the framework was updated to include AI and data-driven technologies with adaptive algorithms [ 140 ].

Furthermore, DTx apps, which are a type of medical device, are not allowed into the UK market unless they comply with the UK GDPR and meet the requirements of DTAC. In addition, they must bear the CE or UK Conformity Assessed marks [ 141 ]. This means that DTx apps must demonstrate their safety and efficacy through clinical trials and comply with the relevant regulations for data protection and quality standards as regulated by the MHRA. DTx products are also recognized as DHTs under the National Institute for Health and Care Excellence Evidence Standards Framework [ 142 ]. DTx incorporates software to treat, prevent, or manage specific diseases or conditions [ 143 , 144 ]. The fact that DTx products typically focus on a narrow clinical indication and generate evidence of clinical efficacy underscores their potential to make a substantial contribution to self-management and health care delivery in general. The increasing recognition of the role of DTx in patient care by regulators is also noteworthy, and the creation of regulatory and reimbursement pathways for approved apps further enables DTx products to continue to play an important role in impacting health care delivery [ 1 , 143 ]. This is a testament to the potential of regulated health apps to revolutionize health care and improve patient outcomes.

Among the many lessons to learn from the experience of the United Kingdom is that the regulation of health apps must evolve to keep pace with advances in DHTs and adapt to the changing needs and demands of digital health. Moreover, efforts are being made to streamline the multifaceted approaches to simplify app regulation and access in the United Kingdom [ 23 ]. Therefore, a robust and dynamic coordination mechanism, along with political will, skilled personnel, reliable funding, and a robust framework for monitoring and evaluating progress and aligning key performance indicators, is essential for countries in sub-Saharan Africa to keep pace with the advancement in the regulation of health apps. There is also a need to strengthen collaboration and ensure regulatory harmonization among national regulatory authorities and continental bodies such as the regional economic communities, AMRH, and the WHO AFRO [ 126 ].

Capacity building and monitoring and evaluation are important factors for ensuring effective regulation of health apps given the complex nature of the process. The regulation of medical products (including health apps) in sub-Saharan Africa generally includes licensing and accreditation, evaluation, inspection, quality control, information dissemination and promotion, and monitoring of adverse events [ 125 ]. Therefore, high-level skills as well as effective monitoring and evaluation will be required to ensure the success of the process. For most countries in sub-Saharan Africa, the NMRA is responsible for coordinating and overseeing the regulatory system of medical products [ 125 , 126 ]. However, in most cases, NMRAs are unable to perform the core regulatory functions expected of them [ 145 ]. More than 90% of African countries have limited or no capacity to regulate medical products, with only 7% having moderately developed capabilities [ 145 ]. The lack of effective NMRAs in Africa exposes the citizens to potential harm by allowing unsafe, low-quality, and fake medical products to circulate and be used [ 145 ].

Although it is the responsibility of governments to establish functional regulatory systems and ensure effective monitoring and evaluation of the regulatory process, the involvement of international and continental organizations to support sub-Saharan African countries improve the regulatory capacity of their national regulatory agencies would be extremely beneficial. For instance, the African Medicines Agency (AMA) was established in November 2019 as a treaty adopted by the African Union Member States to help address the concerns arising from weak regulatory systems on the continent. At present, 37 countries have signed the AMA treaty, including 26 countries that have ratified it [ 146 ]. The main objective of the AMA is to enhance the capacity of States Parties and regional economic communities to regulate medical products to improve the quality, safety, and efficacy of medical products on the continent [ 147 ]. The AMA, in collaboration with other existing capacity building initiatives or organizations, such as the WHO Global Initiative on Digital Health, ITU, AMRH, WHO AFRO, and United Nations Children’s Fund, can assist sub-Saharan African countries in aligning their regulatory requirements with available resources and support them to acquire the necessary tools and skills to build effective and sustainable regulatory systems for health apps. This can be achieved by adopting a decentralized approach to engage a network of technical experts across the African Union similar to the model of the European Medicines Agency [ 148 ].

Actors or Stakeholders

The regulation of health apps often requires working with a wide range of actors or stakeholders. However, in this review, we identified only 2 main actor groups (those who provide digital health services and those who use the ICT infrastructure of the health ministry). These are the groups that are targeted by the included regulatory standards.

From a broader perspective, 12 categories of stakeholders according to their potential role in regulating health apps for the self-management were mapped in this study. The potential contribution of these stakeholders to the regulation of health apps for self-management in sub-Saharan Africa not only depends on their roles and responsibilities but also on their interests, needs, expectations, and influence [ 41 , 149 - 151 ]. Thus, a robust stakeholder analysis is paramount as it can help define the scope of the regulatory process, prioritize the requirements, manage the expectations, and ensure the engagement and participation of stakeholders throughout the regulatory process [ 41 , 152 - 156 ]. Our stakeholder mapping, as presented in Table 2 (refer to Multimedia Appendix 4 for more details), lays the foundation for national governments to conduct a robust stakeholder analysis and to adopt an all-inclusive stakeholder engagement strategy to manage and sustain the engagement and participation of all relevant stakeholders [ 157 , 158 ].

