Master Thesis - University of Tilburg - Tilburg University

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Master Thesis The effect of online coaching interventions on employee’s self-efficacy and resilience at work. A quantitative study in The Netherlands.

Niki Janssen ANR: S128779 Supervisor: Dr. M. van Woerkom 2nd assessor: Mrs. M.C. Meyers MSc January – October 2013 Improving deficits or using strengths? Human Resource Studies

Table of Contents

Table of Contents .................................................................................................................................... 1 Abstract ................................................................................................................................................... 3 Introduction............................................................................................................................................. 4 Theoretical Framework ........................................................................................................................... 7 Individual strengths ............................................................................................................................. 7 Strengths-Use Interventions ............................................................................................................... 7 Self-efficacy ......................................................................................................................................... 7 The influence of strengths-use on self-efficacy .................................................................................. 8 Resilience............................................................................................................................................. 9 The influence of strengths-use on resilience .................................................................................... 10 Deficit Improvement interventions ................................................................................................... 11 The influence of deficit improvement on self-efficacy ..................................................................... 11 The influence of deficit improvement on resilience ......................................................................... 12 Combining a strength- and deficit-based intervention ..................................................................... 13 Conceptual Model ............................................................................................................................. 14 Methods ................................................................................................................................................ 15 Research design................................................................................................................................. 15 Interventions ..................................................................................................................................... 16 Sample and population ..................................................................................................................... 17 Measures ........................................................................................................................................... 18 Analyses ............................................................................................................................................. 19 Results ................................................................................................................................................... 21 Descriptive statistics .......................................................................................................................... 21 Hypothesis testing ............................................................................................................................. 23 Regression analysis after week 3................................................................................................... 23 Regression analysis after week 4................................................................................................... 25 Plots with data of week 5 .............................................................................................................. 26 Conclusion and discussion ..................................................................................................................... 29 Interpretation of the results .............................................................................................................. 29 Limitations ......................................................................................................................................... 31 Practical implications......................................................................................................................... 31 1

Directions for future research ........................................................................................................... 32 Conclusion ......................................................................................................................................... 33 References ............................................................................................................................................. 34 Appendices ............................................................................................................................................ 38 Appendix 1: Frequencies population................................................................................................. 38 Appendix 2: Output reliability analyses Virtues in Action ................................................................. 39 Appendix 3: Output reliability analyses self-efficacy and resilience ................................................. 53 Appendix 4: Output Correlation Matrix ............................................................................................ 57 Appendix 5: Output Frequencies: Mean Self-efficacy and Resilience Week 1 and 3........................ 58 Appendix 6: Output regression analysis after week 3....................................................................... 59 Appendix 7: Output regression analysis after week 4....................................................................... 63 Appendix 8: Plots with data of week 5 .............................................................................................. 65 Appendix 9: Questionnaires .............................................................................................................. 66

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Abstract Self-efficacy and resilience both have been shown to be related to performance in the workplace. Conceptual and beginning empirical evidence was found that self-efficacy and resilience can be developed by the use of online coaching interventions. Therefore, three different online coaching interventions were conducted; a strengths-based intervention, a deficit improvement intervention and an intervention which combines strengths and deficits. Based on previous literature, it was expected that all of three interventions would positive affect self-efficacy and resilience of employees. However, the combined intervention was expected to have a greater impact on self-efficacy and resilience compared to the interventions solely based on either strengths or deficits. The expected relationships were examined through an online coaching intervention in which 120 Dutch respondents participated. During 3 weeks the respondents filled out various questionnaires and developed their strengths or weaknesses or a combination of both. Hierarchical regression analyses were conducted to test the hypotheses. These analyses showed no significant relationships between any of the interventions and self-efficacy and resilience. However, additional analysis with data of week 4 showed significant relationships between strengths use and self-efficacy and resilience. Subsequently, self-efficacy was shown to be influenced by deficit improvement. Combining strengths- and deficits development appears to influence self-efficacy and resilience in a negative way. Discrepancies with the literature can be due to the limitations of the research, which are discussed. Finally, recommendations for future research and practical implications are proposed.

Keywords: Strengths-use, deficit improvement, online coaching intervention, self-efficacy, resilience

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Introduction Self-efficacy is shown to be an important predictor of an employee’s performance. Many studies indicate that an organizations' performance will be higher if the employees experience high levels of self-efficacy (Bandura, 1982; Bandura, Adams, Hardy & Howells, 1980; Feltz, 1982). Self-efficacy is a domain-specific belief that one can accomplish certain goals (Cox, 2005). Judgments of self-efficacy determine how much effort people will expand and how long they will persist in challenging obstacles. People who have high self-efficacy will exert more effort (Bandura, 1982). According to Bandura (1982), low levels of self-efficacy can create stress and impair performance by giving to much attention to concerns over failings and deficiencies. Next to self-efficacy, resilience, which is a state of development in which someone has the capacity to rebound or bounce back from negative events (Luthans, 2002), also has been shown to be related to performance in the workplace (Youssef &Luthans, 2007). Youssef and Luthans (2007) found that resilience has a unique contribution on different aspects of positive organizational behavior, such as job satisfaction, work happiness and organizational commitment. In addition, much research has been done on psychological capital, which consists of hope, optimism, self-efficacy and resilience. There is growing evidence that psychological capital is significantly related to desired employee behaviours (and negatively to undesired behaviours), attitudes and performance. The desired behaviours, attitudes and performance will contribute to the overall organizational performance (Avey, Avolio & Luthans, 2011). According to Avey, Avolio and Luthans (2011), constructs as self-efficacy and resilience are gaining more attention, but still are underrepresented in the organizational behaviour literature about desired employee attitudes and performance. However, conceptual and beginning empirical evidence is found that self-efficacy and resilience can be developed. Luthans, Avey, Avolio, Norman and Combs (2006) developed an online psychological capital intervention training model, but stated that additional research was necessary to find out whether psychological capital can be developed through such an intervention. They conducted a highly focused 2-hour web-based training intervention, including managers from all types of organizations. The results showed that the overall psychological capital of the managers increased with 3 percent after the short training session.

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Since there is still beginning evidence, but not that much, it is important to further investigate whether an online coaching intervention can increase self-efficacy and resilience. Many different interventions can be found in the literature and practice, of which strengths-based intervention and deficiency-based interventions are parts. In the past, many studies in the field of employee development were focused on weaknesses and deficiencies of employees rather than on their strengths (Maslach, Schaufeli & Leiter, 2001). In recent years, a new perspective appeared which is called positive psychology. Approximately one decade ago Seligman, who is considered to be the founder of positive psychology, and Csikszentmihalyi (2000) edited a special issue of American Psychologist devoted to positive psychology. They argued that psychology was not producing enough knowledge about what makes life worth living. This represented a shift in attention from deficiencies to strengths and talents of employees. Positive psychology is the generic term for the study of positive emotion, positive character traits, and enabling institutions (Seligman & Steen, 2005).According to Biswas-Diener, Kashdan and Minhas (2011), professional attention to the topic of strengths has grown dramatically last years. The increase of the attention to strengths goes along with the creation of strengths assessments and interventions (Biswas-Diener, Kashdan & Minhas, 2011). The general definition for a positive psychology intervention is “any intentional activity or method that is based on (a) the cultivation of positive subjective experiences, (b) the building of positive individual traits, or (c) the building of civic virtue and positive institutions” (Meyers, van Woerkom & Bakker, 2012). Several theories describe possible relationships between strengths-use and self-efficacy (Bandura, 1977) and resilience (Grant, Curtayne & Burton, 2009; Fredrickson, 2001). These theories will be further elaborated in the theoretical framework. Although, strengths-use is gaining more attention in literature last years, it is of importance that the opposite of it, the development of deficits, will not be forgotten. Deficit development appears to influence self-efficacy (Gist & Mitchell, 1992; Ericsson, 2006) and resilience (Grotberg, 2003; Holahan, Moos & Schaefer, 1996) as well. Therefore, this research will not solely focus on the strengths-use but also on deficit improvement and on the combination of strengths-use and deficit improvement as well. Since deficit improvement always seemed to be the obvious way to develop employees, not much is written about this particular subject in the literature. This study can contribute to fill this gap in the literature. 5

To summarize, the purpose of this study, which is part of a larger study, is to give an answer on the following research question: What is the effect of online coaching interventions focusing on (a) strengths, (b) deficits or (c) strengths and deficits on employee’s self-efficacy and resilience at work? In order to answer this question, an online coaching intervention will be conducted in the Netherlands. The intervention is focused on the use of strengths, improvement of deficits or a combination of both, and will investigate whether it has an effect on engagement, psychological capital and happiness. During three weeks, respondents will participate in the online coaching tool and have to fill out different questionnaires.

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Theoretical Framework Individual strengths In order to better understand the concept of a strengths-based online coaching intervention, a definition of strengths will be given. According to Forest, Mageau, Crevier-Braud, Bergeron, Dubreuil and Lavigne(2012), there are two definitions of strengths known in the literature. First, strength is defined by Linley and Harrington (2006a, p.88) as “capacities for feeling, thinking, and behaving in ways that are authentic and energizing to the user and that allow optimal functioning in the pursuit of valued outcomes”. Subsequently, Rath (2007) defined strength as “the ability to consistently provide near-perfect performance on a task”. As a result of these definitions, strength can be described as a distinctive characteristic that energizes and motivates people to develop themselves and function optimally (Forest et al., 2012).

