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Record W2743613340 · doi:10.1177/0030222817724307

Death Anxiety Among New Zealanders: The Predictive Roles of Religion, Spirituality, and Family Connection

2017· article· en· W2743613340 on OpenAlexaff
Rod MacLeod, Donna M. Wilson, Jackie Crandall, Phil Austin

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2017
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSpiritualityDeath anxietyPsychologyAnxietyPopulationClinical psychologyGeneralized anxietyReligious orientationSocial psychologyMedicineDemographyPsychiatrySociologyAlternative medicine

Abstract

fetched live from OpenAlex

The aim of this cross-sectional study was to investigate attitudes of New Zealanders toward death and dying. We administered an online version of Collett–Lester Fear of Death Scale and Concerns about Dying Instrument subscales to a representative sample of the New Zealand population. One thousand one people responded to the survey, where the largest age-group lay between 30 and 39 years. Respondents with strong religious beliefs showed strongest agreement to being anxious about their own death compared to those who have no religious beliefs ( p = .0005). Conversely, participants with strong spiritual beliefs did not feel anxious about dying (=.0005). Participants with strong family connections believed their religion/spirituality helped them think about death compared to those with weak family connections ( p > .0001). Our findings show that strong religious beliefs significantly predict higher levels of death anxiety compared to participants with strong spiritual beliefs. This is probably due to the cultural identity of those sampled.

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)0.000
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 score0.039
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.032
GPT teacher head0.314
Teacher spread0.282 · 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

Citations79
Published2017
Admission routes1
Has abstractyes

Explore more

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