1 Introduction

Managerial coaching, referring to behaviors that inspire, facilitate, and guide employees to learn, grow and enhance their performance (Dahling et al., 2016; Heslin et al., 2006), is related to a variety of positive outcomes for employees, such as well-being (e.g., Carrell et al., 2022), job satisfaction (Kim et al., 2013b), job commitment (Kim et al., 2013a), role clarity (Kim, 2014), and lower turnover rates (DiGirolamo & Tkach, 2019). Therefore, many organizations expect managers to incorporate coaching behavior into their management style (Ellinger et al., 2003; Heslin et al., 2006) and the need for managers to exhibit a ‘coaching style’ has been on the rise over the past decade (Lawrence, 2017). However, whereas coaching is generally seen as a crucial part of daily management practices (McCarthy & Milner, 2020), managers struggle with showing coaching behavior because they are not adequately trained to fulfill this role (e.g., Fatien & Otter, 2015; Ladyshewsky, 2010). Moreover, the combination of the manager and the coach role is more complex than the role of a traditional coach who is only concerned with supporting personal development (Ladyshewsky, 2010; McCarthy & Milner, 2020) and managers experience a lack of organizational support in developing their coaching behavior (DiGirolamo & Tkach, 2019. Therefore, it seems crucial for organizations to develop training interventions that support managers in the development of their coaching skills.

One type of intervention that seems promising in this regard is the implementation of a Strength Spotting Intervention (SSI). Strengths spotting is about identifying strengths in oneself and in others (Linley et al., 2010). In a strengths spotting intervention, participants will learn how to identify strengths in other individuals based on physical and voice cues associated with strengths (e.g., better posture, eyes widening and more inflection in the voice). In addition, they will learn how to ask questions about potential strengths and give strengths-based feedback (Biswas-Diener et al., 2016; Linley, 2008; Linley et al., 2010). Managers who participate in an SSI learn to identify unique qualities and strengths in their subordinates and may be inspired to use this as a basis for their coaching behaviors. Because both strengths spotting and coaching are concerned with the facilitation and promotion of optimal human functioning (Linley & Harrington, 2005), learning how to spot strengths in an SSI might function as a steppingstone to managerial coaching by helping managers to give constructive feedback and inspire employees to realize their potential.

According to the Values in Action (VIA) Classification, there are 24-character strengths (e.g., creativity, honesty, kindness) that are based on six virtues such as wisdom, courage, and humanity (Peterson & Seligman, 2004). People typically possess three to seven signature strengths (their highest-ranking strengths). Even though most research is focused on the beneficial outcomes of interventions aimed at using and developing these signature strengths at work (e.g., Tobias et al., 2023) interventions that focus on an individual’s lowest ranking strengths (also called lesser strengths) are recently getting more attention (Green, 2022; Proyer et al., 2015; Rust et al., 2009; Waters & Sun, 2016). Whereas the empirical support for the efficacy of signature strengths interventions is still stronger compared to that of other strengths interventions (Ruch et al., 2020; Schutte & Malouff, 2018), Proyer et al. (2015) have found that so-called lesser strengths interventions have similar positive effects on well-being and enjoyment. However, it is still unclear to what extent interventions that focus on signature strengths are superior to those that focus on lesser strengths (Ruch et al., 2020) and more specifically, it is also unknown to what extent learning how to spot signature strengths versus lesser strengths in employees can help managers in coaching their employees. On the one hand, spotting employees’ signature strengths might motivate managers to engage in coaching behaviors because it stimulates them to look for “positive deviance” in the employees’ behavior, and is therefore a positive activity that may energize managers (Lyubomirsky & Layous, 2013; Meyers et al., 2015). On the other hand, spotting the lesser strengths in an employee, might motivate managers to coach their employees because it gives them insight in how to help their employees in mastering tasks they struggle with (van Woerkom et al., 2016). Although we expect both interventions to be effective in stimulating managerial coaching behavior, we expect that an SSI that focuses on signature strengths will be more effective due to the effect that focusing on signature strengths will have on the positive emotions of the employee (Linley, 2008; Peterson & Seligman, 2004). Based on research on emotional contagion (Hatfield et al., 1994; Van Kleef et al., 2009) we expect that managers will be infected with the employee’s enthusiasm when discussing the use of their signature strengths. This may lead to an increase in exploration and approach behaviors on behalf of the manager, including applying newly learned coaching techniques to support an employee (Fredrickson, 2004).

