Quantifying App Store Dynamics: Longitudinal Tracking of Mental Health Apps

In this review, we aim to summarize research findings and marketplace apps for women with perinatal mood disorders with the goal of informing clinicians and patients about current risks and benefits, as well as proposing clinical implementation advice and a harmonized agenda for both academic and industry advancement in this space. Multiple searches were run of academic databases in 2018–2020, examining literature on mobile apps for peripartum mental health. Multiple searches were also run of the iOS and Android app stores in 2019 and 2020, looking at apps for peripartum mental health. Results were compared within the academic dataset as well within the commercial app dataset; the two datasets were also examined for overlap. The academic search results were notable for small sample sizes and heterogeneous endpoints. The app store search results were notable for apps of generally poor quality (as assessed by a modified Silberg scale). Very few of the mHealth interventions studied in the academic literature were available in the app store; very few of the apps from the commercial stores were supported by academic literature. The disconnect between academically developed apps and commercially available apps highlights the need for better collaboration between academia and industry. More collaboration between the two approaches may benefit both app developers and patients in this demographic moving forwards. Additionally, we present a set of practice guidelines for mHealth in perinatal psychiatry based on the trends identified in this review.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00737-021-01138-z.

BackgroundMobile health services are thriving in the field of maternal and child health in China due to expansions in the field of electronic health and the introduction of the two-child policy. There are numerous maternal and child health apps in computer stores, but the exact number of apps, number of downloads, and features of these apps is not known.ObjectiveThis study aimed to explore the use of maternal and child health apps in Android and iOS app stores and to describe the key functional features of the most popular apps, with the purpose of providing insight into further research and development of maternal and child health mobile health products.MethodsThe researchers conducted a search in the 3 most popular Android app stores (Tencent MyApp, Baidu Mobile Assistant, and 360 Mobile Assistant) and the iTunes App Store in China. All apps regarding family planning (contraception and preparing for pregnancy), pregnancy and perinatal care, neonatal care and health, and development for children under 6 years were included in the initial analysis. Maternal and child health mobile apps with predominant features of product marketing, children’s songs, animation, or games were excluded from the study. The 50 most frequently used apps in each of the Android stores as well as the iTunes store (a total of 78 deduplicated apps) were selected and downloaded for an in-depth analysis.ResultsA total of 5276 Android apps and 877 iOS apps developed for maternal and child health care were identified. Of the 78 most frequently used apps, 43 (55%) apps focused on one stage of MCH care, mainly targeting child care (25 apps) and before pregnancy care (11 apps), whereas 35 (45%) of the apps covered 2 or more stages, most of which (32 apps) included both pregnancy and child care services. The app features that were commonly adopted by the popular apps were health education, communication, health status self-monitoring, a diary, reminders, and counseling. Within the app feature of “health status self-monitoring,” the researchers found 47 specific tools supporting activities such as pregnancy preparation, fetal heart monitoring, blood glucose and blood pressure monitoring, and doctor visits. A few apps were equipped with external devices (n=3) or sensors. No app with intelligent decision-support features to support disease management for conditions such as gestational diabetes and pregnancy-induced hypertension was found. A small number of apps (n=5) had a Web connection with hospital information systems to support appointment making, payments, hospital service guidance, or checking of laboratory results.ConclusionsThere are thousands of maternal and child health apps in the Chinese market. Child care, pregnancy, and before pregnancy were the mostly covered maternal and child health stages, in that order. Various app features and tools were adopted by maternal and child health apps, but the use of internal or external sensors, intelligent decision support, and tethering with existing hospital information systems was rare and these features need more research and development.

