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The Study Of Competency Model Of Medical Cosmetologist

Posted on:2019-04-09Degree:MasterType:Thesis
Country:ChinaCandidate:L R PengFull Text:PDF
GTID:2405330545971784Subject:Applied psychology
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Objective : Taking the medical cosmetologist(cosmetic surgery and cosmetic dermatology)as the research object,refine the competency of excellent medical cosmetologists and general medical cosmetologists,to build the medical cosmetologist’s competency model.According to the model’s discriminatory competence and benchmark competence,it provides reference for the job analysis of medical aesthetic doctors,talent selection,training and development,performance management and hospital system reform.Methods:(1)Using the literature analysis method to summarize the relevant literatures of relevant doctors at home and abroad and to sort out the current situation of talent evaluation of medical aesthetic doctors in the domestic literature and analyze the work tasks;(2)Use open questionnaires to collect competency terms for outstanding medical doctors;(3)Using the expert consultation method to determine the medical cosmetic doctor performance grouping criteria and select the interviewee;(4)Using behavioral event interview method to interview 20 medical cosmetic doctors(12 for the excellent group and 8 for the general group);(5)Statistical analysis was used to analyze the results of interviews.The consistency of coding,the difference in the length of interviews and competency between the two performance groups were used to extract the discriminating competence of outstanding medical and cosmetic doctors.All data were entered using Excel2015 and analyzed by SPSS22.0.Result:(1)Researching on the competencies of relevant doctors at home and abroad and combining the Status Quo of Medical Talent Doctors Evaluation and Task Analysis.Based on the HAY GROUP Universal Competence Dictionary and the Spencer Universal Competence Dictionary,compiling the “Code of Competence for Medical Aesthetic Doctors Competency” including 33 competencies.(2)Two coders randomly selected two texts for precoding to form a unified understanding of the code dictionary.Then the two coders independently coded 20 texts and performed corresponding data collation.(3)The statistical analysis results showed that there was no significant difference in the length of interviews and texts between different performance groups: The consistency coefficient ofthe two coders was between 0.6327 and 0.9381,and the reliability coefficient was between0.7750 and 0.9681,which means the coding data is trustworthy.Text length and frequency,average rating score,the highest rating scores of correlation analysis showed that the frequency stability is low,not suitable for used for difference analysis indicators,on average,are rated and are rated highest is relatively stable,suitable for variance analysis.Analyze the difference according to the average score of the competency and the score of the highest grade with the total number of 10.There was a statistically significant difference in the eight competencies(P<0.05).Conclusion: 20 interviews with a total of 199551 words and research data is sufficient.There are 18 discriminating competencies of the outstanding medical and cosmetic doctors extracted in this study,which are interpersonal comprehension,empathy,inductive thinking,deductive thinking,industry insight,knowledge dissemination,influence,innovation ability,information literacy,concern quality and order,professional enthusiasm,self-confidence,self-control,achievement concept,resilience,initiative,cultivating others and organizational awareness.Comparing with the competency model of hospital,director of the clinical surgery,clinicians,emergency doctors,In terms of deductive thinking,innovation ability,self-confidence and other 9 competencies,there are commonalities,and the characteristics of medical cosmetology doctors exist on 9 items,such as interpersonal understanding,empathy and influence.
Keywords/Search Tags:Medical cosmetology, Medical cosmetologist, Competence, Model construction
PDF Full Text Request
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