Strengths-Use Interventions The typical goal of strengths interventions is to increase well-being or personal achievement through the identification and development of strengths. In the past, these interventions asked participants to self-identify and label their strengths, but more recently, strengths classifications have been developed to assist with strengths identification (Quinlan, Swain & Vella-Brodrick, 2012). The strengths intervention used in this study combines these two strategies of identifying strengths. The Values In Action classification of Peterson and Seligman (2004) will be used as a tool for participants in order to identify their strengths. However, participants are also allowed to identify their strengths by asking their acquaintances. The intervention will focus on both strengths-use and developing strengths. By using one's strengths, employees can develop them. Therefore, strengths-use and developing strengths will be used interchangeably.

Self-efficacy In order to understand the concept of self-efficacy and the relationship with the intervention, a definition of self-efficacy will be given. According to Bandura (1977), self-efficacy is a construct that is derived from social cognitive theory, a theory in which behavior, cognitions and the environment all influence each other in a dynamic way. Wood and Bandura (1989a: p.408) determined that “self-efficacy refers to beliefs in one’s capabilities to mobilize the motivation, cognitive resources, and courses of action that are needed to meet given situational demands”.

Gist and Mitchell (1992) outline three important aspects of this

definition. First, self-efficacy is a judgment of perceived capability for performing a specific 7

task. Second, self-efficacy is a dynamic construct, which means that it can change over time when new information and experiences are acquired. Last, self-efficacy beliefs involve a mobilization component, thus people, who may have the same skills, may perform differently based on their utilization and combination of these skills in a changing context. To summarize, self-efficacy can be defined as “one’s confidence about his or her abilities to mobilize the motivation, cognitive resources or courses of action needed to successfully execute a specific task within a given context” (Stajkovic&Luthans, 1998, p66). This definition corresponds to the definition used in this study, which is the definition of Luthans, Yousseff and Avolio (2007, p.3). They define self-efficacy as “having confidence to take on and put in the necessary effort to succeed at challenging tasks”.

The influence of strengths-use on self-efficacy Performance accomplishments are one of the major influences on self-efficacy. The successes of the employees raise their expectations (Bandura, 1977). This means that having positive past achievements and giving attention to these successes, the expectations of employees will grow and these expectations, in turn, will lead to higher self-efficacy. Hodges and Clifton (in press) addressed different studies in their study that supports this statement. One study was a web-based survey to the impact of strengths awareness on participant behaviors. The conclusion of their study was that focusing on strengths (being aware of them) increases the self-confidence of people. Not only being aware of one's strengths can increase the selfefficacy of employees. Using your strengths is even more important. According to Linley, Nielsen, Wood, Gillett and Biswar-Diener (2010), strengths-use can lead to goal attainment through different mechanisms. This goal attainment can be compared with the successes Bandura (1977) wrote about. Building on this theory, it can be expected that employees who use their strengths can experience higher levels of self-efficacy, because of the growing expectations caused by the accomplished goals. Bandura (1977) also asserted that people could be persuaded to believe that they have the skills and capabilities to succeed. Getting verbal encouragement from others helps people overcome self-doubt and instead focus on giving their best effort to the task at hand. In the strengths-based interventions, participants are assigned to ask their acquaintances about their strengths, which can be seen as verbal encouragement. The influence of performance accomplishments can be explained by the indirect relationship with positive emotions. An emotion can be classified as positive when the personenvironment relationship is beneficial (Lazarus, 1991). In general, variables such as joy, love, 8

pride, amusement, hope and enthusiasm are considered to be positive emotions. These emotions are a part of what is called subjective well-being (SWB). The SWB construct comprises emotional responses (i.e. positive and negative affect) and global judgments of life satisfaction (Proctor, Maltby & Linley, 2011). Govindji and Linley (2007) examined the relationship between strengths use and subjective well-being and found that strengths use is a unique predictor of the variance in SWB. In turn, other research has shown that individuals with positive SWB have consistently high levels of positive emotions (Proctor, Maltby & Linley, 2011). People in a positive mood are more likely to emphasize their control over the outcomes they will receive than those with negative emotion and are more tending to attribute positive consequences to personal rather than external causes. A study of Dunning and Storey (1991) showed that positive people actually do experience more positive outcomes and experiencing positive outcomes in turn will lead to success expectations and thereby to higher self-efficacy. The relationship between strengths-use and self-efficacy is also supported by Wood, Linley, Malty, Kashdan and Hurling (2011). The demonstrated in their longitudinal study among a local community in Northern England that people who use their strengths develop higher levels of self-esteem, which is often used interchangeably with self-efficacy. The expected relationship is formulated in the following hypothesis. Hypothesis 1a: The use of a strengths-based online coaching intervention has a positive effect on someone’s self-efficacy.

Resilience Resilience refers to the positive psychological capacity to rebound, to bounce back from adversity, uncertainty, conflict, failure, or even positive change, progress and increased responsibility (Luthans, 2002, p702). Luther, Cicchetti and Becker (2000) defined resilience as "a dynamic process encompassing positive adaptation within the context of significant adversity". In this study the following definition of resilience will be used: “a state of development that is characterized by: when beset by problems and adversity, sustaining and bouncing back and even beyond to attain success” (Luthans, Youssef &Avolio, 2007). From this definition it can be concluded that individuals who are resilient are more flexible when demands are changing and will be more open for new experiences (Tugade, Fredrickson, & Barrett, 2004).

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The influence of strengths-use on resilience Wood, Linley, Maltby, Kashdan and Hurling (2011) stated that “if strengths use naturally leads to well-being over time, such interventions may be a way to build long term individual resilience and optimal functioning. Lietz (2008) developed a new focus on identifying and developing resiliency skills; the strengths based approach. This new approach recognizes the importance of building upon capacities the one has or can develop. An explanation why a strengths-based intervention may be a way to build resilience can be found in earlier research of Grant, Curtayne and Burton (2009). In their research they demonstrated that cognitive behavioral solution-focused coaching has increased the level of resilience via coaching and goals attainment. By integrating a perspective which focuses on solutions, the coaches help towards the development of personal strengths and on solution building rather than analyzing the problems (Pleunis, 2012). The growing resilience can be explained by the fact that people have to go through several steps, and while doing so they are expected to have to overcome challenges and barriers. Previous research showed more evidence for the relationship between solution-focused coaching and increased resilience of students (Green, Grant & Rynsaardt, 2007). It can be expected that this relationship can be applied to working people as well. Another reason why a strengths-based intervention has a positive effect on resilience can be found in the broaden-and-build theory (Fredrickson, 2001). As demonstrated in the previous section, strengths-use can lead to positive emotions. The broaden-and-build theory of Fredrickson (2001) suggests that positive emotions lead to broadened arrows of thoughts and actions that facilitate the building of important personal resources (social, physiological, and cognitive resources) (Meyers, van Woerkom & Bakker, 2012). It is called the broaden-andbuild theory because positive emotions appear to broaden people’s momentary thought-action repertoires and build their personal resources (Fredrickson, 2004). Furthermore, Fredrickson (2003) suggested that facilitating positive emotions can cause positive upward spirals, in which the created personal resources lead to the experience of positive emotions, which, in turn, will produce even more personal resources. The personal resources acquired during states of positive emotions are lasting. Through experiences of positive emotions, people transform themselves, becoming more resilient individuals (Fredrickson, 2004). For example, people will create a more positive cognitive mindset (cognitive resources), and thereby they can better resist against adversity at work. The expectation that arises from this theory is that

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the use of a strengths-based intervention(strengths-use) will lead to higher resilience, because of the created positive emotions. Taken this together, this has led to the following hypothesis: Hypothesis 1b: The use of a strengths-based online coaching intervention has a positive effect on someone’s resilience.

Deficit Improvement interventions As mentioned before, the concept of positive psychology is gaining more attention in the literature. This can imply that there’s also a shift in the use of interventions into a more positive way. However, there are some critics about the use of positive psychology and it doesn’t mean that the use of a deficit improvement is useless. Since deficit improvement always seemed to be the obvious way to develop employees, not much is written about this particular subject in the literature. However, other literature can be linked to the use of deficit improvement. One theory that supports deficit improvement is the theory of Ericsson (2006). He argued that expert performance can be reached through experience. Of course he noted that the best training environments are not sufficient to produces the very best performers, because there are substantial individual differences, like age. The fact that high performance levels can be reached through experience implies that a deficiency doesn’t necessarily has to be a barrier to success. Deficiencies can be developed by experience, so the weaknesses must be used instead of avoided. After practicing the deficits, they will be developed and can even become strengths and ultimately lead to higher performance.

The influence of deficit improvement on self-efficacy Gist and Mitchell (1992) did a theoretical analysis of the determinants of self-efficacy. According to them, three processes form someone’s self-efficacy. First, an analysis of task requirements has to be made (eg. What does it take to perform well). Second, an employee makes an attributional analysis of experience. This analysis involves the individuals’ judgments about why a particular performance level occurred. The last process that forms self-efficacy is the examination of self and determining the availability of specific resources and constraints for performing the task at different levels. This assessment requires consideration of personal factors (eg. Skill level) and situational factors. Especially when taking the last process in mind, and thinking of the experience theory of Ericsson (2006), it can be expected that someone’s overall skill level will be higher when that person minimizes 11

his or her deficits. This implies that an intervention focusing on improving deficits can lead to higher self-efficacy. This has led to the next hypothesis: Hypothesis 2a: The use of an online intervention focusing on improving deficits will have a positive effect on self-efficacy.