BackgroundSuboptimal understanding of depression and mental health disorders by the general population is an important contributor to the wide treatment gap in depression. Mental health literacy encompasses knowledge and beliefs about mental disorders and supports their recognition, management, and prevention. Besides knowledge improvement, psychoeducational interventions reduce symptoms of depression, enhance help-seeking behavior, and decrease stigma. Mental health apps often offer educational content, but the trustworthiness of the included information is unclear.ObjectiveThe aim of this study is to systematically evaluate adherence to clinical guidelines on depression of the information offered by mental health apps available in major commercial app stores.MethodsA systematic assessment of the educational content regarding depression in the apps available in the Apple App Store and Google Play was conducted in July 2020. A systematic search for apps published or updated since January 2019 was performed using 42matters. Apps meeting the inclusion criteria were downloaded and assessed using two smartphones: an iPhone 7 (iOS version 14.0.1) and a Sony XPERIA XZs (Android version 8.0.0). The 156-question assessment checklist comprised general characteristics of apps, appraisal of 38 educational topics and their adherence to evidence-based clinical guidelines, as well as technical aspects and quality assurance. The results were tabulated and reported as a narrative review, using descriptive statistics.ResultsThe app search retrieved 2218 apps, of which 58 were included in the analysis (Android apps: n=29, 50%; iOS apps: n=29, 50%). Of the 58 included apps, 37 (64%) apps offered educational content within a more comprehensive depression or mental health management app. Moreover, 21% (12/58) of apps provided non–evidence-based information. Furthermore, 88% (51/58) of apps included up to 20 of the educational topics, the common ones being listing the symptoms of depression (52/58, 90%) and available treatments (48/58, 83%), particularly psychotherapy. Depression-associated stigma was mentioned by 38% (22/58) of the apps, whereas suicide risk was mentioned by 71% (41/58), generally as an item in a list of symptoms. Of the 58 included apps, 44 (76%) highlighted the importance of help seeking, 29 (50%) emphasized the importance of involving the user’s support network. In addition, 52% (30/58) of apps referenced their content, and 17% (10/58) included advertisements.ConclusionsInformation in mental health and depression apps is often brief and incomplete, with 1 in 5 apps providing non–evidence-based information. Given the unmet needs and stigma associated with the disease, it is imperative that apps seize the opportunity to offer quality, evidence-based education or point the users to relevant resources. A multistakeholder consensus on a more stringent development and publication process for mental health apps is essential.

Cigarette smoking is a leading cause of preventable death, and identifying novel treatment approaches to promote smoking cessation is critical for improving public health. With the rise of digital health and mobile apps, these tools offer potential opportunities to address smoking cessation, yet the functionality of these apps and whether they offer scientifically based support for smoking cessation are unknown. The goal of this research was to use the American Psychiatric Association app evaluation model to evaluate the top-returned apps from Android and Apple app store platforms related to smoking cessation and investigate the common app features available for end users. We conducted a search of both Android and iOS app stores in July 2021 for apps related to the keywords "smoking," "tobacco," "smoke," and "cigarette" to evaluate apps for smoking cessation. Apps were screened for relevance, and trained raters identified and analyzed features, including accessibility (ie, cost), privacy, clinical foundation, and features of the apps, using a systematic framework of 105 objective questions from the American Psychiatric Association app evaluation model. All app rating data were deposited in mindapps, a publicly accessible database that is continuously updated every 6 months given the dynamic nature of apps available in the marketplace. We characterized apps available in July 2021 and November 2022. We initially identified 389 apps, excluded 161 due to irrelevance and nonfunctioning, and rated 228, including 152 available for Android platforms and 120 available for iOS platforms. Some of the top-returned apps (71/228, 31%) in 2021 were no longer functioning in 2022. Our analysis of rated apps revealed limitations in accessibility and features. While most apps (179/228, 78%) were free to download, over half had costs associated with in-app purchases or full use. Less than 65% (149/228) had a privacy policy addressing the data collected in the app. In terms of intervention features, more than 56% (128/228) of apps allowed the user to set and check in on goals, and more than 46% (106/228) of them provided psychoeducation, although few apps provided evidence-based support for smoking cessation, such as peer support or skill training, including mindfulness and deep breathing, and even fewer provided evidence-based interventions, such as acceptance and commitment therapy or cognitive behavioral therapy. Only 12 apps in 2021 and 11 in 2022 had published studies supporting the feasibility or efficacy for smoking cessation. Numerous smoking cessation apps were identified, but analysis revealed limitations, including high rates of irrelevant and nonfunctioning apps, high rates of turnover, and few apps providing evidence-based support for smoking cessation. Thus, it may be challenging for consumers to identify relevant, evidence-based apps to support smoking cessation in the app store, and a comprehensive evaluation system of mental health apps is critically important.

