DOI: 10.4121/960f87dd-b068-485c-a279-a93c407a1526.v1
title: Survey data underlying the publication: Enhancing Entrepreneurial Behavioral Strategies to increase their Well-being and Performance: An Online Self-training Intervention Study

description: <strong style="color:windowtext;">Methods</strong><strong style="color:windowtext;">Sample </strong>Data were collected among Dutch entrepreneurs who owned private companies and employed less than 50 employees (cf. Jayasekara et al., 2020). After completing the informed consent, respondents filled out the questionnaire. Confidentiality and anonymity of responses were emphasized and assured, and participation was voluntary. The Ethics Review Board of the university approved the study (ERB2020IEIS55).<br>A total of N = 79 entrepreneurs signed up for the intervention and filled out the first questionnaire. Of these N = 79, N = 63 started the self-training intervention and N = 45 participated in the post-questionnaire of the self-training intervention (Dropout of 43%). A total of N = 53 entrepreneurs participated in the pre- and post-measure of the control group (no dropout). Giving a total sample of N = 96 participants. The sample included 56 men (58.3 %) and 39 women (40.6%). Their mean age was 39 years (SD = 13.68). The average age of their business was 5.82 years (SD = 6.65), and most participants were active in business services (16.5%), the culture and leisure sector (16.5%), health and social work 10.3%), and trading (10.3%). The control group and the intervention matched based on gender, education, age of their business, and sector in which the entrepreneur was active. However, the groups differed in age (t = -2.92, p &lt; .05). The intervention group was on average older (M = 39.3, SD = 14.2). In contrast, the control group had an average age of M = 31.8 (SD = 11.2). As age has a positive effect on how entrepreneurs manage their business (Zhao et al., 2021), this variable was added as control variables in our analysis.<br><strong style="color:windowtext;">The intervention</strong>The intervention was a self-help format where entrepreneurs received an invitation for that day to watch the short video lectures, answer the reflection questions of the tool, and specify and fulfill self-set assignments. In designing our intervention, we acknowledge the diversity among entrepreneurs. Additionally, we collaborated with entrepreneurs, and we built an evidence-based foundation for entrepreneurial practice (Williamson et al., 2021). The intervention consisted of six training activities representing the six days of training. Every morning at 7:30, participants received an email with the link to a mini-lecture video containing evidence-based information and explaining the strategy they would use that day. After the mini-lecture, entrepreneurs worked on reflective and interactive exercises to deepen the new understanding. Participants indicated whether they managed to fulfill the previous assignment and, if not, why. After completing that day's exercises, which were explained to the entrepreneurs with text, participants would receive an email with an overview of the training with the answers they provided via e-mail. Each day including the assignment could be followed independently without assuming the previous one had been completed. Each mini-lectured lasted, on average, 4 minutes, whereas each assignment lasted about 5 minutes, excluding the time needed to achieve each goal. The participants could always ask questions to which the trainer could respond immediately.<strong style="color:windowtext;">General survey</strong>All responses were given on 5-point Likert scales ranging from 1 ((almost) never) to 5 ((almost) always) referring to the past two weeks. All variables were in Dutch and rewritten to apply to entrepreneurs.<em>Seeking resources</em> was measured with adapted job crafting scales by Demerouti and Peeters (2018) and Petrou et al. (2012) that had been used previously (Boesten et al., 2023) and was measured with three items (e.g., “I have tried to learn new things for my business”), Cronbach’s α was at T1 was .71 and Cronbach’s α at T2 was.75.<em>Optimizing demands</em> was measured with adapted job crafting scales by Demerouti and Peeters (2018) and Petrou et al. (2012) that had been used previously (Boesten et al., 2023) and was measured with three items (e.g., “I look for ways to do my work more efficiently”), Cronbach’s α was at T1 was .84 and Cronbach’s α at T2 was.87.<em>Idea generation </em>was measured with three items (De Jong & Den Hartog, 2010). For idea generation (e.g., “I came up with original solutions for problems”), Cronbach’s α was at T1 was .81 and Cronbach’s α at T2 was .75.<em>Network diversity</em> was measured with items, e.g., “My network contains contacts with a different age”. Cronbach’s α was at T1 was .72 and Cronbach’s α at T2 was .76.<em>Environmental</em> <em>exploration</em> was measured with four items (Stumpf et al., 1983), e.g., “I researched business opportunities”. Cronbach’s α was at T1 was .80 and Cronbach’s α at T2 was.81.<em>Boundary management</em> was measured with four items (Kossek et al., 2012), e.g., “I determined whether I mixed up my work and personal activities throughout the day”. Cronbach’s α was at T1 was .82 and Cronbach’s α at T2 was .83.<em>Idea implementation</em> was measured with three items (De Jong & Den Hartog, 2010). For idea generation (e.g., “I have systematically translated innovative ideas into practice.”), Cronbach’s α was at T1 was .86 and Cronbach’s α at T2 was .82.<em>Positive work-home interference</em> was measured with four items of (Geurts et al., 2005), e.g., “I am better able to keep appointments at home because my work requires this as well”. Cronbach’s α was at T1 was .84 and Cronbach’s α at T2 was .84.<em>Operational goal attainment </em>was<em> </em>measured with three items in total (Grebner et al., 2010); e.g., “I completed my financial goals”). Cronbach’s α was at T1 was .85 and Cronbach’s α at T2 was .85.<em>Happiness </em>was measured using the 1-item faces measure of Kunin (1998).<strong style="color:windowtext;">Strategy of analysis</strong>Data was analyzed using univariate analyses of covariance (ANCOVA) in R-studio (Egbewale et al., 2014; Valente & MacKinnon, 2017). Only the complete data (N = 45 intervention group; N = 54 control group) was used to examine the effects of the intervention over time. With ANCOVA, the effect of the intervention was tested using T0 as the covariate and T1 as the outcome. Besides ANCOVA being a reliable method to analyze the effect of interventions (Egbewale et al., 2014; Wan, 2021), we also decided to use ANCOVA because of a significant difference in our baseline. The mediating effect of the intervention through the trained strategies was tested using latent change scores (LCS) ANCOVA (Valente et al., 2021).