Student: Judy Middelburg ANR: Project theme: Strengths intervention. Project period: January 2014 summer 2014

Transcription

1 Strengths Intervention and Performance; The moderating role of Proactive Personality in the relation between Strengths Intervention, Strengths Use and Organizational Citizenship Behaviour. Student: Judy Middelburg ANR: Project theme: Strengths intervention Project period: January 2014 summer 2014 Supervisors: Marianne van Woerkom & Christina Meyers 1

2 ABSTRACT This study examines the impact of a strengths intervention on strengths use and organizational citizenship behavior (OCB). It was hypothesized that the intervention would increase strengths use and in turn would lead to increased OCB. Also a positive direct effect of strengths intervention on OCB was proposed. Besides this, the effect of the personality trait proactive personality on the relationship between strengths intervention and strengths use was investigated. Employees who scored higher on proactive personality were expected to use their strengths more in their work and it was expected that the intervention would have a bigger influence on them. A longitudinal field experiment has been done to test these predictions. In total 71 respondents filled out two questionnaires and 32 respondents took part in the intervention. This intervention consisted of a strengths workshop in which participants focused on their strengths and made a plan how to use these strenghts in their work. Contradictory to the expectations, no increase in strengths use was found after the intervention. In fact, a decrease in strengths use was found one month after the intervention, instead of the expected increase. In addition, no positive effect of proactive personality on the relationship between strength intervention and strengths use was found. In contrast to these non-supportive outcomes, results of this study did partly support the positive effect of strengths use towards OCB. A positive relationship between strengths use and self-rated OCB was found, whereas for peer-rated OCB no significant results were observed. In addition, also the positive effect of the intervention on OCB was partly confirmed. On the one hand, no significant effect of the intervention on self-rated OCB was found. On the other hand, the results for peer-rated OCB showed a significant interaction effect between the two groups over time, which means that the intervention caused differences in the outcomes of the two groups for peer-rated OCB. 2

3 INTRODUCTION Traditionally the focus of psychology was on curing diseases and repairing damage (Seligman, Steen, Park, & Peterson, 2005). However, during the last decade positive psychology became more popular, which in the first place shifted the focus back on mental health and well-being (Seligman et al., 2005). Positive psychology is described as a science of positive individual traits, positive institutions and positive subjective experiences (Meyers, van Woerkom, & Bakker, 2012). This is the recent movement of positive psychology which has drawn attention to the study of strengths and the development of positive qualities, next to focusing on health and well-being (Wood, Linley, Maltby, Kashdan, & Hurling, 2011). This new field of research has also captured the attention of organizational psychologists, because according to Buckingham and Clifton (2001), improvement in work performance could best be reached when focusing on talents and strengths, since it enables employees to excel in their strengths and consequently allows them to increase their personal and organizational performance. An effective way to stimulate strengths use at the workplace is strengths intervention (Meyers et al., 2012). A strengths intervention is a process designed to identify and develop strengths in an individual or group (Quinlan, Swain, & Vella-Broderick, 2011, p. 1147) and interventions foster the individual to use and develop their strengths (Quinlan et al., 2011).Therefore, within this study, we test Buckingham and Clifton s assumption about the positive effect of strengths use on performance and the effectiveness of strengths intervention in improving strengths use and performance. In more detail, in this study it is expected that strengths use leads to energizing experiences and makes employees feel good about themselves (Wood et al., 2010). As a consequence, their enthusiasm about and interest in their work increases which eventually stimulates increased performance (van Woerkom & Meyers, in press). In addition, the broaden-and-build theory states that employees who feel good about themselves, what could 3

4 be achieved by strengths use (Wood et al., 2012), will increase their extra-role behaviours, since strengths use expands people s creativity, makes sure they push their limits, help others and envision greater achievements in the future (Frederickson, 2001). This positive effect of strengths use on these extra-role behaviours will be studied. Extra-role behaviours are a principal facet of job performance (Stoner, Perrewé, & Munyon, 2011). One well known form of extra-role behaviors is organizational citizenship behavior (OCB) (Stoner et al., 2011). OCBs are those non-required, not formally rewarded behaviors and efforts that are intended to benefit the organization (Chen et al., 2009). In this study, OCB is expected to be positively influenced by strengths use. Besides the expected positive relationships between strengths use and OCB and strengths intervention and strengths use, strengths use is expected to mediate the relationship between strengths intervention and OCB. The proposition in this study is that strengths use will partially mediate the relationship between strengths intervention and OCB, since the expectation is that there will be a direct effect of strengths intervention on OCB as well. According to Cropanzo & Mitchell (2005), strengths intervention will lead to enhanced performance. Based on the social exchange theory, they state that when employees get support from their organization, e.g. by the organization of a strengths workshop, that would predict OCB, since people feel more committed and are more willing to do something extra for the organization in return. Furthermore, it is likely to assume that personality traits could affect the relationship between strengths intervention and strengths use. Proactive personality is a behavioral ability to identify opportunities to change things at work and to act on those impulses (Li, Liang, & Crant, 2010). The assumption for this study is that the effects of the intervention will be higher for participants who score high on proactive personality and lower for people who score lower on this trait. The initiative of employees with a proactive personality leads to a 4

5 number of cognitions and behaviors, such as identifying new ideas for improving work processes, seeking to better understand company politics and updating their skills (Li et al., 2010). A logical consequence of this would be that people with these characteristics will react more positively to the intervention and because of their active attitude they will see more chances to use their strengths in their work than people with a less proactive personality. Therefore, proactive personality is expected to function as a moderator in the relationship between strengths intervention and strengths use. Thus, the present study aims at developing a strengths intervention that will increase strengths use and OCB, with a moderation effect of proactive personality. This study will contribute to the existing literature which demonstrated the positive effects of strengths interventions on subjective experiences and not yet on objective performance measures (Meyers et al., 2012). Furthermore, this study will be among the first studies to investigate moderating and mediating mechanisms through which these interventions operate. According to a study of Quinlan et al. (2011), it is not clear yet which effects will occur after an intervention and how these might trigger employees to increase the effectiveness of an intervention. Therefore, the following research questions emerged: What is the effect of a Strengths intervention on Strengths use and Organizational Citizenship Behavior and to what extent is the relationship between the Strengths intervention and Strengths use moderated by Proactive personality? 5

