Contextual factors related to aging determine force-based manipulation dosage: a prospective cross-sectional study
Bibliographic record
Abstract
Abstract Background Contextual factors influence clinicians’ delivery of force-based manipulation (FBM), like spinal manipulative therapy (SMT). It is particularly important to discern how contextual factors interact with therapeutic forces delivered to an older adult population, to minimize risk and identify ideal dosage. This study aimed to determine whether contextual factors pertaining to aging result in the modulation of kinetic and kinematic parameters used by experienced clinicians when delivering SMT. Methods Participants were randomly presented with a series of 12 AI-generated patient vignettes, featuring both visual and auditory content and representing varying age-related contextual factors. Factors included chronological (35-, 65- and 85-year-old), pathological (“healthy” vs degenerative spine), and felt (perceived as “young” vs. “old”) age. Participants delivered SMT to a human analogue manikin based on each vignette, presented six times in randomized order. Kinetic and kinematic parameters were collected and analyzed for differences between “young” and “old” contextual factors of age, using a 3-way repeated measures ANOVA model. Results Sixteen licensed chiropractors (8 female, 8 male) participated, with an average age of 45.4 (SD = 9.7, range 34–64) years and 18.3 (SD = 10.8, range 5–39) years of experience. A main effect in peak force was found for both chronological (F( 2,30 ) = 26.18; p <.001, η p 2 = 0.636) and pathological age (F( 1,15 ) = 11.58; p =.004, η p 2 = 0.436), following a stepwise progression of decreased force with increased age and with pathology. No statistically significant differences were found in peak force based on felt age, or in time to peak force for any factor. A main effect was found for chronological age with peak acceleration (F( 2,20 ) = 9.50; p <.001, η p 2 = 0.487) and peak velocity (F( 2,20 ) = 7.20; p =.004, η p 2 = 0.419), but not for pathological or felt age. There was a significant difference in time to peak velocity for felt age (F( 1,10 ) = 12.23; p =.006, η p 2 = 0.550), with a shorter time to peak velocity in response to vignettes with older felt age. Conclusion Contextual factors of aging modulated certain kinetic and kinematic characteristics when delivering SMT. This provides evidence that practitioners differentially discern aspects of aging to inform how they deliver FBM dosage. Future research is needed to identify ideal kinetic and kinematic characteristics based on considerations of aging.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Biomechanics study of how clinicians modulate spinal manipulation force; the object is clinical delivery, not research practice.
The study examines chiropractic manipulation dosage and aging factors, not research practice.
Clinical study of chiropractic force dosage by patient age, not research methods or evaluation.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".