Evaluation of a therapist-guided virtual psychological pain management program when provided as routine care: a prospective pragmatic cohort study
Bibliographic record
Abstract
INTRODUCTION: Numerous randomized controlled trials have evaluated the outcomes of internet-delivered psychological pain management programs (PMPs) as a way of increasing access to care for people with chronic pain. However, there are few reports of the effectiveness of these PMPs when provided as part of routine care. METHODS: The present study sought to report the clinical and demographic characteristics of users (n = 1367) and examine the effectiveness of an established internet-delivered psychological PMP program in improving several pain-related outcomes, when offered at a national digital mental health service over a 5-year period. It also sought to comprehensively explore predictors of treatment commencement, treatment completion, and clinical improvement. RESULTS: Evidence of clinical improvements (% improvement; Hedges g) were found for all outcomes, including pain interference (18.9%; 0.55), depression (26.1%; 0.50), anxiety (23.9%; 0.39), pain intensity (12.8%; 0.41), pain self-efficacy (-23.8%; -0.46) and pain-catastrophizing (26.3%; 0.56). A small proportion of users enrolled but did not commence treatment (13%), however high levels of treatment completion (whole treatment = 63%; majority of the treatment = 75%) and satisfaction (very satisfied = 45%; satisfied = 37%) were observed among those who commenced treatment. There were a number of demographic and clinical factors associated with commencement, completion and improvement, but no decisive or dominant predictors were observed. DISCUSSION: These findings highlight the effectiveness and acceptability of internet-delivered psychological PMPs in routine care and point to the need to consider how best to integrate these interventions into the pathways of care for people with chronic pain.
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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 | 0.030 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".