A Patient Informed Qualitative Program Evaluation of an Internet-Based Chronic Pain Treatment
Bibliographic record
Abstract
An innovative, Internet-based chronic pain treatment tailored to a military and police population was developed using Acceptance and Commitment Therapy (ACT) as a model. The treatment was recently evaluated in randomized controlled trial and found to be superior to treatment as usual in terms of increasing patients’ levels of pain acceptance, decreasing their pain-related catastrophizing, and decreasing their levels of kinesiophobia. In an effort to further increase the efficacy of the treatment, we enlisted patient feedback about the program through a series of focus groups. Participants who had previously completed the online treatment were recruited to participate in a series of focus groups designed to qualitatively evaluate the treatment and offer suggestions for improvements for future versions of the program. Participatory Action Research methodology was used to conduct this study and data were examined using interpretive thematic analysis. Three main themes arose: suggestions for improving the technological “friendliness” of the online program, suggestions for improving the sequencing of content, and suggestions for greater tailoring of the content to the sensitivities of the target population. As an example of the latter, participants suggested removal of the “attending your own funeral” exercise from the values module due to sensitivities around death and dying. Future directions, based on patient feedback, are outlined.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".