The influence of deficit improvement on resilience According to Grotberg (2003), resilience (in studies of children) is based on three categories; external supports (e.g., good role models), inner strengths (e.g., likability, optimism) and interpersonal and problem-solving skills (e.g., staying with a task until it is finished). Although this was based on studies with children, this theory of Grotberg can also be applied to the resilience of employees (Harland, Harrison, Jones & Reiter-Palmon, 2005). The last category of Grotberg’s framework (interpersonal and problem-solving skills) can be linked to deficit improvement. Dealing with your weaknesses can be seen as a kind of problem-solving. This suggests that problem-solving, which almost equals improving problems or deficiencies, can lead to increased resilience. Another explanation of the relationship between deficit improvement and resilience can be found in the different types of coping with challenges. Harland, Harrison, Jones and ReiterPalmon (2005) discuss in their study two types of coping with challenges. One form is avoidance-coping, which involves actions as engaging in substitute tasks to distract one, and trying to forget the issue causing stress. The other type is called approach-coping and involves actions such as logical analysis, positive reappraisal of the situation, seeking guidance and support, and taking problem-solving actions. Avoiding-coping is found to be less effective in causing resilience than approach-coping is (Holahan, Moos & Schaefer, 1996). The deficit improvement intervention in this study is focusing on developing weaknesses at work. This intervention involves employees who are seeking guidance and support in order to develop themselves. Subsequently, the intervention focuses on someone's weaknesses in a positive way. Weaknesses will not only be identified, but more important is the development of the deficiencies. This can be seen as a positive reappraisal of the situation. Meaning that deficit improvement can be seen as a kind of approach-coping, this implies that the use of a deficit improvement will lead to higher resilience. This has resulted in the following hypothesis: Hypothesis 2b: The use of an online intervention focusing on improving deficits has a positive effect on someone’s resilience.

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Combining a strength- and deficit-based intervention

Although the general emphasis in positive psychology is on strengths, many clinical researchers have recognized the need for clients to balance or integrate their psychological work on both strengths and weaknesses (Rust, Diessner & Reade, 2009). Rather than solely developing and using strengths or improving deficits it could be useful to combine the two types of interventions. This resulted in a combined intervention which focuses on both strengths and weaknesses. This combined intervention is supported by Smith (2006). She proposes a more balanced view of human nature, one that recognizes the inherent paradox in life circumstances and the need to assess strengths and deficits. In their study to life satisfaction, Rust, Diessner and Reade (2009), found that participants who focused on character strength and one relative character weakness showed as much gain in life satisfaction as did those who focused on two character strengths. However, a combined intervention is a relatively new construct and not much is written about it. Therefore the relationship between the combined intervention and self-efficacy and resilience can solely be based on logical reasoning. Taking together the expected positive relationships between a strengths-use intervention and a deficit improvement intervention on self-efficacy it can be expected that people treated with a combination of both interventions will achieve higher self-efficacy compared to the group threatened with an intervention solely based on either strengths or deficits. Therefore, the following hypothesis is formulated: Hypothesis 3a: The use of an online strengths-based intervention in combination with an online deficit improvement intervention will lead to higher self-efficacy compared to using an online intervention solely based on strengths or deficits. In the previous sections it is found that resilience can be increased by both a strengths-based online coaching intervention and a deficit improvement online coaching intervention. This can imply that the use of a combination of both interventions will possibly lead to higher resilience than the use of only one of the interventions. Therefore the last hypothesis is formulated: Hypothesis 3b: The use of an online strengths-based intervention in combination with an online deficit improvement intervention will lead to higher resilience compared to using an intervention solely based on strengths-use or deficit improvement.

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Conceptual Model To visualize all the expected relations between the different interventions and the dependent variables self-efficacy and resilience, a conceptual model is shown in figure 1.

Figure 1. Conceptual Model

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Methods In this section the research design, sample and population, operationalization of the concepts and analyses will be explained successively.

Research design The research question of this study will be answered through data obtained from an online coaching intervention. The data were retrieved by questionnaires within an online coaching intervention. These questionnaires were part of a broader study of Tilburg University and the Erasmus University Rotterdam. Potential respondents were approached in different ways. First, a message was placed on the website www.gelukswijzer.nl, with a very broad network. This web community was developed to conduct a large-scale and long-term research into the happiness of Dutch citizens. Subsequently, students tried to reach acquaintances (family, colleagues and friends) from their own network to participate in the online coaching intervention. At last, a flyer was uploaded on various linked-in groups, mainly focused on personal development and coaching. This way of reaching respondents is a combination of purposive sampling and convenience sampling. A purposive sample is a non-representative subset of some larger population and is constructed to serve a very specific need or purpose. In this research, only working people could participate in the online coaching intervention. However, within the group of working people, it was a matter of "taking what you get". As much working people as possible were reached to participate in the research. The respondents were promised that the results would only be used for study purposes. The data were collected during 3 weeks. Every week, the respondents were asked to fill in the same questionnaire, which makes this a longitudinal study. However, only the data of week 1 (before the intervention) and week 3 (after the intervention) will be used in this research. This study is of deductive nature, which means that the hypotheses to be tested are derived from the already existing theory. The hypotheses form the conceptual model that is displayed in figure 1 (page 14). This study is also of a testing nature, because it will test if the conceptual model is a good reflection of reality. For the online coaching intervention, which will be further described below, the respondents were divided in four groups. The first group was only treated with the strengths-use intervention, the second group was coached by a deficit improvement intervention, and the third group had both the strengths-based and deficit improvement intervention. The fourth 15

group, the control group, only had to fill out the starting questions and the weekly questionnaires, but the respondents in this group were not treated with any kind of coaching intervention.

Interventions In this study, a distinction was made between three different intervention groups and a control group. The respondents in the different intervention groups had to take almost the same steps in order to finish the e-coaching sessions. Strengths-use intervention For the respondents in the strengths-use group the intervention started in week 1 with filling out a shortened version of the Values in Action test (VIA) (Peterson & Seligman, 2004). The choice to remove various characteristics has been made on the basis of face validity. Therefore, for example, love and spirituality were released from the test. After shortening, the test consisted of 73 statements that all refer to a characteristic. A division was made between 14 characteristics (e.g. creativity or team player). The cronbach’s alpha of the scales used in the VIA test ranges from .54 to .84. The statements could be answered on a 5-point likert scale, ranging from “doesn’t fit me at all” (1) to “typical of me” (5). Filling out this test resulted in a list of one’s strong and weak characteristics. In addition, the respondents did the “Reflected best self” exercise (Roberts, Dutton, Spreitzer, Heaphy & Quinn, 2005). For this assignment the participants asked about 5 to 7 acquaintances about their strengths. In week 2, the participants had to choose two strong points, based on the assignments in week 1, which they wanted to develop. A concrete plan was made by the respondents about applying and developing their strengths on the work floor. In the third week, the respondents had to use and develop their strengths based on the action plan created in week 2. After that week, the respondents reflected on their goals and actions about the development of their characteristics. Next to these assignments, the respondents had to fill out a questionnaire to measure their engagement, happiness and the four elements of psychological capital (hope, optimism, resilience & self-efficacy) in the first, second and third week. Deficit improvement intervention Respondents in the deficit improvement group also started in week 1 with the shortened version of the VIA test (Peterson & Seligman, 2004). After filling out this test, respondents received a list of their weaknesses. In addition, the “Reflected self” exercise was carried out. The respondents had to ask their acquaintances about their development opportunities. 16

Based on the results of the VIA and the “Reflected self” exercise, the respondents chose two characteristics they wanted to develop in the next weeks. They made a concrete plan to develop their deficits. In the next week, this plan was carried out in order to develop their deficits. Besides the VIA test and the “Reflected self” exercise, the respondents had to fill out a questionnaire to measure their engagement, happiness, hope, optimism, resilience and selfefficacy in the first, second and third week. Strengths-use and deficit improvement intervention Respondents in this group also started the intervention with the shortened version of the VIA test (Peterson & Seligman, 2004). This test resulted in a list on which their strong and weak points were ranked. In addition, they asked their acquaintances about one strong point and one characteristic that could be improved. Based on these exercises, the respondents chose one strong point to use more and one characteristic they wanted to develop in the next week. Again a plan was made in order to improve or use these characteristics. In the first, second and third week of the intervention the respondents had to fill out a questionnaire to measure their engagement, happiness, hope, optimism, resilience and selfefficacy. Control group. The respondents assigned to the control group didn’t receive any kind of coaching intervention. They only had to fill out the starting questionnaire about the demographical characteristics, and in the first, second and third week, they had to answer the questions about psychological capital, engagement and happiness. Respondents who completed the questionnaires of the control group were asked to participate in the strengths-use intervention. Thereby, 10 persons have participated in both the control and strengths-use group. The data of these persons were treated as if it were two different respondents.

Sample and population In total, 313 respondents subscribed for the online coaching program. Only 120 of them filled out the questionnaires of week 1, 2 and 3. This means a response rate of 38,3%. In the strengths-use group, 35 participants completed the program, 26 participants completed the deficits improvement intervention, 25 persons completed the intervention which combined strengths-use and deficit improvement and 34 respondents completed the questionnaires in the control group. The average age of the respondents was 38,23. The youngest respondent was 20 and the oldest participant was 63. Slightly more women participated in the intervention, namely 72 women (60%) against 48 men (40%). The respondents work an average of 31,7 17

hours a week, which is very high. This is probably due to the fact that only working people were allowed to subscribe for the intervention. The respondents were mostly high educated, 87 participants (72,5%) completed higher professional education or university.

