MétaCan
Menu
Back to cohort
Record W2882987546 · doi:10.1177/1043659618790041

The Perceived Caregiver Burden Among Turkish Family Caregivers Providing Care for Frail Older Adults

2018· article· en· W2882987546 on OpenAlexaboutno aff
Zehra Gök Metin, Canan Karadaş, Cafer Balcı, Mustafa Cankurtaran

Bibliographic record

VenueJournal of Transcultural Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersHacettepe Üniversitesi
KeywordsTurkishCaregiver burdenFamily caregiversGerontologyMedicineDementiaPsychologyDisease

Abstract

fetched live from OpenAlex

PURPOSE: The older population has reached to 8.5%, and the prevalence of frailty is reported as 39.2% in Turkey. The purpose of the study was to assess caregiver burden in families who care for frail older adults in Turkish culture. METHOD: This descriptive study was conducted in Turkey between June and October 2017. Frail older adults who had no severe cognitive impairment were included. Data were measured using the Older Adult Information Form, Edmonton Frailty Scale, Caregiver Information Form, and Zarit Burden Interview. RESULTS: In total, 131 older person/caregiver dyads were analyzed; the Zarit Burden Interview mean score was 37.59 ± 18.20. Caregivers with less education and providing care more than 8 hours experienced a higher burden ( p < .05). The severity of frailty significantly correlated with the caregiver scores ( R = .36, p < .01). CONCLUSION: The caregiver burden in Turkish family caregivers was found mild to moderate and correlated with the degree of frailty. Policymakers should focus on culture-specific formal caregiver 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 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)0.001
metaresearch head score (Gemma)0.002
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.001
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 head0.275
Teacher spread0.263 · 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

Citations44
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Transcultural NursingSame topicFrailty in Older AdultsFrench-language works237,207