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Record W3088757921 · doi:10.1017/s0144686x20001294

Perceived stigma towards Alzheimer's disease and related dementia among Chinese older adults: do social networks matter?

2020· article· en· W3088757921 on OpenAlexaboutno aff
Xiang Gao, Fei Sun, Lucas Prieto, V. Iyengar

Bibliographic record

VenueAgeing and Society · 2020
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
Fundersnot available
KeywordsStigma (botany)DementiaGerontologyMainland ChinaPsychologyPopulationPsychological interventionMedicineDiseaseClinical psychologyPsychiatryChinaEnvironmental health

Abstract

fetched live from OpenAlex

Abstract In mainland China, as the population ages, Alzheimer's disease and related dementia (ADRD) is estimated to increase among Chinese older adults. Chinese older adults tend to hold stigmatising beliefs about ADRD that in turn affect their help-seeking behaviour and receipt of prevention and treatment. The Framework Integrating Normative Influences on Stigma provides a rationale for Chinese older adult's stigma about ADRD. Questionnaires were administered in person to 754 older adults (42% male, mean age = 69.54 years) from two urban communities in mainland China. We examined ADRD stigma and the associations with real-life exposure, knowledge of ADRD, health conditions and social networks. This study found that Chinese older adults who had good family quality, lower depression (as measured by the Center for Epidemiological Studies Depression Scale) and better cognitive health (as measured by the Montreal Cognitive Assessment) were more likely to have lower perceived stigma. Conversely, those individuals who experienced neglect and had more ADRD knowledge exhibited higher levels of perceived stigma. Social networks moderated the associations between cognitive scores and perceived stigma. This research suggested that the quality of one's social networks is essential to reduce perceived stigma among Chinese older adults. Future research should continue to explore ADRD stigma among Chinese older adults to help guide relevant interventions, services and supports for this population.

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)0.000
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 score0.133
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.013
GPT teacher head0.296
Teacher spread0.283 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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