6 THEORETICAL FRAMEWORK Strengths intervention and Strengths use Psychological strengths are 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., 2011, p. 1146). Several researchers have argued that using strengths entails individual benefits such as feelings of happiness and fulfilment (Buckingham & Clifton, 2001; Clifton & Harter, 2003; Quinlan et al., 2011). Although strengths use seems to be important, most employees are not able to identify and use their own strengths by themselves (Biswas-Diener et al., 2011). Biswas-Diener et al. (2010) studied the relevance of the identification of strengths and their use by investigating the identify and use approach. According to their study, the majority of people is not able to identify their own strengths and they do not use their strengths very often at work. These results assume that people need a specific tool or stimulator to discover and use their strengths. In order to emphasize the value of individual strengths and to stimulate strengths use, organizations can use strengths interventions (Quinlan et al., 2011). Quinlan et al. (2011) define strengths intervention as a process designed to identify and develop strengths in an individual or group (p. 1147). Interventions are relatively easy to implement and brief (van Woerkom & Meyers, in press). When employees are aware of their strengths and know how to use and develop those strengths, they could also see more opportunities to apply their strengths in their work. In addition, the positive activity model of Lyubomirsky and Layous (2013) states that positive activity interventions increase positive behaviours such as strengths use. Positive activities are positive for an individual since they stimulate increases in positive emotions, positive thoughts and positive behaviours (Lyubomirsky & Layous, 2013). One form of a 6

7 positive activity is the cultivation of a person s strengths, which is the goal of a strengths intervention (Lyubomirsky & Layous, 2013). Therefore, in this study the expectation is that an intervention which cultivates strengths has a positive effect on strengths use. In other words, the level of strengths use after the intervention will be higher compared to the preintervention level of strengths use. Quinlan et al. (2011) already acknowledged in their study that strengths use is essential, if an individual is to benefit from a strengths intervention. Building on the above arguments, the following hypothesis has been formulated: H1: Strengths intervention has a positive effect on strengths use. Strengths use and OCB Beside the proposed positive effect of strengths intervention on strengths use, there are also a lot of studies which investigated the relevance and the positive effects of strengths use. The use of personal and psychological strengths has been suggested to lead to energizing experiences and elevated, sustainable wellbeing, which are subjective experiences (Wood et al., 2010). To explain the effects on individual performance, on the other hand, different theories could be used. Performance is a very broad topic. Two principal facets of the job performance construct are in-role performance and extra-role performance (Stoner et al., 2011). In-role performance are standard job activities and formal tasks, according to the job description (Chen et al., 2009). Extra-role behaviours are outside the officially prescribed boundaries of one's work description (Kane, Magnusen, & Perrewé, 2012). Extra-role performance involves activities that aid the organization but are not explicitly required and discretionary in nature, such as aiding fellow employees, taking actions that protect the company from risks, offering constructive suggestions and gaining knowledge and skills that are beneficial for the organization (Chen et al., 2009). Organizational citizenship behaviour (OCB) is a well- 7

8 known form of extra-role behaviours (Stoner et al., 2011). Organizational citizenship behaviours are those organization-directed behaviours that go above and beyond normal task performance and are critical to the effective functioning of any organization (Kane et al., 2012, p. 29). To explain the effects of strengths use on individual performance, the broaden-andbuild theory could be used to explain the relationship between strengths use and OCB. The broaden-and-build theory of Fredericksen (2001) states that employees who feel good about themselves are motivated to approach stimuli, feel more curiosity and show exploratory behavior (van Woerkom & Meyers, in press). Strengths use is assumed to lead to energizing experiences and makes employees feel good about themselves (Wood et al., 2010). As a consequence, their enthusiasm about and interest in their work increases which will stimulate OCB (van Woerkom & Meyers, in press). Thus, strengths use could lead to OCB, since strengths use expands people s creativity, makes sure they push their limits, help others and envision greater achievements in the future (Frederickson, 2001). According to Biswas- Diener et al. (2011) strengths use is an important motivator for employees and leads directly to more passionate work since strengths often interact with personal values and interests and therefore it increases individual performance. According to above arguments a positive relationship between strengths use and OCB could be expected: H2: Strengths use has a positive effect on OCB An increase in strengths use mediates the relationship between the strengths intervention and increase in OCB. This partial mediation can be derived from hypotheses 1 and 2, where the relationships between the intervention and increase in OCB are described. Thus, in this study it is expected that the strengths intervention has a positive effect on 8

9 strengths use and strengths use will lead to an increase in OCB. Strengths intervention also has a positive direct effect on OCB. To the best of my knowledge, this study will be among the first studies to investigate this mediating mechanism. The following hypothesis is formulated: H3: Strengths use partially mediates the relationship between strengths intervention and OCB The direct effect of Strengths intervention on OCB Besides the expected mediating effect of strengths use in the relationship between strengths intervention and OCB, there are also theoretical implications to expect the direct effect of strengths intervention on OCB. Meyers et al. (2012) did a literature review of 15 studies of which only four of these studies investigated performance. In two of those studies they found evidence that positive psychology interventions, of which strengths intervention is an example, should have a positive effect on performance. They state that positive interventions are probably a promising tool for enhancing performance (Meyers et al. 2012), which will be further investigated in this study. Besides this, a theory that could explain the relationship between strength intervention and OCB is the Social exchange theory. The Social exchange theory states that there is an exchange of activity, tangible or intangible, and more or less rewarding or costly, between at least two parties (Cook, Cheshire, Rice, & Nakagawa, 2013, p.54). To apply this theory to this study; when an organization arranges a positive activity by organizing a strengths workshop for their employees, the expectation is that the employees will show positive extra-role behaviour after the workshop, as an exchange to the effort of the organization. Furthermore, Cropanzo & Mitchell (2005) found in their study that the Social exchange theory is a theoretical explanation for organizational citizenship behaviour. They state that when people get support from their organization, e.g. by the organization of a strengths workshop in case of this study, that would predict OCB, since 9

10 people feel more committed. Consequently, the following is hypothesized based on theoretical arguments: H4: Strengths intervention has a positive effect on OCB The effect of Proactive Personality It is likely to assume that strengths interventions will have a bigger effect on certain persons than on other persons. Numerous studies of personality have documented high variability in study results across individuals (Clifton & Harter, 2003). The way people grow or develop is related to who they are, that is their personal characteristics (Clifton & Harter, 2003). One example of a personality trait is proactive personality (Crant, 2000). According to Li, Liang & Crant (2010), proactive personality and OCB share a focus on behaviors that go beyond direct role requirements and because of this similarity it is expected that proactive personality will affect the outcomes of this study in a positive way. Proactive personality is a behavioral ability to identify opportunities to change things at work and to act on those impulses ( Li et al., 2010). Employees initiative leads to a number of cognitions and behaviors, such as identifying new ideas for improving work processes, seeking to better understand company politics and updating their skills (Li et al., 2010). In comparison to more passive workers, employees with a proactive personality are more likely to actively shape and manipulate the environment to accomplish their goals (Li et al., 2010). In a study of Thompson (2005) proactive personality was a predictor of objective measures, like career success and outcome-based performance measures. Therefore, in this study it is expected that employees with a higher score on proactive personality will have more profit from the strengths intervention, since they will see more opportunities to shape their job in such a way they have more room to use their strengths more often in their job. It is proposed that employees with a proactive personality will take sooner initiative than people with less 10

