Ftors Associated with Hopelessness: A Population Study
Bibliographic record
Abstract
BACKGROUND: Hopelessness is associated with depression and suicidality in clinical as well as in non-clinical populations. However, data on the prevalence of hopelessness and the associated factors in general population are exiguous. AIMS: To assess the prevalence and the associated factors of hopelessness in a general population sample. METHODS: The random population sample consisted of 1722 subjects. The study questionnaires included the Beck Hopelessness Scale (HS), Beck Depression Inventory (BDI), Toronto Alexithymia Scale (TAS-20) and Life Satisfaction Scale (LS). RESULTS: Eleven percent of the subjects reported at least moderate hopelessness. A poor financial situation (OR 3.64), poor subjective health (OR 2.87) and reduced working ability (OR 2.67) independently associated with hopelessness. Moreover, the likelihood of moderate or severe hopelessness was significantly increased in subjects dissatisfied with life (OR 5.99), with depression (OR 4.86), with alexithymia (OR 2.37) and with suicidal ideation (OR 1.85). CONCLUSIONS: This study demonstrated a moderately high prevalence of hopelessness at the population level. Hopelessness appears to be an important indicator of low subjective well-being in the general population that health care personnel should pay attention to.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".