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Record W4293513684 · doi:10.1080/13557858.2022.2115018

The influence of Latino cultural values on the perceived caregiver role of family members with Alzheimer’s disease and related dementias

2022· article· en· W4293513684 on OpenAlexaff
Michelle Jaldin, Guilherme Moraes Balbim, Stephanie J. Colin, Isabela G. Marques, Jasmine Mejia, Melissa Magallanes, Judith S. Rocha, David X. Márquez

Bibliographic record

VenueEthnicity and Health · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of British Columbia
FundersUniversity of Illinois at Chicago
KeywordsDiseasePsychologyAlzheimer's diseaseDementiaGerontologyDevelopmental psychologyClinical psychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Objectives We explored how Latino cultural values play a role in perceived caregiving experiences.Design We conducted a qualitative study that used individual, in-depth, semi-structured interviews with middle-aged and older Latinos who were primary caregivers of family members with Alzheimer’s disease and related dementias (ADRD). The interview guide consisted of questions about participants’ perceptions of family caregiving and interrelationships between the caregiver and care recipient. The interviews were recorded, translated, and transcribed verbatim. We performed direct content analysis.Results Participants were caregivers, 50–75 years old (n = 16), and the majority were female. We identified four cultural values that were salient to participants’ caregiving experiences: (a) familismo, (b) fatalismo (c) marianismo, and (d) machismo.Conclusion Latino cultural values influenced the role of caregiving and caregiving roles of family members with ADRD. Future research should consider these values as they affect different familial and health dynamics.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.005
Scholarly communication0.0020.001
Open science0.0000.002
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 head0.083
GPT teacher head0.383
Teacher spread0.300 · 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

Citations29
Published2022
Admission routes1
Has abstractyes

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