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Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study.

ABSTRACT: BACKGROUND:User engagement is key to the effectiveness of digital mental health interventions. Considerable research has examined the clinical outcomes of overall engagement with mental health apps (eg, frequency and duration of app use). However, few studies have examined how specific app use behaviors can drive change in outcomes. Understanding the clinical outcomes of more nuanced app use could inform the design of mental health apps that are more clinically effective to users. OBJECTIVE:This study aimed to classify user behaviors in a suite of mental health apps and examine how different types of app use are related to depression and anxiety outcomes. We also compare the clinical outcomes of specific types of app use with those of generic app use (ie, intensity and duration of app use) to understand what aspects of app use may drive symptom improvement. METHODS:We conducted a secondary analysis of system use data from an 8-week randomized trial of a suite of 13 mental health apps. We categorized app use behaviors through a mixed methods analysis combining qualitative content analysis and principal component analysis. Regression analyses were used to assess the association between app use and levels of depression and anxiety at the end of treatment. RESULTS:A total of 3 distinct clusters of app use behaviors were identified: learning, goal setting, and self-tracking. Each specific behavior had varied effects on outcomes. Participants who engaged in self-tracking experienced reduced depression symptoms, and those who engaged with learning and goal setting at a moderate level (ie, not too much or not too little) also had an improvement in depression. Notably, the combination of these 3 types of behaviors, what we termed "clinically meaningful use," accounted for roughly the same amount of variance as explained by the overall intensity of app use (ie, total number of app use sessions). This suggests that our categorization of app use behaviors succeeded in capturing app use associated with better outcomes. However, anxiety outcomes were neither associated with specific behaviors nor generic app use. CONCLUSIONS:This study presents the first granular examination of user interactions with mental health apps and their effects on mental health outcomes. It has important implications for the design of mobile health interventions that aim to achieve greater user engagement and improved clinical efficacy.

SUBMITTER: Zhang R

PROVIDER: S-EPMC6942194 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study.

Zhang Renwen R Nicholas Jennifer J Knapp Ashley A AA Graham Andrea K AK Gray Elizabeth E Kwasny Mary J MJ Reddy Madhu M Mohr David C DC

Journal of medical Internet research 20191220 12

<h4>Background</h4>User engagement is key to the effectiveness of digital mental health interventions. Considerable research has examined the clinical outcomes of overall engagement with mental health apps (eg, frequency and duration of app use). However, few studies have examined how specific app use behaviors can drive change in outcomes. Understanding the clinical outcomes of more nuanced app use could inform the design of mental health apps that are more clinically effective to users.<h4>Obj ...[more]

PMID: 31859682

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Project description:BackgroundAs the number of mental health apps has grown, increasing efforts have been focused on establishing quality tailored reviews. These reviews prioritize clinician and academic views rather than the views of those who use them, particularly those with lived experiences of mental health problems. Given that the COVID-19 pandemic has increased reliance on web-based and mobile mental health support, understanding the views of those with mental health conditions is of increasing importance.ObjectiveThis study aimed to understand the opinions of people with mental health problems on mental health apps and how they differ from established ratings by professionals.MethodsA mixed methods study was conducted using a web-based survey administered between December 2020 and April 2021, assessing 11 mental health apps. We recruited individuals who had experienced mental health problems to download and use 3 apps for 3 days and complete a survey. The survey consisted of the One Mind PsyberGuide Consumer Review Questionnaire and 2 items from the Mobile App Rating Scale (star and recommendation ratings from 1 to 5). The consumer review questionnaire contained a series of open-ended questions, which were thematically analyzed and using a predefined protocol, converted into binary (positive or negative) ratings, and compared with app ratings by professionals and star ratings from app stores.ResultsWe found low agreement between the participants' and professionals' ratings. More than half of the app ratings showed disagreement between participants and professionals (198/372, 53.2%). Compared with participants, professionals gave the apps higher star ratings (3.58 vs 4.56) and were more likely to recommend the apps to others (3.44 vs 4.39). Participants' star ratings were weakly positively correlated with app store ratings (r=0.32, P=.01). Thematic analysis found 11 themes, including issues of user experience, ease of use and interactivity, privacy concerns, customization, and integration with daily life. Participants particularly valued certain aspects of mental health apps, which appear to be overlooked by professional reviewers. These included functions such as the ability to track and measure mental health and providing general mental health education. The cost of apps was among the most important factors for participants. Although this is already considered by professionals, this information is not always easily accessible.ConclusionsAs reviews on app stores and by professionals differ from those by people with lived experiences of mental health problems, these alone are not sufficient to provide people with mental health problems with the information they desire when choosing a mental health app. App rating measures must include the perspectives of mental health service users to ensure ratings represent their priorities. Additional work should be done to incorporate the features most important to mental health service users into mental health apps.

