The Quality of Life of Children Under Chiropractic Care Using PROMIS-25: Results from a Practice-Based Research Network
Bibliographic record
Abstract
OBJECTIVES: To characterize pediatric chiropractic and assess pediatric quality of life (QoL). DESIGN: A prospective cohort. Setting/Locations: Individual offices within a practice-based research network located throughout the United States. SUBJECTS: A convenience sample of children (8-17 years) under chiropractic care and their parents. EXPOSURE: Chiropractic spinal adjustments and adjunctive therapies. OUTCOME MEASURES: Survey instrument measuring sociodemographic information and correlates from the clinical encounter along with the Patient Reported Outcomes Measurement Information System (PROMIS)-25 to measure QoL (i.e., depression, anxiety, and pain interference). Sociodemographic and clinical correlates were analyzed using descriptive statistics (i.e., frequencies/percentages, means, and standard deviations). The PROMIS-25 data were analyzed using scoring manuals, converting raw scores to T score metric (mean = 50; SD = 10). A generalized linear mixed model was utilized to examine covariates (i.e., sex, number of visits, and motivation for care) that may have played an important role on the PROMIS outcome. RESULTS: The original data set consisted of 915 parent-child dyads. After data cleaning, a total of 881 parents (747 females, 134 males; mean age = 42.03 years) and 881 children (467 females and 414 males; mean age = 12.49 years) comprised this study population. The parents were highly educated and presented their child for mainly wellness care. The mean number of days and patient visits from baseline to comparative QoL measures was 38.12 days and 2.74 (SD = 2.61), respectively. After controlling for the effects of motivation for care, patient visits, duration of complaint, sex, and pain rating, significant differences were observed in the probability of experiencing problems (vs. no reported problems) across all QoL domains (Wald = 82.897, df = 4, p < 0.05). Post hoc comparisons demonstrated the children were less likely to report any symptoms of depression (Wald = 6.1474, df = 1, p < 0.05), anxiety (Wald = 20.603, df = 1, p < 0.05), fatigue (Wald = 22.191, df = 1, p < 0.05), and pain interference (Wald = 47.422, df = 1, p < 0.05) after a trial of chiropractic care. CONCLUSIONS: The QoL of children improved with chiropractic care as measured by PROMIS.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".