Food security: Who is being excluded? A case of older people with dementia in long-term care homes
Bibliographic record
Abstract
PURPOSE: To explore the extent of food security among older people, particularly those with cognitive impairments residing in Canadian long-term care homes (LTCHs) through a focused review of literature. METHOD: Databases including Medline, Nursing and Health Sciences (SAGE), Psych Info, Social Sciences Abstract, the Cumulative Index of Nursing and Allied Health Literature (CINAHL) and HealthSTAR were searched for peer-reviewed articles related to food experiences of older individuals in industrialized countries including Canada. Only articles that were published in English between 1997-2012 were included. RESULTS: Sixty two studies met the inclusion criteria. Of those 17 focused on older adults in LTCHs. The review found that food security has rarely been examined among older persons living in LTCHs, and has never been examined within the context of cognitive impairment. While a few studies have focused on residents' satisfaction with foods that are provided to them in LTCHs, none have explored the extent of food security in this population. Furthermore, food satisfaction surveys in the LTCH are limited to the assessment of foods that are served to residents, and do not capture residents' food accessibility beyond the food dispensing routines of the organization. Thus, food quality, food preferences, and the traditional meanings and rituals associated with food consumption are not purposefully evaluated. In addition, LTCHs are not required to monitor residents' food satisfaction using a consistent, regular, and standardized approach and there is no regulation in the LTCH Act that requires LTCHs to assess their residents' food security. CONCLUSIONS: The findings highlight the need for: 1) expansion of food security research to non-community-based settings including LTCHs; 2) re-conceptualization of food security and modification of measurement tools to assess the extent and determinants of food security among older adults in LTCHs; 3) mandatory monitoring of food security via standardized and regular surveys tailored to meet the unique preferences and needs of the older population, particularly those with dementia; and 4) education of healthcare professionals regarding food security and its assessment in LTCHs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".