Measures The data were collected in The Netherlands so all items were administered in Dutch. Self-efficacy: In this research self-efficacy is defined as “having confidence to take on and put in the necessary effort to succeed at challenging tasks” (Luthans, Youssef & Avolio, 2007 p.3). In order to measure self-efficacy of the respondents an already existing scale of Luthans, Avolio and Avey (2007) was used. This scale consisted of 6 items, which could be answered on a 6point likert scale from 1 (totally disagree) to 6 (totally agree). The cronbach's alpha of this scale ranges from .75 to .85 (Luthans, Avey, Avolio & Norman, 2007). Because the total questionnaire became too large, it was decided to shorten the scale from 6 items to 4 items. In this research the cronbach’s alpha ranges from .82 in week 1 to .85 in week 3. An example of the used items is: "I feel confident enough to give a presentation to a group of colleagues". Resilience: Resilience is defined as: “a state of development that is characterized by: when beset by problems and adversity, sustaining and bouncing back and even beyond to attain success”(Luthans, Youssef & Avolio, 2007 p.3). This variable was as well measured on interval scale. This scale includes 6 items, which could again be answered on a 6-point likertscale (Luthans, Avolio & Avey, 2007), ranging from totally disagree (1) to totally agree (6). Because the questionnaire was very large, this scale was also shortened into 4 items. The cronbach’s alpha of the total scale ranges from .66 to .72 (Luthans, Avey, Avolio & Norman, 2007). After shortening the scale, the cronbach’s alpha ranges from .87 in week 1 to .93 in week 3. The statement “Normally, I can manage the difficulties at work very well” is an example of the items. The output of the reliability analysis of both dependent variables (selfefficacy and resilience) can be found in the appendix. Control variables: Schwarzer, Bäβler, Kwiatek and Schröder (1997) found that women obtained lower scores on self-efficacy than men. Thus, gender can influence the effect of the interventions on selfefficacy. Subsequently, Wasonga, Christman and Kilmer (2003) found that age and gender influenced factors predicting resilience. Employment status (working full- or part-time) was also found to influence someone's resilience (London, 1993). Therefore, age, gender and 18

working hours per week will be included as control variables. Age, gender and working hours per week were measured in the intake questionnaire. Age and average working hours per week were both measured through an open question, which makes these variables numerical variables. The variable gender was obviously divided into two categories, man or woman. Thereby this variable is a nominal variable. Subsequently, respondents could reflect on the actions they had planned in order to reach their goals. This variable was measured in week 3 through the question “Did you manage to complete the planned action?” The item had to be answered on a 7-point likert scale, ranging from 1 (totally not) to 7 (totally). This variable will be included as control variable as well.

Analyses The different hypotheses will be tested in SPSS through the use of a hierarchical multiple regression analysis in order to give an answer on the research question. With the use of this analysis, answers can be given to three important questions. First: Is there any effect of the interventions on self-efficacy and resilience? The second question that has to be answered is: Do all the different interventions influence the level of self-efficacy and resilience? And the last question is: Which of the treatments has the largest effect on self-efficacy and resilience? If the answer on the first question is no, then the second and third question are redundant. In hierarchical multiple regression analysis, a certain order of entering the variables into the regression equation can be determined. This is needed to control for hidden relationships with other variables. In the first block, the independent variables (the different intervention groups) are entered and in the second block, the control variables (age, gender and working hours per week) are entered. Within this analysis the different interventions are the independent variables and will be converted into dummy variables. A dummy variable is one that takes the value 0 or 1 and dummies are used as devices to sort data into mutually exclusive categories (the respondents were classified to only 1 group). Because there were 4 different groups, three dummy variables were generated. For the strengths group dummy, all respondents in the strengths-use group were coded with value 1 and respondents in all other groups were coded with value 0. For the deficit group dummy, all respondents classified to the deficit improvement group got the value 1 and all other respondents got value 0. Finally the dummy for the group that combined strengths-use and deficit improvement was made. All respondents in the combination group got the value 1 and all other participants got the value 0. The control group was not converted into a dummy variable because this was the reference group. Self-efficacy and resilience are the dependent variables within this analysis. The data of these 19

variables were retrieved in the first, second and third week. Only the data of week 1 and week 3 were used in the analysis. First the average score per respondent in week 1 and week 3 on self-efficacy and resilience were measured. After that a new variable of resilience and selfefficacy was made, which indicates the change in these variables after completing the coaching program (score week 3-score week 1). This variable can now be used in the regression analysis as dependent variable. Any outliers will be treated as missing values, and the missing values will be deleted pair wise. Now only the respondents with a missing value on a used item will be deleted.

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Results In this section, the results of the regression analyses will be described. First information on the descriptive level of the variables used in the analyses will be given.

Descriptive statistics To obtain information on the descriptive level, bi-variate analyses were carried out. Table 1 presents the mean sum scores, standard deviations and intercorrelations for the variables that will be used in the regression analyses for hypothesis testing and other variables that may provide relevant information. The correlation matrix can also be found in the appendix. Table 1: Reports of means (M), standard deviations (SD) and Pearson’s correlations.

** p<0.01, * p<0.05.. Age and working hours per week were measured numerical. For the variable gender, 1 represented men and 2 represented women. Self-efficacy and resilience were measured on a scale from 1 (totally disagree) to 5(totally agree). Action completed was measured on a scale from 1 (totally not) to 7 (totally).

Very remarkable in table 1 is the mean of the change in self-efficacy from week 1 to week 3. This mean is in contrast with all formulated hypotheses, which expected positive effects of all of the interventions (except for the control group) on the change in self-efficacy. The mean of the change in resilience from week 1 to week 3 should also be noticed as remarkable. This average change in resilience is almost equal to zero. The mean scores of self-efficacy and resilience in week 1 were very high (SE, M= 4.70; Resilience. M= 4.48). This indicates that the mean scores of these variables cannot be increased very much from week 1 to week 3, and can ensure that there will be no significant increase in self-efficacy and resilience after completing the intervention. Another mean score that stands out of table 1, is the mean score on the variable "action completed in week 3” (M=3.41). This item measured whether the respondents completed their action in order to achieve their goals. The item could be answered on a 7-point likert scale ranging from 1 to 7. Therefore a mean score of M=3.41 is very low. This indicates that not all 21

respondents completed the intervention seriously and thereby influence the relationship between the different interventions and self-efficacy or resilience, which will be shown in the next section. However, the item that measured the completion of action in week 3 is not significant correlated with both the change in self-efficacy and the change in resilience. Therefore it is decided to exclude this variable in the regression analyses. When looking at the correlations part of the table, the correlations of the different interventions with the variables of self-efficacy and resilience in week 3 and the change in self-efficacy and resilience stand out. None of the correlations is significant at the 0.01 or 0.05 level, which indicates that none of the interventions has a significant effect on self-efficacy and resilience. This will be further examined in the next session. However, there are some significant correlations. The correlation between the change in selfefficacy and the change in resilience is significant (r=.38, p<0.01). Because self-efficacy and resilience are both a component of a larger construct (psychological capital), this is not very surprising. Furthermore, gender is negatively correlated with self-efficacy in week 1 (r=-.20, p<0.05), self-efficacy in week 3 (r=-.21, p<0.05) and resilience in week 1 (r=-.24, p<0.01). This indicates that older people will experience lower levels of self-efficacy and resilience than younger people. Working hours a week is significant correlated with self-efficacy in week 1 (r=.22, p<0.05), resilience in week 1 (r=.27, p<0.01) and the change in resilience (r=.19, p<0.05). Therefore, it is important to control for this variable while carrying out the regression analysis of the change in resilience. Lastly, age and the completion of the planned action are not significant correlated with the change in resilience and the change in selfefficacy.

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Hypothesis testing Regression analysis after week 3

The results of the hierarchical regression analyses are shown in the table below (the total output of the regression analyses is attached in the appendix). In this table standardized regression coefficients (β), proportion explained variance (R² and R² Change) and the corresponding F-values (F and F-Change) can be found. Table 2: Results of the Regression Analyses (week 3): Standardized Regression Coefficients (β), proportion explained variance (R² en R² Change) and the corresponding F-values (F and F Change).

Variables

Dummy Strengths Dummy Deficits Dummy Combi Age Gender Hours/Week R² R² Change F F Change

Change in Self-efficacy Model 1 β p .10 .35 .09 .39 .13 .22

.02 .02 .58 .58

.63 .63

Model 2 β .11 .08 .12 -.09 -.05 -.15 .04 .03 .81 1.04

p .33 .49 .27 .33 .64 .16

.56 .38

Change in Resilience Model 1 β .08 -.02 .08

p .50 .84 .44

.01 .01 .44 .44

.73 .73

Model 2 β .08 -.06 .06 -.18 .03 -.19 .08 .07 1.67 2.88

p .45 .60 .58 .05 .80 .07

.14 .04

Dummy Strengths = Strengths intervention, Dummy deficits = Deficits intervention, Dummy combi = Strengths + deficits intervention. Hours/Week = working hours per week.

The first regression analysis was carried out to check whether self-efficacy is significantly influenced by completing an online coaching intervention focusing on using strengths, completing an online coaching intervention designed to improve deficits or completing an online coaching intervention that combines using strengths and improving deficits. . The results of this analysis can be found in the left part of table 2. In the first model, the control variables are disregarded, so it is more important to interpret the results shown in model 2. In model 2, the standardized regression coefficients, proportion explained variance and corresponding F-values of the different intervention types and the control variables age, gender and working hours per week can be found. Together, the various independent variables explained the change in self-efficacy for only 4% (R²=.04). The total model is not significant (F=.81, p=.56), which indicates that there is no significant effect for any of the interventions on the change in self-efficacy. As mentioned in the methods section, this was the first question to answer after carrying out the regression analysis. The answer on the question “Is there any effect of the interventions on self-efficacy” is no. With this conclusion the two other 23

questions: “Do all the different interventions influence the level of self-efficacy” and “Which of the treatments has the largest effect on self-efficacy” are actually unnecessary. Still, it is interesting to take a look at the rest of the results of the regression analysis. To answer the two remaining

questions,

the

standardized

regression

coefficients

(β)

are

needed.

