Content Validity of the LIMB-Q: A Patient-Reported Outcome Instrument for Lower Extremity Trauma Patients
Bibliographic record
Abstract
BACKGROUND: Limb-threatening lower extremity traumatic injuries can be devastating events with a multifaceted impact on patients. Therefore, evaluating patient-reported outcomes (PROs) in addition to traditional surgical outcomes is important. However, currently available instruments are limited as they were not developed specific to lower extremity trauma patients and lack content validity. The LIMB-Q is being developed as a novel PRO instrument to meet this need, with the goal to measure all relevant concepts and issues impacting amputation and limb-salvage patients after limb-threatening lower extremity trauma. METHODS: This is a qualitative interview-based study evaluating content validity for the LIMB-Q. Patients aged 18 years and older who underwent amputation, reconstruction, or amputation after failed reconstruction were recruited using purposeful sampling to maximize variability of participant experiences. Expert opinion was solicited from a variety of clinical providers and qualitative researchers internationally. Preliminary items and scales were modified, added, or removed based on participant and expert feedback after each round of participant interviews and expert opinion. RESULTS: Twelve patients and 43 experts provided feedback in a total of three rounds, with changes to the preliminary instrument made between each round. One scale was dropped after round one, one scale was added after round two, and only minor changes were needed after round three. Modifications, additions and removal of items, instructions, and response options were made after each round using feedback gathered. CONCLUSION: The LIMB-Q was refined and modified to reflect feedback from patients and experts in the field. Content validity for the LIMB-Q was established. Following a large-scale field test, the LIMB-Q will be ready for use in research and clinical care.
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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 | 0.035 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".