User Acceptance of Computerized Cognitive Behavioral Therapy for Depression: Systematic Review

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Abstract

Background

Computerized cognitive behavioral therapy (cCBT) has been proven to be effective in depression care. Moreover, cCBT packages are becoming increasingly popular. A central aspect concerning the take-up and success of any treatment is its user acceptance.

Objective

The aim of this study was to update and expand on earlier work on user acceptance of cCBT for depression.

Methods

This paper systematically reviewed quantitative and qualitative studies regarding the user acceptance of cCBT for depression. The initial search was conducted in January 2016 and involved the following databases: Web of Science, PubMed, the Cochrane Library, and PsycINFO. Studies were retained if they described the explicit examination of the user acceptance, experiences, or satisfaction related to a cCBT intervention, if they reported depression as a primary outcome, and if they were published in German or English from July 2007 onward.

Results

A total of 1736 studies were identified, of which 29 studies were eligible for review. User acceptance was operationalized and analyzed very heterogeneously. Eight studies reported a very high level of acceptance, 17 indicated a high level of acceptance, and one study showed a moderate level of acceptance. Two qualitative studies considered the positive and negative aspects concerning the user acceptance of cCBT. However, a substantial proportion of reviewed studies revealed several methodical shortcomings.

Conclusions

In general, people experience cCBT for depression as predominantly positive, which supports the potential role of these innovative treatments. However, methodological challenges do exist in terms of defining user acceptance, clear operationalization of concepts, and measurement.

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Most cited references 40

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The effectiveness of SPARX, a computerised self help intervention for adolescents seeking help for depression: randomised controlled non-inferiority trial

Sally N. Merry, Karolina Stasiak, Matthew Shepherd … (2012)

Objective To evaluate whether a new computerised cognitive behavioural therapy intervention (SPARX, Smart, Positive, Active, Realistic, X-factor thoughts) could reduce depressive symptoms in help seeking adolescents as much or more than treatment as usual. Design Multicentre randomised controlled non-inferiority trial. Setting 24 primary healthcare sites in New Zealand (youth clinics, general practices, and school based counselling services). Participants 187 adolescents aged 12-19, seeking help for depressive symptoms, with no major risk of self harm and deemed in need of treatment by their primary healthcare clinicians: 94 were allocated to SPARX and 93 to treatment as usual. Interventions Computerised cognitive behavioural therapy (SPARX) comprising seven modules delivered over a period of between four and seven weeks, versus treatment as usual comprising primarily face to face counselling delivered by trained counsellors and clinical psychologists. Outcomes The primary outcome was the change in score on the children’s depression rating scale-revised. Secondary outcomes included response and remission on the children’s depression rating scale-revised, change scores on the Reynolds adolescent depression scale-second edition, the mood and feelings questionnaire, the Kazdin hopelessness scale for children, the Spence children’s anxiety scale, the paediatric quality of life enjoyment and satisfaction questionnaire, and overall satisfaction with treatment ratings. Results 94 participants were allocated to SPARX (mean age 15.6 years, 62.8% female) and 93 to treatment as usual (mean age 15.6 years, 68.8% female). 170 adolescents (91%, SPARX n=85, treatment as usual n=85) were assessed after intervention and 168 (90%, SPARX n=83, treatment as usual n=85) were assessed at the three month follow-up point. Per protocol analyses (n=143) showed that SPARX was not inferior to treatment as usual. Post-intervention, there was a mean reduction of 10.32 in SPARX and 7.59 in treatment as usual in raw scores on the children’s depression rating scale-revised (between group difference 2.73, 95% confidence interval −0.31 to 5.77; P=0.079). Remission rates were significantly higher in the SPARX arm (n=31, 43.7%) than in the treatment as usual arm (n=19, 26.4%) (difference 17.3%, 95% confidence interval 1.6% to 31.8%; P=0.030) and response rates did not differ significantly between the SPARX arm (66.2%, n=47) and treatment as usual arm (58.3%, n=42) (difference 7.9%, −7.9% to 24%; P=0.332). All secondary measures supported non-inferiority. Intention to treat analyses confirmed these findings. Improvements were maintained at follow-up. The frequency of adverse events classified as “possibly” or “probably” related to the intervention did not differ between groups (SPARX n=11; treatment as usual n=11). Conclusions SPARX is a potential alternative to usual care for adolescents presenting with depressive symptoms in primary care settings and could be used to address some of the unmet demand for treatment. Trial registration Australian New Zealand Clinical Trials ACTRN12609000249257.

