Five‐year observational study of Internet‐delivered cognitive behavioural pain management when offered as routine care by an online therapy clinic
Bibliographic record
Abstract
BACKGROUND: Internet-delivered cognitive behavioural pain management programmes (PMPs) are effective, but less is known about their use outside of research trials. Five years of data from offering the Internet-delivered cognitive behavioural PMP in an online therapy clinic was examined to assess effectiveness, acceptability and predictors of outcomes. METHODS: Patients (N = 293) were offered a previously validated 8-week Internet-delivered cognitive behavioural PMP and administered measures at pre-treatment, post-treatment and 3 months. RESULTS: There was growth in demand for an Internet-delivered cognitive behavioural PMP over time (n = 64 first year to n = 133 fifth year). Moderate-to-large improvements on depression (post-treatment 35% reduction; 3-month 41% reduction) and anxiety (post-treatment 37% reduction; 3-month 41% reduction), and small-to-moderate improvements on disability (post-treatment 19% reduction; 3-month 20% reduction) were found. Lesson completion and satisfaction were high. Lower pain acceptance, lower pain self-efficacy and higher pain intensity were associated with lower improvements on depression, anxiety and disability. CONCLUSIONS: This longitudinal observational study provides support for Internet-delivered cognitive behavioural PMPs when offered as routine care by an online therapy clinic. SIGNIFICANCE: This 5-year observational study provides support for Internet-delivered cognitive behavioural pain management programs (PMPs) offered as routine care in an online therapy clinic. Interest in the service grew over 5 years. Outcomes, engagement and satisfaction were strong. Higher pain acceptance, pain self-efficacy and lower pain severity were associated with greater post-treatment improvements on depression, anxiety and disability.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".