Background: There are currently more than 350,000 health apps in the Android and Apple app stores. The quality of a health app can be assessed by the Organization for the Review of Care and Health Apps (ORCHA), a United Kingdom based company that specialises in the quality assessment of health apps. The ORCHA baseline assessment (OBR) assess three aspects of a health app: 1) professional/clinical assurance (PCA), 2) user experience (UX) and 3) data privacy (DP). These three sections each provide a score but also contribute to an overall ORCHA score from 0 to 100 (where a score of 100 is the highest quality score and a score above 65 is desirable). Objective: To assess if there are any possible disparities in the quality of physical and mental health apps targeting four different age groups: children, teens, adults, and older people. Methods: A secondary dataset was used for this study, which included a total of 604 health apps that were previously assessed for quality using OBR. The 604 health apps comprise of 254 mental and 350 physical health apps. R language and R studio were used to analyse this data. Median and interquartile ranges (IQR) were used to assess the spread of app assessment scores achieved for PCA, UX and DP for each of the considered age groups. Unpaired two sample Wilcoxon tests were used to compare the quality assessment scores of mental and physical health apps across each age group. Bonferroni adjusted p-value was calculated for multiple tests. Results: Only physical health apps for children and older people managed to achieve a median ORCHA score above the acceptable threshold of 65. The median ORCHA score for physical health apps for teens and adults was below 65. The median ORCHA score for mental health apps for all four age groups was below 65. Physical health apps scored better than mental health apps for children, adults, and older people age group; however, this was only statistically significant for older people (p-value =.002). The PCA scores for mental health apps for older people (m=39.7, IQR=33.2) and physical health apps for teens (m=39.4, IQR=42.7) were lower than other age groups. Conclusion: This study indicates that, for older people, overall quality of physical health apps is higher when compared to mental health apps. Moreover, the professional/clinical assurance of both physical and mental health apps could be improved; specifically, mental health apps for older people and physical health apps for teens. To make adjunctive therapy regarding mental health more suitable for older people, improvements to health app quality should be made. This will allow for better integrated care as more people adopt the usage of health apps. A limitation of this analysis is that we are using a secondary dataset to study the quality of apps that were assessed by ORCHA and were included in this dataset. A similar study could be done using a random selection of apps.

BackgroundMobile health (mHealth) apps aim at providing seamless access to tailored health information technology and have the potential to alleviate global health burdens. Yet, they bear risks to information security and privacy because users need to reveal private, sensitive medical information to redeem certain benefits. Due to the plethora and diversity of available mHealth apps, implications for information security and privacy are unclear and complex.ObjectiveThe objective of this study was to establish an overview of mHealth apps offered on iOS and Android with a special focus on potential damage to users through information security and privacy infringements.MethodsWe assessed apps available in English and offered in the categories “Medical” and “Health & Fitness” in the iOS and Android App Stores. Based on the information retrievable from the app stores, we established an overview of available mHealth apps, tagged apps to make offered information machine-readable, and clustered the discovered apps to identify and group similar apps. Subsequently, information security and privacy implications were assessed based on health specificity of information available to apps, potential damage through information leaks, potential damage through information manipulation, potential damage through information loss, and potential value of information to third parties.ResultsWe discovered 24,405 health-related apps (iOS; 21,953; Android; 2452). Absence or scarceness of ratings for 81.36% (17,860/21,953) of iOS and 76.14% (1867/2452) of Android apps indicates that less than a quarter of mHealth apps are in more or less widespread use. Clustering resulted in 245 distinct clusters, which were consolidated into 12 app archetypes grouping clusters with similar assessments of potential damage through information security and privacy infringements. There were 6426 apps that were excluded during clustering. The majority of apps (95.63%, 17,193/17,979; of apps) pose at least some potential damage through information security and privacy infringements. There were 11.67% (2098/17,979) of apps that scored the highest assessments of potential damages.ConclusionsVarious kinds of mHealth apps collect and offer critical, sensitive, private medical information, calling for a special focus on information security and privacy of mHealth apps. In order to foster user acceptance and trust, appropriate security measures and processes need to be devised and employed so that users can benefit from seamlessly accessible, tailored mHealth apps without exposing themselves to the serious repercussions of information security and privacy infringements.

