Quality of Life and Adaptation in People With Spinal Cord Injury: Response Shift Effects From 1 to 5 Years Postinjury
Bibliographic record
Abstract
OBJECTIVE: To investigate response shift effects in spinal cord injury (SCI) over 5 years postinjury. DESIGN: Prospective cohort study observed at 1, 2, and 5 years post-SCI. SETTING: Specialized SCI centers. PARTICIPANTS: Sample included 1125, 760, and 219 participants at 1, 2, and 5 years post-SCI (N = 2104). The study sample was 79% men; 39% were motor/sensory complete (mean age, 44.6±18.3y). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Patient-reported outcomes included the Medical Outcomes Study 36-Item Short-Form Health Survey version 2 and the Life Satisfaction-11 Questionnaire. Participant latent variable scores were adjusted for (1) potential attrition bias and (2) propensity scores reflecting risk of worse outcomes. The Oort structural equation modeling approach for detecting and accounting for response shift effects was used to test the hypothesis that people with SCI would undergo response shifts over follow-up. RESULTS: The study data comprised the time after FIM scores, an objective measure of motor and cognitive function, had improved and stabilized. Three latent variables (Physical, Mental, and Symptoms) were modeled over time. The response shift model indicated uniform recalibration and reconceptualization response shift effects over time. When adjusted for these response shift effects, Physical showed small true change improvements at 2- and 5-year follow-up, despite FIM stability. CONCLUSIONS: We detected recalibration and reconceptualization response shift effects in 1- to 5-year follow-up of people with SCI. Despite stable motor and cognitive function, people with SCI are adapting to their condition. This adaptation reflects a progressive disconnection between symptoms and physical or mental health, and a real improvement in the Physical latent variable.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".