Collaborating in the context of co-location: a grounded theory study
Bibliographic record
Abstract
BACKGROUND: Most individuals with mental health concerns seek care from their primary care provider, who may lack comfort, knowledge, and time to provide care. Interprofessional collaboration between providers improves access to primary mental health services and increases primary care providers' comfort offering these services. Building and sustaining interprofessional relationships is foundational to collaborative practice in primary care settings. However, little is known about the relationship building process within these collaborative relationships. The purpose of this grounded theory study was to gain a theoretical understanding of the interprofessional collaborative relationship-building process to guide health care providers and leaders as they integrate mental health services into primary care settings. METHODS: Forty primary and mental health care providers completed a demographic questionnaire and participated in either an individual or group interview. Interviews were audio-recorded and transcribed verbatim. Transcripts were reviewed several times and then individually coded. Codes were reviewed and similar codes were collapsed to form categories using using constant comparison. All codes and categories were discussed amongst the researchers and the final categories and core category was agreed upon using constant comparison and consensus. RESULTS: A four-stage developmental interprofessional collaborative relationship-building model explained the emergent core category of Collaboration in the Context of Co-location. The four stages included 1) Looking for Help, 2) Initiating Co-location, 3) Fitting-in, and 4) Growing Reciprocity. A patient-focus and communication strategies were essential processes throughout the interprofessional collaborative relationship-building process. CONCLUSIONS: Building interprofessional collaborative relationships amongst health care providers are essential to delivering mental health services in primary care settings. This developmental model describes the process of how these relationships are co-created and supported by the health care region. Furthermore, the model emphasizes that all providers must develop and sustain a patient-focus and communication strategies that are flexible. Applying this model, health care providers can guide the creation and sustainability of primary care interprofessional collaborative relationships. Moreover, this model may guide health care leaders and policy makers as they initiate interprofessional collaborative practice in other health care settings.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".