The Use of Defenses and Physician Health Care Costs: Are Physician Health Care Costs Lower in Persons with More Adaptive Defense Profiles?
Bibliographic record
Abstract
BACKGROUND: The objective of the present study was to determine if persons who use more adaptive defenses have lower physician health care costs compared to those who use less adaptive defenses. METHODS: We randomly selected 667 persons from the 1995 population-based Nova Scotia Health Survey who completed a videotaped structured interview. Each interview was rated for typical defense use by the Defense-Q. We obtained physician health care costs for 3 months before and after the interview, as well as medical diagnoses and measures of psychological functioning. RESULTS: A more adaptive defense profile significantly predicted lower future physician health care costs. These results were found when controlling for other psychosocial variables, before and after controlling for previous physician health care costs, and when testing only within a physically healthy subsample. Results of secondary analyses showed that a more adaptive defense profile was positively related to a number of psychosocial variables, such as nurse's rating of competence, lack of depressive symptoms, and days at work. CONCLUSIONS: The adaptiveness of a person's defense use in managing affect is important in predicting physician health care costs as well as psychosocial functioning.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".