Here's something I prepared earlier: a review of the time to publication of cross-sectional reviews of smartphone health apps

Evaluating the quality, safety, and functionality of commonly used smartphone apps for bipolar disorder mood and sleep self-management

Background

Individuals with bipolar disorder (BD) are increasingly turning to smartphone applications (apps) for health information and self-management support. While reviews have raised concerns regarding the effectiveness and safety of publicly available apps for BD, apps surveyed may not reflect what individuals with BD are using. The present study had two aims: first, to characterize the use of health apps to support mood and sleep amongst people with BD, and second, to evaluate the quality, safety and functionality of the most commonly used self-management apps.

Methods

A web-based survey was conducted to explore which apps people with BD reported using to support self-management of mood and sleep. The characteristics of the most commonly nominated apps were described using a standardized framework, including their privacy policy, clinical foundations, and functionality.

Results

Respondents (n = 919) were 77.9% female with a mean age of 36.9 years. 41.6% of participants (n = 382) reported using a self-management app to support mood or sleep. 110 unique apps were nominated in relation to mood, and 104 unique apps nominated in relation to sleep; however, most apps were only mentioned once. The nine most frequently nominated apps related to mood and sleep were subject to further evaluation. All reviewed apps offered a privacy policy, however user control over data was limited and the complexity of privacy policies was high. Only one app was developed for BD populations. Half of reviewed apps had published peer-reviewed evidence to support their claims of efficacy, but little research was specific to BD.

Conclusion

Findings illustrate the potential of smartphone apps to increase the reach of psychosocial interventions amongst people with BD. Apps were largely created by commercial developers and designed for the general population, highlighting a gap in the development and dissemination of evidence-informed apps for BD. There may be risks in using generic health apps for BD self-management; clinicians should enquire about patients’ app use to foster conversations about their particular benefits and limitations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40345-022-00256-6.

Assessing mental health apps marketplaces with objective metrics from 29,190 data points from 278 apps

OBJECTIVE

Utilizing a standard framework that may help clinicians and patients to identify relevant mental health apps, we sought to gain a comprehensive picture of the space by searching for, downloading, and reviewing 278 mental health apps from both the iOS and Android stores.

METHODS

278 mental health apps from the Apple iOS store and Google Play store were downloaded and reviewed in a standardized manner by trained app raters using a validated framework. Apps were evaluated with this framework comprising 105 questions and covering app origin and accessibility, privacy and security, inputs and outputs, clinical foundation, features and engagement style, and interoperability.

RESULTS

Our results confirm that app stars and downloads-even for the most popular apps by these metrics-did not correlate with more clinically relevant metrics related to privacy/security, effectiveness, and engagement. Most mental health apps offer similar functionality, with 16.5% offering both mood tracking and journaling and 7% offering psychoeducation, deep breathing, mindfulness, journaling, and mood tracking. Only 36.4% of apps were updated with a 100-day window, and 7.5% of apps had not been updated in four years.

CONCLUSION

Current app marketplace metrics commonly used to evaluate apps do not offer an accurate representation of individual apps or a comprehensive overview of the entire space. The majority of apps overlap in terms of features offered, with many domains and other features not well represented. Selecting an appropriate app continues to require personal matching given no clear trends or guidance offered by quantitative metrics alone.

eHealth for the prevention of healthcare-associated infections: a scoping review

BACKGROUND

The increase in smartphone use and mobile health applications (apps) holds potential to use apps to reduce and detect healthcare-associated infections (HAIs) in clinical practice.

AIM

To obtain an overview of available apps for HAI prevention, by selecting the clinically relevant apps and scoring functionality, quality and usefulness.

METHODS

This scoping review of available apps in the iOS and Android app stores uses an in-house-developed tool (scraper https://holtder.github.io/talos) to systematically aggregate available apps relevant for HAI prevention. The apps are evaluated on functionality, assessed on quality using the 'Mobile Application Rating Scale' (MARS), and assessed on potential use in clinical infection prevention.

FINDINGS

Using the scraper with CDC HAI topics through 146 search terms resulted in 92,726 potentially relevant apps, of which 28 apps met the inclusion criteria. The majority of these apps have the functionality to inform (27 of 28 apps) or to instruct (20/28). MARS scores for the 28 apps were high in the following domains: functionality (4.19/5), aesthetics (3.49/5), and information (3.74/5), with relatively low scores in engagement (2.97/5), resulting in a good average score (3.57/5).

CONCLUSION

Low engagement scores restrict apps that intend to inform or instruct, possibly explained by the often-academic nature of the development of these apps. Although the number of HAI prevention apps increased by 60% in 5 years, the proportion of clinically relevant apps is limited. The variation in HAI app quality and lack of user engagement, could be improved by co-creation and development in the clinical setting.

Quantity and type of peer-reviewed evidence for popular free medical apps: Cross-sectional review

INTRODUCTION

- Mobile apps are being increasingly used as a tool to deliver clinical care. Evidence of efficacy for such apps varies, and appropriate levels of evidence may depend on the app's intended use. The UK's National Institute for Health and Care Excellence (NICE) recently developed an evidence standards framework, aiming to explicitly set out the required standards of evidence for different categories of digital health technologies. To determine current compliance with the evidence standards framework, the current study quantified the amount and type of peer-reviewed evidence associated with a cross-section of popular medical apps.

METHODS

- Apps were identified by selecting the top 100 free medical apps in the Apple App Store and all free apps in the NHS Apps Library. Each app was assigned to one of the four tiers (1, 2, 3a, 3b) in the NICE evidence standards framework. For each app, we conducted searches in Ovid-MEDLINE, Web of Science, Google Scholar, and via manufacturer websites to identify any published articles that assessed the app. This allowed us to determine our primary outcome, whether apps in tiers 3a/3b were more likely than apps in tier 1/2 to be associated with academic peer-reviewed evidence.

RESULTS

- We reviewed 125 apps in total (Apple App Store (n = 72), NHS Apps Library (n = 45), both (n = 8), of which 54 were categorized into the higher evidence standards framework tiers, 3a/3b. After screening, we extracted 105 relevant articles which were associated with 25 of the apps. Only 6 articles, pertaining to 3 apps, were reports of randomised controlled trials. Apps in tiers 3a/3b were more likely to be associated with articles than apps in lower tiers (χ² = 5.54, p = .01). The percentage of tier 3a/3b apps with associated articles was similar for both the NHS Apps Library (10/28) and Apple App store (7/24), (χ² = 0.042, p = .84).

DISCUSSION

- Apps that were in higher tiers 3a and 3b, indicating higher clinical risk, were more likely to have an associated article than those in lower categories. However, even in these tiers, supporting peer-reviewed evidence was missing in the majority of instances. In our sample, Apps from the NHS Apps Library were more no more likely to have supporting evidence than popular Apple App Store apps. This is of concern, given that NHS approval may influence uptake of app usage.