The impact of web-based approaches on psychosocial health in chronic physical and mental health conditions
Open accessAbstract
Chronic conditions such as cancer, cardiovascular disease and mental illness are increasingly prevalent and associated with considerable psychosocial burden. There is a need to consider population health approaches to reducing this burden. Web-based interventions offer an alternative to traditional face-to-face interventions with several potential advantages. This systematic review explores the effectiveness, reach and adoption of web-based approaches for improving psychosocial outcomes in patients with common chronic conditions. A systematic review of published work examining web-based psychosocial interventions for patients with chronic conditions from 2001 to 2011. Seventy-four publications were identified. Thirty-six studies met the criteria for robust research design. A consistent significant effect in favour of the web-based intervention was identified in 20 studies, particularly those using cognitive behavioural therapy for depression. No positive effect was found in 11 studies, and mixed effects were found in 5 studies. The role of sociodemographic characteristics in relation to outcomes or issues of reach and adoption was explored in very few studies. Although it is possible to achieve positive effects on psychosocial outcomes using web-based approaches, effects are not consistent across conditions. Robust comparisons of the reach, adoption and cost-effectiveness of web-based support compared with other options such as face-to-face and print-based approaches are needed.
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Web- and mobile-based interventions can be less costly and may not rely heavily on psychotherapists.
“Third, web- and mobile-based interventions can be less costly and may not rely heavily on psychotherapists [20,21].”
From Effects and Mechanisms of a Web- and Mobile-Based Acceptance and Commitment Therapy Intervention for Anxiety and Depression Symptoms in Nurses: Fully Decentralized Randomized Controlled Trial. (2023) · cites this paper as [20]
The Introduction says web-based approaches may reduce the resource constraints of face-to-face support, and the Results describe interventions that did not include a live therapist. But the Conclusion calls for head-to-head cost-effectiveness comparisons, so lower cost is not established; the paper also does not extend these points to mobile-based interventions. (LLM, conf=0.85)
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- Authors
- Paul, C. L., Carey, M. L., Sanson-Fisher, R. W., Houlcroft, L. E., & Turon, H. E.
- Affiliations
- Hunter Medical Research Institute (AU)
- Corresponding author
- Paul, C. L.
- Venue
- Health Education Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-05-09
- Volume
- 28
- Issue
- 3
- Pages
- 450-471
- ISSN
- 0268-1153 (ISSN-L)
- 1465-3648
- PMC
- PMC3649214
- OpenAlex
- W2096749009
- Cited by
- 51
- References
- 86
- Citations by year
- 2025: 1 · 2023: 4 · 2022: 3 · 2021: 4 · 2019: 3 · 2018: 6 · 2017: 8 · 2016: 8 · 2015: 7 · 2014: 4 · 2013: 3
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Health Education Research (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Figshare (submittedVersion)
- NOVA (University of Newcastle Australia) (submittedVersion)
- Funders
- Hunter Medical Research Institute
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- online intervention, psychosocial health, chronic physical illness, chronic mental illness, cancer, cardiovascular disease, cognitive behavioral therapy, depression, intervention effectiveness, cost-effectiveness, sociodemographic factors
- MeSH terms
- Adaptation, Psychological, Mental Disorders, Chronic Disease, Humans, Social Adjustment, Therapy, Computer-Assisted, Internet
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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