Literature DB >> 33980099

Development of a questionnaire to assess student behavioral confidence to undertake interprofessional education activities.

Sharron Blumenthal1, Kareena McAloney-Kocaman1, Nichola McLarnon1, Lindsey Burns1, Jamie McDermott1.   

Abstract

Measurement of the impact of interprofessional education (IPE) is the golden chalice educationalists chase. We undertook the development of a scale to measure IPE Academic Behavioral Confidence (IPE-ABC) in allied health, nursing, and social work pre-registration students. This work formed part of the evaluation of a large IPE framework embedded across two Scottish universities. General ABC has been shown to influence student perceptions of study experiences and it is thus reasonable to postulate that ABC could influence student perceptions of IPE. This research developed a questionnaire to ascertain health and social care students' confidence to engage in IPE, utilizing a mixed method approach. Fifteen different professional groups of pre-registration students (n = 565) participated in the assessment of the 38 item questionnaire. Exploratory factor analysis identified three factors: 1/interprofessional teamwork, 2/behaviors underpinning collaboration, and 3/interprofessional communication collectively accounting for 38.2% of the variance. Internal consistency of the overall scale (Cronbach's α = .93) was very good with subscales demonstrating very good internal consistency, 1 (α = .89), or respectable consistency 2 (α = .78) and 3 (α = .79). We conclude the IPE-ABC questionnaire could be utilized to enhance and assess the success of IPE related activities.

Entities:  

Keywords:  Academic behavioral confidence; interprofessional education; interprofessional learning; mixed methods; pre-registration; questionnaire design

Mesh:

Year:  2021        PMID: 33980099     DOI: 10.1080/13561820.2021.1894104

Source DB:  PubMed          Journal:  J Interprof Care        ISSN: 1356-1820            Impact factor:   2.338


  1 in total

1.  The Acceptability of Traditional Culture under the Background of Deep Learning.

Authors:  Qian Sima; Shan Wu
Journal:  Comput Intell Neurosci       Date:  2022-08-23
  1 in total

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