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Record W2168857549 · doi:10.1177/0020764004040961

Ftors Associated with Hopelessness: A Population Study

2004· article· en· W2168857549 on OpenAlexaboutno aff
Kaisa Haatainen, Antti Tanskanen, Jari Kylmaä, Kirsi Honkalampi, Heli Koivumaa‐Honkanen, Jukka Hintikka, Heimo Viinamäki

Bibliographic record

VenueInternational Journal of Social Psychiatry · 2004
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsBeck Hopelessness ScaleAlexithymiaPopulationPsychologyDepression (economics)Toronto Alexithymia ScaleClinical psychologyBeck Depression InventoryPsychiatrySuicidal ideationMedicinePoison controlSuicide preventionAnxietyMedical emergency

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.304
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations68
Published2004
Admission routes1
Has abstractyes

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