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Record W2405749296 · doi:10.1186/s12955-016-0486-7

Factors influencing changes in health related quality of life of caregivers of persons with multiple chronic conditions

2016· article· en· W2405749296 on OpenAlexafffundabout
Wendy Duggleby, Allison Williams, Sunita Ghosh, Heather Moquin, Jenny Ploeg, Maureen Markle‐Reid, Shelley Peacock

Bibliographic record

VenueHealth and Quality of Life Outcomes · 2016
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsAlberta Health ServicesMcMaster UniversityUniversity of SaskatchewanUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsQuality of life (healthcare)Psychological interventionMental healthFamily caregiversGerontologyPopulationMedicinePsychologyCaregiver burdenTelephone interviewClinical psychologyPsychiatryEnvironmental healthDiseaseNursing

Abstract

fetched live from OpenAlex

BACKGROUND: The majority of care for older adults with multiple chronic conditions (MCC) is provided by family (including friends) caregivers. Although caregivers have reported positive benefits to caregiving they also experience decreases in their physical and mental health. As there is a critical need for supportive interventions for this population, it is important to know what influences the health of family caregivers of persons with MCC. This research examined relationships among the changes from baseline to 6 months in health related quality of life (SF12v2) of family caregivers caring for older adults with multiple chronic conditions and the following factors: a) demographic variables, b) gender identity [Bem Sex Role Inventory (BSRI)] c) changes in general self-efficacy [General Self Efficacy Scale (GSES) (baseline to 6 months) and d)) changes in caregiver burden [Zarit Burden Inventory (ZBI)] baseline to 6 months. Specific hypothesis were based on a conceptual framework generated from a literature review. METHODS: This is a secondary analysis of a study of 194 family caregivers who were recruited from two Canadian provinces Alberta and Ontario. Data were collected in-person, by telephone, by Skype or by mail at two time periods spaced 6 months apart. The sample size for this secondary analysis was n = 185, as 9 participants had dropped out of the study at 6 months. Changes in the scores between the two time periods were calculated for SF12v2 physical component score (PCS) and mental component score (MCS) and the other main variables. Generalized Linear Modeling was then used to determine factors associated with changes in HRQL. RESULTS: Participants who had significantly positive increases in their MCS (baseline to 6 months) reported lower burden (ZBI, p < 0.001), and higher general self-efficacy (GSES, p < 0.001) and Masculine BSRI (p = 0.025). There were no significant associations among variables and changes in PCS (baseline to 6 months). CONCLUSIONS: Our findings suggest that a masculine gender identity (which incorporates assertive and instrumental approaches to caregiving), and confidence in the ability to deal with difficult situations was positively related to improvement in mental health for caregivers of persons with MCC. Decreases in perceptions of burden in this populations was also associated with improvements in mental health. Further research is needed to explore ways to support caregivers of older persons with multiple chronic conditions living at home.

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)0.006
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 score0.101
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.149
GPT teacher head0.401
Teacher spread0.252 · 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

Citations85
Published2016
Admission routes3
Has abstractyes

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