This study contributes to the literature in three ways. First, to date most research on managerial coaching has focused on its favorable outcomes but overlooked the antecedents of such behavior (Beattie et al., 2014; Hagen, 2012). By investigating strength spotting interventions as a means to enhance critical coaching skills (Linley et al., 2010) and by investigating the differences between the spotting of signature strengths versus lesser strengths we shed more light on the predictors of managerial coaching behavior. Second, we contribute to the literature on strengths use in the workplace that has only started to identify the important role of the leader in providing support for employee strengths use (e.g., Ding & Yu, 2022; Wang et al., 2023). However, whereas existing studies highlight the beneficial effects of leader support for strengths use (e.g., van Woerkom & Kroon, 2020), actionable knowledge on how managers can best be trained in providing such support is limited. Third, previous studies on the effectiveness of SSIs focused on teachers spotting strengths in students or parents in their children (Haslip et al., 2019; Waters & Sun, 2016) thereby overlooking the work context and the manager-employee relationship. Because relationships between managers and employees differ in nature and purpose from relationships between teachers and students or parents and children, it is important to investigate whether the findings of these studies also apply to the work context.

1.1 Strengths and Strengths Spotting Interventions

Strengths refer to “ways of behaving, thinking or feeling that an individual has a natural capacity for, enjoys doing, and which allow the individual to achieve optimal functioning while they pursue valued outcomes” (Quinlan et al., 2012, p. 1146). Moreover, in character strengths research, strengths are seen as components of “good character” (Peterson & Seligman, 2004). According to Park and Peterson’s (2006, 2009) definition, “good character” refers to a cluster of morally valued positive traits that are deemed essential for a fulfilling life, and which are expressed through an individual’s thoughts, emotions, and actions. Most individuals possess between three and seven “signature” strengths, which are the ones “[…] that a person owns, celebrates, and frequently exercises” and which can be ranked based on their centrality to the individual (Peterson & Seligman, 2004, p.18).

An SSI is a specific type of character strengths intervention which helps managers to identify their own and others’ strengths. Traditionally, signature strengths are identified using a survey-based strengths assessment such as the VIA inventory of strengths (Peterson & Seligman, 2004). Since lesser strengths are seen as strengths with comparatively lower expressions that are less central to the individual, one can also use the VIA to identify a person’s lesser strengths (Proyer et al., 2015). Another approach to identify strengths is the use of open-ended strengths identification tools, in which the person’s own description of strengths is used instead of predetermined labels as is the case with survey-based assessments (Linley et al., 2010). Since the use of signature strengths is associated with a rise in enthusiasm and psychological arousal (Linley, 2008), a range of physical (e.g., increased smiling) and voice cues (e.g., more rapid speech) can be used to determine whether signature strengths are being discussed or displayed. By contrast, the absence of these cues might point to lesser strengths. The advantage of an open-ended approach to strengths identification is that the language used to describe the strength and the construction of the strengths are grounded in the lived experience of the person, making it more authentic and creating a feeling of ownership (Linley et al., 2010). Although survey-based strengths assessment and open-ended strengths identification each have their own benefits, the choice of method depends on the demand of the situation. A combination is recommended over the use of a single method to yield a more complete and accurate image of a person’s strengths (Miglianico et al., 2020).

Next to identifying a person’s strengths, scholars like Linley et al. (2010) and Biswas-Diener et al. (2011) advocate that strengths should be seen as dynamic traits that can be developed over time (Biswas-Diener et al., 2011). Strengths interventions should therefore not only focus on identifying and using strengths but also on strengths development. The same argument holds true for strengths-spotting interventions.

For the purpose of this study, we developed two versions of an SSI (based on signature and lesser strengths). Both start with teaching participants how to spot (signature or lesser) strengths in themselves and others. In addition, both interventions focus on building a growth mind-set regarding strengths (i.e., believing that both signature strengths and lesser strengths can be developed by adequate effort, use of strategies, and input form others) (Dweck, 2016). More specifically, our SSI’s instruct managers on how to initiate strengths-based conversations based on the recommendations made by Biswas-Diener et al. (2016). These conversations include giving positive feedback on the instances when employees used their strengths, checking whether employees identify with these spotted strengths and agree with the labels used to describe these strengths, and discussing suggestions for how to further these strengths (Aguinis et al., 2012; Linley, 2008; Locke & Latham, 1990) based on specific and challenging action plans (Locke & Latham, 1990, 2002, 2006).

