MétaCan
Menu
Back to cohort
Record W4386590310 · doi:10.1521/bumc.2023.87.3.266

Understanding loneliness: The roles of self- and interpersonal dysfunction and early parental indifference

2023· article· en· W4386590310 on OpenAlexaff
Laura Labonté, David Kealy

Bibliographic record

VenueBulletin of the Menninger Clinic · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLonelinessPsychologyPersonalityBig Five personality traitsPsychosocialMediationDevelopmental psychologyInterpersonal communicationInterpersonal relationshipClinical psychologyPsychological interventionPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Many factors are implicated in developing and maintaining loneliness, including aspects of personality functioning and experience of early adverse childhood events. This study aimed to examine the relationship between domains of personality dysfunction, including self- and interpersonal functioning, and loneliness and determine whether such personality factors mediate the relationship between childhood parental indifference and loneliness. In total, 393 community-dwelling adults, mean age 34.3 (SD = 12.67), were recruited online for cross-sectional assessment of loneliness, personality functioning, big-five personality traits and perceived childhood parental indifference. Linear regression analyses were conducted followed by a parallel mediation model. Self- and interpersonal dysfunction were positively associated with loneliness and remained significant predictors of loneliness after controlling for five-factor personality traits. Impaired personality functioning accounted for 12% of loneliness variance. Finally, self-dysfunction mediated the relationship between childhood parental indifference and loneliness. Findings emphasize the importance of addressing personality functioning when developing psychosocial interventions aimed at tackling loneliness.

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 score0.016
Threshold uncertainty score0.284

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 studies0.0000.000
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 head0.097
GPT teacher head0.332
Teacher spread0.235 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBulletin of the Menninger ClinicSame topicHealth disparities and outcomesFrench-language works237,207