A qualitative exploratory study of user experience with a peer-support based, self-management website for people with a cardiovascular condition and diabetes
Bibliographic record
Abstract
Background: Cardiovascular disease and Type 2 diabetes are two serious chronic health conditions that impact patients, families, and health services. Patients who experience both conditions can struggle to access relevant programmes to guide and educate them on successful self-management. Peer support has been proven to assist patients in managing these dual conditions, but the experience of using an online platform has not been previously explored. Aim: To understand the experience of using a theory-based, peer-support, self-management website for people with cardiovascular and diabetes conditions in an Australian regional health service. Design: An exploratory qualitative study was undertaken. Our study is reported according to COREQ guidelines. Methods: Data were collected via online, semi-structured interviews approximately one week after participants were asked to engage with the website. Interviews were conducted to focus on the user experience, feasibility and usefulness of accessing the website, and how it helped support development of self-management skills. Interview data were transcribed from audio recordings into text files, thematic analysis was conducted for evolving themes. Results: Fifteen participants agreed to be interviewed for the study. Findings revealed that participants found the website useful for providing relevant, comprehensive, and reliable online health information to help them manage their comorbidities. Participants appreciated the opportunity to share their experiences with others, and some expressed their interest in becoming peer supporters, to help others who might be trying to manage similar comorbidities. Conclusion: Users' experience of the peer-support, web-based programme was positive overall and supported the physical and emotional well-being of the participants, who were trying to manage two complex chronic health conditions. Considerations for further development are reported on.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".