Psychometric validation of team experiences questionnaire in preregistration Chinese health and social care students in Hong Kong.
Fraide A GanoticeLap Ki ChanPublished in: Journal of interprofessional care (2018)
The complexity of patients' healthcare needs can be addressed more adequately by professionals working as a healthcare team. In view of this, it is important to prepare students for collaborative work when they become professionals through a students' team training at the preregistration level. As intervention programs are implemented to promote students' collaboration, instruments like Team Experiences Questionnaire (TEQ) are needed. In this connection, this study which involved 335 Chinese students enrolled in eight health and social care programs from two universities in Hong Kong investigated the factor structures of the TEQ using construct validation approach. Using confirmatory factor analysis, we examined the fit of three competing models: unidimensional model, first-order correlated model, and second-order hierarchical model. The results demonstrated that the second-order hierarchical model obtained the best fit, with a higher-order construct called total team experiences subsuming the following first order factors: overall satisfaction with team experiences, team impact on quality of learning, satisfaction with team evaluation, team impact on clinical reasoning ability, and professional development. The "total team experience" construct explained from 21.1% to 35.7% of the variance in predicting students' future perception of team competency and autonomy, perceived need for cooperation, and perception of actual cooperation. Results support the applicability of the TEQ second-order hierarchical model. Implications are discussed.
Keyphrases
- palliative care
- healthcare
- quality improvement
- mental health
- public health
- high school
- randomized controlled trial
- end stage renal disease
- depressive symptoms
- chronic kidney disease
- prognostic factors
- newly diagnosed
- physical activity
- health insurance
- high resolution
- peritoneal dialysis
- data analysis
- health promotion
- affordable care act