11 proactive personalities, because the intervention will trigger those employees more to take initiative to search for extra opportunities to use their strengths in their work. Therefore, hypothesis 5 is formulated: H5: Proactive personality moderates the relationship between Strengths intervention and Strengths use The research question and hypotheses can be visualized in the conceptual model presented below. Proactive personality Strengths intervention + + Strengths + use + Organizational citizenship behavior + METHODS Research set-up In order to test the hypotheses, a quasi-experimental study was conducted. All research participants were divided into two groups, an experimental and a waitlist-control group. During the subscription period, participants could choose among four dates to subscribe for the workshop, not knowing they would belong to different research groups. Employees who subscribed for one of the first two workshops were in the experimental group and the other employees were in the waitlist-control group. The experimental group participated in a strengths training, in which they identified their strengths and reflected on how to deploy their strengths into their jobs. The workshop for the control group took place after the research was finished. Participants were asked to fill in three questionnaires at three different points in 11

12 time, one two weeks before the first workshop, one immediately after the workshop and one four weeks after the workshop. The experimental group filled in two of the three questionnaires online and the questionnaire immediately after the workshop with paper and pencil. The control group filled in all three questionnaires online. Sample The respondents all work at Heijmans, a Dutch construction company. The study was conducted at Young Heijmans, a special part of the organization Heijmans. The employees who are member of Young Heijmans received an invitation with information about the study and the strengths workshop. Employees could subscribe voluntarily to participate in the workshop. In the end, we strived to include a sample of 100 employees in this study, of which 50 employees would be in the experimental group and 50 in the control group. Finally, we had a total sample of 71 employees who filled in the first questionnaire, of which 32 were in the experimental group and 39 were in de control group. The sample consisted of 47 male (66.20%) and 24 female (33.80%) respondents. The average age of the respondents was (SD = 3.54, range years). The respondents were highly educated, 75% completed higher or academic education. The one month follow-up questionnaire was filled in by 57 respondents. Procedure This study is a longitudinal field experiment with three measurement waves (t1=baseline, t2=immediate post-measurement, t3=one month follow-up). In total there were four workshops, on average 18 people participated in each workshop. Two weeks before the first workshop all participants were asked to complete an online questionnaire (pre-test). In addition, also one colleague of each participant was asked to fill in a questionnaire about their 12

13 view of the functioning and extra-role behavior (OCB) of the employee. Two weeks later the experimental group participated in the workshops. After the workshop both groups filled in an immediate post-measurement questionnaire. Four weeks after the first workshop, the experimental group received the third questionnaire (post-test), in order to measure their work outcomes after the intervention. Also the same colleagues had to fill in a questionnaire about the participants. The control group and their colleagues filled in the questionnaires at the same time, to investigate if there were differences in outcomes between the two groups. The workshops for the control group took place after all research questionnaires had been filled in. Instruments Dutch questionnaires were used to measure the variables strengths use, proactive personality and organizational citizenship behaviour. The variable proactive personality was only measured in the pre-test, because it was a trait like variable and the moderation effect of this variable was tested. Gender and educational level of the respondents were used as control variables. Factor analyses and reliability analyses of all scales were conducted (Pallant, 2007). To test the reliability of the scales by interpreting Cronbach s alpha, values above.70 are considered acceptable, but values above.80 are preferable. If values were below.70, the reliability was questionable and probably unacceptable (George & Mallery, 2003). The data was adequate for being subjected to factor analysis, when the Kaiser-Meyer-Olkin (KMO) had a minimal value of.60 (Pallant, 2007). To determine the factor structure, we looked at the eigenvalues and screeplot. 13

14 Proactive personality During this study the Proactive Personality Scale of Claes, Beheydt, & Lemmens, (2005) was used to measure this variable. An example question was: I am always looking for better ways to do things. This questionnaire included a total of six items which were all answered using a 7-point rating scale which ranges from certainly not agree (1) to certainly agree (7). In this study, factor analysis indicated a KMO of.77 with a significant value on the Bartlett s test (p=.00). All factors were loading on one component, also the eigenvalues and screeplot confirmed that only one eigenvalue was above 1 (2.89). Reliability analysis illustrated an acceptable Cronbach s α of.78. Alpha it Item Deleted showed that none of the items would increase the reliability if they were deleted. Also all Corrected Item-Total Correlations were above.30, which indicated a good internal consistency. Organizational citizenship behaviour OCB was assessed with a 6 item scale which covered interpersonal facilitation (3 items) and job dedication (3 items), by Van Scotter, Motowidlo, & Cross (2000). OCB was measured by a self-rated scale, but also by a peer-rated scale. Participants answered questions about themselves and a colleague also filled in questions about the participant. An example question of the self-rated scale at pre-measurement was: I praise co-workers when they were successful. An example question of the self-rated scale at the one-month follow-up measurement was: Last month I helped others uninvited. Colleagues rated a participant with for example the question: This employee praised co-workers when they were successful. All respondents used a 10-point Likert-type scale to indicate the relative strength of their agreement or disagreement with responses ranging from 1 (totally not applicable to me) to 10 (totally applicable to me). 14

15 Factor analysis (PCA) of the self-rated scale at pre-measurement illustrated a KMO of.69 and a significant value on the Bartlett s test (p =.00). The result of the factor analysis and the screeplot indicated the option of two factors. The first factor had a big Eigenvalue of 2.56 in comparison to the other factor (1.32). On basis of these outcomes and the literature of Van Scotter et al. (2000), who distinguished two dimensions of OCB, this should be a logical result. According to the literature of Van Scotter et al. (2000), three items should load on job dedication and three on interpersonal facilitation. However, this was not the case since all six items loaded on one factor and the third until the sixth item loaded on the second factor. In total these factors explained 64.62% of the variance. Because this result did not correspond exactly with what was expected on basis of theory, a one factor solution was forced. This resulted in a lowest factor loading of.49, which was also the lowest value of the two factor solution. Because the two factor solution did not meet the theoretical expectations, there was decided to opt for a one-factor solution. Reliability analysis illustrated a sufficient Cronbach s α of.70. Alpha it Item Deleted showed that if the item I say things that give others a good feeling about themselves or their team was deleted, the reliability would increase to.71. Also the Corrected Item-Total Correlations of this item was lower than.30 (.28), which indicated an insufficient internal consistency. Despite these results there was decided not to remove this item, since the difference in reliability would be very small. The self-rated scale used for the measurement after the intervention, had a KMO of.56 with a significant value on the Bartlett s test (p=.00). The results of the factor analysis and the screeplot indicated the option of three factors. On basis of the literature of Van Scotter et al. (2000), who distinguished two dimensions of OCB, a two factor solution was forced to test if these dimensions were shown. Again, the PCA did not divide the items towards the two factors which could be linked to interpersonal facilitation and job dedication, as was proposed by theory. Therefore, a one-factor solution was also forced and these results showed that all 15

