Effectiveness of Acceptance and Commitment-Based Therapy (ACT Rehab) on Quality of Life, Severity and Duration of Pain; in Women With Chronic Low Back Pain
Bibliographic record
Abstract
Objectives: Most of the women around the globe experience low back pain which often has a psychological overlay. Acceptance and Commitment Therapy (ACT) can enhance psychological condition and subsequently improve mental health. Thereby the quality of life of individuals with chronic low back pain gets improved. The study rationale aimed to assess the effectiveness of ACT on quality of life, severity and duration of pain in women with chronic low back pain. Methods: Twenty subjects (women aged between 23 to 34 years) with chronic low back pain from a rehabilitation clinic in Rasht city in the year 2016 were included in the study by convenience sampling method. They were then randomly divided into experimental and control groups (in each group, n=10). Data were collected by a three-part checklist containing demographic characters, World Health Organization Quality of Life questionnaire and McGill Pain Questionnaire. The rehabilitation interventions were based on ACT carried out for eight sessions of one hour each, twice a week. The collected data were analyzed by SPSS software via Paired t-test and independent t-test method. Results: There was a significant increase in all subscales of quality of life (P<0.001) except subscale of physical health (P<0.38) in experimental group. Independent t-test showed a significant decline in mean severity and duration of pain in the experimental group compared to control group. Discussion: The effects of ACT rehabilitation technique on women with chronic low back pain were impressive, which augmented the quality of life. Hence this method can be used as a rehabilitation tool for women with chronic low back pain.
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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 | 0.001 | 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) | 0.002 | 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 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".