Low self-esteem and psychiatric patients: Part I – The relationship between low self-esteem and psychiatric diagnosis
Bibliographic record
Abstract
BACKGROUND: The objective of the current study was to determine the prevalence and the degree of lowered self-esteem across the spectrum of psychiatric disorders. METHOD: The present study was carried out on a consecutive sample of 1,190 individuals attending an open-access psychiatric outpatient clinic. There were 957 psychiatric patients, 182 cases with conditions not attributable to a mental disorder, and 51 control subjects. Patients were diagnosed according to DSM III-R diagnostic criteria following detailed assessments. At screening, individuals completed two questionnaires to measure self-esteem, the Rosenberg self-esteem scale and the Janis and Field Social Adequacy scale. Statistical analyses were performed on the scores of the two self-esteem scales. RESULTS: The results of the present study demonstrate that all psychiatric patients suffer some degree of lowered self-esteem. Furthermore, the degree to which self-esteem was lowered differed among various diagnostic groups. Self-esteem was lowest in patients with major depressive disorder, eating disorders, and substance abuse. Also, there is evidence of cumulative effects of psychiatric disorders on self-esteem. Patients who had comorbid diagnoses, particularly when one of the diagnoses was depressive disorders, tended to show lower self-esteem. CONCLUSIONS: Based on both the previous literature, and the results from the current study, we propose that there is a vicious cycle between low self-esteem and onset of psychiatric disorders. Thus, low self-esteem increases the susceptibility for development of psychiatric disorders, and the presence of a psychiatric disorder, in turn, lowers self-esteem. Our findings suggest that this effect is more pronounced with certain psychiatric disorders, such as major depression and eating disorders.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".