16 items loaded on one factor, with a lowest factor loading of.21. Even though this is very low, there was opted for the one factor solution as for self-rated OCB at pre-measurement that was also the case. With regard to the reliability, the Cronbach s α was.65. Alpha if item deleted showed that if the item Last month I helped others uninvited was deleted, the reliability would increase to.69. Also the Corrected Item-Total Correlation was lower than.30 (.11). All these results indicate that this item should be removed. However, if the item would be removed in this scale, it should also be removed in the pre-measurement scale. In the pre-measurement scale, this item contributed to the reliability and also the Corrected Item-Total Correlation was sufficient (.40). For this reason there was decided not to remove this item. For the peer-rated scale at pre-measurement, the Cronbach s α was.70. Only the item this employee praises coworkers when they are successful had a lower Corrected Item-Total Correlation below.30 (.29). The Cronbach s α would stay the same if this item was deleted, so the item was not deleted. The KMO of this scale was.60 with a significant value on the Bartlett s test (p=.00). Factor analysis indicated a two factor solution and this was also supported by the screeplot. All items loaded on one factor and only three items (item 2, 5 and 6) loaded on the second factor. In total these factors explained 66.07% of the variance. A one factor solution was forced, again based on the incorrect item division with regard to job dedication and interpersonal facilitation of Van Scotter et al. (2000). The lowest factor loading in the one factor solution was.50 and the variance explained was 40.63%. Even though the percentage of variance explained became lower by using a one factor solution, still there was opted for a one-factor solution in this research, because of the high factor loadings on one scale. 16

17 The Cronbach s α of the one month follow-up measurement of peer-rated OCB was.65. Only one item scored lower than.30 on the Corrected Item-Total Correlation (.27), but because the Cronbach s α would not become higher if this item would have been deleted, this item was not removed. Factor analysis indicated a KMO of.55 with again a significant value on the Bartlett s test (p=.00). The result of the factor analysis indicated the option of three factors, with these factors explaining 77.37% of the variance. The screeplot supported the outcome of a three factor solution. When a two factor solution was forced, based on the theoretical expectations, the theoretical division of the items over the two dimensions of OCB was not found. Two factors explained 58.84% of the variance. When a one factor solution was forced, the lowest factor loading would become.36 and the variance explained would be 37.65%. Even though the lowest factor loading and the total variance explained were not that high, there was still opted for a one factor solution since for peer-rated OCB at premeasurement this was also the case. The conclusion of these results indicate that in none of the factor analyses the items were divided towards the two dimensions job dedication and interpersonal facilitation, as expected by the theory of Van Scotter et al. (2000). Therefore a consistent solution was found and there was decided to opt for one OCB scale. Strengths use The scale used for strengths use was a scale developed by Van Woerkom et al. (under review). Slightly different versions were used for baseline and follow-up measurement. This scale was constructed out of 9 items, but depending on the pre- or post-measurement, the wording of the scale was adapted slightly. All questions were measured on a 7-point Likert scale which ranged from almost never (0) to almost always (6). An example question for the pre-measurement was: I try to develop my strengths as well as possible. In the post- 17

18 measurement questionnaire a question was: Last month I tried to develop my strengths as well as possible. For this scale, factor analysis indicated a KMO of.86 with a significant value on the Bartlett s test (p=.00). The factors were loading on two components. All items loaded on the first factor. The screeplot indicated a one factor solution and the two factor solution explained 68.35% of the variance, of which the second factor only explained 12.28%. After OBLIMIN rotation factor 1 had a big eigenvalue in comparison to the rest of the components (5.05 in comparison to 1.10,.88,.48 and lower). When a one factor solution was forced, the lowest factor loading was.56. Based on these results, there was chosen for the one factor solution. Reliability analysis illustrated a high Cronbach s α of.90. The scale used for the measurement after the intervention, had a KMO of.84 with a significant value on the Bartlett s test (p=.00). The results of the factor analysis indicated the option of two factors, but again all items loaded on the first factor. The eigenvalue of factor 1 was again high in comparison to the rest of the components (5.04 in comparison to 1.12 and lower). The screeplot also indicated a one factor solution. Therefore again a one factor solution was forced and again based on the strong factor loadings (lowest.51) there was chosen for the one factor solution. Cronbach s α of this scale was.90. Control variables Common control variables in OCB literature are age and gender of individuals, educational level and organizational factors. According to a study of Lovell, Kahn, Anton, Davidson, Dowling, Post, and Mason (1999), gender affects the degree of OCB. They found in their study that women performed higher levels of OCB than males, especially in the area of altruistic behavior. Ng and Feldman (2009) found in their study that highly educated workers tend to display greater creativity and demonstrate more citizenship behaviors than 18

19 less educated workers. Also Smith, Organ, & Near (1983) found a positive relationship between OCB and educational level in their study. However, if we look at the other variables with regard to organizational factors and age, in a study of Lee and Allen (2002), they could not find significant influences of the control variables organizational tenure, organizational level and age on OCB. Consequently, according to the above research results for OCB, in this study only the variables gender and educational level were included. The categorical variable gender was included as a dummy variable and educational level as an ordinal variable. Statistical analysis To perform all statistical analyses the software program SPSS was used. First of all, data was checked for errors, missing values and outliers. We did the analyses with a datafile including the outliers and one without the outliers, to test whether these outliers were not influencing the research results. There were two multivariate outliers which were extreme for strengths use, since the scores the participants filled in were very low in comparison to the rest of the respondents and the scores were indicated with an asterisk (Pallant, 2007). Finally, we concluded that all outliers could stay in the data file, since there were no differences in the results. All scales were reliable and therefore a Pearson correlation analysis was executed for all variables at all measurement points. To test whether there were group differences in the study variables at premeasurement between the experimental and control group, a multivariate analysis of variance (MANOVA) was used with strengths use and OCB as dependent variables and strength intervention as independent variable. Subsequently, a mixed within-between subjects ANOVA was executed to test whether the strengths intervention has led to increases in OCB 19