It was expected that using strengths would have influenced self-efficacy in a positive way. Although the Beta of the dummy of the strengths group is positive, it cannot be said that hypothesis 1a: “The use of a strengths-based online coaching intervention has a positive effect on someone’s self-efficacy”, is supported, because the Beta is far from significance (β.11, p=.33). This also applies to the expected relationship between deficit improvement and selfefficacy (β=.08, p=.49). Thereby, hypothesis 2a: “The use of an online intervention focusing on improving deficits will have a positive effect on self-efficacy” is not confirmed. The Beta for the combination group was almost equal to the Beta’s of the other groups. It was expected in hypothesis 2b that this intervention would have a greater effect on self-efficacy than the other interventions. Again this Beta was not significant (β.12, p=.27) and therefore, hypothesis 3a: “The use of an online strengths-based intervention in combination with an online deficit improvement intervention will lead to higher self-efficacy compared to using an online intervention solely based on strengths or deficits” is not supported. In order to test hypotheses, 1b, 2b and 3b the right part of table 2, in which the results of the regression analysis of resilience are shown, is needed. This regression analysis was carried out to check whether resilience is influenced by using strengths, improving deficits or a combination of these. After controlling for hidden relationships with age, gender and working hours a week, the total model (model 2) showed no significant relationship between any of the interventions and resilience (F=1.67, p=.14). The three interventions explained 1% of the variance of resilience (R²=.01). Together with the control variables age, gender and working hours a week this increased to 8% (R²=.08). Similar to the results of self-efficacy, the Beta’s of all three interventions are insignificant for resilience. It was expected that using strengths would lead to higher resilience. This expectation cannot be confirmed (β=.08, p=.45), so hypothesis 1b “The use of a strengths-based online coaching intervention has a positive effect on someone’s resilience” is not supported. Neither the expected positive relationship between improving deficits and resilience can be assumed (β=-.06, p=.60). Although this Beta is not significant, it is noteworthy, because it indicates a negative relationship between improving deficits and resilience. Hypothesis 2b: “The use of an online intervention focusing on improving deficits has a positive effect on someone’s resilience” is not supported. 24

The remaining expected relationship is the relationship between the intervention that combines strengths-use and deficit improvement and the change in resilience. As shown in the conceptual model, it is expected that respondents in the combination group will grow in resilience stronger than those in the other groups. The Beta of this group is unexpected slightly lower than the Beta of the strengths group and again it is not significant (β=.06, p=.58). This means that the last hypothesis, hypothesis 3b “The use of an online strengthsbased intervention in combination with an online deficit improvement intervention will lead to higher resilience compared to using an intervention solely based on strengths-use or deficit improvement”, cannot be confirmed. . To summarize, none of the hypotheses were supported after week 3. To check whether this is due to the short duration of the research, additional regression analyses were carried out with the data that was available after week 4. The results of these analyses will be described in the following section. Regression analysis after week 4

It was decided to carry out the regression analysis after week 3, because of the very low number of respondents in other weeks. However, there were some respondents that completed the program for 4 or 5 weeks. In week 4, this concerns 86 respondents (Ntotal=86, Nstrengths=26, Ndeficits=20, Ncombi=10, Nconrol=30). The results of the regression analysis with data of week 4 are shown in the table below (table 3). Table 3: Results of the Regression Analyses (week 4): Standardized Regression Coefficients (β), proportion explained variance (R² en R² Change) and the corresponding F-values (F and F Change).

Variables

Dummy Strengths Dummy Deficits Dummy Combi Age Gender Hours/Week R² R² Change F F Change

Change in Self-efficacy Model 1 β p .31 .01 .23 .05 -.06 .57

.12 .12 3.66 3.66

.02 .02

Model 2 β .32 .23 -.07 .05 .05 -.15 .15 .04 2.40 1.13

p .01 .06 .56 .63 .70 .21

.04 .34

Change in Resilience Model 1 β .26 .15 -.02

p .04 .22 .85

.07 .07 1.92 1.92

.13 .13

Model 2 β .29 .12 .01 -.12 .11 -.26 .18 .12 2.92 3.72

p .02 .31 .85 .26 .37 .03

.01 .02

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In week 4, the total model (Model 2, including control variables) explained the change in selfefficacy for 15%, and the model is significant (R²=.15, F=2.40, p=.04). The standardized regression coefficients were significant for the strengths-use group (β=.32, p=.01), on the borderline of significance for the deficit improvement group (β=.23, p=.06) but not for the combination group (β=-.07, p=.56). This means that in week 4 hypothesis 1a: “The use of a strengths-based online coaching intervention has a positive effect on someone’s self-efficacy” and hypothesis 2a: “The use of an online intervention focusing on improving deficits will have a positive effect on self-efficacy” can be confirmed. However, the relationship between the combination group and the change in self-efficacy is negative after week 4, which is contrary to the expected strong positive relationship. So in week 4 hypothesis 3a: “The use of an online strengths-based intervention in combination with an online deficit improvement intervention will lead to higher self-efficacy compared to using an online intervention solely based on strengths or deficits” is not confirmed as well as in week 3. For the change in resilience, some significant relationships were found with the data of week 4 as well. The total model (model 2), explained the change in resilience for 18% and the model was significant (R²=.18, F=2.92, p=.01). For the change in resilience, the strengths-use intervention was the only significant predictor (β=.29, p=.02), thereby hypothesis 1b: “The use of a strengths-based online coaching intervention has a positive effect on someone’s resilience” is supported after week 4. According to the results, the deficit improvement intervention was no significant predictor for the change in resilience (β=.12, p=.31), so hypothesis 2b: “The use of an online intervention focusing on improving deficits has a positive effect on someone’s resilience”, is not confirmed. The standardized regression coefficient for the combination group was again lower than for the other groups (β=.01, p=.96). This means that hypothesis 3b: “The use of an online strengths-based intervention in combination with an online deficit improvement intervention will lead to higher resilience compared to using an intervention solely based on strengths-use or deficit improvement” is not confirmed and even is contradicted. Plots with data of week 5

In addition to the regression analyses after week 4, some plots were made with the data of week 5 (the plots can also be found in the appendix) According to these measures, there is a slight increase in self-efficacy for both the strengths-use group (blue line) and the deficit improvement group (green line). The mean of self-efficacy for the combination group (brown line) is very unpredictable. For example, the mean of self-efficacy in week 2 is relatively 26

high, but in the next week it is much lower and in the fourth week it is high again. However the plot shows a small increase in self-efficacy from week 1 to week 5.

Figure 2. Estimated marginal means of self-efficacy

These effects were also found for resilience. Especially the respondents in the strengths-use group (blue line) and de deficit improvement group (green line) showed an increase in resilience. The resilience of the participants in the combination group (brown line) barely increased.

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Figure 3. Estimated marginal means of resilience

Because very little respondents filled out the questionnaires of week 5, it is necessary to be careful while interpreting these results (Nstrengths=15, Ndeficits=15, Ncombi=10, Ncontrol=26). In the next section the results of the analyses will be discussed and a short conclusion will be given.

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Conclusion and discussion This section will start with the interpretation of the results described in the previous chapter, followed by the limitations of this research and practical implications. Finally, directions for future research will be suggested and a short conclusion will be drawn.

Interpretation of the results The purpose of this study was to get an insight in the effects of different types of online coaching interventions on self-efficacy and resilience. This insight was obtained by studying the direct effect of a strengths-use online coaching intervention on self-efficacy and resilience, the direct effect of a deficit improvement online coaching intervention on self-efficacy and resilience and the direct effect of a combined intervention that focuses on both strengths-use and improving deficiencies on self-efficacy and resilience. According to the literature, it was expected that all types of intervention would have a positive effect on self-efficacy and resilience. It was also assumed that the combined intervention would have a stronger positive effect on both self-efficacy and resilience than the strengths-use intervention or the deficit improvement intervention. None of these expectations is confirmed by the results of the regression analyses in week 3. An explanation of the contrasting results in week 3 and hypotheses can be found in the duration of the research. The relationship between strengths-use and self-efficacy was explained by the theory of Bandura (1977). According to him, performance accomplishments are one of the major influences on self-efficacy. Within the short time period (3 weeks) of this research it was hard for respondents to reach their goals. A logical consequence is that the self-efficacy of the respondents will not increase significant in that period. This can also be applied to the respondents of the deficit group. It was stated that an employee would achieve a higher level of self-efficacy if he minimizes his deficits (Gist & Mitchell, 1992). Those deficits could be minimized by experience, according to Ericsson (2006). Though, it is impossible to practice so much in one or two weeks and let your deficits become strengths. Both the theory of Bandura and the theory of Ericsson would be applicable if the research would take longer than 3 weeks. Because no significant relationships were found, additional regression analyses with the results of week 4 were carried out. These analyses showed several significant relations. Self-

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efficacy and resilience were both significantly influenced by the use of strengths. Furthermore, the deficit improvement intervention is significantly related with self-efficacy. These findings are supported by the plots made with the results of week 5. These plots showed a strong increase in self-efficacy and resilience for the participants in the strengthsuse group and in the deficit improvement group. Subsequently, a very small increase of selfefficacy and resilience for the participants in the combination group can be found in the plots, but these lines are not really linear. The results after week 4 and 5 are interesting; they indicate that especially strengths-use can be an important tool in improving the self-efficacy and resilience of employees. Since deficit improvement always seemed to be the obvious way to develop employees, not much was written about this particular subject in the literature. Therefore, deficit improvement in the theoretical framework was compared with problem solving and approachcoping. However, these constructs were not used in the intervention. This could also be an explanation for the discrepancies between the expected relations between deficit improvement and resilience and the outcomes of the regression analyses. The expected positive relationships between the strengths-use intervention and self-efficacy and resilience and the deficit improvement intervention and self-efficacy and resilience were all based on previous literature. Although, Smith (2006) proposed a more balanced view of human nature and Rust, Diessner and Reade (2009) found a positive relationship between a combined intervention and life satisfaction, a relationship between a combined intervention and self-efficacy and/or resilience could not be found in literature. The assumptions made about the relationship between the combined intervention and self-efficacy and resilience were only based on the literature that focused on strengths or deficits separately. It was expected that the combined intervention would have an extra strong positive effect on selfefficacy and resilience. However, the standardized regression coefficients of the dummy for the combination group were very low in week 3 and in week 4 they were even negative. Because there is a clear distinction between strengths-use and improving deficits (in literature and practice), it may be that the two differ too much to combine them in the same intervention. The results of the combined intervention indicate that it would be better to focus solely on strengths or deficits in order to achieve higher levels of self-efficacy and resilience.

