Competency Based Clinical Supervision Model data
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PROVIDER: S-BSST1117 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:Competency-based supervision of trainees has recently come to the forefront of behavior analytic practice; however, there are minimal data to support the effectiveness of various supervision practices on trainee outcomes. Accordingly, this paper is intended to spark further discussion and research activity regarding the supervision of those seeking to become Board Certified Behavior Analysts (BCBA). We present a practice model and considerations for supervising applied behavior analytic trainees consistent with the Behavior Analyst Certification Board (BACB) Supervisor Training Curriculum Outline (Behavior Analyst Certification Board, 2012b), the Professional and Ethical Compliance Code for Behavior Analysts (Behavior Analyst Certification Board, 2014), and extant literature from behavior analysis and related fields. Inherent to the current model is a focus on bi-directional feedback and collaboration between the supervisor and trainee to frequently evaluate the acceptability of the procedures, process, outcomes, and effectiveness of supervision. We present a Supervision Monitoring and Evaluation Form consistent with the current model and discuss the assumed importance of objective and subjective self-assessment of supervisor competence to the ultimate advancement of the practice of applied behavior analysis.
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Project description:BackgroundSupportive supervision has been found to be more effective than corrective fault-oriented inspections. Uganda's Ministry of Health in 2012 implemented a comprehensive strategy (SPARS) to build medicines management capacity in public sector health facilities. The approach includes supportive supervision. This structured observational study assesses supportive supervision competency among medicines management supervisors (MMS).MethodThe study used structured observations of two groups of five purposely selected MMS-one group supervising facilities with greater medicines management improvement during one year of SPARS and one group with less improvement, based on quantitative metrics. We observed and scored behaviors and skills of supervisors in 11 categories deemed critical for effective and supportive supervision.ResultsSupportive supervision was not evenly or adequately implemented, with the median supportive supervision competency score for all observed supervisors being 38%. Supervisors' main strengths were problem identification, data interpretation, education, and providing constructive feedback (45%-47%). Their weakest areas were assuring continuity and setting targets (17%), and most MMS were fair to strong in effective communication, use of tools, and problem solving. MMS of facilities with little improvement in medicines management over time were weak in setting targets and promoting participation. There was a 33 percentage point difference in the median supportive supervision competency scores between MMS of facilities with more versus less improvement (57%-24%) and a 77 percentage point difference in competency between the highest and lowest scoring MMS (77%-0%). We did not find a relationship between MMS experience (number of visits implemented) and their supportive supervision competency or facility improvement in medicines management. However, there is a likely relationship between supportive supervision competency and facility improvement.ConclusionCompetency of MMS in supportive supervision among the sampled MMS was generally weak, but with much individual variation. Our results suggest that MMS' supportive supervision competency is positively related to the SPARS effectiveness scores of the facilities they supervise. We recommend strategies to strengthen supportive supervision behaviors and skills.