20 and strengths use. Group was used as between-subject factor, and time as within-subject factor. Moreover, hypotheses were tested using four multiple regression analyses. Three hierarchical multiple regression analyses were done to test the mediating effect and one hierarchical multiple regression analysis was done to test for moderation. By using multiple regression analyses it was possible to test how well the set of variables predicted particular outcomes, and whether a particular predictor variable was still able to predict an outcome when the effects of other variables were controlled for (Pallant, 2007). To avoid multicolliearity, the average Variance Inflation Factor (VIF) value should not exceed 10 (Myers, 1990). Thus, data had to be checked at VIF-values lower than 10 and otherwise the usability of multiple regressions had to be considered again. Before conducting a hierarchical multiple regression analysis, assumptions about outliers, normality, homoscedasticity, and independence of residuals were met. The groups were included as a categorical predictor in the analyses, with 1 for the experimental group and 0 for the control group. To test the mediating effect, three hierarchical multiple regression analyses were done. Hypothesis 3 was tested using a mediating analysis and it was performed by steps as instructed by MacKinnon, Fairchild and Fritz (2007). They recommended to test for mediation by assessing the significance of strengths intervention to strengths use. Then the significance of the relationship between strengths use and OCB (both self-rating and peerrating), controlling for the strengths intervention was tested. In the first analysis, strengths use was the dependent variable. First the control variables and strengths use t1 were integrated and after that the intervention was included. In the second hierarchical multiple regression analysis, again done to test for mediation, self-rated OCB t3 was the dependent variable. As independent variables, first the control variables and self-rated OCB t1 were added. Then, the intervention was included and in the block after that strengths use t3 was added. A sobel test 20

21 was used to test if the mediation effect was significant. Next, a third hierarchical multiple regression analysis was done with peer-rated OCB t3 as dependent variable. In the first block the control variables and peer-rated OCB t1 were added. Then, the intervention was included and in the block after that strengths use t3 was added. After that again a sobel test was done. The interpretation of these analyses will be described in the conclusion and discussion section of this study. To test for moderation, another hierarchical multiple regression was executed and grand-mean centres for the variables group and proactive personality were created by recoding them into new variables by subtracting its overall mean. After that, proactive personality and group were computed in an interaction term. In this analysis, the first block contained control variables gender and education and strengths use t1, in the second block the two grand-mean centred variables were included, and in the third block the interaction term was added. After that the results were interpreted, which will be described in the conclusion and discussion section of this study. RESULTS Correlation analysis A Pearson correlation analysis was conducted to reveal the strength of the relationship between the variables in the model and the control variables (Pallant, 2007). The correlations, means, standard deviations and Cronbach s alphas are presented in Table 1. At pre-measurement a positive significant relationship was found between strengths use and OCB (r=.571, p <.01). According to Cohen (1988) this correlation is large. At premeasurement, also a moderate positive relationship between proactive personality and strengths use (r=.528, p<.01) was found. In addition, moderate positive relationships between strengths use t1 and OCB t3 (r=.388, p<.01) and strengths use t3 and OCB t3 (r=.432, p<.01) 21

22 were found. A large positive relationship between OCB t3 and proactive personality t1 (r=.523, p<.01) and a moderate positive correlation between strengths use t3 and proactive personality t1 (r=.460, p<.01) was found. Table 1 Means, Standard Deviations, Correlations, Reliabilities Mean SD N Gender 1 1,35 0, Education 2 4,12 0, ,24* - 3 Group 3 0,44 0, ,07-0,02-4 Strengths use t1 4 4,90 0, ,10 0,09 0,15 (0,90) 5 self-rated OCB t1 5 7,60 0, ,14-0,02-0,02 0,57** (0,70) 6 Proactive personality t1 6 5,08 0, ,09 0,11 0,20 0,53** 0,47** (0,78) 7 Strengths use t3 7 3,74 0, ,00-0,12 0,03 0,60** 0,38** 0,46** (0,90) 8 self-rated OCB t3 8 5,12 1, ,13-0,10-0,01 0,39** 0,59** 0,52** 0,43** (0,65) 9 Peer-rated OCB t1 7,51 0, ,02 0,02-0,03 0,04 0,03 0,12-0,02 0,22 (0,70) 10 Peer-rated OCB t3 7,53 0, ,18 0,04 0,11-0,01-0,10-0,12-0,02 0,06 0,67** (0,65) Note: N=71, 78 N=57, * p <.05; ** p <.01 t1 = pre-measurement, t3 = one month follow up measurement 1 male = 0, female = 1. 2 primary school= 1, secondary school = 2, secondary vocational education = 3, higher education = 4, academic education = 5 3 experimental group = 1, control group = 0. Cronbach s alphas are displayed between brackets on the diagonal. Furthermore, a multivariate analysis of variance (MANOVA) was done to check if there were significant differences between the experimental and control group on premeasurement level (Appendix I). No assumptions with regard to sample size, homogeneity of variance-covariance matrices and equality of variance were violated. There were no significant differences between the groups on self-rated OCB, peer-rated OCB, strengths use and proactive personality, (F(4, 57) =1.36, p =.26; Wilk s Lambda =.91; partial η2=.09). When the results of the dependent variables were considered separately, there were no differences in self-rated OCB, (F (1, 60) =.01, p =.91, partial η2=.00), in peer-rated OCB, (F (1,60) =.04, p = 0.85, partial η2=.00), in strengths use, (F (1, 60) = 1.41, p = 0.24, partial η2 =.02) and in proactive personality, (F (1, 60) = 3.79, p =.06, partial η2 =.06). None of these results were significant. An inspection of the mean scores indicated that the experimental 22

23 group reported slightly higher levels of strengths use (M = 5.07, SD =.64) than the control group (M = 4.84, SD =.88). Also the mean scores of proactive personality were higher for the experimental group (M = 5.26, SD =.56) than for the control group (M = 4.91, SD =.79). A striking result with regard to proactive personality was that there was found an almost significant difference at the baseline measurement (p=.052) when executing the MANOVA. Besides this, a mixed between-within subject analysis of variance (ANOVA) was conducted to assess the effect of the intervention on strengths use and OCB across the two measurement points. This analysis also partly tested the direct effect between strengths intervention and strengths use and strengths intervention and OCB. The results for self-rated OCB showed there was no significant interaction between the groups and time (Wilk s Lambda = 1.00, F (1, 55) =.07, p =.79, partial η2 =.00). There was also no substantial main effect for time (Wilk s Lambda =.94, F (1, 55) = 3.63, p =.06, partial η2 =.06). A repeated measures ANOVA was conducted for peer-rated OCB. There was no substantial main effect for time (Wilk s Lambda =.98, F (1, 47) =.78, p =.38, partial η2 =.02). The results for the interaction between the groups and time, however, showed a significant effect (Wilk s Lambda =.94, F (1, 47) = 2.82, p = 0.01, partial η2 =.06). There was a marginally significant effect of intervention on peer-rated OCB and we reached statistical significance because we could use one-sided testing in this case. These results showed that intervention has a direct effect on peer-rated OCB, which means hypothesis 4 is partially supported: Strength intervention has a positive effect on OCB. For strengths use, again a mixed between-within subject analysis of variance (ANOVA) was conducted to assess the effect of the intervention on strengths use across the two measurement points. The results showed there were no significant differences between the groups over time (Wilk s Lambda =.99, F (1, 55) =.46, p = 50, partial η2 =.01). For time 23

