Improving Health and Reducing Absence Days at Work: Effects of a Mindfulness- and Skill-Based Leadership Intervention on Supervisor and Employee Sick Days

Participants in the intervention group (IG) were recruited from organizations participating in the study. Inclusion criteria for the organizations to take part were that (a) they carried out at least one complete series of seminars (see below for a description of the intervention), each with 10 to 13 supervisors from the same hierarchical level; (b) they agreed to conduct surveys of supervisors and employees; and (c) they provided the opportunity for an information event to be offered at their workplace before the start of the study. A total of 12 organizations registered for the IG (N = 147 supervisors and N = 1731 employees). Five of these companies from two branches (science and healthcare) consented to participate in the analysis of work disability data (n = 55 supervisors and n = 349 employees). Work disability data could be collected only from participants who were insured through the cooperating health insurance company (n = 14 supervisors and n = 255 employees). In addition, we had to exclude certain participants because (i) work disability data were incomplete (n = 1 supervisor, n = 21 employees), or (ii) data on variables included as covariates in the statistical model were missing or incorrect (n = 38 employees). Finally, data from a total of n = 13 supervisors and n = 196 employees in the IG could be analyzed.

Study participants in the control group (CG) included adult healthcare insurance holders who did not take part in the intervention program. To achieve the highest possible level of comparability, we recruited study participants in the CG in two steps using propensity score matching (PSM)—a statistical method to build comparable CGs in observational studies (Austin, 2011). During the first step, a cohort of N = 59,846 participants were selected via PSM, including their potentially relevant covariates that are routinely recorded for all healthcare insurance holders (age, sex, supervisor (yes/no), employment (full-/part-time), branch) and invited to participate in the study. By mail, they received a cover letter with information about the study, including a questionnaire for psychometric evaluation of the intervention, and an informed consent form asking them to provide written consent for analysis of their work disability data for scientific purposes, which were routinely collected by their health insurer. Participants were asked to return their signed consent form by mail to participate in the study. A total of n = 848 supervisors and 5546 employees consented to participate in the CG of the evaluation study. Of those, n = 297 supervisors and n = 1532 employees were insured by the cooperating health insurance company and gave their consent to analyze their work disability data. In addition, we had to exclude some participants because (i) work disability data were incomplete (n = 3 supervisors, n = 14 employees), or (ii) data on variables included as covariates in the statistical model were missing or incorrect (n = 166 supervisors, n = 25 employees). This led us to a final sample of n = 269 supervisors and n = 1352 employees in the CG that could be analyzed (Fig. 1).

The mindfulness and skill-based leadership intervention was developed by the authors of this study in collaboration with a German health insurance company based on the HoL concept of Franke et al. (2014). It consisted of 3 full-day courses and two 3-hr booster sessions: (a) health-promoting self-care, (b) health-promoting staff care, and (c) addressing employees under stress. The aim of the intervention was to promote supervisors’ health-related awareness and their value of health, as well as their health-behavior (Franke et al., 2014). To address the dimension corresponding to “value of health,” all the courses included information transfers, demonstrating their scientific backgrounds and emphasizing the importance of each topic. To address the dimension corresponding to “health behavior,” all the courses focused on teaching practical everyday skills to foster behavioral change. To address the dimension corresponding to “health awareness,” all the courses were based on mindfulness practices.

Mindfulness training was delivered according to the mindfulness concept developed in dialectical behavior therapy (Linehan, 2014). This concept focuses on mindfulness practice under daily life conditions and on mindfulness as a skills-based approach rather than on long meditation exercises (Baer, 2015). Meanwhile, this skills-based approach is also being used in healthy populations to facilitate the application of mindfulness in participants’ daily lives (e.g., Lothes et al., 2021; Lyssenko et al., 2015). Various short mindfulness exercises were practiced in which participants learned to focus and open their minds nonjudgmentally, effectively, and one-mindfully (i.e., doing one thing at a time) toward the present moment (How-Skills) to observe what is going on inside and outside without doing anything to change; to describe their thoughts, feelings, and sensations by adding words to their observations; and to participate and immerse themselves in the present moment of their daily life (What-Skills). Exemplary mindfulness exercises were short breathing-meditations, body scans, or mindful body movements.