1.2 Strengths Spotting Interventions and Managerial Coaching Behavior

According to Heslin et al. (2006), managerial coaching behavior consists of three components, i.e., guidance, facilitation, and inspiration. Guidance refers to clarifying expectations regarding employees’ work achievements and providing constructive feedback to help employees perform better in the future. Facilitation can be described as supporting employees to find new, creative solutions to deal with unexpected issues and improve their performance. Inspiration involves encouraging employees to fulfill their potential. Empirical evidence has highlighted that providing managers with opportunities to work on their coaching skills helps them to adapt to their new role as coach and increase their managerial coaching behaviors (e.g., David & Matu, 2013; Ratiu et al., 2017).

A strengths-spotting intervention may be a good opportunity to develop coaching skills with implications for all three coaching behaviors described by Heslin et al. (2006). As for guidance, by learning how to spot employee strengths, give strengths-based feedback that is closely connected to the lived experience of the employee (Biswas-Diener et al., 2016), and help employees set specific strengths development goals, managers are better able to clarify their expectations of employees and help employees to perform better in the future (Aguinis et al., 2012; Linley, 2008). These clarified expectations will benefit employees, no matter whether the focus is on signature or lesser strengths. As for facilitation, by learning how to identify employees’ strengths and having conversations with them about how to make better use of these strengths in situations they struggle with, managers acquire tools to support employees in finding creative solutions for challenging situations. For employees, drawing on either signature or lesser strengths may be a creative, new way to tackle challenges. As for inspiration, when managers know their employees’ strengths and how to give strengths-based feedback, they are better able to encourage employees to fulfill and evolve their potential. One may argue that inspiration will be greater when managers focus on employees’ signature strengths, the strengths that employees ‘own and celebrate’ (Peterson & Seligman, 2004). However, we argue that employees may feel equally inspired when managers use a positive frame of reference to help them work on the strengths they do not yet own.

In addition to the arguments above, Miglianico et al. (2020) argue that by teaching managers how to identify, use and develop their employees’ strengths, a growth mindset is promoted which allows managers to see their employees’ abilities as “a malleable quantity that can be increased with effort and learning” (Dweck et al., 2014, p. 5). This argument applies to both signature and lesser strengths. Empirical evidence has shown that a growth mindset is associated with an increase in coaching behavior by managers (Özduran & Tanova, 2017).

In sum, we propose the following hypotheses:

Hypothesis 1

Participating in a signature strengths spotting intervention results in an increase in managerial coaching behavior over time.

Hypothesis 2

Participating in a lesser strengths spotting intervention results in an increase in managerial coaching behavior over time.

1.3 Signature Strengths Versus Lesser Strengths Spotting

A Strengths Spotting Intervention (SSI), regardless of its focus on signature or lesser strengths, presumably helps managers to develop their coaching behaviors since it is concerned with identifying areas for development and planning for future development. Nevertheless, a signature strength spotting intervention might be more effective in this regard. We expect this based on a combination of strengths theory (Peterson & Seligman, 2004), emotional contagion theory (Hatfield et al., 1994), and the broaden and build theory of positive emotions (Fredrickson, 2004). First, because strengths theory proposes that working on signature strengths triggers feelings of excitement, invigoration, and authenticity, among others, (Linley, 2008; Peterson & Seligman, 2004), we expect that employees who are coached based on their signature strengths experience a stronger surge in positive emotions than employees who are coached based on lesser strengths. Second, theory on emotional contagion (Hatfield et al., 1994) proposes that humans tend to align with the emotions of others in social interactions and that emotions can be contagious by simply observing others (e.g., an employee with a strength in creativity who gives an enthusiastic pitch on an innovative way to reduce the workload may inspire coworkers). Due to the contagious nature of positive emotions (Van Kleef et al., 2009), we expect that managers will also experience a rise in positive emotions when discussing the signature strengths of their employees. Third, according to the broaden and build theory of positive emotions (Fredrickson, 2004), the rise in positive emotions will expand the manager’s mindset, in turn leading to exploration and approach behaviors. These behaviors are beneficial while coaching, allowing the manager to maintain an open and curious attitude towards employees, and to support them in exploring new avenues towards growth and success, which will in turn inspire positive emotions in the employee, and so on. This reciprocal effect of positive emotions in managers and employees would also be in line with theorizing on resource gain spirals (Hobfoll et al., 2018) suggesting that initial resource gain produces future resource gain and that these gain spirals may also develop in interpersonal dynamics (Halbesleben & Wheeler, 2015). Due to this iterative process triggered by an initial increase in employee positive emotions, we expect a stronger increase in coaching behavior among the mangers who participated in the signature strengths spotting, compared to the lesser strengths spotting intervention.

