<p>Community Health Care Workers’ Experiences on Enacting Policy on Technology with Citizens with Mild Cognitive Impairment and Dementia</p>
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Bibliographic record
Abstract
PURPOSE: Assistive technologies and digitalization of services are promoted through health policy as key means to manage community care obligations efficiently, and to enable older community care recipients with mild cognitive impairment (MCI) and dementia (D) to remain at home for longer. The overall aim of this paper is to explore how community health care workers enacted current policy on technology with home-dwelling citizens with MCI/D. PARTICIPANTS AND METHODS: Twenty-four community health care workers participated in one of five focus group discussions that explored their experiences and current practices with technologies for citizens with MCI/D. Five researchers took part in the focus groups, while six researchers collaboratively conducted an inductive, thematic analysis according to Braun & Clarke. RESULTS: Two main themes with sub-themes were identified: 1) Current and future potentials of technology; i) frequently used technology, ii) cost-effectiveness and iii) "be there" for social contact and 2) Barriers to implement technologies; i) unsystematic approaches and contested responsibility, ii) knowledge and training and iii) technology in relation to user-friendliness and citizen capacities. CONCLUSION: This study revealed the complexity of implementing policy aims regarding technology provision for citizens with MCI/D. By use of Lipsky's theory on street-level bureaucracy, we shed light on how community health care workers were situated between policies and the everyday lives of citizens with MCI/D, and how their perceived lack of knowledge and practical experiences influenced their exercise of professional discretion in enacting policy on technology in community health care services. Overall, addressing systematic technology approaches was not part of routine care, which may contribute to inequities in provision of technologies to enhance occupational possibilities and meaningful activities in everyday lives of citizens with MCI/D. TRIAL REGISTRATION: NSD project number 47996.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| 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 it