Evaluation of Treatment Descriptions and Alignment With Clinical Guidance of Apps for Depression on App Stores: Systematic Search and Content Analysis

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

The use of apps for the treatment of depression shows great promise. However, there is uncertainty regarding the alignment of publicly available apps for depression with clinical guidance, their treatment fidelity and evidence base, and their overall safety.

Objective

Built on previous analyses and reviews, this study aims to explore the treatment and safety issues of publicly available apps for depression.

Methods

We conducted a content analysis of apps for depression in the 2 main UK app stores (Google Play and Apple App Store). App store listings were analyzed for intervention content, treatment fidelity, and fit with the National Institute for Health and Care Excellence (NICE) guidelines for the treatment of depression in adults.

Results

A total of 353 apps for depression were included in the review. App descriptions reported the use of 20 treatment approaches and 37 treatment strategies. Many apps used transdiagnostic (155/353, 43.9%) and multitheoretical interventions to treat multiple disorders including depression. Although many interventions appeared to be evidence-informed, there were issues with treatment fidelity, research evidence, and fit with clinical guidelines. None of the apps fully aligned with the NICE guidelines for depression.

Conclusions

App developers have adopted many evidence-informed treatments in their interventions; however, more work is needed to improve clinical validity, treatment fidelity, and the safety of apps. We urge developers to consult relevant guidelines and standards, and to engage in reflective questioning on treatment and safety to address these issues and to improve treatment content and intervention design.

Related collections

Most cited references 73

Record: found
Abstract: found
Article: not found

The efficacy of smartphone-based mental health interventions for depressive symptoms: a meta-analysis of randomized controlled trials.

Joseph Firth, John Torous, Jennifer Lynn Nicholas … (2017)

The rapid advances and adoption of smartphone technology presents a novel opportunity for delivering mental health interventions on a population scale. Despite multi-sector investment along with wide-scale advertising and availability to the general population, the evidence supporting the use of smartphone apps in the treatment of depression has not been empirically evaluated. Thus, we conducted the first meta-analysis of smartphone apps for depressive symptoms. An electronic database search in May 2017 identified 18 eligible randomized controlled trials of 22 smartphone apps, with outcome data from 3,414 participants. Depressive symptoms were reduced significantly more from smartphone apps than control conditions (g=0.38, 95% CI: 0.24-0.52, p<0.001), with no evidence of publication bias. Smartphone interventions had a moderate positive effect in comparison to inactive controls (g=0.56, 95% CI: 0.38-0.74), but only a small effect in comparison to active control conditions (g=0.22, 95% CI: 0.10-0.33). Effects from smartphone-only interventions were greater than from interventions which incorporated other human/computerized aspects along the smartphone component, although the difference was not statistically significant. The studies of cognitive training apps had a significantly smaller effect size on depression outcomes (p=0.004) than those of apps focusing on mental health. The use of mood monitoring softwares, or interventions based on cognitive behavioral therapy, or apps incorporating aspects of mindfulness training, did not affect significantly study effect sizes. Overall, these results indicate that smartphone devices are a promising self-management tool for depression. Future research should aim to distil which aspects of these technologies produce beneficial effects, and for which populations.

0 comments Cited 360 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

The Use of Mobile Apps and SMS Messaging as Physical and Mental Health Interventions: Systematic Review

Amy Rathbone, Julie Prescott (2017)

Background The initial introduction of the World Wide Web in 1990 brought around the biggest change in information acquisition. Due to the abundance of devices and ease of access they subsequently allow, the utility of mobile health (mHealth) has never been more endemic. A substantial amount of interactive and psychoeducational apps are readily available to download concerning a wide range of health issues. mHealth has the potential to reduce waiting times for appointments; eradicate the need to meet in person with a clinician, successively diminishing the workload of mental health professionals; be more cost effective to practices; and encourage self-care tactics. Previous research has given valid evidence with empirical studies proving the effectiveness of physical and mental health interventions using mobile apps. Alongside apps, there is evidence to show that receiving short message service (SMS) messages, which entail psychoeducation, medication reminders, and links to useful informative Web pages can also be advantageous to a patient’s mental and physical well-being. Available mHealth apps and SMS services and their ever improving quality necessitates a systematic review in the area in reference to reduction of symptomology, adherence to intervention, and usability. Objective The aim of this review was to study the efficacy, usability, and feasibility of mobile apps and SMS messages as mHealth interventions for self-guided care. Methods A systematic literature search was carried out in JMIR, PubMed, PsychINFO, PsychARTICLES, Google Scholar, MEDLINE, and SAGE. The search spanned from January 2008 to January 2017. The primary outcome measures consisted of weight management, (pregnancy) smoking cessation, medication adherence, depression, anxiety and stress. Where possible, adherence, feasibility, and usability outcomes of the apps or SMS services were evaluated. Between-group and within-group effect sizes (Cohen d) for the mHealth intervention method group were determined. Results A total of 27 studies, inclusive of 4658 participants were reviewed. The papers included randomized controlled trials (RCTs) (n=19), within-group studies (n=7), and 1 within-group study with qualitative aspect. Studies show improvement in physical health and significant reductions of anxiety, stress, and depression. Within-group and between-group effect sizes ranged from 0.05-3.37 (immediately posttest), 0.05-3.25 (1-month follow-up), 0.08-3.08 (2-month follow-up), 0.00-3.10 (3-month follow-up), and 0.02-0.27 (6-month follow-up). Usability and feasibility of mHealth interventions, where reported, also gave promising, significant results. Conclusions The review shows the promising and emerging efficacy of using mobile apps and SMS text messaging as mHealth interventions.

