Adaptation of Direct Observation of Procedural Skills (DOPS) for assessments in podiatry

FOCUS ON HEALTH PROFESSIONAL EDUCATION-A MULTIDISCIPLINARY JOURNAL(2018)

引用 0|浏览5
暂无评分
摘要
Background: The Direct Observation of Procedural Skills (DOPS) is a workplace-based assessment tool widely used in medicine to assess a learner's ability to execute a technical skill. The aim of this paper is to report on the development phase of the adaptation of the DOPS for the assessment of podiatry learners' procedural skills. Podiatry learners are required to practise and demonstrate a variety of procedural skills in the management of foot complaints. Such skills include the use of scalpel blades, needles and local anaesthetic applied to a variety of disorders. The DOPS provides an avenue by which a learner's procedural skills can be assessed and timely feedback provided in the workplace or in simulated environments. Methods: The DOPS was initially adapted for podiatry by a faculty team consisting of a podiatry educator, a clinical education specialist and a clinical educator from another allied health discipline. The first iteration was circulated among podiatry faculty at three other Australian universities. The second iteration was reviewed by clinical supervisors from Southern Cross University (SCU). The third iteration was administered by two clinical supervisors at SCU working with 12 learners during real-time clinical events. Eleven learners used DOPS to assess their peers during five real-time and six simulated learning events. Results: A new tool, the Direct Observation of Procedural Skills in Podiatry (DOPS-P) has emerged from this process. Face and construct validity have been confirmed, and faculty and students consider DOPS-P contributes to learning. Conclusions: Further research is necessary to confirm the validity and reliability of the DOPS-P to support assessment decisions about students' achievement of podiatry competencies.
更多
查看译文
关键词
Direct Observation of Procedural Skills,workplace-based assessment,podiatry
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要