BackgroundResearchers have largely turned to commercial app stores, randomized trials, and systematic reviews to make sense of the mHealth landscape. Few studies have approached understanding by collecting information from target end users. The end user perspective is critical as end user interest in and use of mHealth technologies will ultimately drive the efficacy of these tools.ObjectiveThe purpose of this study was to obtain information from end users of mHealth technologies to better understand the physical and mental health apps people use and for what purposes.MethodsPeople with depressive or anxious symptoms (N=176) seeking entry into a trial of mental health and well-being apps for Android devices completed online questionnaires assessing depression and anxiety (Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7), past and current mental health treatment-seeking behavior, overall mobile device use, and use of mobile health apps. Participants reported the physical health and mental health apps on their devices and their reasons for using them. Data were extracted from the participant self-reports and apps and app purposes were coded in order to categorize them.ResultsParticipants were largely white, middle-aged females from the Midwest region of the United States recruited via a health care organization and Web-based advertising (135 female, 41 male, mean age 38.64 years, age range 19-75 years.) Over three-quarters (137/176, 77.8%) of participants indicated having a health app on their device. The top 3 kinds of apps were exercise, fitness, and pedometers or heart rate monitoring apps (93/176, 52.8%); diet, food, or calorie counting apps (65/177, 36.9%); and mental health/wellness apps (46/177, 26.1%). The mean number of mobile physical and mental health apps on a participant’s phone was 2.15 (SD 3.195). Of 176 participants, 107 (60.8%) specifically reported the top 5 health apps that they used and their purposes. Across the 107 participants, a total of 285 apps were reported, with 139 being unique apps. The majority of these apps were free (129/139, 92.8%). Almost two-thirds of participants (67/107, 62.6%) reported using health apps at least on a daily basis.ConclusionsAmong those seeking support for their well-being via physical and mental health apps, people are using a variety of health apps. These people use health apps on a daily basis, especially free apps. The most common reason for using a health app is to track some health-related data; for mental health apps specifically, training or habit building was the most popular reason. Understanding the end user perspective is important because it allows us to build on the foundation of previously established mHealth research and may help guide future work in mHealth.Trial RegistrationClinicaltrials.gov NCT02176226; https://clinicaltrials.gov/ct2/show/NCT02176226 (Archived by WebCite at http://www.webcitation.org/6rGc1MGyM)

China has the world's largest Android population with 270 million active users. However, Google Play is only accessible by about 30% of them, and third-party app stores are thus used by 70% of them for daily Android apps (applications) discovery. The trustworthiness of Android app stores in China is still an open question. In this paper, we present a comprehensive study on the trustworthy level of top popular Android app stores in China, by discovering the identicalness and content differences between the APK files hosted in the app stores and the corresponding official APK files. First, we have selected 25 top apps that have the highest installations in China and have the corresponding official ones downloaded from their official websites as oracle, and have collected total 506 APK files across 21 top popular app stores (20 top third party stores as well as Google Play). Afterwards, APK identical checking and APK difference analysis are conducted against the corresponding official versions. Next, assessment is applied to rank the severity of APK files. All the apps are classified into 3 severity levels, ranging from safe (identical and higher level), warning (lower version or modifications on resource related files) to critical (modifications on permission file and/or application codes). Finally, the severity levels contribute to the final trustworthy ranking score of the 21 stores. The study indicates that about only 26.09% of level APK files are safe, 37.74% of them are at warning level, and 36.17% of them are surprisingly at critical level. We have also found out that 10 (about 2%) APK files are modified and resigned by unknown third-parties. In addition, the average trustworthy ranking score (47.37 over 100) has also highlighted that the trustworthy level of the Android app stores in China is relatively low. In conclusion, we suggest Android users to download APK files from its corresponding official websites or use the highest ranked third-party app stores, and we appeal app stores to ensure all hosting APK files are trustworthy enough to provide a "safe-to-download" environment.

The rapid growth in development and using mobile health applications had significant potential in the field of health. The study objective was to describe apps in the most popular Iranian Android and iOS app stores. Detail information of apps was extracted, categorised by subject and descriptive analyses were done. 3,331 Android and 277 iOS apps were remained for study. 88% of popular Android mHealth apps were free on the other hand, 70% of popular iOS apps were paid. The average price of Android and iOS paid apps were $0.37 and $6.55. The average of rating value for all Android subcategories (total average 4.33) is higher than iOS subcategories (total average 3.58). Our study confirmed fitness was the most popular topic. The average of rating value for all Android subcategories was higher than iOS subcategories. It seems large number of mHealth app users preferred using applications which can update their content continuously.

