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Record W2973162978 · doi:10.1177/0891988719874119

Sources of Caregiving Burden in Middle-Aged and Older Latino Caregivers

2019· article· en· W2973162978 on OpenAlexaff
Guilherme Moraes Balbim, Melissa Magallanes, Isabela G. Marques, Karen Ciruelas, Susan Aguiñaga, Jacqueline Guzman

Bibliographic record

VenueJournal of Geriatric Psychiatry and Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDementiaCaregiver burdenGerontologyFamily caregiversDiseaseCaregiver stressPerceptionMedicinePrimary caregiverPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: We aimed to identify sources of caregiver burden in middle-aged and older Latino caregivers of people with Alzheimer disease and related dementia (ADRD). METHODS: Participants were recruited through an agreement with the Rush Alzheimer's Disease Center Clinic Data Repository. We conducted semistructured interviews with 16 middle-aged and older Latinos who were the primary caregiver for a family member diagnosed with ADRD. The interview guide consisted of questions and probes to capture participants' perceptions of family caregiving. Direct content analysis was performed. RESULTS: Participants were aged 50 to 75 years (n = 16) and a majority female (n = 12). The sources of burden identified were (1) caregiver responsibilities, (2) caregiving-related health decline, (3) lack of support, (4) financial status, (5) vigilance, and (6) concerns about the future. CONCLUSIONS: The influence of gender roles seemed to play a role in caregivers' perceptions of sources of burden, especially on caregiver responsibilities and perceptions of lack of support. Latinos cultural values such as familismo and marianismo likely reinforced gender disparities in family caregiving.

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 score0.005
Threshold uncertainty score0.308

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 studies0.0000.000
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 head0.008
GPT teacher head0.250
Teacher spread0.241 · 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

Citations39
Published2019
Admission routes1
Has abstractyes

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