MétaCan
Menu
Back to cohort
Record W2127340106 · doi:10.1177/1471301215583148

Dementia informal caregiver obtaining and engaging in food-related information and support services

2015· article· en· W2127340106 on OpenAlexfundno aff
Iliatha Papachristou, Gary Hickey, Steve Iliffe

Bibliographic record

VenueDementia · 2015
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersUniversity of SurreyAlzheimer Society
KeywordsDementiaPsychologyGerontologyNursingMedicineDisease

Abstract

fetched live from OpenAlex

As dementia progresses, caregivers increasingly have to manage the decline of food-related abilities with little outside information or input from support services The provision of food coping skills and knowledge can lessen the burden on caregivers. However, there is little research on caregivers' perspectives on food-related services. This paper reports on a qualitative study to investigate informal caregivers' experiences of, and views on, food-related information and support services in dementia. Twenty informal caregivers were interviewed and the transcripts from these interviews were analysed using both deductive and inductive thematic analysis. Four categories emerged. 'Direct food-related Information', covers written material, training, 'Direct food-related informal support': lunch clubs, 'Indirect non-food related formal support services' covers respite services and domestic help at home. Finally 'no services required' covers those who did not feel they needed any form of intervention due to confidence in managing food-related processes or having no change in dementia progression and food responsibility. Most caregivers will need different levels of information and support at different stages of dementia. It is necessary therefore to undertake ongoing individual assessment of food information and support needs.

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)0.001
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 score0.036
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueDementiaSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207