An internet‐delivered self‐management programme for bipolar disorder in mental health services in Ireland: Results and learnings from a feasibility trial
Bibliographic record
Abstract
Bipolar disorder (BD) is a chronic condition that requires continued care. Psychological interventions are recommended by clinical guidelines but there are treatment barriers that prevent patients to access these services. Internet-delivered self-management interventions are promising alternatives to improve treatment accessibility in patients with BD. Several studies indicate that these interventions are acceptable and beneficial for patients with BD, but no studies have been conducted in routine care settings. This trial aimed to examine the feasibility, acceptability, and preliminary efficacy of implementing an internet-delivered, clinician-supported intervention for BD as an adjunct to treatment as usual at two secondary-care services in Ireland. This study used an uncontrolled design with mixed-methods evaluation. Feasibility and acceptability were assessed in terms of recruitment, use of the intervention, and satisfaction from both clinicians and patients' perspectives. Personal recovery, quality of life, and severity of symptoms were measured at baseline and post-intervention. Fifteen patients signed consent and used the programme for 10 weeks. Usage of the intervention was adequate with high frequency of tool usage. There was a significant improvement in patients' sense of personal recovery (z = 2.38, p = .017). The intervention was found acceptable and easy-to-use; however, implementation barriers will need to be overcome for scaling the intervention. This is the first study testing the feasibility of a digital intervention for patients with BD in public mental health services in Ireland. More research is needed in order to increase the understanding of how to promote the integration and the uptake of digital interventions for individuals with BD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".