To our knowledge, there is no prior research that directly compares these two types of strengths spotting interventions in terms of their effect on managerial behavior. However, prior research shows that behavioral change interventions that focus on identifying, using, and/or developing a person’s signature strengths outperform interventions that focus on identifying and developing characteristics that are less central to a person, like lesser strengths. For instance, Meyers et al. (2015) found in two different experimental studies that students in a strengths intervention improved more on their personal growth initiative compared to students in a deficiency intervention. Also, Hiemstra and van Yperen (2015) found in two different randomized experimental studies that students in a strength-based self-regulated learning condition scored higher on professional development intentions compared to students in a deficit-based condition. Based on this reasoning and evidence, we propose the following hypothesis:

Hypothesis 3

Participating in a signature strengths spotting intervention results in a stronger increase of managerial coaching behavior over time compared to participating in a lesser strengths spotting intervention.

2 Method

To increase transparency, we report in our methods section how we determined our sample size, all data exclusions (if any), all manipulations, and all measures in the study as recommended by Simmons et al. (2012).

2.1 Participants and Procedure

The sample consisted of managers who supervised at least one employee. Managers were approached via the personal network of the researchers either in person, via e-mail, social media, or website/newsletter. After the managers signed up to participate in the study, they were randomly assigned to either the signature strengths spotting intervention, or the lesser strengths spotting intervention and were asked to fill in one pre-intervention (T1) and two post-intervention online surveys (T2, T3). Both the surveys and the interventions were available in Dutch and English. The total duration of this study was nine weeks. In the first week of the study, participants received an email with information about the study and a link to the first questionnaire (T1). Two weeks after receiving the first questionnaire, the strengths spotting interventions started and lasted for three weeks. Every week, participants received an email with a link to an online webinar and a corresponding assignment. One week after completing the strength spotting intervention, the participants received an e-mail with the link to a post intervention survey (T2). Four weeks after the intervention, they received the follow-up survey (T3). All surveys were the same except that demographics were only asked at the first measurement moment and some evaluative questions about the interventions were added at the second measurement moment.

In the beginning of 2021, 197 participants completed the first survey (T1). Subsequently in early 2022, 113 participants completed the second survey (T2) and 104 participants completed the last survey (T3). Since not all participants filled out all three measurements, we conducted a drop-out inquiry, which showed that the most frequent reason for ending participation was a lack of time. Additional analyses showed that the group of participants that dropped out did not score significantly different on managerial coaching behavior than the rest of the participants at baseline (F(1, 178) = 0.01, p = 0.93, Drop-outs: M = 3.38, SD = 0.72, Participants: M = 3.39, SD = 0.62). Although the setup of the research was identical over the different waves, contextual factors could have varied. For example, during the first wave (T1), there was a Covid-19 lockdown in the Netherlands (locality of most participants) resulting in people having to work from home. During the following waves in 2022 (T2, T3), the Covid-19 rules were less strict in the Netherlands, and people were allowed to work at the office again. Also note that Covid-19 led to additional workload for many managers.

Overall, we obtained 414 datapoints (L1) from 255 unique individuals (L2). The mean age of the participants was 43.14 years old (SD = 11.58) and the mean number of working hours per week was 36.52 h (SD = 5.83). Most participants had an academic or applied sciences bachelor’s degree (55.3%), followed by an academic master’s or doctorate degree (26.4%), and a vocational education or upper secondary education degree (17.8%). On average, participants reported a job tenure of 10.06 years (SD = 9.13) and most participants worked in industry (15.2%), health and welfare (13.7%), or the public administration and public services sector (12.2%). Most of the participants had the Dutch nationality (59.22%). Other reported nationalities were German (7.06%), Portuguese (4.71%), Belgian (2.35%), Ukrainian (2.35%), Surinamese (0.65%), Danish (0.39%), and Luxembourgish (0.39%).

2.2 Strengths Spotting Interventions

Both strengths spotting interventions (spotting signature strengths vs. lesser strengths) consisted of three 10-to-20-min online webinars which were prerecorded and available in both Dutch and English. German and Portuguese participants were also provided with a written script in their native language in case they had trouble understanding the English webinar. Each webinar was followed by an assignment which took 30 to 60 min to complete. Each week, participants received a link to the webinar and assignment on Monday morning and were given the opportunity to find a suitable time that week to watch the webinar and work on the assignment.

