PSYCHOMETRIC PROPERTIES OF THE LIFE-SPACE ASSESSMENT AMONG CANADIAN COMMUNITY-DWELLING ADULTS
Bibliographic record
Abstract
BACKGROUND Life-space mobility refers to the extent of movement into the environment and community. The Life-Space Assessment (LSA) is a self-report measure that measures life-space mobility. Prior to its use in a Canadian community-dwelling population, the LSA should be validated, and reference values need to be generated. As such, this thesis has the following aims: 1) To establish sex-stratified reference values for the LSA; 2) To determine the construct (convergent and known-groups) validity of the LSA, and 3) To determine the predictive validity of the LSA in predicting health outcomes such as hospitalizations at 3 years among community-dwelling Canadian adults. METHODS The Canadian Longitudinal Study on Aging (CLSA) was used. For reference values, percentile regressions were used to estimate the age-specific percentiles (i.e., 5th to 95th) for LSA scores. For convergent and divergent validity, Spearman correlation coefficients were used to compare the LSA against other measures. For known-groups validity, a change of 5 or more points on the LSA was considered between known-groups (i.e., those with chronic disease and those with a falls history). For predictive validity, Receiver Operating Characteristic curves were used. Analyses were stratified by age and sex. RESULTS References values demonstrated lower LSA scores for females and older age groups. Convergent validity hypotheses (r >0.5) were not met; however divergent validity (r <0.3) and known-groups validity (5 or more points on the LSA) hypotheses were met. Lastly, predictive validity hypotheses (area under the curve >0.7) were not met.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".