Web-based cognitive behavioural therapy (W-CBT) for diabetes patients with co-morbid depression: design of a randomised controlled trial
Open accessAbstract
BACKGROUND: Depression is common among people with diabetes, negatively affecting quality of life, treatment adherence and diabetes outcomes. In routine clinical care, diabetes patients have limited access to mental health services and depression therefore often remains untreated. Web-based therapy could potentially be an effective way to improve the reach of psychological care for diabetes patients, at relatively low costs. This study seeks to test the effectiveness of a web-based self-help depression programme for people with diabetes and co-morbid depression. METHODS/DESIGN: The effectiveness of a web-based self-help course for adults with diabetes with co-morbid depression will be tested in a randomised trial, using a wait-list controlled design. The intervention consists of an 8-week, moderated self-help course that is tailored to the needs of persons living with diabetes and is offered on an individual basis. Participants receive feedback on their homework assignments by e-mail from their coach. We aim to include 286 patients (143/143), as power analyses showed that this number is needed to detect an effect size of 0.35, with measurements at baseline, directly after completing the web-based intervention and at 1, 3, 4 and 6 months follow-up. Patients in the control condition are placed on a waiting list, and follow the course 12 weeks after randomisation. Primary outcomes are depressive symptoms and diabetes-specific emotional distress. Secondary outcomes are satisfaction with the course, perceived health status, self-care behaviours, glycaemic control, and days in bed/absence from work. Questionnaires are administered via the Internet. DISCUSSION: The intervention being trialled is expected to help improve mood and reduce diabetes-specific emotional distress in diabetes patients with depression, with subsequent beneficial effects on diabetes self-care and glycaemic outcomes. When proven efficacious, the intervention could be disseminated to reach large groups of patients with diabetes and concurrent depressive symptoms. TRIAL REGISTRATION: Current Controlled Trials ISRCTN24874457.
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Digital depression interventions can work for people with diabetes.
“As one example, Bendig et al. (2021) reported on a failed trial examining an intervention for depression in people with coronary artery disease, while we do know that this kind of intervention can work e.g. for people with diabetes (Nobis et al., 2018; Nobis et al., 2015; van Bastelaar et al., 2008).”
From Special issue on digital health interventions in chronic medical conditions: Editorial (2022) · cites this paper as van Bastelaar et al., 2008
The Background says web-based CBT is an effective treatment option for depression generally, but says this study would be the first to test diabetes-specific online CBT. The Aims of the Trial section describes effectiveness for people with diabetes as a hypothesis, not a demonstrated result. Thus the paper does not establish that digital depression interventions work for this population. (LLM, conf=0.88)
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- Authors
- van Bastelaar, K. M., Pouwer, F., Cuijpers, P., Twisk, J. W., & Snoek, F. J.
- Affiliations
- Amsterdam Public Health (NL)
- Venue
- BMC Psychiatry
- Published
- 2008-02-19
- Volume
- 8
- Issue
- 1
- Pages
- 9-9
- ISSN
- 1471-244X (ISSN-L)
- PMC
- PMC2277386
- OpenAlex
- W2146679997
- Cited by
- 57
- References
- 35
- Citations by year
- 2025: 1 · 2023: 2 · 2022: 3 · 2021: 3 · 2019: 1 · 2018: 2 · 2017: 3 · 2016: 2 · 2015: 2 · 2014: 3 · 2013: 2 · 2012: 10
- FWCI
- 9.95
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (acceptedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Pure Amsterdam UMC (submittedVersion)
- Research portal (Tilburg University) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- VU Research Portal (submittedVersion, other-oa)
- Funders
- Diabetes Fonds
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- diabetes mellitus, depression, comorbidities, self-help intervention, glycemic control, diabetes self-care, e-mental health, medication adherence
- MeSH terms
- Adult, Depressive Disorder, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Female, Follow-Up Studies, Humans, Male, Patient Compliance, Patient Education as Topic, Personality Inventory, Self Care, Software Design, Comorbidity, Cognitive Behavioral Therapy, Treatment Outcome, Internet, Feedback, Psychological
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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