Development and validation of the Treatment Related Impact Measure of Weight (TRIM-Weight)
Bibliographic record
Abstract
BACKGROUND: The use of prescription anti-obesity medication (AOM) is becoming increasingly common as treatment options grow and become more accessible. However, AOM may not be without a wide range of potentially negative impacts on patient functioning and well being. The Treatment Related Impact Measure (TRIM-Weight) is an obesity treatment-specific patient reported outcomes (PRO) measure designed to assess the key impacts of prescription anti-obesity medication. This paper will present the validation findings for the TRIM-Weight. METHODS: The online validation battery survey was administered in four countries (the U.S., U.K., Australia, and Canada). Eligible subjects were over age eighteen, currently taking a prescription AOM and were currently or had been obese during their life. Validation analyses were conducted according to an a priori statistical analysis plan. Item level psychometric and conceptual criteria were used to refine and reduce the preliminary item pool and factor analysis to identify structural domains was performed. Reliability and validity testing was then performed and the minimally importance difference (MID) explored. RESULTS: Two hundred and eight subjects completed the survey. Twenty-one of the 43 items were dropped and a five-factor structure was achieved: Daily Life, Weight Management, Treatment Burden, Experience of Side Effects, and Psychological Health. A-priori criteria for internal consistency and test-retest coefficients for the total score and all five subscales were met. All pre-specified hypotheses for convergent and known group validity were also met with the exception of the domain of Daily Life (proven in an ad hoc analysis) as well as the 1/2 standard deviation threshold for the MID. CONCLUSION: The development and validation of the TRIM-Weight has been conducted according to well-defined principles for the creation of a PRO measure. Based on the evidence to date, the TRIM-Weight can be considered a brief, conceptually sound, valid and reliable PRO measure.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".