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Record W4223481439 · doi:10.1080/07317115.2022.2058440

Perceived Need, Mental Health Literacy, Neuroticism and Self- Stigma Predict Mental Health Service Use Among Older Adults

2022· article· en· W4223481439 on OpenAlexafffundabout
Corey S. Mackenzie, Lily Pankratz

Bibliographic record

VenueClinical Gerontologist · 2022
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of Manitoba
FundersMovember Canada
KeywordsMental healthMental health literacyHelp-seekingNeuroticismPsychological interventionMarital statusPsychologyClinical psychologyStigma (botany)PsychiatryHealth literacySocial supportGerontologyMedicineMental illnessPopulationPersonalityHealth careSocial psychologyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: Older adults are the least likely age group to seek mental health services. However, few studies have explored a comprehensive range of sociodemographic, psychological, and social barriers and facilitators to seeking treatment in later life. METHODS: A cross-sectional, national sample of Canadian older adults (55+, N = 2,745) completed an online survey including reliable and valid measures of predisposing, enabling, and need characteristics, based on Andersen's behavioral model of health, as well as self-reported use of mental health services. Univariate and hierarchical logistic regressions predicted past 5-year mental health service use. RESULTS: Mental health service use was most strongly and consistently associated with greater perceived need (OR = 11.48) and mental health literacy (OR = 2.16). Less self-stigma of seeking help (OR = .65) and greater neuroticism (OR = 1.57) also predicted help-seeking in our final model, although their effects were not as strong or consistent across gender, marital status, and age subgroups. CONCLUSIONS: The need category was crucial to seeking help, but predisposing psychological factors were also significant barriers to treatment. CLINICAL IMPLICATIONS: Interventions that target older adults high in neuroticism by improving perceptions of need for treatment, mental health literacy, and self-stigma of seeking help may be particularly effective ways of improving access to mental health services.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.424
Teacher spread0.353 · 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.

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

Citations24
Published2022
Admission routes3
Has abstractyes

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