A Biopsychosocial-Ecological Framework for Family-Framed Dementia Care
Bibliographic record
Abstract
The biopsychosocial model has been applied through collaborative care dementia models to the diagnosis, symptom management, and treatment of dementia with a focus specifically on the person with dementia. Because individuals with dementia are increasingly dependent upon others particularly as the illness advances, dementia care requires the involvement and commitment of others, usually family, along with support from community-based resources. Hence, the quality and effectiveness of a person's dementia care are shaped in large part by the foundation of family relationships and the social and community networks in which they are embedded. While most current dementia care models incorporate biopsychosocial principles and recognize the essential role that family members play as caregivers, they fail to consider a patient's family system and relationships as potential risk factors or social determinants for care outcomes. This paper introduces a biopsychosocial-ecological framework to dementia care that is person-centered and "family-framed" in that it targets factors that influence care considerations at both the individual and relational levels of the social ecological networks that the patient and their family members occupy. We use this model to illustrate how current dementia care practices tend to focus exclusively on the individual patient and caregiver levels but fail to identify and address important relational considerations that cut across levels. We call for the need to add assessment of family relational histories of persons with dementia and family members who care for them in order to better meet the needs of the patient and the caregiver and to prevent harm. This model accentuates the need for interprofessional education on family assessments and caregiver-centered care, as well as interdisciplinary, collaborative models of dementia care that assume more accountability for meeting the needs of family caregivers in addition to those of persons with dementia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".