24 there was a substantial main effect (Wilk s Lambda =.86, F (1, 55) =9.16, p =.00, partial η2 =.14). This suggests there was a change in strengths use scores across the two different time periods, with both groups showing a reduction in strengths use across the two time periods (Field, 2009). The main effect was significant and this result suggests a large effect size according to the guidelines of Cohen (1988). These results only showed a significant interaction effect between the two groups over time for peer-rated OCB. The other results on strengths use and OCB showed that there were no differences between the respondents in the control group and the experimental group over time. For strengths use there was a significant reduction in scores between the two time periods for both groups. For more details, see Appendix 1. Hypotheses testing Hierarchical multiple regression analyses were done to assess the effects of the strengths intervention on strengths use and OCB. First, a hierarchical multiple regression analysis was executed to test hypothesis 1: Strengths intervention has a positive effect on strengths use t3. First, the control variables were entered at block 1, explaining 39.00% of the variance in strengths use (table 2a). After adding the intervention in block 2, the total variance explained by the model as a whole was 40.00%, (F (4, 52) = 8.48, p<.00). The intervention explained an additional 1.00% of the variance in strengths use, after controlling for gender and education, (R 2 Change =.01, F change (1, 52) =.63, p>0.1). The effect of the intervention on strengths use was not significant and therefore hypothesis 1 could not be confirmed. 24

25 Table 2a Hierarchical multiple regression analysis predicting Strengths use t3 from Strengths intervention Model 1 Model 2 B SE β B SE β Gender¹ -0,04 0,19-0,03-0,03 0,19-0,02 Education² -0,17 0,11-0,17-0,17 0,11-0,17 Strengths use t1 0,57 0,10 0,62 ** 0,59 0,10 0,63 ** Strenghts Intervention³ -0,14 0,18-0,09 R²,39,40 R²,39,01 F 11,17 8,48 Dependent variable; Strengths use t3 Note: b=unstandardized regression coefficient, SE= standard error, β= standardized regression coefficient **=p<.01, *=p<.05, # = p<.10 ¹ 0=male, 1=female. ²1=elementary =, 2=basic, 3=secondary, 4=higher, 5=academic. ³0=control group, 1=experimental group Another hierarchical multiple regression analysis was done in order to test hypothesis 2: Strengths use has a positive effect on OCB t3, hypothesis 3: Strengths use partially mediates the relationship between the strengths intervention and OCB t3 and hypothesis 4: Strengths intervention has a positive effect on OCB t3. Self-rated OCB t3 was the dependent variable in this analysis. Again, the control variables were entered in block 1, together with self-rated OCB t1, which explained 39.80% of the variance in self-rated OCB (table 2b). In the second block the intervention was added, which explained 0.00% of the variance in selfrated OCB, (R 2 Change=.00, F Change=.00, p >.10). In the last block strengths use t3 was added, explaining an additional 4.40% of the variance in self-rated OCB, (R 2 Change=.04, F Change= 4.02, p =.05). The effect of the intervention on self-rated OCB t3 was not significant, and therefore hypothesis 4 was rejected with regard to self-rated OCB. In contrast to the non-significant effect of strength intervention on self-rated OCB t3, the effect of strengths use t3 was significant, which means that strengths use t3 has a positive effect on self-rated OCB t3. Thus, hypothesis 2 could be partly confirmed with regard to self-rated OCB t3. In addition, to conclude whether there was a mediating effect of strengths use in the relationship between intervention and self-rated OCB t3 (hypothesis 3), the results of both 25

26 hierarchical multiple regression analyses were used. As earlier acknowledged, results of Table 2a and 2b demonstrated that the effects of intervention on self-rated OCB t3 (β = -.01, p >.05) and intervention on strengths use (β = -.09, p >.05) were not significant. In contrast, the effect of strengths use t3 on self-rated OCB t3 (β =.23, p =.05) was significant. Because no significant relations were found for intervention towards strengths use t3 and intervention towards self-rated OCB t3, neither a mediating nor a partial mediating effect could exist. A Sobel-test also provided no significant results for proving a mediation effect. Table 2b Hierarchical multiple regression analysis predicting self-rated OCB t3 from Strengths intervention and Strengths use t3 Model 1 Model 2 Model 3 B SE β B SE β B SE β Gender¹ -0,31 0,17-0,21 # -0,31 0,17-0,21 # -0,30 0,16-0,20 # Education² -0,04 0,10-0,04-0,04 0,10-0,04-0,01 0,10-0,02 Self-rated OCB t1 0,59 0,10 0,62** 0,59 0,10 0,62** 0,50 0,11 0,53** Strenghts Intervention³ 0,00 0,16 0,00-0,01 0,15-0,01 Strengths use t3 0,20 0,10 0,23* R²,40,40,44 R²,40,00,04 F 11,66 8,58 8,07 Dependent variable; self-rated OCB t3 Note: b=unstandardized regression coefficient, SE= standard error, β= standardized regression coefficient **=p<.01, *=p<.05, # = p<.10 ¹ 0=male, 1=female. ²1=elementary =, 2=basic, 3=secondary, 4=higher, 5=academic. ³0=control group, 1=experimental group Another hierarchical multiple regression analysis was done, but then with peer-rated OCB t3 as dependent variable, to test whether there was a mediating effect of strengths use in the relationship between strength intervention and peer-rated OCB t3. Again, the control variables were entered in block 1, together with peer-rated OCB t1, which explained 48.10% of the variance in peer-rated OCB t3 (Table 3). In the second block the intervention was added, which explained an additional 1.30% of the variance in peer-rated OCB t3 (R 2 Change=.01, F Change= 1.00, p >.10). Lastly, in the third block strengths use t3 was added, 26

