Exploration of Multidimensional Needs in a Dementia Colombian Population: Preliminary Qualitative Results
Bibliographic record
Abstract
Abstract Background World population is ageing, and as a result, dementias are becoming one of the major challenges for societies. Dementia involves patients, caregivers, professionals and the health system; for this reason, in Colombia, we need inplemented a diffent health policy models with a social justice approach. To contribute as input to a national strategy on dementia, our first step is multidimensional needs information gathering. To evaluate the perceived needs of a group of Colombian patients with dementia and their caregivers under a Social Justice framework using the Needs Assessment Methodology. Method We designed an information‐gathering program consisting of the first phase of a semi‐structured interview and the second phase of focal groups. We will triangulate both results using mixed methods. Nevertheless, this abstract only addresses the first phase. Due to social distancing, we designed a computerized interview using google forms that could be self‐answered through the internet or assisted through telephone. We obtained a telephonic approved informed consent before we enrolled any participant. In this interview, we evaluated the seven aspects of the need assessment methodology regarding the caregiving of dementia or the experience of suffering dementia. Result We conducted the interviews between September 2021 to December 2021. We included a total of 68 caregivers and fifteen dementia patients. Most caregivers were women, with ages between 27 to 72 years. Two‐thirds were familiar unpaid caregivers. We found that caregivers identified a lack of adequate resources provided by the health system. However, the burden of caregiving appears to be low in our context, and the results suggest that informal agreements within the families allow to distribute of the responsibilities. Conclusion caregivers in Colombia appear to present high resiliency and be assumed as an extended family responsibility even under the perception of neglected provision of resources by the health system.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".