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Record W2947976580 · doi:10.3233/wor-192919

Yoga improves occupational performance, depression, and daily activities for people with chronic pain

2019· article· en· W2947976580 on OpenAlexaboutno aff
Arlene A. Schmid, Marieke Van Puymbroeck, Christine A. Fruhauf, Matthew J. Bair, Jennifer Dickman Portz

Bibliographic record

VenueWork · 2019
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialPhysical therapyMedicinePsychological interventionChronic painIntervention (counseling)Depression (economics)Activities of daily livingOccupational therapyPsychiatry

Abstract

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BACKGROUND: Chronic pain is a complex accumulation of physical, psychological, and social conditions, thus interventions that address pain and promote occupational performance are needed. A holistic intervention, with mind and body components, is likely necessary to best treat the complexities of chronic pain. Thus, we developed and tested a yoga intervention for people with chronic pain. OBJECTIVES: In a randomized control trial (RCT), participants with chronic pain were randomized to a yoga intervention or usual care group. Between and within group differences for pre-and post-outcome measure scores were assessed for: occupational performance, completion of activities, and depression. METHODS: Pilot RCT with participant allocation to 8 weeks of yoga or usual care. Both groups received ongoing monthly self-management programming. Data were collected before and after the 8-week intervention. Participants were randomized to yoga or usual care after baseline assessments. Demographics were collected and measures included: Canadian Occupational Performance Measure (COPM) to assess occupational performance; the 15-item Frenchay Activities Index (FAI)(activities); and the 9-item Patient Health Questionnaire (PHQ-9) for depression. Independent t-tests were used to assess differences between groups. Paired t-tests were used to assess differences between pre- and post 8-week intervention for both the yoga and the usual care groups. Percent change scores and effect sizes were calculated. RESULTS: 83 people were recruited for the study and completed baseline assessments; 44 individuals were randomized to yoga and 39 to the control group. The average age of all participants was 51.4±10.5 years, 68% were female; and 60% had at least some college education. There were no significant differences in demographics or outcome measures between groups at baseline or 8 weeks; however, the study was not powered to see such differences. Individuals randomized to the control group did not significantly improve in any outcome measure over the 8 weeks. There were significant improvements in COPM performance and COPM satisfaction scores for individuals randomized to the yoga group; both scores significantly improved. COPM performance improved by 27% with a moderate to large effect size (3.66±1.85 vs 4.66±1.93, p < 0.001, d = 0.76). COPM satisfaction significantly improved by 78% (2.14±2.31 vs. 3.80±2.50, p < 0.001) and had a large effects size (d = 1.02). FAI scores improved, indicating increased activity or engagement in daily occupation during the 8-week intervention. Scores increased by 5% (38.13±8.48 vs. 39.90±8.57, p = 0.024) with a small effect size (d = 0.37). Depression significantly decreased from 13.21±5.60 to 11.41±5.82, p = 0.041, with a small effect size. CONCLUSION: Data from this pilot RCT indicate yoga may be an effective therapeutic intervention with people in chronic pain to improve occupational performance, increase engagement in activities, and decrease depression. Occupational therapy practitioners may consider adding yoga as a treatment intervention to address the needs of people with pain.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.011
GPT teacher head0.272
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2019
Admission routes1
Has abstractyes

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