My Wellbeing Journal: Development of a communication and goal‐setting tool to improve care for older adults with chronic conditions and multimorbidity
Bibliographic record
Abstract
BACKGROUND: Chronic conditions and multimorbidity, the presence of two or more chronic conditions, are increasingly common in older adults. Effective management of chronic conditions and multimorbidity in older adults requires a collaborative and person-centred approach that considers the individual's goals, preferences and priorities. However, ensuring high-quality personalised care for older adults with multimorbidity can be challenging due to the complexity of their care needs, limited time and a lack of patient preparation to discuss their personal goals and preferences with their healthcare team. OBJECTIVE: To codesign a communication and goal-setting tool, My Wellbeing Journal, to support personalised care planning for older adults with chronic conditions and multimorbidity. DESIGN: We drew on an experience-based codesign approach to develop My Wellbeing Journal. This article reports on the final end-user feedback, which was collected via an online survey with older adults and their carers. SETTING AND PARTICIPANTS: Older adults with chronic conditions, multimorbidity and informal carers living in Australia. Personalised care planning was considered in the context of primary care. RESULTS: A total of 88 participants completed the online survey. The survey focused on participants' feedback on the tool in terms of effectiveness, efficiency, satisfaction and errors encountered. This feedback resulted in modifications to My Wellbeing Journal, which can be used during clinical encounters to facilitate communication, goal setting and progress tracking. DISCUSSION AND CONCLUSIONS: Clinicians and carers can use the tool to guide discussions with older adults about their care planning and help them set realistic goals that are meaningful to them. The findings of this study could be used to inform the development of recommendations for healthcare providers to implement person-centred, goal-oriented care for older adults with chronic conditions and multimorbidity. PATIENT OR PUBLIC CONTRIBUTION: Older adults living with chronic conditions and multimorbidity and their carers have contributed to the development of a tool that has the potential to significantly enhance the experience of personalised care planning. Their direct involvement as collaborators has ensured that the tool is optimised to meet the standards of effectiveness and usability.
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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 | 0.025 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".