2 resultados para Clinical Intervention

em QSpace: Queen's University - Canada


Relevância:

60.00% 60.00%

Publicador:

Resumo:

When ligaments within the wrist are damaged, the resulting loss in range of motion and grip strength can lead to reduced earning potential and restricted ability to perform important activities of daily living. Left untreated, ligament injuries ultimately lead to arthritis and chronic pain. Surgical repair can mitigate these issues but current procedures are often non-anatomic and unable to completely restore the wrist’s complex network of ligaments. An inability to quantitatively assess wrist function clinically, both before and after surgery, limits the ability to assess the response to clinical intervention. Previous work has shown that bones within the wrist move in a similar pattern across people, but these patterns remain challenging to predict and model. In an effort to quantify and further develop the understanding of normal carpal mechanics, we performed two studies using 3D in vivo carpal bone motion analysis techniques. For the first study, we measured wrist laxity and performed CT scans of the wrist to evaluate 3D carpal bone positions. We found that through mid-range radial-ulnar deviation range of motion the scaphoid and lunate primarily flexed and extended; however, there was a significant relationship between wrist laxity and row-column behaviour. We also found that there was a significant relationship between scaphoid flexion and active radial deviation range of motion. For the second study, an analysis was performed on a publicly available database. We evaluated scapholunate relative motion over a full range of wrist positions, and found that there was a significant amount of variation in the location and orientation of the rotation axis between the two bones. Together the findings from the two studies illustrate the complexity and subject specificity of normal carpal mechanics, and should provide insights that can guide the development of anatomical wrist ligament repair surgeries that restore normal function.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Background: Academic integrity (AI) has been defined as the commitment to the values of honesty, trust, fairness, respect, and responsibility with courage in all academic endeavours. The senior years of nursing studies provide an intersection for students to transition to professional roles through student clinical practice. It is essential to understand what predicts senior nursing students’ intention to behave with AI so that efforts can be directed to initiatives focused on strengthening their commitment to behaving with AI. Research Questions: To what extent do students differ on Theory of Planned Behaviour (TPB) variables? What predicts intention to behave with academic integrity among senior nursing students in clinical practice across three different Canadian Schools of Nursing? Method: The TPB framework, an elicitation (n=30) and two pilot studies (n=59, n=29) resulted in the development of a 38 question (41-item) self-report survey (Miron Academic Integrity Nursing Survey—MAINS: α>0.70) that was administered to Year 3 and 4 students (N=339). Three predictor variables (attitude, subjective norm, perceived behavioural control) were measured with students’ intention to behave with AI in clinical. Age, sex, year of study, program stream, students’ understanding of AI policies, and locations where students accessed AI information were also measured. Results: Hierarchical multiple regression analyses revealed that background, site, and TPB variables explained 32.6% of the variance in intention to behave with academic integrity. The TPB variables explained 26.8% of the variance in intention after controlling for background and site variables. In the final model, only the TPB predictor variables were statistically significant with Attitude having the highest beta value (beta=0.35, p<0.001), followed by Subjective Norm (beta=0.21, p<0.001) and Perceived Behavioural Control (beta=0.12, p<0.02). Conclusion: Student attitude is the strongest predictor to intention to behave with AI in clinical practice and efforts to positively influence students’ attitudes need to be a focus for schools, curricula, and clinical educators. Opportunities for future research should include replicating the current study with students enrolled in other professional programs and intervention studies that examine the effectiveness of specific endeavours to promote AI in practice.