In module (a) health-promoting self-care, supervisors received information on the stress-process and their current stressors and strains were identified using Pennebaker’s expressive writing technique (Pennebaker & Chung, 2007). They learned how they can use mindfulness skills to control their attention, be aware of their own thoughts, emotions, and bodily sensations, and recognize their own stressors and limits. To select and use suitable coping strategies, the participants learned to distinguish between changeable and unchangeable stressors. The participants practiced acceptance-based techniques based on mindfulness to address unchangeable stressors. Changeable stressors were addressed by means of an evidence-based problem-solving technique to foster active coping. In addition, the participants learned how to use mindfulness skills to effectively recover from work and to develop and plan regenerative activities (e.g., physical activity).

In module (b) health-promoting staff care, supervisors were sensitized to the importance of health for the efficacy and satisfaction of working teams and educated about basic psychological needs (Grawe, 2004). Mindfulness exercises were deepened and the ways in which mindfulness can contribute to health-promoting staff care were discussed. Supervisors learned how they can improve healthy working conditions and promote a cooperative team climate (organizational leadership). On the level of personal leadership, the participants determined how they could specifically address the individual needs and competencies of their employees, e.g., by formulating specific tasks. Finally, appreciation, as a central leadership element, was trained with numerous communication role-playing exercises.

In module (c) addressing employees under stress, mindfulness practice was further deepened and the possibilities and limits of leadership were discussed. In order to reduce uncertainties, participants were familiarized with the development and symptoms of stress-related mental illnesses and their recognition by means of case studies. Using a guide that supervisors can apply in response to observed stress, supervisors learned how to address mental distress in communication settings and practiced this in role plays. Further conversation settings such as regular check-ins, return interviews, and operational reintegration discussions were discussed.

The two 3-hr booster sessions aimed to enhance the sustainability of the intervention and to support participants in implementing the intervention content to their daily lives. The two 3-hr booster sessions were divided into three parts: a reflection on the implementation of the goals, an analysis of the unimplemented goals with a focus on barriers, and planning the next steps.

All modules were delivered at intervals of 4 weeks. Courses were led by health coaches and psychologists from the health insurance company, who had at least 5 years of experience in delivering preventive health interventions and received several days of training and continuous supervision. The total training time was 30 hr over a period of 6 months. A more detailed description of the intervention can be found in Vonderlin et al. (2021).

All data were selected from routine health-insurance statistics. For data protection reasons, all analyses were conducted independently of the psychometric assessments in the evaluation study; i.e., questionnaire and work disability data were not merged.

Many individuals do not generate any single sick days. Therefore, sick day data are usually not normally distributed but represent a probability distribution, with a positive mass at 0 (discrete distribution) and a continuous distribution above 0. This type of distribution is called a compound Poisson-gamma distribution, which belongs to the broader statistical family of Tweedie distributions that describe semi-continuous data with a positive mass at 0 (Hasan & Dunn, 2011). This type of distribution can be modeled in generalized linear models and has been shown to be a good fit healthcare cost data, which are typically non-negative, right-skewed, and have excess zeros for non-users or people with no sick days (Kurz, 2017). After examining the distribution of sick day data visually, we decided to conduct a generalized linear model with Tweedie log-link function to analyze the nonspecific and specific sick days as the dependent variable. Sickness absence days post-intervention (up to 24 months after the intervention starts) were adjusted for sickness absence days prior to the intervention (24 months before the start of the intervention). As control variables, gender, age, and branch were included. Education was not included in the model because it would have resulted in high dropout of participants in the intervention group due to missing data (Table 1). Instead, we decided to enter the covariate complexity of work into the model, as it was significantly correlated with school education (r = 0.36, p < 0.001). Because of the small sample size in the intervention group and the high heterogeneity in sick day data, we performed sensitivity analyses in addition to the statistical model. In doing so, we first calculated descriptive mean scores, analyzed them visually, and used a bootstrapping t-test (5000 samples) to compare post-intervention scores between groups. In addition, we calculated pre–post median scores in each group, which are more robust to outliers. To handle outliers, we decided to conduct robust sensitivity analyses and to not exclude them, since there was no evidence that outliers were caused by systematic error. All analyses were performed using SPSS 26.0.

This research has far-reaching implications. Our findings support that MBPs at the workplace not only affect subjectively assessed health-related outcomes, but they also reflect on supervisors’ sick days. This might result in (financial) benefits for organizations and the healthcare system. These results could contribute to further expanding the range of MBPs in promoting mental health in the work context and provide important information for organizations thinking about implementing MBPs for their workforce. The major strength of our study relates to its longitudinal and multilevel intervention design by also including objective health data like sickness absence days to investigate the effectiveness of the program. However, there are some limitations that should be taken into account when interpreting the results.

