Facilitators and barriers to interprofessional collaboration among health professionals in primary healthcare centers in Qatar: a qualitative exploration using the “Gears” model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The number of patients seeking medical care is increasing, necessitating more access to primary healthcare services. As several of these patients usually present with complex medical conditions, the need for interprofessional collaboration (IPC) among health professionals in primary care is necessary. IPC is essential for facing the increasing and challenging healthcare demands. Therefore, the facilitators of and the barriers to IPC should be studied in the hope that the results will be used to promote such endeavors. OBJECTIVES: This study aimed to explore the perspectives of different health professionals regarding the facilitators of and the barriers to IPC in the primary healthcare settings in Qatar. METHODS: A qualitative study using focus groups was conducted within the Primary Health Care Corporation (PHCC) in Qatar. Several health professionals were invited to participate in the focus groups. The focus groups were uniprofessional for general practitioners (GPs), nurses, and dentists, while they were interprofessional for the other health professionals. Focus groups were audio-recorded and transcribed verbatim and validated by the research team. The data were analyzed by deductive thematic analysis using the "Gears" Conceptual Model as a coding framework. RESULTS: Fourteen focus groups were conducted involving 58 participants (including 17 GPs, 12 nurses, 15 pharmacists, 3 dentists, and 11 allied health professionals) working in PHCC in Qatar. The findings revealed a spectrum of factors influencing IPC, categorized into four main domains: Macro, Meso, Micro, and individual levels, with each accompanied by relevant barriers and facilitators. Key challenges identified included a lack of communication skills, insufficient professional competencies, and power imbalances, among others. To address these challenges, recommendations were made to implement dedicated training sessions on IPC, reduce hierarchical barriers among different health professionals, and enhance the effectiveness of existing systems. Conversely, it was emphasized that projects and campaigns focused on IPC, alongside the development of enhanced communication skills and the presence of supportive leadership, as essential for facilitating effective IPC in PHCCs. CONCLUSION: The interplay between the meso, macro, micro, and individual levels highlight the significance of a multifaceted approach to interventions, aiming to enhance the successes of IPC. While initiatives like interprofessional education training are underway, numerous challenges persist before achieving improved collaboration and more efficient integration of IPC in the PHCC setting.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it