Chapter 1 A Comparison of Four Person-Environment Fit Models Applied to Older Adults
Bibliographic record
Abstract
Abstract Inthispaper, we comparefour Person-Environment(P-E) Fit models in terms of their ability to predict well-being among older adults. The models tested include: Lawton and Nahemow's (1973) competence model (model 1); Carp and Carp's (1984) congruence model (model 2); and two models based on Kahana's (1982) proposition that subjective prioritizing of multi-level environmental needs is a required element of P-E fit measures. The first priority model (model 3) represents unmet needs in the environmental domain with the highest subjective priority. The weighted priority model (model 4) scales P-E scores according to the prioritization of all environmentaldomains under study. A total sample of 174 seniors dwelling in the Vancouver community were used in this research; divided into a vulnerablesub-sample of Adult Day Care (ADC) clients (n = 115) and a non-frail community sub-sample (n = 59). Lawton's (1997) Valuation of Lifescale (VOL)was used as a measure of well-being. Model 4 was found to predict the largest amount of variance in VOL for the total sample and both sub-samples, after controlling for several covariates. Model 3 was the second best model in predicting VOL for the ADC sample, whereas model 2 wasthe second best predictor of VOL for the non-frail sample. The findings are discussed in terms of their implications for theory development, for explaining research showing that frail and non-frail older persons exhibit similar levels of well-being, and for client-centered service program-ming.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".