Both interventions were made as similar as possible to make sure that the effects of the intervention could be attributed to the difference in foci (signature strengths vs. lesser strengths) instead of other factors. Therefore, both interventions (webinars and assignment) were similar in length and content apart from the focus on either signature or lesser strengths. Moreover, the webinars of both interventions were delivered by the same person. In the first week managers were taught how to spot their own strengths based on the use of the VIA inventory of strengths (signature strengths intervention: top 5 strengths. Lesser strengths intervention: 5 lowest ranking strengths) and asking peer feedback (Peterson & Seligman, 2004). In the second week, managers were asked to spot the strengths of one of their employees (either signature strengths or lesser strengths) based on physical and voice ques (Linley, 2008), and label the identified strengths in terms of the 24 VIA character strengths (Peterson & Seligman, 2004). In the third and last week, managers were taught to give strengths-based feedback and set up a strengths-based conversation with their employee (Aguinis et al., 2012; Linley, 2008; Locke & Latham, 1990). In addition, since the employees probably work in teams, the managers were educated about strengths use in a team context (Meyers et al., 2023; van Woerkom, et al., 2020). See Table 1 and Table 2 for a detailed description of the content of the webinars, assignments, and the theoretical underpinnings for both interventions.

Table 1 Content of the webinars and assignments of the signature strength spotting intervention as well as its theoretical underpinnings
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Table 2 Content of the webinars and assignments of the lesser strengths intervention and its theoretical underpinnings
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2.3 Measures

2.3.1 Managerial Coaching Behavior

Managerial Coaching Behavior was measured with a 10-item scale developed by Heslin et al. (2006), covering three components of managerial coaching (i.e., guidance, facilitation, and inspiration). The items were slightly adapted to be self-rated by managers instead of rated by employees. Example items are “I provide guidance to my employees regarding performance expectations.” (guidance), “I act as a sounding board for my employees to help them develop their ideas” (facilitation), and “I support my employees in taking on new challenges” (inspiration). The items were rated on a five-point Likert scale, ranging from one (not at all) to five (to a very great extent). The data showed that a second-order model in which all items loaded on their respective managerial coaching dimensions, and ultimately on one managerial coaching factor, provided a good fit to the data (χ2 = 8268, df = 32; CFI = 0.98; TLI = 0.98; RMSEA = 0.05; SRMR = 0.03). A one-factor model fitted significantly worse (χ2 = 214.07, df = 35; CFI = 0.93; TLI = 0.91; RMSEA = 0.09; SRMR = 0.04; Δχ2 = 92.15; Δdf = 3; p < 0.001), while a three-factor model presented no significant improvement in fit (χ2 = 813.65, df = 35; CFI = 0.67; TLI = 0.57; RMSEA = 0.21; SRMR = 0.39; Δχ2 = 599.57; Δdf = 0; p > 0.05).

Therefore, we continued in the analyses with a unitary managerial coaching behavior variable. Cronbach’s alphas for this variable ranged between 0.85 and 0.93.

Because our study was part of a larger research project, we also included measures related to well-being (e.g., work engagement), personality (e.g., extraversion), positive emotions (e.g., optimism), and leadership (e.g., authentic leadership) that were not used in the current study.

2.4 Analyses

Prior to the actual analyses, we wanted to ensure that there were no pre-intervention differences between the signature strengths and lesser strengths intervention groups. One way ANOVA’s showed that at baseline managerial coaching behavior was significantly higher in the lesser strengths group (Mlesser = 3.55, Msignature = 3.34, F(1, 195) = 2.30, p = 0.029, η2 = 0.024), but aside from this, there were no significant differences in age (F(1, 195) = 37.48, p = 0.598, η2 = 0.001), work hours (F(1, 195) = 0.34, p = 0.921, η2 = 0.001), or tenure (F(1, 195) = 72.86, p = 0.405, η2 = 0.004). Chi square tests also showed no significant differences in educational level (χ2(3) = 3.60, p = 0.308) or gender composition (χ2(1) = 0.01, p = 0.908) between the two groups.