27 which explained in total 49.40% of the variance in peer-rated OCB t3 (R 2 Change=.00, F Change= 0.01, p >.10). The effect of the intervention on peer-rated OCB was not significant, which means that hypothesis 4 was rejected for peer-rated OCB t3. The results above show that hypothesis 2 was rejected with regard to peer-rated OCB t3, since no significant positive effects were found (Table 3). Furthermore, there were no results that indicated the hypothesized mediation effect in hypothesis 3 (Table 2a, 2b and 3). Therefore hypothesis 3 was rejected. Table 3 Hierarchical multiple regression analysis predicting peer-rated OCB t3 from Strengths intervention and Strengths use t3 Model 1 Model 2 Model 3 b SE β B SE β B SE β Gender¹ 0,27 0,16 0,20 # 0,26 0,16 0,19 0,26 0,16 0,19 Education² -0,02 0,10-0,02-0,02 0,10-0,02-0,02 0,10-0,02 Peer-rated OCB t1 0,51 0,09 0,67** 0,51 0,09 0,67** 0,51 0,09 0,67** Strenghts Intervention³ 0,15 0,15 0,11 0,15 0,15 0,11 Strengths use t3-0,01 0,09-0,01 R²,48,49,49 R²,48,01,00 F 12,68 9,76 7,61 Dependent variable; Peer-rated OCB t3 Note: b=unstandardized regression coefficient, SE= standard error, β= standardized regression coefficient **=p<.01, *=p<.05, # = p<.10 ¹ 0=male, 1=female. ²1=elementary =, 2=basic, 3=secondary, 4=higher, 5=academic. ³0=control group, 1=experimental group To test for the moderation effect of proactive personality (hypothesis 5), first grandmean centres for the variables group and proactive personality were created. In the regression analysis, the first block contained control variables gender and education and strengths use t1, in the second block the two grand-mean centred variables were included, and in the third block the interaction term of proactive personality and group was added. The first block explained 38.70% (Table 4) of the variance of strengths use, the second block 43.30% (R 2 Change=.05, F Change= 2.05, p >.10) and the third block explained an additional 0.02% (R 2 27

28 Change=.00, F Change= 0.19, p >.10). No significant relationships between the variables were found and therefore hypothesis 5 was not confirmed. Table 4 Hierarchical multiple regression analysis predicting Strengths use t3 from Proactive personality Model 1 Model 2 Model 3 B SE β B SE β B SE β Gender¹ -0,44 0,19-0,03 0,04 0,19 0,02 0,03 0,19 0,02 Education² -0,17 0,11-0,17-0,20 0,11-0,19 * -0,19 0,11-0,19 # Strenghts use t1 0,57 0,10 0,62 ** 0,47 0,12 0,51 ** 0,47 0,12 0,50 ** Strenghts Intervention³ -0,19 0,18-0,12-0,18 0,18-0,11 Proactive personality 0,27 0,14 0,24 # 0,25 0,15 0,22 Interaction Intervention and Proactive personality -0,12 0,28-0,05 R²,39,43,44 R²,39,05,00 F 11,17* 7,79 6,42 Dependent variable; Strengths use t3 Note: b=unstandardized regression coefficient, SE= standard error, β= standardized regression coefficient **=p<.01, *=p<.05, # = p<.10 ¹ 0=male, 1=female. ²1=elementary =, 2=basic, 3=secondary, 4=higher, 5=academic. ³0=control group, 1=experimental group CONCLUSION AND DISCUSSION Conclusion The aim of this study was to test whether a strengths intervention had a positive impact on strengths use and OCB. In total 71 respondents participated in this study and completed three questionnaires. From these respondents, 32 respondents took part in the intervention consisting of a strengths workshop in which participants focused on their strengths and made a plan how to use these strengths in their work. An increase of strengths use was expected as a result of the workshop, which was theoretically supported by the positive activity model of Lyubomirsky and Layous (2013). In turn a positive effect of strengths use on OCB was expected, based on the broaden-and-build theory of Frederickson (2001) and because several other studies mentioned OCB as a positive result of strengths use 28

29 (Wood et al., 2010; van Woerkom & Meyers, in press). In addition, a positive effect of strength intervention on OCB was expected, based on the Social exchange theory and several other theories (Cook et al., 2013; Cropanzo & Mitchell, 2005; Meyers et al., 2012). Also the effect of the personality trait proactive personality was tested. The prediction was that employees with a proactive personality would have more profit from the strengths intervention. Based on the above expected relationships, the following research question was formulated: What is the effect of a Strengths intervention on Strengths use and Organizational Citizenship Behavior and to what extent is the relationship between the Strengths intervention and Strengths use moderated by Proactive personality? The expected positive effect of the intervention on strengths use could not be confirmed in this study. Although no significant results were found which supported the positive relationship, other remarkably significant results were found, which showed a decrease in strengths use for both the experimental and the control group one month after the intervention instead of the expected increase. These results are inconsistent with expected outcomes based on prior research (Quinlan et al., 2011; Lyubomirsky and Layous, 2013). One possible explanation for these inconsistent results could relate to the fact that participants in the experimental group knew more about strengths after the workshop than before, which could have influenced the way they filled in the one month follow-up measurement. To elaborate on this argument, theory of Biswas-Diener et al. (2011) could be used which explains another interpretation of the positive activity model. Lyubomirsky and Layous (2013) expect with their model that an intervention is experienced as a positive activity by employees, which in turn leads to positive behaviors and stimulation of strengths use. However, Biswas-Diener et al. (2011) found that interventions could also cause feelings of disappointment and disengagement as a consequence of focusing on strengths use. These 29

30 feelings can occur when employees experience failures or setbacks when working in areas of strengths, especially when they are more vulnerable to failures associated with strengths use in comparison to failures associated with the use of weaknesses. Thus, consciousness about strengths and attempts to apply them in work, which will not always be experienced by employees as successful, could lead to mixed feelings. This phenomenon is called response shift bias and it occurs when the person's view of the construct being measured, in this case the awareness and stimulation of strengths use, changes between the pre test and the post test due to the influence of the intervention (Drennan & Hyde, 2008). Employees could rate their ability on a different dimension at the post test than they did at the pre-test due to the development of a greater understanding of strengths use (Drennan & Hyde, 2008). This possible explanation could only be applicable for the experimental group, since they were the only group who participated in the workshop before filling in the one month follow-up questionnaire. In line with this reasoning, a possible explanation for the control group could be the raised consciousness of strengths use after filling in the first questionnaire. The fact that they had to answer questions about strengths use in the first questionnaire could have affected the way they filled in the second and third questionnaire with regard to their view on strengths. Also the timing of the third questionnaire, which was very close to the holiday break, could have influenced the way both groups filled in the answers. It could have been the case they were busy with finishing their tasks before the holiday break instead of being busy with their strengths. Another explanation for the decrease in strengths use for the experimental group, based on theory of Arthur, Bennet, Edens, & Bell (2003), could be a non-supportive work environment towards the application of new skills and behaviors learned in training or the lack of post-training activities. Arthur et al. (2003) state that the post-training environment and the social context play an important role in facilitating the transfer of trained skills to the 30

