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Record W2947967782

The aching backbone: perceptions and experiences of care aides in long term residential care

2018· dissertation· en· W2947967782 on OpenAlexaboutno aff
Laura Booi

Bibliographic record

VenueSummit (Simon Fraser University) · 2018
Typedissertation
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)Long-term carePerceptionNursingPsychologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Purpose: Care aides provide most of the direct care for residents in long-term residential care (LTRC), and thus hold the greatest potential to improve residents' quality of life.Twothirds of residents in these facilities are older adults with dementia.The number of care aides working in LTRC needed to support Canada's aging population is only expected to increase with time.Like residents in LTRC, care aides are a disenfranchised population.There is little understanding of what are the experiences and perceptions of care aides in LTRC.This doctoral thesis adds to the scarce body of knowledge that sheds light on the experience of care aides in LTRC.This study was informed by the literature on personcentered care and personhood theory, as well as critical gerontology and institutional theory.The purpose of this study was to understand the experiences and perceptions held by care aides in LTRC and to identify their perceived barriers and facilitators toward the delivery of care to residents. Method:The overall methodology for this study was a qualitative design, using ethnographic data-generating methods from one complex-care floor located within a campus of care facility in rural and remote Western Canada.Data sources for this study included the following: semi-structured interviews (70 hours) with 31 care aides, naturalistic observation (170 hours), and reflexive journaling (20,000 words).Thematic analysis was used to examine all data sources.Results: Care aides' experiences entering and working in LTRC are varied; however, there are common overarching themes, including not being adequately trained for the realities of working as care providers and the scope of practice they are expected to fulfill within LTRC, as well as being under supported in their role.Participants report strong feelings of responsibility and affection for their residents, yet they perceive insurmountable barriers in their role that prevent them from delivering the care they would like to give.These barriers include the following: (i) lack of standardized education and training; (ii) lack of proper equipment; (iii) lack of autonomy over their residents; (iv) politics and bullying within the power hierarchy of LTRC; and (v) chronic unaddressed moral distress among care aides.Suggestions for improvement of care delivery in LTRC include the following: (i) standardization of care aide education and training; (ii) incorporation of reporting measures specifically for care aides; and (iii) increased autonomy of care aides over their residents.Implications: The support and empowerment of care aides in LTRC are fundamental in the delivery of good care to residents.Care aides have expressed that their attitudes toward their job are low because they feel unheard and voiceless within their work environment.Efforts to empower care aides' voices should be developed and implemented to meet the needs of a large segment of Canada's population living with dementia-residents in LTRC.Keywords: care aides,

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.008
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.314
Teacher spread0.301 · 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 designQualitative
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

Citations0
Published2018
Admission routes1
Has abstractyes

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