Supporting family carers of people living with dementia through online education: a case study from an Irish NGO
Bibliographic record
Abstract
The purpose of this research is to examine if and how an online education course offered by The Alzheimer Society of Ireland supports family carers of people living with dementia. \n \nThe incidence of dementia is rising in Ireland and around the world. Much of the care for people living with dementia is undertaken informally by close family members. Caring for someone living with dementia can be very demanding. Family carers of people living with dementia require training and support to prepare and sustain them for the complex and changing nature of their role. This thesis considers Home Based Care Home Based Education one such online course. It is the first such Irish study of an online course aimed at supporting family carers of people living with dementia. \n \nThis thesis uses a case study methodology with the online course being ‘the case’. With a convenience sampling strategy, it used multiple methods, first in the form of an anonymous online questionnaire, followed by 12 one-to-one interviews. Quantitative data was analysed using simple descriptive statistics. Qualitative data was examined using template analysis which is a form of ‘codebook’ thematic analysis. It is presented as a series of themes to answer the two research questions: (1) how does the course support dementia family carers, and (2) how can the course better support dementia family carers? \n \nEvidence suggests that the online course supports participants in a number of ways. Learners gained new knowledge and a range of practical skills through interactions with tutors, peers and course materials. However, participants offered suggestions on how to make the course more supportive to participants. Findings are presented which will be of assistance to The Alzheimer Society of Ireland as they continue to deliver online training for family carers of people living with dementia into the future.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".