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Harnessing Context Sensing to Develop a Mobile Intervention for Depression

Michelle Burns, Mark Begale, Jennifer Duffecy … (2011)

Background Mobile phone sensors can be used to develop context-aware systems that automatically detect when patients require assistance. Mobile phones can also provide ecological momentary interventions that deliver tailored assistance during problematic situations. However, such approaches have not yet been used to treat major depressive disorder. Objective The purpose of this study was to investigate the technical feasibility, functional reliability, and patient satisfaction with Mobilyze!, a mobile phone- and Internet-based intervention including ecological momentary intervention and context sensing. Methods We developed a mobile phone application and supporting architecture, in which machine learning models (ie, learners) predicted patients’ mood, emotions, cognitive/motivational states, activities, environmental context, and social context based on at least 38 concurrent phone sensor values (eg, global positioning system, ambient light, recent calls). The website included feedback graphs illustrating correlations between patients’ self-reported states, as well as didactics and tools teaching patients behavioral activation concepts. Brief telephone calls and emails with a clinician were used to promote adherence. We enrolled 8 adults with major depressive disorder in a single-arm pilot study to receive Mobilyze! and complete clinical assessments for 8 weeks. Results Promising accuracy rates (60% to 91%) were achieved by learners predicting categorical contextual states (eg, location). For states rated on scales (eg, mood), predictive capability was poor. Participants were satisfied with the phone application and improved significantly on self-reported depressive symptoms (betaweek = –.82, P < .001, per-protocol Cohen d = 3.43) and interview measures of depressive symptoms (betaweek = –.81, P < .001, per-protocol Cohen d = 3.55). Participants also became less likely to meet criteria for major depressive disorder diagnosis (bweek = –.65, P = .03, per-protocol remission rate = 85.71%). Comorbid anxiety symptoms also decreased (betaweek = –.71, P < .001, per-protocol Cohen d = 2.58). Conclusions Mobilyze! is a scalable, feasible intervention with preliminary evidence of efficacy. To our knowledge, it is the first ecological momentary intervention for unipolar depression, as well as one of the first attempts to use context sensing to identify mental health-related states. Several lessons learned regarding technical functionality, data mining, and software development process are discussed. Trial Registration Clinicaltrials.gov NCT01107041; http://clinicaltrials.gov/ct2/show/NCT01107041 (Archived by WebCite at http://www.webcitation.org/60CVjPH0n)

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Barriers to the uptake of computerized cognitive behavioural therapy: a systematic review of the quantitative and qualitative evidence.

Emma Waller, S Gilbody (2009)

Studies of cognitive behavioural therapy delivered by computer (cCBT) show clinical efficacy for treating anxiety and depression, but have not focused on barriers to uptake. Potential barriers include adverse consequences, accessibility and acceptability. An integrated systematic review was conducted of quantitative and qualitative studies and surveys from multiple electronic databases where computers delivered cCBT for anxiety or depression. Substantial numbers of potential participants are lost prior to trials commencing with little explanation. Among trial participants, drop-outs may be higher in the cCBT groups (odds ratio 2.03, 95% confidence interval 0.81-5.09). Only a median of 56% completed a full course of cCBT and personal circumstance was a more common cause of drop-out than difficulties with the technology or social background. Risk was rarely assessed in the majority of programs. Significant staff time was needed to support clients. Therapists were more negative about cCBT than clients. While cCBT is likely to be an effective and acceptable intervention for some people, there are barriers to its uptake that will substantially limit its impact if not addressed. These included investigating the outcome and attitudes of those who do not make it as far as cCBT trials and why so few finish a full course of cCBT.

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Author and article information

Contributors

Steffi G Riedel-Heller:

Institute of Social Medicine, Occupational Health and Public HealthMedical FacultyUniversity of LeipzigBuilding A, 3rd Fl.Philipp-Rosenthal-Str. 55Leipzig, 04103Germany49 341971540849 3419724569Steffi.Riedel-Heller@medizin.uni-leipzig.de

ORCID: http://orcid.org/0000-0003-4321-6090

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J. Med. Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: September 2017

Publication date (Electronic): 13 September 2017

Volume: 19

Issue: 9

Electronic Location Identifier: e309

Affiliations

[1] ¹ Institute of Social Medicine, Occupational Health and Public Health Medical Faculty University of Leipzig Leipzig Germany

[2] ² Department of Psychosomatic Medicine University Medical Centre University of Leipzig Leipzig Germany

[3] ³ Mental Health and Psychotherapy Stiftung Rehabilitation Heidelberg University of Applied Health Services Gera Germany

[4] ⁴ Integrated Research and Treatment Center (IFB) AdiposityDiseases University Hospital Leipzig Germany

Author notes

Corresponding Author: Steffi G Riedel-Heller Steffi.Riedel-Heller@ 123456medizin.uni-leipzig.de

Author information

Theresia Rost http://orcid.org/0000-0002-8738-8532

Janine Stein http://orcid.org/0000-0003-2982-9747

Margrit Löbner http://orcid.org/0000-0001-5984-8127

Anette Kersting http://orcid.org/0000-0002-5451-490X

Claudia Luck-Sikorski http://orcid.org/0000-0001-9791-3911

Steffi G Riedel-Heller http://orcid.org/0000-0003-4321-6090

Article

Publisher ID: v19i9e309

DOI: 10.2196/jmir.7662

PMC ID: 5617907

PubMed ID: 28903893

SO-VID: 460510a2-dc06-4e77-9a0e-f6e98ce905dd

Copyright © ©Theresia Rost, Janine Stein, Margrit Löbner, Anette Kersting, Claudia Luck-Sikorski, Steffi G Riedel-Heller. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.09.2017.

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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 10 March 2017

Date revision requested : 20 April 2017

Date revision received : 9 June 2017

Date accepted : 7 July 2017

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