First, our intervention is not only a pure mindfulness intervention but also includes other elements based on behavioral change and psychoeducation. Thus, a causal interpretation regarding the mechanism of change is not possible. In addition to mindfulness training, other intervention elements may have contributed to the impact on sick days, particularly from the self-care module (e.g., improved problem-solving skills). However, all courses were based on mindfulness practice as the major conceptual framework, and this reflects the naturally occurring heterogeneity of mindfulness-based intervention in workplaces (Vonderlin et al., 2020). Interestingly, the results of the psychometric analyses showed that the effect of the intervention on supervisors’ mental health was moderated by the extent of their mindfulness practice at home (Vonderlin et al., 2021). Thus, we hypothesize that mindfulness training is at least one important mechanism that leads to improved health and, in turn, affects sick days. However, future studies should attempt to replicate our findings with pure mindfulness interventions to shed more light on the processes involved.

Second, due to data protection issues, we were not able to merge the data on sick days with questionnaire data from the evaluation study (Vonderlin et al., 2021). Therefore, we were not able to examine possible mechanisms of change in more detail. The results of the psychometric evaluation of the intervention suggest that the impact of the intervention on supervisors’ mental health was mediated by an improvement in their health-oriented self-care (Vonderlin et al., 2021). We therefore assume that this increased self-care and improvement in their mental health is also the process by which the intervention may have affected sick days. However, it would have been interesting to explore this assumption further and demonstrate whether a decrease in sick days also translates into increased mindfulness and self-care or decreased subjectively perceived psychological distress among supervisors.

Third, assignment to the groups was not randomized, and the control group was a passive control cohort recruited outside the organizations. This could have led to systematic biases between groups (e.g., due to organizational culture). To address this limitation, we used propensity score matching to control for key confounding variables (e.g., age, gender). However, future research should replicate our findings using randomized controlled trials and active control cohorts.

Finally, our results on decreased sick days give a first indication of possible financial benefits for organizations. However, our analysis does not represent a full cost-effectiveness analysis. This would also require analyzing the costs associated with implementing the intervention, which were not available in this study. However, Doyle et al. (2019) estimated average costs of US$515 and $1217 per participant to implement an MBP, which is lower than our estimated potential benefit of EUR 1995 per participant over 2 years.

Against the background of the current COVID-19 pandemic, this study points out several implications. It is important to note that the intervention was conducted before the onset of the spread of COVID-19 in Germany. However, the recording of sick days after the intervention (2 years after the intervention until 02/2021) showed an overlap with the onset of the COVID pandemic in Germany (02/2020). Although data from Germany show that sick days remained stable during the pandemic (2019: 10.9 days per employee, 2020: 11.2 days per employee, 2021: 11.2 days per employee; German Federal Statistical Office [Statistisches Bundesamt], 2023), this indicates the importance of our control group to account for potential systematic bias due to COVID. Nevertheless, practitioners and researchers agree that the COVID-19 pandemic represents a profound crisis in workplace health, and the resulting stressors will continue to affect mental health in the workplace (Shoss, 2021). Thus, it will continue to be a major challenge for supervisors to manage COVID-specific stressors and strains on their employees (e.g., telecommunications and loneliness; Andel et al., 2021). Previous research has shown that MBPs can help buffer COVID-related psychological stress (Al Ozairi et al., 2023; Bossi et al., 2022). The present study adds to these findings by suggesting that a mindfulness- and skill-based program for supervisors could help improve their health and stabilize their nonspecific sick days at work. Given that the COVID-19 pandemic is estimated by most to be one of many crises that society will face in the near future (Boin, 2019) and the central role of supervisors in managing workplace crises (Klebe et al., 2021), our study suggests that mindfulness-based interventions for supervisors could help stabilize sick days during times of increased psychological stress.

In conclusion, our data show that our mindfulness-based leadership intervention not only was effective in reducing mental distress among supervisors but also showed significant effects on their sickness absences. Sensitivity analyses showed that this effect was mainly driven by stabilization of supervisors’ sick days in the MBP group compared to an increase of sick days in the control group. In addition to reducing individual suffering, this can also have (financial) benefits for organizations and society. Overall, these findings could make an important contribution to the large-scale implementation of MBPs in the work context and inform decision makers in organizations that are considering implementing MBPs for their workforce.