MétaCan
Menu
Back to cohort
Record W3175075345 · doi:10.22605/rrh6497

Psychosocial predictors of adverse outcomes in rural heart failure caregivers

2021· article· en· W3175075345 on OpenAlexaboutno aff
Joan S. Grant, Lucinda J. Graven, Glenna Schluck, Laurie Abbott

Bibliographic record

VenueRural and Remote Health · 2021
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialHeart failureMedicineAdverse effectGerontologyPsychologyNursingPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Depressive symptoms, negative life changes, poor self-care, and higher caregiver burden are common in caregivers who assist individuals with heart failure (HF) in managing daily activities and disease-related symptoms. Previous research findings suggest social support, problem solving, and family function may influence these outcomes. However, the influence of these factors on outcomes in rural HF caregivers is unknown. The purpose of this study is twofold: (1) to examine whether social support, problem solving, and family function predicted depressive symptoms, caregiving-related life changes, self-care, and caregiver burden in rural HF caregivers; and (2) to compare differences in these variables between rural and urban caregivers. METHODS: Rural caregivers (n=114) completed an online researcher-developed sociodemographic and clinical survey and standardized (Likert-type) self-report instruments. Participants were recruited locally from south-eastern USA (using face-to-face and telephone contacts, posted flyers, newspaper advertisements, and social media), nationally (newspaper advertisements and social media sites) and internationally (using social media). Potential participants were directed to the study website to complete the online surveys. These methods recruited participants who lived in 24 states within the USA, as well as from Canada, England, Ireland, Scotland, and Wales. Demographic statistics and Mann-Whitney U-test, as well as bivariate correlations, multivariate linear modelling, and Roy's largest root, were used to analyse data, controlling for covariates. RESULTS: Rural (n=114) caregivers were primarily Caucasian (84.2%), women (58.8%), and 41.45 (&plusmn;9.013) years old. Social support had significant effects on depressive symptoms (&eta;p2=0.384, p<0.001), self-care (&eta;p2=0.108, p=0.001), and life changes (&eta;p2=0.055, p=0.016), while problem solving showed significant effects on depressive symptoms (&eta;p2= 0.078, p=0.004) and caregiver burden (&eta;p2=0.23, p<0.001). Family function had significant effects on life changes (&eta;p2=0.104, p=0.001), self-care (&eta;p2=0.088, p=0.002), and caregiver burden (&eta;p2=0.116, p<0.001). Compared to urban (n=412) participants, rural caregivers experienced significantly less social support (p=0.001), worse problem-solving skills (p=0.003) and family functioning (p=0.009), and greater depressive symptoms (p&le;0.01) and subjective burden (p=0.001). There were no significant differences in caregiver self-care (p=0.416) and perceived life changes (p=0.346) among rural and urban caregivers. CONCLUSION: Both social support and problem solving have significant effects on depressive symptoms in rural HF caregivers, while social support and family function influences self-care. Problem solving and family function also affect caregiver burden, while social support and family functioning influences caregiver life changes. Rural caregivers are often separated by long distances, and have transportation issues and limited access to healthcare providers and support services; therefore, innovative strategies are needed to explore the usefulness of these variables in improving caregiver outcomes.

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 score0.093
Threshold uncertainty score0.373

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 head0.010
GPT teacher head0.285
Teacher spread0.275 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRural and Remote HealthSame topicHeart Failure Treatment and ManagementFrench-language works237,207