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Record W4400221825 · doi:10.59249/okab8606

Examining the Impact of Social Support on Psychological Well-BeingAmong Canadian Individuals With COPD: Implications for GovernmentPolicies

2024· article· en· W4400221825 on OpenAlexaffabout
Rosina E. Mete

Bibliographic record

VenueThe Yale Journal of Biology and Medicine · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsYorkville University
Fundersnot available
KeywordsCOPDAnxietyMental healthSocial supportPopulationGovernment (linguistics)PsychologyAllianceDepression (economics)Scale (ratio)Clinical psychologyMedicinePsychiatryGerontologySocial psychologyEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

Chronic obstructive pulmonary disease (COPD) is a significant respiratory disease and is globally ranked as the third leading cause of death. In Canada, the direct healthcare costs associated with COPD are estimated to be $1.5 billion annually. This study utilized quantitative analyses to examine the impact of specific dimensions of social support, namely, guidance, reliable alliance, reassurance of worth, attachment, and social integration within a clinically identified population of individuals with COPD who exhibit symptoms of depression and anxiety. The study was based on the Social Provisions Theory and stress-buffering hypothesis, utilizing large-scale population data from Statistics Canada's 2012 Canadian Community Health Survey (CCHS) Mental Health component. On a national scale, individuals were more likely to report a decreased sense of belonging to a group of friends (social integration) and struggle to depend on others in stressful times (reliable alliance) while experiencing symptoms of anxiety and depression. These findings underscore the potential benefits of integrating peer support, socialization initiatives, and caregiver training into clinical programs designed for individuals with COPD.

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)0.006
metaresearch head score (Gemma)0.020
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.454

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0090.002
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.067
GPT teacher head0.439
Teacher spread0.372 · 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

Citations7
Published2024
Admission routes2
Has abstractyes

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Same venueThe Yale Journal of Biology and MedicineSame topicHealth disparities and outcomesFrench-language works237,207