0 comments Cited 172 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

The Use and Effectiveness of Mobile Apps for Depression: Results From a Fully Remote Clinical Trial

Patricia A Areán, Kevin A Hallgren, Joshua T Jordan … (2016)

Background Mobile apps for mental health have the potential to overcome access barriers to mental health care, but there is little information on whether patients use the interventions as intended and the impact they have on mental health outcomes. Objective The objective of our study was to document and compare use patterns and clinical outcomes across the United States between 3 different self-guided mobile apps for depression. Methods Participants were recruited through Web-based advertisements and social media and were randomly assigned to 1 of 3 mood apps. Treatment and assessment were conducted remotely on each participant’s smartphone or tablet with minimal contact with study staff. We enrolled 626 English-speaking adults (≥18 years old) with mild to moderate depression as determined by a 9-item Patient Health Questionnaire (PHQ-9) score ≥5, or if their score on item 10 was ≥2. The apps were (1) Project: EVO, a cognitive training app theorized to mitigate depressive symptoms by improving cognitive control, (2) iPST, an app based on an evidence-based psychotherapy for depression, and (3) Health Tips, a treatment control. Outcomes were scores on the PHQ-9 and the Sheehan Disability Scale. Adherence to treatment was measured as number of times participants opened and used the apps as instructed. Results We randomly assigned 211 participants to iPST, 209 to Project: EVO, and 206 to Health Tips. Among the participants, 77.0% (482/626) had a PHQ-9 score >10 (moderately depressed). Among the participants using the 2 active apps, 57.9% (243/420) did not download their assigned intervention app but did not differ demographically from those who did. Differential treatment effects were present in participants with baseline PHQ-9 score >10, with the cognitive training and problem-solving apps resulting in greater effects on mood than the information control app (χ22=6.46, P=.04). Conclusions Mobile apps for depression appear to have their greatest impact on people with more moderate levels of depression. In particular, an app that is designed to engage cognitive correlates of depression had the strongest effect on depressed mood in this sample. This study suggests that mobile apps reach many people and are useful for more moderate levels of depression. ClinicalTrial Clinicaltrials.gov NCT00540865; https://www.clinicaltrials.gov/ct2/show/NCT00540865 (Archived by WebCite at http://www.webcitation.org/6mj8IPqQr)

0 comments Cited 134 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Dionne Bowie-DaBreo:

ORCID: https://orcid.org/0000-0002-0050-0115

Research and Innovation CentreLeeds Teaching Hospitals NHS TrustSt James's University HospitalBeckett StreetLeeds, LS9 7TFUnited Kingdom44 113 206 0469dionne.bowie@nhs.net

Journal

Journal ID (nlm-ta): JMIR Form Res

Journal ID (iso-abbrev): JMIR Form Res

Journal ID (publisher-id): JFR

Title: JMIR Formative Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Electronic): 2561-326X

Publication date Collection: November 2020

Publication date (Electronic): 13 November 2020

Volume: 4

Issue: 11

Electronic Location Identifier: e14988

Affiliations

[1 ] Research and Innovation Centre Leeds Teaching Hospitals NHS Trust Leeds United Kingdom

[2 ] Department of Psychology Lancaster University Lancaster United Kingdom

[3 ] School of Computing and Communications Lancaster University Lancaster United Kingdom

[4 ] Research and Innovation Northern Care Alliance NHS Group Salford United Kingdom

[5 ] University of Salford Salford United Kingdom

Author notes

Corresponding Author: Dionne Bowie-DaBreo dionne.bowie@ 123456nhs.net

Author information

Dionne Bowie-DaBreo https://orcid.org/0000-0002-0050-0115

Sandra I Sünram-Lea https://orcid.org/0000-0001-9889-9867

Corina Sas https://orcid.org/0000-0001-9297-9612

Heather Iles-Smith https://orcid.org/0000-0002-0520-2694

Article

Publisher ID: v4i11e14988

DOI: 10.2196/14988

PMC ID: 7695532

PubMed ID: 33185566

SO-VID: 671573e3-c3c5-42c4-a118-77bbae98db23

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on http://formative.jmir.org, as well as this copyright and license information must be included.

History

Date received : 10 June 2019

Date revision requested : 5 August 2019

Date revision received : 19 May 2020

Date accepted : 2 June 2020

Comments

Comment on this article

scite_

Cited by 7

See all cited by

Most referenced authors 477

See all reference authors

Submit your digital health research with an established publisher
- celebrating 25 years of open access