Acceptance and commitment therapy: an appropriate treatment option for older adults with chronic pain
Bibliographic record
Abstract
Commentary on : Wetherell JL, Petkus AJ, Alonso-Fernandez M, et al. Age moderates response to acceptance and commitment therapy versus cognitive behavioral therapy for chronic pain. Int J Geriatr Psychiatry 2016;31:302–8.[OpenUrl][1][CrossRef][2][PubMed][3] Chronic pain is a complex, multifactored condition that affects and is influenced by both physical and psychological function. Successful treatment requires addressing both these factors.1 The evidence is indisputable that psychotherapy can help people manage their chronic pain, however, we do not know enough about what patient factors and which … [1]: {openurl}?query=rft.jtitle%253DInt%2BJ%2BGeriatr%2BPsychiatry%26rft.volume%253D31%26rft.spage%253D302%26rft_id%253Dinfo%253Adoi%252F10.1002%252Fgps.4330%26rft_id%253Dinfo%253Apmid%252F26216753%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1002/gps.4330&link_type=DOI [3]: /lookup/external-ref?access_num=26216753&link_type=MED&atom=%2Febnurs%2F19%2F4%2F123.atom
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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 | 0.003 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.021 | 0.019 |
| Insufficient payload (model declined to judge) | 0.043 | 0.013 |
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".