Reconsidering the minimally important difference: evidence of instability over time and across groups
Bibliographic record
Abstract
BACKGROUND CONTEXT: Underlying cognitive factors have been found to influence patients' symptom experience. Current evidence suggests that concomitant changes in appraisal must be taken into account to accurately interpret change as measured by standard spine patient-reported outcomes (PROs). PURPOSE: To investigate changes in patients' minimally important differences (MID) over recovery from spinal surgery; whether and how cognitive appraisal processes are implicated in the change trajectories. STUDY DESIGN/SETTING: Longitudinal cohort study with up to 12 months follow-up. PATIENT SAMPLE: Surgical patients (n = 167) with a diagnosis of disc herniation or spinal stenosis. OUTCOME MEASURES: Standard spine patient-reported PROs were used (Rand-36, Oswestry Disability Index, Numerical Rating Scale for pain, PROMIS Pain Impact). METHODS: This study was funded by the Feldberg Chair in Spinal Research, Sunnybrook Health Sciences Centre and the authors have no conflicts of interest. MID used an anchor technique and was computed by global assessment of change (GAC) grouping. Participants were binned into groups based on their GAC response patterns at all time points: Consistently better post-surgery, consistently worse post-surgery, and bouncers, whose GAC ratings fluctuate (ie, better-then-worse-then-better; or vice versa). Individuals' longitudinal quality of life (QOL) and appraisal slope scores were computed. QOL-appraisal slopes' correlations were computed by GAC group. Fisher's Z transformation tested the hypothesis that GAC groups differed in the QOL-appraisal relationship over time. RESULTS: Moderate to large changes are recognized as clinically important in the early stages of recovery (ie, 6 weeks post-surgery), and over time smaller and smaller changes become important. The three pattern groups emphasized and deemphasized different standards of comparison over time, with the Better group emphasizing personal goals and the Worse and Bouncers deemphasizing doctors' input. These group differences translated to differential relationships between PRO change and appraisal changes over time. CONCLUSIONS: The MID reflects increasingly subtle change over time in PROs. Appraisal may influence how patients experience the same (MID) change over time, with better outcomes associated with emphasizing long-term goals. PRO change seems to be driven by different standards of comparison. Potential avenues for clinical intervention are discussed.
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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 | 0.052 | 0.247 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".