Psychosocial Characteristics Discriminating Between Battered Women and Other Women Psychiatric Inpatients
Bibliographic record
Abstract
BACKGROUND: Research has shown that abused women often come to outpatient clinics and that their psychological symptoms are often confused with those of psychiatric patients. OBJECTIVES: The purpose of this research was to examine the psychosocial differences between battered and nonbattered women admitted to a psychiatric unit in a French New Brunswick hospital. STUDY DESIGN: Data were collectedfrom 221 medical records of women admitted to a psychiatric unit over a 5-year period. The following data were collected. information on the general characteristics of the women and their husbands (age, marital status, and occupation), information on the presence or absence of physical violence, and the psychiatric diagnosis, symptoms, and treatment of the patients. RESULTS: Of the 221 medical records studied of women admitted into one psychiatric unit, 30 (13.7%) belonged to women who admitted having been battered. The battered women typically were in their thirties, were divorced or separated, had married against their parents' will and had theirfirst child before marriage. They most likely had grown up in a violent or broken home. Most battered inpatients had experienced sexual difficulties and had trouble with their in-laws. They were less likely to have disorganized thinking and their conditions were more likely to go undiagnosed than those of nonbattered women. They tended to express feelings of anger and guilt more freely than did nonbattered women. These actions are not characteristic of helpless women but of aggressive and independent women. CONCLUSIONS: The questionnaire for taking the social history of psychiatric patients should seek information about domestic violence. Therapy should build on the independence and anger of battered women instead of trying to eliminate those coping mechanisms.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".