Developing a Conceptual Model for How Occupational Therapists Can Address “Wicked Problems”: A Critical Review
Bibliographic record
Abstract
IMPORTANCE: Wicked problems are those that are messy and complex and have no obvious solution. Occupational therapists and their clients encounter wicked problems in all areas of practice, and therefore it is essential that they know how to address them. OBJECTIVE: To identify the key constructs involved in addressing wicked problems, discover considerations for occupational therapists, and develop a conceptual model that supports how to address these problems. DESIGN: This study had a critical review design and focused on literature from sectors such as health care, social services, policy, business, management, and leadership. It followed a traditional critical review process and extracted records from Scopus, CINAHL and Ovid databases. RESULTS: A total of 36 articles were included in the review. The results indicated that, to address wicked problems, one must first identify the problem as wicked. The key constructs identified in the literature include collaboration, leadership, perspectives, and innovation, with collaboration and leadership as the most prominent constructs. Subthemes include interdisciplinary teams and diverse perspectives, visualizing interdependencies, team communication, leadership style, leadership communication, and shared vision. CONCLUSIONS AND RELEVANCE: The key constructs identified in this review are interconnected and imperative when addressing wicked problems as depicted in the new Addressing Wicked Problems conceptual model. Occupational therapists are well suited to extend between the traditional role and be key stakeholders in addressing wicked problems by using their leadership and collaboration skills and attitudes. What This Article Adds: Collaboration, leadership, perspective, and innovation are the key constructs for addressing wicked problems. The Addressing Wicked Problems conceptual model highlights the interconnectedness of these constructs.
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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 | 0.190 | 0.281 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.031 | 0.018 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.019 | 0.031 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".