Abstract
Objective To describe the adaption and psychometric testing of the Picker Employee Questionnaire to measure work environment, work experience, and employee engagement with midwives. Design Expert interviews, cognitive testing, and online survey for data collection. Setting Obstetric departments in Germany. Participants Midwives employed in German obstetric departments: 3,867 were invited to take part, and 1,692 (44%) responded to the survey. Methods Questionnaire adaption involved expert interviews and cognitive testing. Psychometric evaluation was done via exploratory factor analysis, reliability analysis, and construct validity assessment. Results The adaption of the Picker Employee Questionnaire resulted in a tool with 75 closed questions referring to central aspects of work environment, experience, and engagement. Factor analysis yielded 10 factors explaining 51% of the variance. Themes covered were Support from Management (Immediate Superior and Hospital Management), Workload, Overtime, Scheduling, Education and Training, Interaction with Colleagues (Midwives, Physicians, and Nurses), and Engagement. Eight scales had a Cronbach's alpha coefficient of 0.7 or greater; the remaining two were 0.6 or less. The questionnaire distinguished between different subgroups of midwives and hospitals. Conclusion The questionnaire is well suited for the measurement of midwives’ work experience, environment, and engagement. It is a useful tool that supports employers and human resource managers in shaping and motivating an efficient work environment for midwives.
Original language | English |
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Journal | JOGNN - Journal of Obstetric, Gynecologic, and Neonatal Nursing |
Volume | 46 |
Issue number | 3 |
Pages (from-to) | e105-e117 |
ISSN | 0884-2175 |
DOIs | |
Publication status | Published - 05.2017 |
Research Areas and Centers
- Health Sciences
DFG Research Classification Scheme
- 205-02 Public Health, Health Services Research and Social Medicine
- 205-10 Toxicology, Occupational Medicine, Clinical Chemistry
- 205-01 Epidemiology, Medical Biometrics/Statistics