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Project description:BackgroundAround the world, regulatory bodies have taken the lead in determining the competencies required to become a physician. As a first step in addressing this project, it was decided to develop a set of core competencies that were unique to China and that might serve as a basis for medical education. The purpose of this paper was to construct a competency model for clinical physicians in China.MethodsData was collected using a cross-sectional survey of 6247 clinicians from seven administrative regions (31 provinces, autonomous regions and municipalities directly under the central government) in China. The total sample was randomly divided into two sub-samples, an initial sample (Sample 1) and a replication sample (Sample 2). Independent exploratory factor analysis was conducted in each sample and the results were compared to determine the stability. After that the confirmatory factor analysis was used to ascertain the competency model for physicians. The reliability, convergent and discriminant validity of competency-based instrument were also examined.Results76 items with 8 dimensions were identified, accounting for 68.41% of the construct's total variance in the initial sample and 67.47% in the replication sample. For the two samples, the overall scale reliability (Cronbach's alpha) was both 0.985 with dimensions from 0.905 to 0.954 for the initial sample and from 0.902 to 0.955 for the replication sample after deleting the items. In confirmatory factor analysis, the result showed that all items had acceptable goodness of fit index. RMSEA and SRMR were less than 0.08 (RMSEA = 0.046, SRMR = 0.040), while GFI, NFI, IFI, and CFI were higher than 0.9 (GFI = 0.905, NFI = 0.903, IFI = 0.909, CFI = 0.909), leading to acceptable construct validity. All construct reliability values of the factors were higher than 0.70, and all average variance extracted values exceeded 0.50. Thus, we considered the reliability and validity of the 8 dimensions were acceptable.ConclusionsThe instrument was shown to be both valid and reliable for measuring clinical physicians' competency in China. The results of the competency-based instrument can be used by ministry of health and administrators of hospitals to assess physicians' competencies, encourage and guide them to modify their behaviors according to the evaluation criteria, and also cultivate physicians with strong clinical practice, innovation and independent scientific research ability. Through these measurements and understandings, the overall level of clinical physicians will be increased in China.
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Project description:We compared the performance of several prediction techniques for breast cancer prognosis, based on AU-ROC performance (Area Under ROC) for different prognosis periods. The analyzed dataset contained 1,981 patients and from an initial 25 variables, the 11 most common clinical predictors were retained. We compared eight models from a wide spectrum of predictive models, namely; Generalized Linear Model (GLM), GLM-Net, Partial Least Square (PLS), Support Vector Machines (SVM), Random Forests (RF), Neural Networks, k-Nearest Neighbors (k-NN) and Boosted Trees. In order to compare these models, paired t-test was applied on the model performance differences obtained from data resampling. Random Forests, Boosted Trees, Partial Least Square and GLMNet have superior overall performance, however they are only slightly higher than the other models. The comparative analysis also allowed us to define a relative variable importance as the average of variable importance from the different models. Two sets of variables are identified from this analysis. The first includes number of positive lymph nodes, tumor size, cancer grade and estrogen receptor, all has an important influence on model predictability. The second set incudes variables related to histological parameters and treatment types. The short term vs long term contribution of the clinical variables are also analyzed from the comparative models. From the various cancer treatment plans, the combination of Chemo/Radio therapy leads to the largest impact on cancer prognosis.
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Project description:Introduction: Pharmacists need to be adaptable, flexible, and capable of advancing their practice to adapt to rapidly changing population health needs. We describe an educational approach to pharmacy workforce transformation in Indonesia through an advanced practice competency framework development using an "adopt and adapt" methodology. Methods: The competency framework development process comprised a translation phase, an adopt and adapt phase, validation through a nationwide mapping survey, and a completion phase through leadership consensus panels. We conducted a forward-backwards translation of a previously validated Advanced to Consultancy Level Framework (ACLF) to yield the Indonesian Advanced Development Framework (IADF) draft. The subsequent adoption and adaptation process was conducted through a series of consensus panels. We validated the IADF through a nationwide workforce survey. The final phase included leadership consensus panels with the professional leadership body in Indonesia. We analyzed the qualitative data thematically and the quantitative data using a Multiple Correspondence Analysis (MCA) technique. Results: We identified conceptual challenges in adopting and adapting the existing ACLF, which were addressed by providing a national glossary and concrete examples. A total of 6,212 pharmacists participated in the national workforce survey, of which 43% had <2 years of post-license (post-registration) experience. The MCA results showed that practitioner self-assessment to the IADF could discriminate their career development stages. The results also indicated a four-stage career model (including early years career training). Embedding this model in a structured national training program will enhance the professional workforce development through a more structured career journey. Conclusions: We describe the first validation of an advanced competency development framework for the pharmacy workforce in a non-Anglophone country, showing the possibility of transnational applicability of this framework. We argue that this methodology can be used in Low and Middle-income countries (LMICs) for the more rapid advancement of pharmaceutical care practice.
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