Recommendations

Our review found that the regulation of health apps in sub-Saharan Africa is especially poor and almost nonexistent, as only Kenya has national standards that could address some of the regulatory issues related to health apps. Therefore, we recommend the following actions to help sub-Saharan African countries improve the regulation of health apps to support self-management:

• Establish a clear and consistent definition of what constitutes a health app (considering AI or machine learning) and what level of regulation is required for different types of apps.
• Develop and implement criteria and guidelines that ensure the quality, safety, and usability of health apps.
• Engage with independent app evaluators, such as ORCHA, to adopt a common framework that can guide the evaluation and accreditation of health apps and use the framework to create and maintain decentralized and transparent platforms that showcase and evaluate health apps for users and health care professionals.
• Develop and implement policies and regulations that enable sustainable funding for health apps such as integrating the use of health apps for self-management into existing health systems and financing pathways or mechanisms.
• Support and facilitate innovation and collaboration across the sub-Saharan Africa region, especially in areas including but not limited to data security and privacy, interoperability standards, usability, accessibility, funding, capacity building, and monitoring and evaluation of the regulatory process.
• Manage and sustain the engagement, involvement, and participation of all relevant stakeholders in the regulatory process by conducting a robust stakeholder analysis and adopting an all-inclusive stakeholder engagement strategy.

Strengths and Limitations of the Study

This study has several strengths, which include an extensive search of gray literature and repositories, contact with key individuals, and the use of a systematic approach. Given that regulatory standards and guidance are unavailable in scientific databases, a wide range of gray literature and repositories were searched. In addition, contact was made with key staff members to obtain relevant documents, including those at the MOHs, the WHO country offices, and the WHO AFRO. Second, to enhance the strength of the study, a policy analysis framework was adapted and used to systematically organize the key study findings, whereas a deductive descriptive qualitative content analysis approach was used to identify and analyze texts that contained relevant concepts and other related information based on the 4 predefined themes. Third, the RISA tool was used to guide the mapping of key stakeholders. This has further increased the robustness of the study findings.

The limitations of this study include the fact that our literature search was conducted in English. Although the literature search was conducted in English, it yielded documents written in French and Portuguese from the ICTworks repository. Second, regulatory standards and guidance are not readily available on scientific databases; hence, it is possible that some relevant documents might have been missed. However, efforts were made to obtain these documents by contacting key stakeholders including key contact persons at the WHO AFRO, WHO country offices, and MOHs. In addition, contacting key individuals only for the purposes of requesting documents rather than conducting direct interviews was one of the limitations of this study. Interviewing key contact persons and stakeholders to obtain additional information could have strengthened the review; however, we did not interview any key individuals or stakeholders because it was beyond the scope of this review. Nonetheless, we recommend that future studies consider incorporating interviews to explore the perspectives of key stakeholders.

Conclusions

Health apps are increasingly being used by patients to manage their health, and sub-Saharan African countries can leverage these apps to advance their progress toward achieving SDG 3 (good health and well-being) and UHC, especially given the rapid advancement of AI and big data. However, our study has established that the regulation of health apps in sub-Saharan Africa is inadequate to ensure that health apps are technically reliable and clinically safe; interoperable across systems; compliant with the principles of confidentiality of information and data privacy; culturally appropriate and relevant; and accessible to everyone regardless of gender, ethnicity, location, or income. Therefore, the region can learn from the experiences of some high-income countries such as the United Kingdom and Germany to develop and implement a robust and responsive regulatory system that supports the widespread adoption of safe, effective, and beneficial health apps for its population.

Following the publication of this review, a summary of the findings will be disseminated to the relevant organizations. In addition, the key findings will be summarized and presented at national, regional, and international conferences.

Acknowledgments

The authors would like to thank Rebecca Jones, the Library Manager and Liaison Librarian at Charing Cross Library, who advised and assisted with the search strategy for this study. This work is part of the PhD research of BAB, which is sponsored by the government of Nigeria. AM and JC were supported by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration Northwest London (NIHR200180). The views expressed in this publication are those of the authors and not necessarily those of the government of Nigeria or the NIHR or the Department of Health and Social Care. In the Results and Discussion sections, Microsoft Copilot in Bing [ 159 ] was used to help summarize and modify a few texts as well as suggest some citations.

Data Availability

The search strategy for PubMed, Scopus, and the World Health Organization AIM is presented in Multimedia Appendix 1 . All data generated or analyzed during this study are included in this published article (and its supplementary information files). The documents analyzed are available directly from the relevant institutional websites, ICTworks repository [ 44 ] or upon request from the relevant government departments in each country. Additionally, documents in the list of references that are not accessible on the web can be solicited from the corresponding author on reasonable request.

Authors' Contributions

BAB and JC conceived the study. BAB designed the study with contributions from JC and NM. BAB drafted the manuscript, and JC, NM, AM, SI, KPF, BIH, and NU read and contributed to it. AM was the clinical lead, and JC acted as a guarantor for this study. The final manuscript was read and approved by all the authors.

Conflicts of Interest

None declared.

PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist.

Database search strategy.

Details of included documents.

Mapping of the stakeholders according to their potential role in regulating health apps for self-management.

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Abbreviations

Edited by A Mavragani; submitted 19.05.23; peer-reviewed by N O'Brien, A Essén; comments to author 07.09.23; revised version received 08.12.23; accepted 23.02.24; published 11.04.24.

©Benard Ayaka Bene, Sunny Ibeneme, Kayode Philip Fadahunsi, Bala Isa Harri, Nkiruka Ukor, Nikolaos Mastellos, Azeem Majeed, Josip Car. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.04.2024.

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