A Real-Life Laboratory Setting for Clinical Practice, Education, and Research in Family Systems Care: Protocol for a Transformational Action Research Study
Bibliographic record
Abstract
BACKGROUND: Burdening health and illness issues such as physical or mental illnesses, accidents, disabilities, and life events such as birth or death influence the health and functioning of families and contribute to the complexity of care and health care costs. Considerable research has confirmed the benefits of a family systems-centered care approach for patients, family caregivers, families, and health care professionals. However, health care professionals face barriers in working with families, such as feeling unprepared. Family systems-centered therapeutic conversations support families' day-to-day coping, resilience, and health. A family systems care unit (FSCU) was recently established as a real-life laboratory at one of the Swiss Universities of Applied Sciences. In this unit, health care professionals offer therapeutic conversations to families and individual family members to support daily symptom management and functioning, soften suffering, and increase health and well-being. These conversations are observed in real time through a 1-way window by other health care professionals, students, and trainees and are recorded with video for research and education. Little is known about how therapeutic conversations contribute to meaningful changes in burdened families and the benefits of vicarious learning in a real-life laboratory setting for family systems care. OBJECTIVE: In this research program, we aim to deepen our understanding of how therapeutic conversations support families and individuals experiencing burdening health and illness issues and how the FSCU laboratory setting supports the learning of students, clinical trainees, and health care professionals. METHODS: Here we apply a transformational action research design, including parallel and subsequent substudies, to advance knowledge and practice in family systems care. Qualitative multiple-case study designs will be used to explore the benefits of therapeutic conversations by analyzing recordings of the therapeutic conversations. The learning processes of students, trainees, and professionals will be investigated with descriptive qualitative study designs based on single and focus group interviews. The data will be analyzed with established coding methods. RESULTS: Therapeutic conversations have been investigated in 3 single-case studies, each involving a sequence of 3 therapeutic conversation units. Data collection regarding the second research question is planned. CONCLUSIONS: Preliminary results confirm the therapeutic conversations to support families' coping. This renders the FSCU a setting for ethically sensitive research. This program will not only support the health and well-being of families, but also contribute to relieving the financial and workforce burdens in the health and social care system. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53090.
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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 | 0.111 | 0.089 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.079 | 0.020 |
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".