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Record W4390192654 · doi:10.1002/alz.071454

Exploring Social Engagement in a Virtual Participatory Culinary Nutrition Education Intervention for Dementia Prevention

2023· article· en· W4390192654 on OpenAlexaff
JulieAnne E Beitel, Megan E. O’Connell, Jessica Lieffers, Karen Lawson, Allison Cammer

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFacilitatorThematic analysisPsychologyPsychological interventionFocus groupApplied psychologyMedical educationDementiaQualitative researchSocial psychologyMedicineSociology

Abstract

fetched live from OpenAlex

Abstract Background Providing nutrition education through participatory cooking programs is a strategy to support adoption of healthy eating practices for dementia risk reduction. Social engagement, a modifiable risk factor for dementia, is an important feature of in‐person culinary interventions; few recommendations exist for virtual delivery. We aimed to examine participant social engagement within ‘The Cognitive Kitchen: Virtual Culinary Intervention for Dementia Prevention’. Method A six‐week virtual nutrition education and applied cooking class was delivered to two groups of 10 older adult participants. Two Registered Dietitians led discussions and cooking demonstrations focused on dementia risk reduction. Participants were invited to cook during sessions or prepare the recipes at their convenience. The study was guided by Interpretive Description methodology. Data included facilitator session notes, participant weekly virtual journal entries, two virtual focus group discussions, and individual interviews with 15 participants. The Positive emotion, Engagement, Relationships, Meaning, and Accomplishments (PERMA) model of well‐being helped structure thematic analysis examining participants’ experiences in the program and the function of social interaction. Result Participants appreciated the flexibility of the virtual setting and very few technical issues were observed. Thematic analysis revealed commonalities among participants’ experiences, including enjoyment of learning about creative ingredient transformation, enhanced accountability for meal preparation, and an appreciation for cooking as a social activity. Many participants recorded notes about meal preparation practices shared by other group members, and some participated in virtual recipe‐sharing, suggesting peer learning was a valuable component. Though the virtual program could not include casual social contact that would normally occur in an in‐person program, participants appreciated discussion questions to encourage social interaction. However, some found that cooking along with the demonstration limited their ability to learn and socialize. Conclusion Benefits to virtual delivery of a participatory cooking program include ability to expand program reach and reduced barriers to participation (e.g., travel, inclement weather, time). These considerations may be even more relevant for older adult care partners of persons with dementia. However, some elements of in‐person participation that foster social engagement are challenging to replicate virtually; additional effort by facilitators is required to ensure this important program component is maintained.

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)0.005
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.346
GPT teacher head0.437
Teacher spread0.090 · 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 designNon-randomized trial
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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