Dataset Information

E-Therapies in England for stress, anxiety or depression: how are apps developed? A survey of NHS e-therapy developers.

ABSTRACT: OBJECTIVE:To document the quality of web and smartphone apps used and recommended for stress, anxiety or depression by examining the manner in which they were developed. DESIGN:The study was conducted using a survey sent to developers of National Health Service (NHS) e-therapies. DATA SOURCES:Data were collected via a survey sent out to NHS e-therapy developers during October 2015 and review of development company websites during October 2015. DATA COLLECTION/EXTRACTION METHODS:Data were compiled from responses to the survey and development company websites of the NHS e-therapies developers. RESULTS:A total of 36 (76.6%) out of the 48 app developers responded. One app was excluded due to its contact details and developer website being unidentifiable. Data from the missing 10 was determined from the app developer's website. The results were that 12 out of 13 web apps and 20 out of 34 smartphone apps had clinical involvement in their development. Nine out of 13 web apps and nine out of 34 smartphone apps indicated academic involvement in their development. Twelve out of 13 web apps and nine out of 34 smartphone apps indicated published research evidence relating to their app. Ten out of 13 web apps and 10 out of 34 smartphone apps indicated having other evidence relating to their app. Nine out of 13 web apps and 19 out of 34 smartphone apps indicated having a psychological approach or theory behind their app. CONCLUSIONS:As an increasing number of developers are looking to produce e-therapies for the NHS it is essential they apply clinical and academic best practices to ensure the creation of safe and effective apps.

SUBMITTER: Bennion MR

PROVIDER: S-EPMC7062334 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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e-Therapies in England for stress, anxiety or depression: how are apps developed? A survey of NHS e-therapy developers.

Bennion Matthew Russell MR Hardy Gillian E GE Moore Roger K RK Kellett Stephen S Millings Abigail A

BMJ health & care informatics 20190601 1

<h4>Objective</h4>To document the quality of web and smartphone apps used and recommended for stress, anxiety or depression by examining the manner in which they were developed.<h4>Design</h4>The study was conducted using a survey sent to developers of National Health Service (NHS) e-therapies.<h4>Data sources</h4>Data were collected via a survey sent out to NHS e-therapy developers during October 2015 and review of development company websites during October 2015.<h4>Data collection/extraction ...[more]

PMID: 31171556

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Project description:BackgroundThere is a disconnect between the ability to swiftly develop e-therapies for the treatment of depression, anxiety, and stress, and the scrupulous evaluation of their clinical utility. This creates a risk that the e-therapies routinely provided within publicly funded psychological health care have evaded appropriate rigorous evaluation in their development.ObjectiveThis study aims to conduct a meta-analytic review of the gold standard evidence of the acceptability and clinical effectiveness of e-therapies recommended for use in the National Health Service (NHS) in the United Kingdom.MethodsSystematic searches identified appropriate randomized controlled trials (RCTs). Depression, anxiety, and stress outcomes at the end of treatment and follow-up were synthesized using a random-effects meta-analysis. The grading of recommendations assessment, development, and evaluation approach was used to assess the quality of each meta-analytic comparison. Moderators of treatment effect were examined using subgroup and meta-regression analysis. Dropout rates for e-therapies (as a proxy for acceptability) were compared against controls.ResultsA total of 24 studies evaluating 7 of 48 NHS-recommended e-therapies were qualitatively and quantitatively synthesized. Depression, anxiety, and stress outcomes for e-therapies were superior to controls (depression: standardized mean difference [SMD] 0.38, 95% CI 0.24 to 0.52, N=7075; anxiety and stress: SMD 0.43, 95% CI 0.24 to 0.63, n=4863), and these small effects were maintained at follow-up. Average dropout rates for e-therapies (31%, SD 17.35) were significantly higher than those of controls (17%, SD 13.31). Limited moderators of the treatment effect were found.ConclusionsMany NHS-recommended e-therapies have not been through an RCT-style evaluation. The e-therapies that have been appropriately evaluated generate small but significant, durable, beneficial treatment effects.Trial registrationInternational Prospective Register of Systematic Reviews (PROSPERO) registration CRD42019130184; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=130184.