We defined two levels in our data, namely the within-person level (L1: time) and the between-person level (L2: individual manager level). Therefore, to account for the nested structure of the data (managerial coaching behavior: ICC(1) = 0.45, ICC(2) = 0.57), we adopted hierarchical linear modelling (HLM) with full maximum likelihood (FML). In doing so, we report the marginal R2 (i.e., variance explained by fixed effects) and the conditional R2 (i.e., variance explained by both fixed and random effects). While our L1 (n = 414) and L2 (n = 255) sample sizes were considered large enough to test the hypotheses in the research model (L1 ≥ 200, L2 ≥ 30; Arend & Schäfer, 2019), we also conducted a post-hoc power analysis using Monte Carlo simulations in SIMR (Green & MacLeod, 2016). Almost all predictors where L2 predictors and thus grand mean centered as per recommendations (cf. Enders & Tofighi, 2007). Dummies where not centered. Time was also not centered and treated as a continuous variable, which is appropriate given the unequally spaced timepoints in our dataset (de Haan-Rietdijk et al., 2017). The main analyses were performed on data in long format with nlme (Pinheiro et al., 2017) in R v.4.2.2. The data and codebook used to conduct the analyses are freely available at OSF (Tobias et al., 2024).

3 Results

3.1 Descriptive Statistics and Correlations

Figure 1 displays the association between the two intervention groups and managerial coaching behavior over time. As can be seen in this figure, an increase of managerial coaching behavior over time can be witnessed in both groups. Table 3 reports the means, standard deviations, and correlations of the study variables. There was a significant negative correlation between intervention (signature strengths) and managerial coaching behavior (r = − 0.15, p < 0.01). This mirrors the finding that the signature strengths group displayed lower levels of managerial coaching behavior than the lesser strengths group at the first measurement point. Managerial coaching behavior was also significantly positively correlated with time (r = 0.30, p < 0.01), indicating an increase in coaching behavior across the three measurement points. Age (r = 0.15, p < 0.01), tenure (r = 0.16, p < 0.01), education (r = 0.20, p < 0.01), and work hours (r = 0.22, p < 0.01) also correlated significantly with managerial coaching behavior. As suggested by Bernerth and Aguinis (2016), such bivariate associations indicate the need to control for these variables in further analyses.

Fig. 1
figure 1

Note: Time 1 = two weeks before the start of the intervention, Time 2 = one weeks after the end of the intervention, and Time 3 = four weeksn after the end of the intervention

Plot of association between condition and managerial coaching over time.

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Table 3 Descriptive statistics and correlations
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3.2 Hypotheses Testing

Table 4 reports the HLM results. First, we estimated a random intercept model (Model 1) for managerial coaching behavior to assess the respective variances at the within (time) and between (individual) level. Since 55.90% of the variance is situated at the within-person level and 44.10% at the between level, the use of multilevel modelling is warranted. Subsequently, we estimated a predictive model (Model 2) which only includes the effect of the control variables. In subsequent steps, we added the main effect of intervention (Model 3) and the interaction effect of time and intervention (Model 4). Finally, we estimated a random slopes model (Model 5) in which we allowed the slope for intervention on managerial coaching behavior to be random across time. Model 5 is the best model to test our hypotheses, based on a lower Deviance score and smaller value for the Akaike Information Criterion (AIC; Hox et al., 2017). Based on 1000 repetitions and an α of 0.05, a post-hoc power analysis indicated a power of 78.40% (95% CI: LL = 75.72, UL = 80.91). In line with Hypothesis 1 and Hypotheses 2, we see a significant increase of managerial coaching behavior over time (Model 2: b = 0.21, CI 0.16–0.27, p =  < 0.001) and this effect seems rather consistent across models, even when the intervention is introduced into the model (Model 3: b = 0.21, CI 0.16–0.27, p =  < 0.001) or its interaction with time (Model 4: b = 0.23, CI 0.15–0.30, p =  < 0.001) and random slopes are considered (Model 5: b = 0.21, CI 0.14–0.28, p =  < 0.001). Counter to Hypothesis 3, there is no significant interaction between intervention and time (Model 4: b = − 0.02, CI − 0.13 to − 0.08, p = 0.650), also not when slopes are allowed to be random (Model 5: b = 0.01, CI − 0.10 to − 0.09, p = 0.906). This means that the signature strengths spotting intervention did not lead to a stronger increase in managerial coaching behavior than the lesser strengths spotting intervention. A negative relationship between signature strengths spotting intervention and coaching behavior is visible in multiple models (Model 3: b = − 0.18, CI − 0.34 to − 0.02, p = 0.027; Model 4: b = − 0.19, CI − 0.36 to − 0.03, p = 0.024; Model 5: b = − 0.17, CI − 0.32 to − 0.03, p = 0.024). This indicates that across all time points, participants of the signature strengths intervention scored lower on managerial coaching behavior than participants of the lesser strengths intervention. However, based on Fig. 1, it seems that both groups experienced proportionally similar growth over time.