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Limitations Some findings in this study were in contrast with the expected relationships defined in the hypotheses. These discrepancies can be due to the limitations of this study. To start with, there were some reasons which caused attrition of respondents. The questionnaires were very long and respondents commented that many questions were quite the same. This could have caused fatigue respondents. Subsequently, many ICT-related problems were reported by the participants. Therefore, many people could not log into the online coaching program. This resulted in a very low number of respondents (N=120), which gives less power to the results of the study. The sample size determines the amount of sampling error inherent in a test result. Other things being equal, effects are harder to detect in smaller samples. Considering the very long questionnaires, respondents tend to answer the questions randomly. Subsequently, the means of resilience and self-efficacy were already high in week 1. This can be caused by the fact that people tend to give socially desirable answers. This study allowed participants to choose the characteristics they wanted to develop randomly. Maybe it would be better to just use the VIA test in order to identify strengths or deficits and then choose two of them to develop. In this research it is not clear whether the strengths chosen by a participant are really his or her strengths. In addition, the dependent variables are highly subjective. The questions can be interpreted in different ways by different respondents. Self-efficacy and resilience are not only determined by participating in a coaching intervention. Many other factors can influence self-efficacy and resilience each week. For example, someone can be affected by circumstances in the private life and occurrences at work. This study did not control for all these factors. At last, the fact that this intervention was just an online coaching intervention makes it difficult to ensure whether respondents truly succeeded the assignments. This is supported by the low mean of the variable 'action completed in week 3'.

Practical implications Although this study has some limitations and not all of the expected relations are confirmed, the results can be used to give some practical implications. When looking at the standardized regressions coefficient of the different intervention groups, it can be seen that the groups that focuses on strengths or deficits solely are a better predictor of both self-efficacy and resilience than the group that focuses on a combination of strengths and deficits. In week 4, the regression coefficients of the combination group were even negative. Therefore it is 31

recommended to organizations or coaching institutes to develop coaching programmes that focuses exclusively on strengths-use or exclusively on deficit improvement. Especially the strengths-use intervention showed strong significant relations with self-efficacy and resilience. Thereby, it is important for organizations to stimulate their employees in using their strong points, rather than highlighting their weaknesses. When looking at the results of the control variables, it can be found that employees who work more hours a week on average experience lower levels of self-efficacy and resilience than employees who work less hours a week. Now it is known that strengths use is significant related to self-efficacy and resilience (after week 4), employers should provide strengths based intervention to the employees who work a lot of hours a week. Then, the overall level of self-efficacy and resilience in the organization can increase possibly. Subsequently, practitioners who want to implement a strengths based intervention should use predetermined strengths to develop. Finally, an intervention should be conducted over a long time period in order to achieve a major increase in self-efficacy and resilience.

Directions for future research Future research should be carried out over an extended period of time. Such research can prove whether a longer coaching program will lead to larger changes in self-efficacy and resilience. In order to reduce attrition of respondents, it is necessary in future research to shorten the weakly questionnaires of the coaching program. This can be done in several ways. In this research, the respondents had to fill in the questionnaires about psychological capital, engagement and happiness every week, but only the data of the first and the last week were used in the analyses. It is recommended to ask the questions that measure these variables only in the first and last week. Then, the respondents will not recognize the questions of last week and will give a more realistic answer. Another way to shorten the program is to remove the "reflected self" exercise of week 1. It is recommended to only use the VIA test in order to identify strengths or deficits. Future researchers should, like the practitioners, focus on interventions that are solely based on strengths or deficits. The results of this study have shown that especially a strengths-based intervention will influence self-efficacy and resilience of employees in a positive way. It should be further examined how the interventions should be best implemented and which employees are most beneficial to such interventions.

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In addition, the online coaching program could be extended by 1 or 2 real live meetings. In this research, the respondents were coached by a fully computerized program. Maybe, people will take more action if they have a real coach. Finally, the number of respondents should be higher in future research. This will give more power to a study and makes it easier to generalize the results to a bigger population and thereby, more accurate conclusions can be made. Finally, future research should try to control for other factors that can influence self-efficacy and resilience.

Conclusion To conclude, after three weeks it was not proved that strengths-use, deficit improvement or a combination of these will lead to higher levels of self-efficacy or resilience. However, results of later weeks showed that strengths-use lead to higher self-efficacy and resilience and deficit improvement is a predictor of self-efficacy. Several reasons for discrepancies with the literature were mentioned. This study had some limitations and the study can be improved easily. Future research is recommended to focus on the positive outcomes of this study. Especially further developing strengths-based interventions is of importance.

33

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Fredrickson, B.L. (2004). The broaden-and-build theory of positive emotions. Philosophical Transactions of the Royal Society, 359, 1367-1377. Gable, S.L., &Haidt, J. (2005). What (and why) is positive psychology? Review of General Psychology, 9(2), 103-110. Gist, M.E., & Mitchell, T.R. (1992). Self-efficacy: A theoretical analysis of its determinants and malleability. The Academy of Management Review, 17(2), 183-211. Govindji, R., & Linley, P.A. (2007). Strengths use, self-concordance and well-being: Implication for strengths coaching and coaching psychologist. International Coaching Psychology Review, 2, 143-153. Grant, A.M., Curtayne, L., & Burton, G. (2009). Executive coaching enhances goal attainment, resilience and workplace well-being: A randomized controlled study. The Journal of Positive Psychology, 4(5), 396-407. Green, S., Grant, A., & Rynsaardt, J. (2007). Evidence-based life coaching for senior high school students: Building hardiness and hope. International Coaching Psychology Review, 2(1), 24-32. Grotberg, E. (2003). Resilience for Today: Gaining Strength from Adversity. Westport, CT: Praeger. Harland, L., Harrison, W., Jones, J.R., & Reiter-Palmon, R. (2005). Leadership behaviors and subordinate resilience. Journal of Leadership and Organizational Studies, 11(2), 2-14. Hodges, T.D., & Clifton, Strength-based development in practice. (In press). Accepted for publication in: Linley, P.A., & Joseph, S. (In press). International handbook of positive psychology in practice: From research to application. New Jersey: Wiley and Sons. Holahan, C., Moos, R., & Schaefer, J. (1996). Coping, stress resistance, and growth: Conceptualizing adaptive functioning. In M. Zeidner& N. Endler (Ed.), Handbook of Coping: Theory, Research, Applications (p. 24-43). New York, NY: Wiley. Kaiser, R.B., &Overfield, D.V. (2011). Strengths, strengths overused and lopsided leadership. Consulting Psychology Journal: Practice and Research, 63(2), 89-109. Lietz, C.A. (2008). Resiliency based social learning: A strengths based approach. Residential Treatment for Children & Youth, 22(2), 21-36. Linley, P.A., & Harrington, S. (2006a). Strengths coaching: A potential-guided approach to coaching psychology. International Coaching Psychology Review, 1(1), 37-46. London, M. (1993). Career motivation of full- and part-time workers in mid and late career. International Journal at Career Management, 5 (1).

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Luthans, F. (2002). The need for and meaning of positive organizational behavior. Journal of Organizational Behavior, 23, 695-706. Luthans, F., Avey, J.B., Avolio, B.J., & Norman, S.M. (2007). Positive psychological capital: Measurement and relationship with performance and satisfaction. Personnel Psychology, 60, 541-572. Luthans, F., Avey, J. B., Avolio, B. J., Norman, S. M., & Combs, G. J. (2006). Psychological capital development: Toward a micro-intervention. Journal of Organizational Behavior, 27, 387–393. Luthans, F., Avey, J.B., &Patera, J.L. (2008). Experimental analysis of a web-based training intervention to develop positive psychological capital. Academy of Management Learningand Education, 7(2), 209-221. Luthans, F., Avolio, B. J., &Avey, B. (2007). Psychological Capital Questionnaire, 12 core items of self rater form. Mind Garden, Inc. Luthans, F., Youssef, C.M., &Avolio, B.J. (2007). Psychological Capital: Developing the Human Competitive Edge. Oxford, United Kingdom: Oxford University Press. Luthar, S.S., Cicchetti, D., & Becker, B. (2000). The construct of resilience: A critical evaluation and guidelines for future work. Child Development, 71(3), 543-562. Maslach, C., Schaufeli, W.B., &Leiter, M.P. (2001). Job burnout. Annual Review of Psychology, 52, 397-422. Meyers, M.C., Van Woerkom, M., & Bakker, A.B. (2012). The added value of the positive: A literature review of positive psychology interventions in organizations. European Journal of Work and Organizational Psychology, 1-15. Peterson, C., & Seligman, M.E.P. (2004). Character Strengths and Virtues: A Handbook and Classification. New York, Oxford University Press. Pleunis, I. (2012). Strength versus deficiencies: A comparison of workshop effectiveness. Master Thesis Tilburg University, Tilburg Proctor, C., Maltby, J., & Linley, P.A. (2011). Strengths use as a predictor of well-being and health related quality of life. Journal of Happiness Studies, 12, 153-169. Quinlan, D., Swain, N., & Vella-Brodrick, D. (2012). Character strengths interventions: Building on what we know for improved outcomes. Journal of Happiness Studies, 13, 1145-1163. Rath, T. (2007). Strengths Finder 2.0. New York: Gallup Press.