31 job and may attenuate the effectiveness of training. For this intervention, the focus might not have been enough on post-training activities. Participants had to make a plan of how to use their strengths in their work, but their managers and colleagues might not have always been involved enough in this process. This could have influenced the negative results if the participants did not feel supported after the intervention or forgot to focus on their strengths because they did not get enough space and time to work with it (Arthur et al., 2003). In contrast to the non-significant results above, the positive effect of strengths use on OCB could be partly confirmed. Significant results were found for the effect of strengths use on self-rated OCB, which is in line with expectations based on the broaden-and-build theory of Frederickson (2001). On the other hand no significant results were found for the effect of strengths use on peer-rated OCB. Also the mediating effect of strengths use in the relationship between the intervention and OCB was not supported. In addition, the positive effect of the intervention on OCB was partly confirmed. On the one hand, no significant results for the effect of the intervention on self-rated OCB were found. On the other hand, the results for peer-rated OCB showed a significant interaction effect between the two groups over time, which means that the intervention caused differences in the outcomes of the two groups for peer-rated OCB. Participants in the experimental group were evaluated as improved in OCB and the participants in the control group did not improve OCB according to the opinions of their colleagues. These results are in line with propositions derived from the social exchange theory (Cook et al., 2013), which state that participating in a strengths intervention could result in positive organizational outcomes like increased OCB and performance. When organizations arrange a positive activity by organizing a strengths workshop for their employees, the reaction appears to be that employees will show positive extra-role behaviour after the workshop, as an exchange to the effort of the organization (Cook et al., 2013). Although the results for OCB were mixed, 31

32 the positive relationship between intervention and OCB is confirmed for peer-rated OCB. These results are important and a new contribution to the existing literature. A possible explanation why participants did not rate themselves higher at postmeasurement than at pre-measurement, could be that it is difficult to evaluate OCB for yourself. Organ and Ryan (1995) found in their study that because ratings of OCB are inherently subjective, ratings of a person's own OCB are a poor substitute for independent judgments. Self-ratings of OCB could be easily influenced by the employees mood at that particular moment which is influenced by other organizational factors and therefore selfratings could be misleading since they do not reflect the reality (Organ & Ryan, 1995). Lastly, the moderating effect of proactive personality in the relationship between intervention and strengths use was also not confirmed. A possible explanation could be the almost significant difference in scores between the experimental and the control group for proactive personality at the baseline measurement. This would indicate that there was already a slight difference before the intervention between the experimental and control group regarding this personality trait. In addition, the mean scores on proactive personality of the experimental group were higher than the scores of the control group. This would indicate that there cannot be made a good comparison of the results between the groups, because there was already a difference at the baseline measurement that may have affected the other measures of the research. This could be further explained by a theory of Thompson (2005). He states that people that have a less proactive personality are less likely to respond to invitations concerning taking part in a research. With this in mind, it is possible that more employees with a proactive personality subscribed for the workshop. Since this study was dependent on voluntary applications for the workshop, this could have happened in this research. 32

33 Limitations and future research There are several limitations which need to be taken into account in this study. A major limitation of this review is the sample. The power of the sample was probably insufficient and that could explain insignificant results of this study. For future research a larger sample should be used in order to increase the representativity of the sample and to be better able to detect whether the hypothesized relationships exist. A second limitation could be the time period between the measurement points of the questionnaires. There were only four weeks between the first questionnaire and the questionnaire at the one month follow up. Previous studies on strength interventions have shown that the effects of such interventions on results can grow stronger over a six-month period (Seligman et al., 2005), which might declare why some effects were not yet observable in the present study. Therefore, for future research it would be advisable to expand the period to at least six months so that longer-term effects can be captured. Third, it could have happened that some participants in the control group already got the results of the preparation exercise from their colleagues before they filled in the second and third questionnaire. The exercise was sent to the participants directly after they filled in the first questionnaire. The participants of the control group also received the assignment when they completed the first questionnaire and therefore it is possible that they already started the assignment. This could have raised their awareness for strengths and it could have influenced the way they filled in the second and third questionnaire while they should have been neutral. Future research should provide the assignments to the control group after they have completed the last questionnaire. Another limitation, in line with this, is the fact that participants might get a better understanding of strengths use during the intervention. Participants became aware of their 33

34 personal strengths during the preparation exercise and during the training. They might have realized that they are less or perhaps more aware of strengths use than they had expected. This may cause a different approach towards the one month follow-up questionnaire. Subsequently, it could have been the case that the strengths intervention did not cause the expected positive feelings but caused feelings of disappointment and disengagement as a result of focusing on strengths use. If the progression or use of strengths of employees did not meet their expected effects soon, it could have caused feelings of failure instead of positive effects. Therefore, the awareness of strengths could be two-sided and thus affect the way employees filled in the follow-up questionnaire. Fifthly, participants in this study were not randomly assigned to the experimental and control group. The participants could subscribe to one of the four workshops that suited their schedules best, but because they did not know which workshops belonged to the experimental and which to the control group, the procedure came close to a random allocation. Comparisons of the pre-intervention scores of the experimental and control group on the study variables could confirm this. For future research it would be interesting to further investigate the effects on extrarole behaviour, since in this study the only outcomes are the positive effect strength intervention on peer-rated OCB and the positive effect of strengths use on self-rated OCB. With a bigger sample and longitudinal research, these effects could be proved more extendedly, which will be beneficial for organizations in the future. For future research, it would also be an addition to implement post-training activities and to focus on workplace involvement, to increase the effectiveness of the training (Arthur et al., 2003). 34

35 Theoretical and practical implications Limited research has been done on the concept of strength interventions. This study contributed to the existing literature, since this research focused on objective performance measures where previous research mainly focused on the positive effects of strengths interventions on subjective experiences. Furthermore, this study was among the first studies to investigate moderating and mediating mechanisms through which these interventions operate. As proposed by the Social exchange theory, in this study the effect of the strengths intervention on an increase in OCB as rated by colleagues of employees was confirmed. Also the positive effect of strengths use on self-rated OCB was confirmed, which was expected based on the broaden-and-build theory. Managers should be aware of the positive potential that lies within the use of strengths interventions and strengths use. Since strengths interventions influence OCB from a colleague s point of view, it could be seen as a means to stimulate performance. Therefore, awareness of how to increase organizational citizenship behaviour of employees may be beneficial for organizations and this study could be guiding in the future research and the stimulation of this. Strengths interventions can be seen as a useful organizational tool because they are easy to implement and they are relatively efficient with regard to the invested time compared to many other interventions with durations of several weeks (Van Woerkom & Meyers, in press). Derived from these outcomes, organizations should be aware of the positive impact strengths interventions can have for the entire organization. 35

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41 APPENDIX I MANOVA and ANOVA results Scores self-rated OCB for the experimental and control group at two points in time Experimental group Control group n M SD n M SD 1. Pre-measurement One month follow up ANOVA table self-rated OCB Sum of Squares df Mean Square F Sig. Between groups Within groups

42 Scores peer-rated OCB for the experimental and control group at two points in time Experimental group Control group n M SD n M SD 1. Pre-measurement One month follow up ANOVA table peer-rated OCB Sum of Squares df Mean Square F Sig. Between groups Within groups