Table 4 Hierarchical linear modelling (HLM) results for models predicting Managerial Coaching Behaviors
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4 Discussion

Due to the increasing focus on employee learning and development (Fatien & Otter, 2015), managers are more and more expected to provide coaching as part of their management role (Heslin et al., 2006; Lawrence, 2017). However, managers often lack the necessary skills and support from their organizations to effectively implement coaching behavior (DiGirolamo & Tkach, 2019; Fatien & Otter, 2015). For this reason, we investigated whether a strengths spotting intervention can be utilized to elicit managerial coaching behavior. More specifically, we compared the effects of two different kinds of strengths spotting interventions (i.e., signature strengths spotting vs. lesser strengths spotting) on managerial coaching behavior. Our results showed that both types of strengths spotting interventions were related to increases in managerial coaching behavior over time and that this increase did not differ between both interventions.

Our results indicate that training managers in spotting either the most prominent strengths, or the lesser strengths of their employees might function as a steppingstone to boost managerial coaching behaviors in terms of providing guidance, facilitation, and inspiration to employees (Heslin et al., 2006). Since all three coaching behaviors aim to bring out the best in employees and to stimulate their growth and development, particularly the strengths development part as advocated for by scholars like Linley et al. (2010) and Biswas-Diener et al. (2016) may have helped the managers to develop their coaching behavior. Using a strengths development approach may instill a growth mindset in managers (Biswas-Diener et al., 2011; Dweck, 2016), which has been shown to positively impact managerial coaching behavior (e.g., Han & Stieha, 2020). Future research could investigate whether the relationship between an SSI and managerial coaching is indeed mediated by the mindset of the manager.

We hypothesized that a signature strengths spotting intervention would lead to a larger increase in coaching behavior, because witnessing positive emotions in employees when discussing their signature strengths could lead to more positive emotions in managers due to emotional contagion (Hatfield et al., 1994; Van Kleef et al., 2009). Because positive emotions encourage approach behavior towards others, as well as novel thoughts and actions (Fredrickson, 2004), they might also stimulate managers to expand their coaching skills even more than managers who engage in lesser strengths spotting. However, contrary to our hypothesis, our results indicated that both interventions led to similar increases in managerial coaching behavior over time. Possibly, managers who engage in positively framed conversations with employees elicit positive reactions from them, independent of whether these conversations concern signature or lesser strengths. This reasoning would be in line with the findings of a previous study by Proyer et al. (2015) that has shown that participating in a signature strengths intervention and a lesser strengths intervention had highly comparable results when it comes to its effect on happiness, enjoyment, and satisfaction with life. This may indicate that working on lesser strengths may be equally rewarding for employees as working on signature strengths. Therefore, the emotional contagion-, as well as broaden-and-build processes that affect managers might be similar across interventions. If so, this could possibly solve the problem that is raised by scholars like Peterson (2006) and Rust et al. (2009) who criticize a strengths-based approach for ignoring a person’s weaknesses, since our research indicates that this approach can be used as a positive framework to work on the ‘less developed sides’ of employees as well.

In addition, it is possible that emotional contagion processes play a less important role than we assumed. Instead, the broaden-and-build processes (Fredrickson, 2004) that lead managers to approach their employees and embrace new (coaching) behaviors may have been set in motion more directly by the interventions which both provide managers with a clear, positive framework that they can apply in their daily interactions with their employees. This may arouse enthusiasm among managers and may inspire them to coach their employees. Learning that there are positive ways to address employees’ weaker areas, may even be particularly uplifting for managers in the lesser strengths-spotting intervention. This would be supported by van Woerkom and de Bruijn (2016) who argue that performance appraisals that focus on employee weaknesses lead to frustration and dissatisfaction, making it an unpleasant experience for employees and managers alike. Instead, by addressing weaker areas in a positive way and seeing them as strengths that are present, but less prominently developed, performance appraisal (or coaching) might become more uplifting and pleasant. Future research will be needed to clarify the mechanisms that explain the positive effects of strengths spotting interventions on managers’ coaching behavior. In addition, it might also be valuable to look at possible moderating variable that might affect the relationship between an SSI and managerial coaching. For example, the intervention might be less valuable for manager that have already received training in how to coach their subordinates. Also, managers’ interpersonal skills such as their abilities to communicate and motivate others (Carvalho et al., 2021), or the time constraints these managers experience (McCarthy et al., 2020) may affect the effectiveness of an SSI.