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Roberts, L. M., Dutton, J. E., Spreitzer, G. M., Heaphy, E. D., & Quinn, R. E. (2005). Composing the reflected best-self portrait: Building pathways for becoming extraordinary in work organizations. Academy of Management Review, 30 (4), 712736. Rust, T., Diessner, R., & Reade, L. (2009). Strengths only or strengths and relative weaknesses? A preliminary study. The Journal of Psychology, 143(5), 465-476. Schwarzer, R., Bäβler, J., Kwiatek, P., & Schröder, K. (1997). The assessment of optimistic self-beliefs: Comparison of the German, Spanish, and Chinese versions of the general self-efficacy scale. Applied Psychology: An International Review, 46 (1), 69-88. Seligman, M. E. P., & Csikszentmihalyi, M. (2000). Positive psychology: An introduction. AmericanPsychologist, 55, 5–14. Seligman, M.E.P., Steen, T.A., Park, N., & Peterson, C. (2005). Positive psychology progress: Empirical validation of interventions. American Psychologist, 60, 410-421. Smith, E.J. (2006). The strength-based counseling model. The Counseling Psychologist, 34, 13-79. Stajkovic, A., & Luthans, F. (1998). Social cognitive theory and self-efficacy: Going beyond traditional motivational and behavioral approaches. Organizational Dynamics, 26, 62– 74. Staw, B.M., Sutton, R.I., &Pelled, L.H. (1994). Employee positive emotion and favorable outcomes at the workplace. Organization Science, 5(1), 51-71. Tugade, M. M., Fredrickson, B. L., & Barrett, L. F. (2004). Psychological resilience and emotional granularity: Examining the benefits of positive emotions on coping and health. Journal of Personality, 72, 1161–1190. Wasonga, T., Christman, D.E., & Kilmer, L. (2003). Ethnicity, gender and age: Predicting resilience and academic achievement among urban high school students. American Secondary Education, 32 (1), 62-74. Wood, R.E., & Bandura, A. (1989a). Impact of conceptions of ability on self-regulatory mechanisms and complex decision making. Journal of Personality and Social Psychology, 56, 407-415. Wood, A.M., Linley, P.A., Maltby, J.M., Kashdan, T.B., & Hurling, R. (2011). Using personal and psychological strengths leads to increase in well-being over time: A longitudinalstudy and the development of the strengths use questionnaire. Personality and Individual Differences, 50, 15-19

37

Appendices Appendix 1: Frequencies population Frequencies Age Statistics 1.) ... jaar N

Valid

120

Missing

0

Mean

38,23

Minimum

20

Maximum

63

Frequencies Gender 2.) Ben je man of vrouw? Cumulative Frequency Valid

Percent

Valid Percent

Percent

Man

48

40,0

40,0

40,0

Vrouw

72

60,0

60,0

100,0

120

100,0

100,0

Total

Frequencies Education level 4.) Wat is je hoogst behaalde opleidingsniveau? Frequency Valid

Percent

Valid Percent

Cumulative

6

5,0

5,0

Percent 5,0

19

15,8

15,8

20,8

HAVO

5

4,2

4,2

25,0

VWO/Gymnasium

3

2,5

2,5

27,5

HBO

53

44,2

44,2

71,7

Universiteit

34

28,3

28,3

100,0

120

100,0

100,0

VMBO (LTS, MAVO, MULO, MBO LBO, VBO)

Total

Frequencies Working hours a week Statistics 6.) ... uur per week N

Valid Missing

Mean

120 0 31,77

38

Appendix 2: Output reliability analyses Virtues in Action Scale: Creativity/creatief Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .774

5

Item-Total Statistics

17.) Ik ben in staat met

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

14.92

6.452

.742

.679

15.06

6.385

.612

.711

14.80

7.078

.588

.727

15.15

6.342

.466

.767

15.60

6.312

.441

.780

nieuwe ideeën en invalshoeken te komen. 17.) Ik denk graag na over nieuwe manieren om dingen te doen. 17.) Ik bedenk nieuwe oplossingen voor problemen. 17.) Ik ben een oorspronkelijk denker. 17.) Mijn verbeelding gaat die van mijn vrienden te boven.

39

Scale: Studious/leergierig

Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .707

5

Item-Total Statistics

18.) Ik span mij in om iets

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

15.57

7.683

.333

.704

15.52

6.911

.615

.619

15.63

6.283

.632

.593

15.87

5.289

.608

.589

16.06

6.855

.263

.760

nieuws onder de knie te krijgen. 18.) Ik vind het heerlijk als ik iets nieuws leer. 18.) Ik kijk altijd uit naar mogelijkheden om te groeien en te leren. 18.) Een leven lang leren is echt iets voor mij. 18.) Ik lees veel en graag.

40

Scale: Wise/wijs Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .658

5

Item-Total Statistics

19.) Ik heb een veelzijdige

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

15.59

4.103

.526

.550

15.83

4.405

.445

.590

15.60

4.595

.233

.705

15.60

4.171

.545

.544

15.84

4.891

.363

.627

kijk op wat er gebeurt. 19.) Ik word beschouwd als een wijs persoon. 19.) Ik verlies niet uit het oog wat het belangrijkst is in het leven. 19.) Ik ben er goed in om uit te vogelen waar het eigenlijk om gaat. 19.) Ik word vaak om advies gevraagd door anderen.

41

Scale: Decisive/doortastend Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .764

6

Item-Total Statistics

20.) Ik stop niet met een

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

19.94

7.467

.602

.704

19.69

7.983

.614

.707

19.48

7.523

.641

.695

19.21

8.967

.397

.756

20.38

7.580

.377

.783

19.38

8.027

.500

.732

taak voordat die is afgerond. 20.) Ik ben een doelgericht persoon. 20.) Ik maak dingen af, ondanks hindernissen onderweg. 20.) Ik ben een harde werker. 20.) Ik raak niet afgeleid als ik werk. 20.) Ik geef niet gemakkelijk op.

42

Scale: Brave/moedig Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .835

5

Item-Total Statistics

21.) Ik heb regelmatig

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

14.62

8.545

.665

.793

14.31

7.677

.738

.771

14.41

8.950

.558

.823

14.42

8.058

.690

.786

13.73

10.034

.548

.826

stellingen ingenomen en verdedigd die slecht lagen in een groep. 21.) Ik aarzel niet om een onpopulaire mening te uiten 21.) Ik ben een dapper persoon. 21.) Ik vermijd geen ongemakkelijke situaties. 21.) Ik kom op voor de dingen waarin ik geloof.

43

Scale: Enthusiastic/enthousiast Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .639

5

Item-Total Statistics

22.) Ik kijk niet van de zijlijn

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

15.24

4.893

.332

.617

14.94

5.044

.298

.633

22.) Ik houd van wat ik doe.

14.85

4.812

.499

.540

22.) Ik kijk uit naar elke

14.97

4.575

.554

.511

15.12

4.927

.323

.621

toe, maar ga helemaal op in wat er gebeurt. 22.) Ik benader dingen niet halfslachtig.

nieuwe dag. 22.) Ik kan niet wachten om aan een project te beginnen.

44

Scale: Righteous/rechtvaardig Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .659

6

Item-Total Statistics

23.) Ik geef het toe als ik

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

19.93

6.019

.331

.639

20.01

4.906

.479

.583

19.77

6.134

.293

.653

19.60

5.889

.507

.580

19.76

5.998

.466

.594

19.59

6.809

.315

.642

ongelijk heb. 23.) Ik behandel alle mensen op dezelfde manier. 23.) Ik ben een goede luisteraar 23.) Ik geloof dat de rechten van iedereen even belangrijk zijn. 23.) Ik geef iedereen een kans. 23.) Ik vind dat iedereen zijn zegje moet kunnen doen.

45

Scale: Leadership/leider

Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .793

5

Item-Total Statistics

24.) Ik probeer iedereen het

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

13.95

9.292

.458

.787

13.92

9.676

.455

.790

14.66

7.261

.678

.717

14.26

6.663

.728

.697

14.19

7.589

.579

.753

gevoel te geven dat zij deel uitmaken van de groep. 24.) Ik kan mensen goed helpen om samen te werken. 24.) Ik heb gehoord dat ik een sterke en rechtvaardige leider ben. 24.) Ik kan in een groep goed het heft in handen nemen. 24.) Ik ben goed in het plannen van groepsactiviteiten.

46

Scale: Teamplayer/teamspeler Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .694

5

Item-Total Statistics

25.) Ik sla geen

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

15.72

3.827

.397

.670

15.06

3.350

.597

.573

15.00

4.071

.464

.640

15.36

4.445

.340

.685

15.14

3.745

.462

.639

groepsbijeenkomsten over. 25.) Ik vind het prettig deel uit te maken van een groep. 25.) Ik ondersteun mijn teamgenoten. 25.) Ik heb het gevoel dat ik de beslissingen van de groep moet respecteren. 25.) Ik ben goed in het werken in een groep.

47

Scale: Friendly/vriendelijk Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .790

6

Item-Total Statistics

26.) Ik ben nooit te druk om

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

19.65

7.289

.592

.746

19.95

7.527

.475

.773

19.48

7.005

.547

.757

19.84

7.761

.405

.790

19.60

7.865

.520

.764

19.67

6.269

.727

.706

een vriend te helpen. 26.) Ik span mij in om mensen die somber zijn op te vrolijken. 26.) Ik vind het heerlijk anderen een plezier te doen. 26.) Ik ben net zo blij met het goede dat anderen ten deel valt als met wat mijzelf ten deel valt. 26.) Ik vind het prettig om anderen te laten delen in aandacht en waardering. 26.) Ik probeer anderen vaak een plezier te doen.

