Caregiver‐centered care health workforce competencies: Taking steps to support family caregivers of people living with dementia throughout the care trajectory
Bibliographic record
Abstract
Abstract Background Family caregivers [FCGs] are the backbone of the health system [1‐3]. They provide over 80% of the care for people with dementia, chronic illnesses and impairments [4 5]. Despite evidence of their contributions and consequences of caregiving, support for FCGs has not been a health system priority[6‐8]. Multi‐level interdisciplinary Alberta stakeholders recommended developing Caregiver‐Centered Care Education for the health workforce to fill this gap [9‐14]. Education to prepare health providers to effectively identify, engage, assess, and support FCGs throughout the care trajectory is an innovative approach in addressing inconsistent system of supports for FCGs [5 6 15‐17]. Objective: We report on development and validation of the Caregiver‐Centered Care Competency Framework to help with curricular design and subsequent evaluation of effectiveness of care providers working within healthcare settings to engage and support FCGs. Project description: We used a modified Delphi approach. In the first 2 rounds, multi‐level, interdisciplinary participants, rated the indicators in terms of importance and relevance. In the 3rd round consensus meeting, participants validated the final competency indicators in small group sessions. Participants: Expert panel of international, national, and provincial stakeholders were invited to a 2‐day symposium March 14‐15, 2019 and participate in the Modified Delphi Process. Results An expert panel of 42 international, national, and provincial stakeholders participated. Thirty‐four experts (81%) participated in the round 1, 36 (85.7%) in round 2, and 42 people (100%) in round 3. There was stable consensus across all three rounds, 96.07% of participants rated the indicators as essential or important (Round 1, 95.81%; Round 2, 94.15; Round 3, 98.23%). Six competency domains, including indicators, were validated. Discussion: FCG research has been primarily focused on educating FCGs to provide care [18‐20]. Our stakeholder engagement processes [9‐14] is critical to intervention research and practice that supports FCGs. The direct inclusion of multilevel stakeholders, particularly the FCGs, provided a robust forum for discussion and increased consensus around the value of a healthcare workforce trained to support FCGs. Conclusions These competencies will shape the design of educational curricula and interdisciplinary training programs aimed at supporting the health and social care workforce to provide caregiver‐centred care.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".