Project description:BackgroundDigital health apps are among the most visible facets of the ongoing digital transition in health care, with mental health-focused apps as one of the main therapeutic areas. However, concerns regarding their scientific robustness drove regulators to establish evaluation procedures, with Germany's Digitale Gesundheitsanwendungen program pioneering in app prescription with costs covered by statutory health insurance. Portugal gathers a set of conditions and requirements that position it as an excellent test bed for digital health apps. Its daunting mental health landscape reinforces the potential interest in new interventions. To understand if they would be acceptable, we need to understand the supply side's attitudes and perceptions toward them, that is, those of psychiatrists and psychologists.ObjectiveThis study aims to understand the attitudes and expectations of psychiatrists and psychologists toward digital mental health apps (DMHAs) in the Portuguese context, as well as perceived benefits, barriers, and actions to support their adoption.MethodsWe conducted a 2-stage sequential mixed methods study. Stage 1 consisted of a cross-sectional web survey adapted to the Portuguese context that was delivered to mental health professionals and psychologists. Stage 2 complemented the insights of the web survey results with a key opinion leader analysis.ResultsA total of 160 complete survey responses were recorded, most of which were from psychologists. This is the most extensive study on mental health professionals' attitudes and perceptions of DMHAs in Portugal. A total of 87.2% (136/156) of the respondents supported the opportunity to prescribe DMHAs. Increased health literacy (139/160, 86.9%), wider adherence to treatment (137/160, 85.6%), and proper disease management (127/160, 79.4%) were the most frequently agreed upon benefits of DMHAs. However, only less than half (68/156, 43.6%) of the respondents planned to prescribe or recommend DMHAs, with psychologists being more favorable than psychiatrists. Professionals faced substantial barriers, such as a lack of information on DMHAs (154/160, 96.3%), the level of initial training effort (115/160, 71.9%), and the need for adjustments of clinical processes and records (113/160, 70.6%). Professionals reported that having more information on the available apps and their suitability for health objectives (151/160, 94.4%), more scientific evidence of the validity of the apps as a health intervention (147/160, 91.9%), and established recommendations of apps by specific clinical guidelines or professional societies (145/160, 90.6%) would be essential to foster adoption.ConclusionsMore information about DMHAs regarding their clinical validity and how they work is necessary so that such an intervention can be adopted in Portugal. Recommendations from professional and scientific societies, as well as from governmental bodies, are strongly encouraged. Although the benefits of and the barriers to using these apps are consensual, more evidence, along with further promotion of mental health professionals' digital literacy, is needed.International registered report identifier (irrid)RR2-10.2196/41040.