48

Scale: Socially skilled/sociaal vaardig Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .720

6

Item-Total Statistics

27.) Ik ben in staat mij te

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

19.55

8.298

.272

.742

19.30

8.355

.454

.684

19.51

7.853

.566

.653

19.47

7.546

.442

.686

19.35

7.595

.466

.677

19.45

7.404

.583

.642

voegen naar iedere situatie. 27.) Ik heb het vermogen anderen het gevoel te geven dat zij ertoe doen. 27.) Ik weet wat anderen beweegt. 27.) Ik kan goed opschieten met mensen die ik net heb ontmoet. 27.) Ik kan goed registreren wat anderen voelen. 27.) Ik weet wat ik moet zeggen om anderen een goed gevoel te bezorgen.

49

Scale: Thoughtful/bedachtzaam Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .685

5

Item-Total Statistics

28.) Ik neem pas een

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

15.87

4.395

.407

.653

15.71

5.573

.164

.739

15.31

4.736

.454

.629

15.43

3.942

.605

.552

15.21

4.356

.614

.563

beslissing als ik alle feiten ken. 28.) Ik word door anderen gewaardeerd vanwege mijn objectiviteit. 28.) Ik geloof dat het zin heeft zaken goed te doordenken. 28.) Ik weeg de plussen en de minnen goed af. 28.) Ik probeer goede redenen te hebben voor belangrijke beslissingen.

50

Scale: Humorous/humoristisch Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .540

4

Item-Total Statistics

29.) Ik probeer mijn

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

12.10

2.824

.221

.549

11.97

3.069

.146

.596

11.99

1.941

.481

.310

12.19

2.130

.481

.323

vrienden op te vrolijken als ze een sombere bui hebben. 29.) Ik probeer plezier te hebben in allerlei situaties. 29.) Ik probeer humor in te zetten bij alles wat ik doe. 29.) Ik behoud mijn gevoel voor humor in sombere situaties.

51

Scale: Hope/hoopvol Case Processing Summary N Cases

Valid a

Excluded Total

% 86

71.7

34

28.3

120

100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha

N of Items .647

5

Item-Total Statistics

30.) Het glas is bij mij altijd

Corrected Item-

Cronbach's

Scale Mean if

Scale Variance

Total

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Deleted

15.21

4.426

.463

.563

15.07

4.348

.457

.565

14.94

4.197

.572

.508

15.09

6.179

.021

.735

15.50

4.276

.507

.539

halfvol. 30.) Ik ben in staat het positieve te vinden in wat anderen negatief vinden. 30.) Ik blijf hoopvol ondanks tegenslagen. 30.) Ik zal de doelen halen die ik mijzelf heb gesteld. 30.) Als ik me rot voel, denk ik aan het goede in mijn leven.

52

Appendix 3: Output reliability analyses self-efficacy and resilience Scale: Self-Efficacy Week 1

Reliability Statistics Cronbach's Alpha Based on Cronbach's

Standardized

Alpha

Items ,824

N of Items ,826

4

Item-Total Statistics

10.) Ik voel me zeker

Corrected Item-

Squared

Cronbach's

Scale Mean if

Scale Variance

Total

Multiple

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Correlation

Deleted

14,05

8,401

,537

,373

,825

14,21

7,057

,744

,561

,737

13,97

6,873

,623

,460

,793

14,18

6,398

,714

,514

,747

genoeg om een lange termijn probleem te analyseren en daarvoor een oplossing te vinden. 10.) Ik voel me zeker genoeg om bij te dragen aan het stellen van doelen van mijn afdeling. 10.) Ik voel me zeker genoeg om contact op te nemen met mensen buiten de organisatie (bijvoorbeeld leveranciers, klanten) om problemen te bespreken. 10.) Ik voel me zeker genoeg om informatie te presenteren voor een groep collega's.

53

Scale: Self-Efficacy week 3 Reliability Statistics Cronbach's Alpha Based on Cronbach's

Standardized

Alpha

Items ,845

N of Items ,850

4

54

Scale: Resilience week 1 Reliability Statistics Cronbach's Alpha Based on Cronbach's

Standardized

Alpha

Items ,867

N of Items ,872

4

Item-Total Statistics

11.) Gewoonlijk kan ik

Corrected Item-

Squared

Cronbach's

Scale Mean if

Scale Variance

Total

Multiple

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Correlation

Deleted

13,36

7,610

,735

,571

,832

13,49

6,655

,735

,594

,822

13,36

6,854

,668

,472

,850

13,52

6,134

,761

,584

,813

moeilijkheden op mijn werk op de een of andere manier wel aan. 11.) Gewoonlijk neem ik stressvolle dingen op het werk er gewoon bij. 11.) Moeilijke momenten op het werk kan ik best aan, want ik heb al voor hetere vuren gestaan. 11.) Ik heb het gevoel dat ik veel dingen tegelijkertijd aankan op mijn werk.

55

Scale: Resilience week 3 Reliability Statistics Cronbach's Alpha Based on Cronbach's

Standardized

Alpha

Items ,927

N of Items ,928

4

Item-Total Statistics

2.) Moeilijkheden op mijn

Corrected Item-

Squared

Cronbach's

Scale Mean if

Scale Variance

Total

Multiple

Alpha if Item

Item Deleted

if Item Deleted

Correlation

Correlation

Deleted

13,42

8,413

,817

,682

,910

13,58

7,909

,865

,753

,894

13,36

8,450

,805

,652

,914

13,59

7,605

,843

,716

,903

werk kan ik op de een of andere manier wel aan. 2.) Stressvolle dingen op het werk neem ik er gewoon bij 2.) Moeilijke momenten op het werk kan ik best aan, want ik heb al voor hetere vuren gestaan 2.) Ik heb het gevoel dat ik veel dingen tegelijkertijd aankan op mijn werk.

56

Appendix 4: Output Correlation Matrix

Correlations

** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

57

Appendix 5: Output Frequencies: Mean Self-efficacy and Resilience Week 1 and 3 Statistics

N

Valid

SEWEEK1_TO

SEWEEK3_TO

RESWEEK1_T

RESWEEK3_T

TAAL

TAAL

OTAAL

OTAAL

120

120

120

120

0

0

0

0

Mean

4,7000

4,6979

4,4771

4,4958

Std. Deviation

,86821

,81664

,85134

,93709

Missing

58

Appendix 6: Output regression analysis after week 3 Regression Self-efficacy Variables Entered/Removed Variables

Variables

Entered

Removed

Model 1

DummyCombi,

b

Method

.

Enter

.

Enter

DummyDeficits, DummyStrength s 2

Man of vrouw, ....jaar, Hoeveel uur per week werk je

a. All requested variables entered. b. Dependent Variable: DELTA_SE c

Model Summary

Change Statistics

Model

R

1 2

R Square

Adjusted R

Std. Error of the

R Square

Square

Estimate

Change

F Change

df1

,121

,015

-,011

,71795

,015

,579

3

116

,203

b

,041

-,010

,71755

,027

1,042

3

113

a. Predictors: (Constant), DummyCombi, DummyDeficits, DummyStrengths b. Predictors: (Constant), DummyCombi, DummyDeficits, DummyStrengths, Man of vrouw, ....jaar, Hoeveel uur per week werk je c. Dependent Variable: DELTA_SE c

ANOVA Model 1

2

df2

a

Sum of Squares Regression

df

Mean Square

,895

3

,298

Residual

59,792

116

,515

Total

60,687

119

2,505

6

,418

Residual

58,182

113

,515

Total

60,687

119

Regression

F

Sig. ,579

,630

a

,811

,564

b

a. Predictors: (Constant), DummyCombi, DummyDeficits, DummyStrengths b. Predictors: (Constant), DummyCombi, DummyDeficits, DummyStrengths, Man of vrouw, ....jaar, Hoeveel uur per week werk je c. Dependent Variable: DELTA_SE

59

60

Regression Resilience

c

ANOVA Model 1

2

Sum of Squares Regression

df

Mean Square

,836

3

,279

Residual

74,059

116

,638

Total

74,895

119

6,099

6

1,017

Residual

68,796

113

,609

Total

74,895

119

Regression

F

Sig. ,436

,727

a

1,670

,135

b

a. Predictors: (Constant), DummyCombi, DummyDeficits, DummyStrengths b. Predictors: (Constant), DummyCombi, DummyDeficits, DummyStrengths, Man of vrouw, ....jaar, Hoeveel uur per week werk je c. Dependent Variable: DELTA_RES

61

62

Appendix 7: Output regression analysis after week 4 Regression Self-efficacy

63

Regression Resilience

64

Appendix 8: Plots with data of week 5 Self-efficacy:

Resilience:

65

Appendix 9: Questionnaires Self-efficacy: 1) Ik voel me zeker genoeg om een lange termijn probleem te analyseren en daarvoor een oplossing te vinden. 2) Ik voel me zeker genoeg om bij te dragen aan het stellen van doelen van mijn afdeling. 3) Ik voel me zeker genoeg om contact op te nemen met mensen buiten de organisatie (bijvoorbeeld leveranciers, klanten) om problemen te bespreken. 4) Ik voel me zeker genoeg om informatie te presenteren voor een groep collega's.

Resilience: 1) Moeilijkheden op mijn werk kan ik op de een of andere manier wel aan. 2) Stressvolle dingen op het werk neem ik er gewoon bij 3) Moeilijke momenten op het werk kan ik best aan, want ik heb al voor hetere vuren gestaan 4) Ik heb het gevoel dat ik veel dingen tegelijkertijd aankan op mijn werk.

66

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Master Thesis - University of Tilburg - Tilburg University

Master Thesis The effect of online coaching interventions on employee’s self-efficacy and resilience at work. A quantitative study in The Netherlands...

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