Engaging older adults in self-management talk in healthcare encounters: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Clinical practice guidelines for the management of complex chronic conditions in older adults encourage healthcare providers to engage patients in shared decision-making about self-management goals and actions. Yet, healthcare decision-making and communication for this population can pose significant challenges. As a result, healthcare professionals may struggle to help patients define and prioritise their values, goals, and preferences in ways that are clinically and personally meaningful, incorporating physical functioning and quality of life, when faced with numerous diagnostic and treatment alternatives. The aim of this systematic review is to locate and synthesise a body of fine-grained observational research on communication between professionals, older adults, and carers regarding self-management in audio/audio-visually recorded naturalistic interactions. METHODS/DESIGN: The paper describes a systematic review of the published conversation analytic and discourse analytic research, using an aggregative thematic approach and following the PRISMA-P guidelines. This review will include studies reporting on adult patients (female or male) aged ≥ 60 years whose consultations are conducted in English in any healthcare setting and stakeholders involved in their care, e.g. general practitioners, nurses, allied health professionals, and family carers. We will search nine electronic databases and the grey literature and two independent reviewers will screen titles and abstracts to identify potential studies. Discrepancies will be resolved via consultation with the review team. The methodological quality of the final set of included studies will be appraised using the Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research and a detailed description of the characteristics of the included studies using a customised template. DISCUSSION: This is the first systematic review to date to locate and synthesise the conversation analytic research on how healthcare professionals raise and pursue talk about self-management with older adults in routine clinical interactions. Amalgamating these findings will enable the identification of effective and potentially trainable communication practices for engaging older adults in healthcare decision-making about the self-management goals and actions that enable the greatest possible health and quality of life in older adulthood. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42019139376.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".