The rapid growth in development and using mobile health applications had significant potential in the field of health. The study objective was to describe apps in the most popular Iranian Android and iOS app stores. Detail information of apps was extracted, categorised by subject and descriptive analyses were done. 3,331 Android and 277 iOS apps were remained for study. 88% of popular Android mHealth apps were free on the other hand, 70% of popular iOS apps were paid. The average price of Android and iOS paid apps were $0.37 and $6.55. The average of rating value for all Android subcategories (total average 4.33) is higher than iOS subcategories (total average 3.58). Our study confirmed fitness was the most popular topic. The average of rating value for all Android subcategories was higher than iOS subcategories. It seems large number of mHealth app users preferred using applications which can update their content continuously.

BackgroundNumerous mental health apps have been developed and made available to users on the current app market. Users may find it difficult and overwhelming to select apps from the hundreds of choices that are available in the app marketplace. Clarifying what information cues may impact a user’s selection and adoption of mental health apps is now a critical and pressing issue.ObjectiveThe aim of this study was to investigate the impact of information cues on users’ adoption of anxiety apps using observational data from the Android app market.MethodsA systematic search of anxiety apps was conducted on the Android app store by using keywords search. The title and metadata information of a total of 274 apps that met our criteria were collected and analyzed. Three trained researchers recorded the app rankings from the search results page on different dates and Web browsers.ResultsOur results show that ratings (r=.56, P<.001) and reviews (r=.39, P<.001) have significant positive correlations with the number of installs, and app prices have significant negative correlations with installs (r=−.36). The results also reveal that lower-priced apps have higher ratings (r=−.23, P<.001) and a greater number of app permission requests (r=.18, P=.002) from the device. For app titles, we found that apps with titles related to symptoms have significantly lower installs than apps with titles that are not related to symptoms (P<.001).ConclusionsThis study revealed a relationship between information cues and users’ adoption of mental health apps by analyzing observational data. As the first of its kind, we found impactful indicators for mental health app adoptions. We also discovered a labeling effect of app titles that could hinder mental health app adoptions and which may provide insight for future designs of mental health apps and their search mechanisms.

Mental health screening and diagnostic apps can provide an opportunity to reduce strain on mental health services, improve patient well-being, and increase access for underrepresented groups. Despite promise of their acceptability, many mental health apps on the market suffer from high dropout due to a multitude of issues. Understanding user opinions of currently available mental health apps beyond star ratings can provide knowledge which can inform the development of future mental health apps. This study aimed to conduct a review of current apps which offer screening and/or aid diagnosis of mental health conditions on the Apple app store (iOS), Google Play app store (Android), and using the m-health Index and Navigation Database (MIND). In addition, the study aimed to evaluate user experiences of the apps, identify common app features and determine which features are associated with app use discontinuation. The Apple app store, Google Play app store, and MIND were searched. User reviews and associated metadata were then extracted to perform a sentiment and thematic analysis. The final sample included 92 apps. 45.65% (n = 42) of these apps only screened for or diagnosed a single mental health condition and the most commonly assessed mental health condition was depression (38.04%, n = 35). 73.91% (n = 68) of the apps offered additional in-app features to the mental health assessment (e.g., mood tracking). The average user rating for the included apps was 3.70 (SD = 1.63) and just under two-thirds had a rating of four stars or above (65.09%, n = 442). Sentiment analysis revealed that 65.24%, n = 441 of the reviews had a positive sentiment. Ten themes were identified in the thematic analysis, with the most frequently occurring being performance (41.32%, n = 231) and functionality (39.18%, n = 219). In reviews which commented on app use discontinuation, functionality and accessibility in combination were the most frequent barriers to sustained app use (25.33%, n = 19). Despite the majority of user reviews demonstrating a positive sentiment, there are several areas of improvement to be addressed. User reviews can reveal ways to increase performance and functionality. App user reviews are a valuable resource for the development and future improvements of apps designed for mental health diagnosis and screening.

