76 | Chapter 4 Personal resources were measured using the Dutch translation of the Psychological Capital Questionnaire (PCQ).36. We used the constructs of psychological capital because they are relatively malleable and open to development.37 For this study, optimism, hope and resilience were included in the questionnaire. The PCQ has a 6-point Likert scale (1=strongly disagree, 6=strongly agree). Each of the PCQ scale scores is calculated by taking the mean of all items in the scale. This resulted in a score that ranged from 1 to 6.36 To measure self-efficacy, we used the Dutch General Self-Efficacy Scale (GSE).38 The answers on the GSE consist of a four-point Likert scale (1=completely false, 4=completely true).38 The score was obtained by calculating the sum of the scores of all 10 items (range from 10 to 40); a higher score means a higher degree of self-efficacy.38 Questions about socio-demographic characteristics were inspired by the WHELM studies.39 We adopted questions about age distribution, marital status, educational level, working context and employment status and adapted them to the Dutch language and context. Pilot testing of questionnaire The preliminary online questionnaire was pilot tested online by a panel of 10 midwives, 5 fourth-year students and 5 midwives (lecturers). Based on their feedback, we added information about the time needed to complete the questionnaire to the introduction text. We also decided to exclude the relationship with superior and participation subscales because community-based midwives did not recognise these items in their work due do their self-employed status. Analysis The descriptive statistics relating to socio-demographic characteristics, work engagement and burnout symptoms are presented with reference to work experience. Missing data (missing items per subscale) were examined for all variables. Work engagement and burnout symptoms and the socio-demographic variables showed no missing data. For job demands, job resources and personal resources, the amount of missing data was less than one percent and completely random. We carried out a simple imputation of the missing data with the average score for each specific item. We used descriptive statistics to answer the first research question about the occurrence of burnout symptoms and high work engagement, and the differences between experience levels. To identify the determinants of burnout symptoms and high work engagement, we first performed univariable regression analysis to assess associations between dichotomised dependent variables (burnout symptoms and work engagement). We then conducted a multivariable regression analysis between the dichotomised dependent variables (burnout and work engagement) and experience levels (NQMs and
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