4.1 Limitations and Future Research

The results of this study are subject to several limitations. First, because both conditions saw an increase in managerial coaching behavior from baseline to follow-up and since baseline managerial coaching behavior was significantly higher in the lesser strengths group, our results should be interpreted with caution. Given these results we cannot rule out that other factors besides the intervention might have played a role in this effect (i.e., effects of repeated testing, Hawthorne effect etc.). Future research might therefore add a waiting list control condition. Also, a one-month follow-up might not have been sufficient to detect behavioral changes because it might take some time to transfer newly developed skills to the workplace (Baldwin & Ford, 1988). Therefore, our follow-up measure may only have captured managers’ first attempts to try out their newly learned skills on the job (Axtell et al., 1997; Laker, 1990).

Second, although the final sample size was quite large (N = 255), we only collected 414 data points (of the 765 which we planned to collect) due to participant dropout. Although steps were taken to prevent dropout (short webinars, frequent reminders, and the possibility to watch the webinars and work on assignments at a moment of one’s own choosing), not all participants filled-out all surveys due to various reasons. Since part of the study took place during the Covid-19 pandemic, it was challenging to keep participants involved due to the high levels of workload for managers during the pandemic (e.g., Slaymaker, et al., 2023). However, our additional analyses showed that participants who dropped out were not different from the remaining other participants in terms of their coaching behavior. Therefore, it can be assumed that our results are not influenced by attrition bias. Still, it is recommended for future research to take further measures to limit dropout. These measures may include shortening the questionnaire to increase response rates (Nakash et al., 2006) and combining online with face-to-face intervention elements to lower attrition (e.g., Cunningham et al., 2014).

Third, since most of the participants were from the Netherlands, our findings can only be generalized to populations with similar cultures. Coaching behaviors shown by managers depend on underlying cultural values and non-western cultures might value different approaches to coaching than coaches in western counties like the Netherlands (Noer et al., 2007). Therefore, the application of an SSI in non-western cultures warrants further research.

Fourth, we measured managerial coaching behavior based on managers’ self-reported data, which can lead to socially desirable answers even when anonymity is guaranteed (Rosenman et al., 2011). For future research, it is therefore suggested to also include ratings of subordinates. Moreover, it would also be interesting for further research to investigate the effects of an SSI on employees via managerial coaching. For example, it would be interesting to investigate whether employees actually get more motivated to develop themselves and whether results are equal for both types of SSI’s.

Fifth, to stimulate intervention fidelity, we made use of short, pre-recorded webinars that participants could watch at a convenient time and we gave detailed assignment instructions. However, we were not able to check whether participants completed assignments in line with the instructions, making it impossible to guarantee complete intervention fidelity. Future intervention research could therefore check whether participants have correctly executed and completed the assignments that are part of the intervention.

4.2 Practical Implications

Although coaching is increasingly seen as a managerial responsibility, managers are often not adequately trained to take on the role as coach (Fatien & Otter, 2015; Ladyshewsky, 2010; McCarthy & Milner, 2020). Our results suggest that an SSI, regardless of its focus on signature or lesser strengths, is a useful tool for organizations that want to increase coaching behaviors among their managers. This training intervention may help managers to fulfill their role as coach (e.g., Ratiu et al., 2017), by giving them tools to bolster their subordinates’ development with a non-directive and trust-driven, positive approach (Ladyshewsky, 2010). Moreover, our study indicates that these results can be accomplished with an online intervention which does not take up too much of managers’ valuable time. In addition, our results indicate that both the spotting of signature strengths and of lesser strengths can function as a starting point of guiding, facilitating and inspiring employees to realize their potential. Possibly, the focus on strengths, irrespective of whether these are prominent or still underdeveloped, functions as a positive frame of reference that inspires managers to engage in coaching behaviors.

5 Conclusion

The importance of managerial coaching for employee outcomes and how to elicit these kinds of behaviors has started to get more attention in research (e.g., Carrell, et al., 2022). The present study shows that a strengths spotting intervention, regardless of its focus on employees’ signature strengths or lesser strengths, can help managers to increase their coaching behaviors. Therefore, our study highlights that learning to have an eye for employees’ strengths can be the starting point of becoming a coaching manager that helps employees to realize their potential.