Mobile health applications (apps) hold promise as tools for symptom tracking and management of chronic rheumatic diseases such as PsA. Apps for PsA have not been systematically evaluated. We conducted a comprehensive review of apps designed for patients with PsA. The iOS and Android app stores were searched using the term 'arthritis' and individual app descriptions were reviewed for 'psoriatic arthritis'. Apps were downloaded and rated using the Mobile Application Rating Scale (MARS). Additionally, the apps were evaluated to determine functionality, use of symptom scales and potential for integration within clinical care. The search was conducted in spring 2024 and 130 apps were found that mentioned 'arthritis'. Seven had specific mentions of PsA in their description. We found several other relevant apps by following recommendations in the app stores. In total, 10 apps for patients with PsA were identified. MARS scores suggest they were moderate to excellent in quality. The functionality of the 10 apps differed: 7 allowed for symptom tracking, 3 allowed for data export to health records, 2 allowed for medication tracking and 1 contained a patient community platform. The symptom tracking capabilities varied widely and we could find only one published study of any of the apps. We analysed apps for PsA to identify potential unmet needs and found that there are few publicly available apps, their functionality varies tremendously and testing of these apps is almost non-existent. There appears to be room for improvement of apps for PsA.

BackgroundA large number of health apps are available directly to consumers through app marketplaces. Little information is known, however, about how consumers search for these apps and which factors influence their uptake, adoption, and long-term use.ObjectiveThe aim of this study was to understand what people look for when they search for health apps and the aspects and features of those apps that consumers find appealing.MethodsParticipants were recruited from Northwestern University’s Center for Behavioral Intervention Technologies’ research registry of individuals with mental health needs. Most participants (n=811) completed a survey asking about their use and interest in health and mental health apps. Local participants were also invited to participate in focus groups. A total of 7 focus groups were conducted with 30 participants that collected more detailed information about their use and interest in health and mental health apps.ResultsSurvey participants commonly found health apps through social media (45.1%, 366/811), personal searches (42.7%, 346/811), or word of mouth (36.9%, 299/811), as opposed to professional sources such as medical providers (24.6%, 200/811). From the focus groups, common themes related to uptake and use of health apps included the importance of personal use before adoption, specific features that users found desirable, and trusted sources either developing or promoting the apps.ConclusionsAs the number of mental health and health apps continue to increase, it is imperative to better understand the factors that impact people’s adoption and use of such technologies. Our findings indicated that a number of factors—ease of use, aesthetics, and individual experience—drove adoption and use and highlighted areas of focus for app developers and disseminators.

BackgroundAccurate and user-friendly assessment tools for quantifying alcohol consumption are a prerequisite for effective interventions to reduce alcohol-related harm. Digital assessment tools (DATs) that allow the description of consumed alcoholic drinks through animation features may facilitate more accurate reporting than conventional approaches.ObjectiveThis review aims to identify and characterize freely available DATs in English or Russian that use animation features to support the quantitative assessment of alcohol consumption (alcohol DATs) and determine the extent to which such tools have been scientifically evaluated in terms of feasibility, acceptability, and validity.MethodsSystematic English and Russian searches were conducted in iOS and Android app stores and via the Google search engine. Information on the background and content of eligible DATs was obtained from app store descriptions, websites, and test completions. A systematic literature review was conducted in Embase, MEDLINE, PsycINFO, and Web of Science to identify English-language studies reporting the feasibility, acceptability, and validity of animation-using alcohol DATs. Where possible, the evaluated DATs were accessed and assessed. Owing to the high heterogeneity of study designs, results were synthesized narratively.ResultsWe identified 22 eligible alcohol DATs in English, 3 (14%) of which were also available in Russian. More than 95% (21/22) of tools allowed the choice of a beverage type from a visually displayed selection. In addition, 36% (8/22) of tools enabled the choice of a drinking vessel. Only 9% (2/22) of tools allowed the simulated interactive pouring of a drink. For none of the tools published evaluation studies were identified in the literature review. The systematic literature review identified 5 exploratory studies evaluating the feasibility, acceptability, and validity of 4 animation-using alcohol DATs, 1 (25%) of which was available in the searched app stores. The evaluated tools reached moderate to high scores on user rating scales and showed fair to high convergent validity when compared with established assessment methods.ConclusionsAnimation-using alcohol DATs are available in app stores and on the web. However, they often use nondynamic features and lack scientific background information. Explorative study data suggest that such tools might enable the user-friendly and valid assessment of alcohol consumption and could thus serve as a building block in the reduction of alcohol-attributable health burden worldwide.Trial RegistrationPROSPERO International Prospective Register of Systematic Reviews CRD42020172825; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020172825