Effectiveness of acupuncture in treating patients with pain and mental health concerns: the results of the Alberta Complementary Health Integration Project
Bibliographic record
Abstract
Background: This study presents real-world evidence on the clinical outcomes of the Alberta Complementary Health Integration Project (ABCHIP), which utilized acupuncture to address pain and mental health issues in two vulnerable populations in Alberta: youth (aged 24 and below) and elderly (aged 55 and above). Methods: Over 282 days, a total of 606 patients received 5,424 acupuncture treatments. Tailored to each patients' specific pain and mental health concerns, an individualized treatment plan was selected, following a standard treatment protocol lasting 1 to 3 months. Patients were evaluated at least twice: initially and upon completing therapy. Primary treatment outcomes were assessed using various measures, including the Brief Pain Inventory (BPI), Pittsburgh Sleep Quality Index (PSQI), Patient Health Questionnaire 9 (PHQ9), PROMIS Anxiety 8a and its pediatric form PROMIS Anxiety-Pediatric, PROMIS Short Form v1.0 Fatigue 8a and its pediatric counterpart PROMIS Pediatric Short Form v2.0 Fatigue 10a, PROMIS Short Form v1.1 Anger 5a and its version PROMIS SF v2.0 5a, and EQ-5D-5L. These measures gauged pain reduction, improved sleep quality, reduced depression, anxiety, fatigue, anger, and quality of life, respectively. Results: Analysis of data from 500 patients who received at least 6 acupuncture sessions through ABCHIP showed statistically significant improvements in clinical outcomes. Among this group, the subgroup of 235 patients who received at least 12 sessions demonstrated the most favorable treatment outcomes, including an 75.5% reduction in pain severity, a 53.1% improvement in sleep quality, a 78.4% drop in depression, a 41.1% decline in anxiety, a 43.7% decrease in fatigue, a 38.2% decrease in anger, and a 42.6% improvement in overall quality of life. Conclusion: Integrating acupuncture with usual care demonstrates promise in enhancing mental health, alleviating chronic and general pain, and improving overall quality of life. The findings suggest that integrative programs, such as ABCHIP, present an effective approach to addressing pain and mental health concerns in vulnerable populations, providing valuable insights for future healthcare interventions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".