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Record W2609489944 · doi:10.1177/1078390317705450

The Paradox of Well-Being and Holocaust Survivors

2017· article· en· W2609489944 on OpenAlexfundno aff
Yaacov G. Bachner, Sara Carmel, Norm O’Rourke

Bibliographic record

VenueJournal of the American Psychiatric Nurses Association · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLife satisfactionPsychologyConstruct (python library)Scale (ratio)Quality of life (healthcare)Clinical psychologyAssociation (psychology)Confirmatory factor analysisGerontologyMedicineStructural equation modelingSocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Life satisfaction is a core component of well-being. Across age groups, satisfaction with life was found to be integral to individual mental and physical health. Surprisingly, there appears to be little or no association between age and life satisfaction. Recent longitudinal research suggests that life satisfaction may even increase in late life. This is known as the paradox of well-being. OBJECTIVE: To compare levels of life satisfaction reported by Israeli Holocaust survivors (HS) vis-à-vis other older Israelis and older Canadians. DESIGN: We interviewed 295 HS, 205 other older Israelis, and 335 older Canadians each of whom completed the Life Satisfaction Scale with items measuring both concurrent and retrospective aspects. Separate confirmatory factor analytic models were computed for each group. RESULTS: Overall, levels of life satisfaction were indistinguishable across groups. Both concurrent and retrospective items contributed significantly to measurement of a single latent construct. Yet differences between groups in the latent structure of response to certain scale items emerged. CONCLUSIONS: It may be that HS report high life satisfaction not despite, but because of, experiencing early life trauma, juxtaposing early years with the comparatively good conditions of their lives today.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.077
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.313
Teacher spread0.306 · 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

Citations14
Published2017
Admission routes1
Has abstractyes

Explore more

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