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Record W7019876114

Health Care Provider Perspectives during COVID-19 on Nutrition at End-of-Life in Long-Term Care

2023· dissertation· en· W7019876114 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2023
Typedissertation
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionFeelingDescriptive statisticsAdvance care planningHealth careConversationNursing homes
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Older adults are admitted to long-term care (LTC) homes with advanced disease progression, complexity and acuity. There is a need for starting end-of-life (EOL) conversations earlier. Poor communication surrounding anticipated decline may result in unwanted interventions for residents and leave substitute decision makers (SDMs) feeling unsupported during the dying process. COVID-19 increases the need for earlier conversations. Objectives: (1) Examine current end-of-life nutrition related practices/standardized conversations in Canadian LTC homes with health care providers (HCPs) (2) Determine the acceptability of current EOL practices and timing of these practices in LTC homes among staff in Canada (3) Examine starting points for initiating informal EOL discussions between residents, substitute decision makers, and HCPs in LTC (4) Determine the impact of COVID-19 on EOL discussions. Methods: An online survey was sent to LTC HCPs across Canada from April 21 to July 30, 2021. Participant demographics, facility characteristics, information on current EOL policy and practice, and changes during COVID-19 was collected. Seventy completed surveys were analyzed using descriptive statistics (100% Female; 40.8 years ±11.54), Chi-Square and Fisher’s Exact Tests. Results: Participants included registered dietitians (82.6%), nurses (10.1%), administrators (2.9%), speech language pathologists, social workers, and occupational therapists (4.2%). Most represented provinces included British Columbia (31.4%), New Brunswick (22.9%), and Manitoba (20.0%). Seventy-Two percent of respondents indicated their LTC home had no policy outlining who is responsible for initiating EOL conversations or when EOL conversations should occur (73.6%). HCPs ranked their preferred times to initiate EOL conversations as on admission, as requested by the SDM, or as identified by the HCP. Respondents indicated they were comfortable/confident with nutrition at EOL conversations with residents (77.4%) and SDMs (87.1%). A total of 19 variables were examined as contributing to HCP comfort/confidence. None were statistically significant (alpha 0.05). HCPs found nutrition at EOL conversations more stressful during COVID 19. Conclusion: HCPs indicate they are comfortable/confident with nutrition at EOL conversations. However, HCPs feel timing of informal EOL conversations could start as early as on admission. During COVID-19, HCPs had feelings of increased stress with EOL discussions. This stress may be due to the government restrictions that were implemented resulting in understaffing, and increased workloads.

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)0.006
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.790

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.322
Teacher spread0.288 · 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
Published2023
Admission routes1
Has abstractyes

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