Project description:BACKGROUND:A large number of mobile health (mHealth) apps have been created to help users to manage their health or receive health care services. Many of these mHealth apps have proven to be helpful for maintaining or improving their users' health. However, many people still choose not to use mHealth apps or only use them for a short period. One of the reasons behind this lack of use is the concern for their health information security and privacy. OBJECTIVE:The goal of this study was to determine the relationship between users' characteristics and their security and privacy concerns and to identify desired security features in mHealth apps, which could reduce these concerns. METHODS:A questionnaire was designed and validated by the research team. This questionnaire was then used to determine mobile app users' security and privacy concerns regarding personal health data in mHealth apps as well as the security features most users' desire. A semistructured interview was used to identify barriers to and facilitators of adopting mHealth apps. RESULTS:In total, 117 randomly selected study participants from a large pool took part in this study and provided responses to the validated questionnaire and the semistructured interview questions. The results indicate that most study participants did have concerns about their privacy when using mHealth apps. They also expressed their preferences regarding several security features in mHealth apps, such as regular password updates, remote wipe, user consent, and access control. An association between their demographic characteristics and their concerns and preferences in security and privacy was identified; however, in most cases, the differences among the different demographic groups were not statistically significant, except for a few very specific aspects. These study participants also indicated that the cost of apps and lack of security features in mHealth apps were barriers for adoption, whereas having free apps, strong but easy-to-use security features, and clear user protection privacy policies might encourage them to use mHealth apps in their health management. CONCLUSIONS:This questionnaire and interview study verified the security and privacy concerns of mHealth app users, identified the desired security and privacy features, and determined specific barriers to and facilitators of users adopting mHealth apps. The results can be used to guide mHealth app developers to create apps that would be welcomed by users.

Project description:BackgroundNovel approaches in mobile mental health (mHealth) apps that make use of Artificial Intelligence (AI), Ecological Momentary Assessments, and Ecological Momentary Interventions have the potential to support young people in the achievement of mental health and wellbeing goals. However, little is known on the perspectives of young people and mental health experts on this rapidly advancing technology. This study aims to investigate the subjective needs, attitudes, and preferences of key stakeholders towards an AI-informed mHealth app, including young people and experts on mHealth promotion and prevention in youth.MethodsWe used a convergent parallel mixed-method study design. Two semi-structured online focus groups (n = 8) and expert interviews (n = 5) to explore users and stakeholders perspectives were conducted. Furthermore a representative online survey was completed by young people (n = 666) to investigate attitudes, current use and preferences towards apps for mental health promotion and prevention.ResultsSurvey results show that more than two-thirds of young people have experience with mHealth apps, and 60% make regular use of 1-2 apps. A minority (17%) reported to feel negative about the application of AI in general, and 19% were negative about the embedding of AI in mHealth apps. This is in line with qualitative findings, where young people displayed rather positive attitudes towards AI and its integration into mHealth apps. Participants reported pragmatic attitudes towards data sharing and safety practices, implying openness to share data if it adds value for users and if the data request is not too intimate, however demanded transparency of data usage and control over personalization. Experts perceived AI-informed mHealth apps as a complementary solution to on-site delivered interventions in future health promotion among young people. Experts emphasized opportunities in regard with low-threshold access through the use of smartphones, and the chance to reach young people in risk situations.ConclusionsThe findings of this exploratory study highlight the importance of further participatory development of training components prior to implementation of a digital mHealth training in routine practice of mental health promotion and prevention. Our results may help to guide developments based on stakeholders' first recommendations for an AI-informed mHealth app.

