A Rasch analysis of the Conley Scale in patients admitted to a general hospital
Bibliographic record
Abstract
Purpose: The Conley Scale (CS) is a widely used tool for assessing the risk of falling for inpatients. The purpose of this study was to assess its unidimensionality, internal construct validity, targeting and reliability using Confirmatory Factor Analysis (CFA) and Rasch analysis (RA).Methods: The CS was administrated to a sample of 58,370 subjects admitted to a general hospital.Results: The CFA supported the unidimensionality of the CS (Root Mean Square Error of Approximation (RMSEA) = 0.040) only after adjusting for local dependency between two items. The scale did not fit the Rasch model (χ218 = 4688.5; p = 0.0000) and this was confirmed notwithstanding adjusting for type-I error (by creating 10-subsample of 250 subjects) and extensive post-hoc modifications. The analysis of targeting showed a marked floor effect (47.1%), whereas the reliability appeared adequate for group measurement (0.800) only after adjusting for the skewed distribution of the calibrating sample.Conclusion: The results of this study suggested that the CS, although unidimensional, could not provide interval-scale measurement of the risk of falling, had a measurement range that mismatched the ability range of the population being measured, and had a reliability inadequate for individual person measurements. Given these findings, the use of the CS to identify inpatients at risk of falling is not recommended.Implications for rehabilitationThe Conley Scale is a unidimensional tool according to Confirmatory Factor Analysis.However, Rasch analysis demonstrated that the tool could not provide interval-scale measurement of the risk of falling, had a measurement range that did not fit the ability range of the population being measured, and had a level of reliability which was inadequate for its intended purpose, that is individual person measurement.The diagnostic utility of the known published cutoff is severely hampered by the severe mistargeting and reduced reliability of the tool.Given these shortcomings, the Conley Scale cannot be recommended to identify inpatients at risk of falling.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".