Project description:BACKGROUND:Emerging research suggests that mobile apps can be used to effectively treat common mental illnesses like depression and anxiety. Despite promising efficacy results and ease of access to these interventions, adoption of mobile health (mHealth; mobile device-delivered) interventions for mental illness has been limited. More insight into patients' perspectives on mHealth interventions is required to create effective implementation strategies and to adapt existing interventions to facilitate higher rates of adoption. OBJECTIVE:The aim of this study was to examine, from the patient perspective, current use and factors that may impact the use of mHealth interventions for mental illness. METHODS:This was a cross-sectional survey study of veterans who had attended an appointment at a single Veterans Health Administration facility in early 2016 that was associated with one of the following mental health concerns: unipolar depression, any anxiety disorder, or posttraumatic stress disorder. We used the Veteran Affairs Corporate Data Warehouse to create subsets of eligible participants demographically stratified by gender (male or female) and minority status (white or nonwhite). From each subset, 100 participants were selected at random and mailed a paper survey with items addressing the demographics, overall health, mental health, technology ownership or use, interest in mobile app interventions for mental illness, reasons for use or nonuse, and interest in specific features of mobile apps for mental illness. RESULTS:Of the 400 potential participants, 149 (37.3%, 149/400) completed and returned a survey. Most participants (79.9%, 119/149) reported that they owned a smart device and that they use apps in general (71.1%, 106/149). Most participants (73.1%, 87/149) reported interest in using an app for mental illness, but only 10.7% (16/149) had done so. Paired samples t tests indicated that ratings of interest in using an app recommended by a clinician were significantly greater than general interest ratings and even greater when the recommending clinician was a specialty mental health provider. The most frequent concerns related to using an app for mental illness were lacking proof of efficacy (71.8%, 107/149), concerns about data privacy (59.1%, 88/149), and not knowing where to find such an app (51.0%, 76/149). Participants expressed interest in a number of app features with particularly high-interest ratings for context-sensitive apps (85.2%, 127/149), and apps focused on the following areas: increasing exercise (75.8%, 113/149), improving sleep (73.2%, 109/149), changing negative thinking (70.5%, 105/149), and increasing involvement in activities (67.1%, 100/149). CONCLUSIONS:Most respondents had access to devices to use mobile apps for mental illness, already used apps for other purposes, and were interested in mobile apps for mental illness. Key factors that may improve adoption include provider endorsement, greater publicity of efficacious apps, and clear messaging about efficacy and privacy of information. Finally, multifaceted apps that address a range of concerns, from sleep to negative thought patterns, may be best received.

Project description:BACKGROUND:Mobile mental health apps have become ubiquitous tools to assist people in managing symptoms of anxiety and depression. However, due to the lack of research and expert input that has accompanied the development of most apps, concerns have been raised by clinicians, researchers, and government authorities about their efficacy. OBJECTIVE:This review aimed to estimate the proportion of mental health apps offering comprehensive therapeutic treatments for anxiety and/or depression available in the app stores that have been developed using evidence-based frameworks. It also aimed to estimate the proportions of specific frameworks being used in an effort to understand which frameworks are having the most influence on app developers in this area. METHODS:A systematic review of the Apple App Store and Google Play store was performed to identify apps offering comprehensive therapeutic interventions that targeted anxiety and/or depression. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist was adapted to guide this approach. RESULTS:Of the 293 apps shortlisted as offering a therapeutic treatment for anxiety and/or depression, 162 (55.3%) mentioned an evidence-based framework in their app store descriptions. Of the 293 apps, 88 (30.0%) claimed to use cognitive behavioral therapy techniques, 46 (15.7%) claimed to use mindfulness, 27 (9.2%) claimed to use positive psychology, 10 (3.4%) claimed to use dialectical behavior therapy, 5 (1.7%) claimed to use acceptance and commitment therapy, and 20 (6.8%) claimed to use other techniques. Of the 162 apps that claimed to use a theoretical framework, only 10 (6.2%) had published evidence for their efficacy. CONCLUSIONS:The current proportion of apps developed using evidence-based frameworks is unacceptably low, and those without tested frameworks may be ineffective, or worse, pose a risk of harm to users. Future research should establish what other factors work in conjunction with evidence-based frameworks to produce efficacious mental health apps.

