Impact and Perceived Value of iGeriCare e-Learning Among Dementia Care Partners and Others: Pilot Evaluation Using the IAM4all Questionnaire
Bibliographic record
Abstract
BACKGROUND: Care partners of people living with dementia may benefit from web-based education. We developed iGeriCare, an award-winning internet-based platform with 12 multimedia e-learning lessons about dementia. OBJECTIVE: Our objective was to evaluate users' perceptions of impact. METHODS: From March 17, 2021 to May 16, 2022, data were collected upon lesson completion. We used the content-validated Information Assessment Method for all (IAM4all) for patients and the public adapted for dementia care partners. The IAM4all questionnaire assesses outcomes of web-based consumer health information. Responses were collected using SurveyMonkey, and data were analyzed using IBM SPSS Statistics (version 28). RESULTS: A total of 409 responses were collected, with 389 (95.1%) survey respondents completing the survey. Of 409 respondents, 179 (43.8%) identified as a family or friend care partner, 84 (20.5%) identified as an individual concerned they may have mild cognitive impairment or dementia, 380 (92.9%) identified the lesson as relevant or very relevant, and 403 (98.5%) understood the lesson well or very well. Over half of respondents felt they were motivated to learn more, they were taught something new, or they felt validated in what they do, while some felt reassured or felt that the lesson refreshed their memory. Of 409 respondents, 401 (98%) said they would use the information, in particular, to better understand something, discuss the information with someone else, do things differently, or do something. CONCLUSIONS: Users identified iGeriCare as relevant and beneficial and said that they would use the information. To our knowledge, this is the first time the IAM4all questionnaire has been used to assess patient and caregiver feedback on internet-based dementia education resources. A randomized controlled trial to study feasibility and impact on caregiver knowledge, self-efficacy, and burden is in progress.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".