Content validity of the comprehensive home fall hazard checklist, an observational study
Bibliographic record
Abstract
One strategy to reduce the number of falls in older adults is through home hazards assessment checklists. The comprehensive home fall hazard checklist (CHFHC) was designed to guide individuals through their home, assessing fall hazards. The checklist systematically prompts the individuals to check 10 general locations in the house The purpose of this study was to assess the content validity of the comprehensive home fall hazard checklist. A 4-point ordinal Likert rating scale was used to evaluate the content validity of each of the 74 items on the checklist. The relevance and clarity of each item was assessed. Nine experts rated the content validity of each test in relation to the 5 tasks in the rating protocol. The item content validity index, and the scale content validity index were determined, and a kappa rating was calculated. Three of the 74 items on the CHFHC were determined to be not relevant receiving a content validity index of 0.78 or less. All of the items were ranked as being quite clear or highly clear, with all items receiving at least 0.78 on the content validity index. The Kappa score indicates expert agreement. The content validity index was determined to be excellent, with high ratings for both relevance and clarity for 71 of 74 items on the CHFHC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.033 | 0.136 |
| 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 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".