Project description:BackgroundHospital nurses are exposed to various work-related factors that may be associated with increased risk of developing different mental disorders. Empirical evidence on the prevalence and correlates of individual mental health problems such as stress, anxiety and depression is widely reported, while a combined pattern of these conditions is unknown. This study aims to examine the co-occurrence of stress, anxiety and depression among clinical nurses, and to explore socio-demographic characteristics of, and working conditions experienced by, nurses that may be associated with these three mental health conditions.MethodsA cross-sectional study was implemented in one tertiary hospital in Hanoi city, Vietnam, from May to September 2015. A self-reported questionnaire including a short version of the Depression, Anxiety and Stress scale 21 items and questions on demographic and work-related characteristics was delivered to 787 registered nurses. 600 completed questionnaires was used in the final analysis (76.2% response rate). The two-step clustering analysis was performed to identify sub groups. Chi square test and post hoc ANOVA analysis with Bonferroni correction were used to examine differences in psychological status, demographic characteristics and working conditions among the clusters (two-tailed p?<?0.05).ResultsThe prevalence of self-reported stress, anxiety and depression were 18.5%, 39.8% and 13.2%, respectively. 45.3% participants reported symptoms of at least one mental disorder, 7.3% had all three. Nurses in the first cluster (high prevalence of mental disorders), had high task demand and conflict at work with low job control and reward. The second cluster nurses (moderate percentage of mental strain) were significantly older and in marital relationship, high task demand and job control, and presence of chronic diseases. The lowest proportion of self-perceived mental disorders were observed in the cluster three who were younger and had fewer years of services, moderate task demand and low job control and better physical health in comparison with those in the other two clusters (p?<?0.05).ConclusionsStress, anxiety and depression were prevalent among clinical nurses. Heterogeneity in demographic characteristics and working conditions were observed across clusters with different patterns of mental disorders. Institutional effort should be emphasized to support nurses in their career development to reduce psychological strains.

Project description:BACKGROUND:Developers of medicines-related apps collect a variety of technical, health-related, and identifying user information to improve and tailor services. User data may also be used for promotional purposes. Apps, for example, may be used to skirt regulation of direct-to-consumer advertising of medicines. Researchers have documented routine and extensive sharing of user data with third parties for commercial purposes, but little is known about the ways that app developers or "first" parties employ user data. OBJECTIVE:We aimed to investigate the nature of user data collection and commercialization by developers of medicines-related apps. APPROACH:We conducted a content analysis of apps' store descriptions, linked websites, policies, and sponsorship prospectuses for prominent medicines-related apps found in the USA, Canada, Australia, and UK Google Play stores in late 2017. Apps were included if they pertained to the prescribing, administration, or use of medicines, and were interactive. Two independent coders extracted data from documents using a structured, open-ended instrument. We performed open, inductive coding to identify the range of promotional strategies involving user data for commercial purposes and wrote descriptive memos to refine and detail these codes. KEY RESULTS:Ten of 24 apps primarily provided medication adherence services; 14 primarily provided medicines information. The majority (71%, 17/24) outlined at least one promotional strategy involving users' data for commercial purposes which included personalized marketing of the developer's related products and services, highly tailored advertising, third-party sponsorship of targeted content or messaging, and sale of aggregated customer insights to stakeholders. CONCLUSIONS:App developers may employ users' data in a feedback loop to deliver highly targeted promotional messages from developers, and commercial sponsors, including the pharmaceutical industry. These practices call into question developers' claims about the trustworthiness and independence of purportedly evidenced-based medicines information and may create a risk for mis- or overtreatment.

Dataset Information

E-Therapies in England for stress, anxiety or depression: how are apps developed? A survey of NHS e-therapy developers.

Publications

e-Therapies in England for stress, anxiety or depression: how are apps developed? A survey of NHS e-therapy developers.

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