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Record W3193705466 · doi:10.1097/nmd.0000000000001407

Conditional Process Modeling of the Relationship Among Self-Reliance, Loneliness, and Depressive Symptoms, and the Moderating Effect of Feeling Understood

2021· article· en· W3193705466 on OpenAlexaffabout
John S. Ogrodniczuk, John L. Oliffe, David Kealy, Zac E. Seidler, Nick Black, Simon Rice

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLonelinessFeelingPsychologyAssociation (psychology)Moderated mediationMediationSocializationDepressive symptomsClinical psychologyDepression (economics)ModerationDevelopmental psychologySocial psychologyPsychotherapistCognitionPsychiatry

Abstract

fetched live from OpenAlex

ABSTRACT: Self-reliance features as one of the notable male norms espoused by traditional masculine socialization. Strict adherence to a self-reliant attitude has been found to confer risk for depression and suicidality among men. Yet, little research has investigated the factors that may contribute to self-reliance having a negative impact for men. Using data from a large sample of Canadian men (N = 530), the present study examined the association between self-reliance and depression, while also assessing the roles of loneliness and not feeling understood as contributing factors in this process. Findings indicated that the moderated mediation model was significant, pointing to loneliness as a significant mediator in the association between self-reliance and depression. Furthermore, the findings revealed that not feeling understood moderated the relationship between self-reliance and loneliness, indicating that this association applies mainly to those men who do not feel understood by at least one important person in their life.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.014
GPT teacher head0.293
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2021
Admission routes2
Has abstractyes

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