Project description:Background:E-mental health is an established mode of delivering treatment for common mental disorders in many high income countries. However, evidence of its effectiveness in lower income countries is lacking. This mixed methods study presents lessons learned and preliminary data on the feasibility of a minimally guided e-mental health intervention in Lebanon. The aim was to pilot test Step-by-Step, a WHO guided e-mental health intervention, and research methods prior to future, controlled testing. Methods:Participants were recruited using social media and advertisements in primary care clinics. Participants completed baseline and post-intervention questionnaires on depression symptoms (primary outcome, PHQ-8), anxiety symptoms, well-being, disability and self-perceived problem severity, and a client satisfaction questionnaire. In addition, seven completers, four drop-outs, 11 study staff, and four clinic managers were interviewed with responses thematically analyzed. Website analytics were used to understand participant behavior when using the website. Results:A total of 129 participants signed up via the Step-by-Step website. Seventy-four participants started session 1 after completing pre-test questionnaires and 26 completed both baseline and post-intervention data. Among those who completed post-assessments, depression symptoms improved (PHQ-8 scores (t=5.62, p < 0.001 two-tailed, df = 25). Wilcoxon signed ranks tests showed a significant difference between baseline and post-Step-by-Step scores on all secondary outcome measures. Client satisfaction data was positive. Interview responses suggested that the intervention could be made more appropriate for younger, single people, more motivating, and easier to use. Those who utilized the support element of the intervention were happy with their relationship with the non-specialist support person (e-helper), though some participants would have preferred specialist support. E-helpers would have liked more training on complex cases. Website analytics showed that many users dropped out before intervention start, and that some re-entered screening data having been excluded from the study. Conclusion:Step-by-Step skills and techniques, model of service integration, and its non-specialist support element are acceptable. Though the sample was small and non-controlled and drop-out was high, results suggest that it may be effective in reducing depression and anxiety symptoms and increasing well-being. Lessons learned will inform content revision, the development of an app version of Step-by-Step, and the research methodology of upcoming effectiveness studies.

Project description:IntroductionOutcome measurement instruments (OMIs) are used to gauge the effects of treatment. In post-stroke aphasia rehabilitation, benchmarks for meaningful change are needed to support the interpretation of patient outcomes. This study is part of a research programme to establish minimal important change (MIC) values (the smallest change above which patients perceive themselves as importantly changed) for core OMIs. As a first step in this process, the views of people with aphasia and clinicians were explored, and consensus was sought on a threshold for clinically meaningful change.MethodsSequential mixed-methods design was employed. Participants included people with post-stroke aphasia and speech pathologists. People with aphasia were purposively sampled based on time post-stroke, age and gender, whereas speech pathologists were sampled according to their work setting (hospital or community). Each participant attended a focus group followed by a consensus workshop with a survey component. Within the focus groups, experiences and methods for measuring meaningful change during aphasia recovery were explored. Qualitative data were transcribed and analysed using reflexive thematic analysis. In the consensus workshop, participants voted on thresholds for meaningful change in core outcome constructs of language, communication, emotional well-being and quality of life, using a six-point rating scale (much worse, slightly worse, no change, slightly improved, much improved and completely recovered). Consensus was defined a priori as 70% agreement. Voting results were reported using descriptive statistics.ResultsFive people with aphasia (n = 4, > 6 months after stroke; n = 5, < 65 years; n = 3, males) and eight speech pathologists (n = 4, hospital setting; n = 4, community setting) participated in one of four focus groups (duration: 92-112 min). Four themes were identified describing meaningful change as follows: (1) different for every single person; (2) small continuous improvements; (3) measured by progress towards personally relevant goals; and (4) influenced by personal factors. 'Slightly improved' was agreed as the threshold of MIC on the anchor-rating scale (75%-92%) within 6 months of stroke, whereas after 6 months there was a trend towards supporting 'much improved' (36%-66%).ConclusionOur mixed-methods research with people with aphasia and speech pathologists provides novel evidence to inform the definition of MIC in aphasia rehabilitation. Future research will aim to establish MIC values for core OMIs.Patient or public contributionThis work is the result of engagement between people with lived experience of post-stroke aphasia, including people with aphasia, family members, clinicians and researchers. Engagement across the research cycle was sought to ensure that the research tasks were acceptable and easily understood by participants and that the outcomes of the study were relevant to the aphasia community. This engagement included the co-development of a plain English summary of the results. Advisors were remunerated in accordance with Health Consumers Queensland guidelines. Interview guides for clinicians were piloted by speech pathologists working in aphasia rehabilitation.

Dataset Information

Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study.

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Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study.

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