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Open Access

Peer-reviewed

Research Article

Positive organizational behavior: Longitudinal effects on subjective well-being

  • Kathrin Heinitz ,

    Contributed equally to this work with: Kathrin Heinitz, Timo Lorenz, Daniel Schulze

    Roles Conceptualization, Methodology, Writing – original draft, Writing – review & editing

    kathrin.heinitz@fu-berlin.de

    Affiliation Department of Education and Psychology, Freie Universitaet Berlin, Berlin, Germany

    ⨯
  • Timo Lorenz ,

    Contributed equally to this work with: Kathrin Heinitz, Timo Lorenz, Daniel Schulze

    Roles Conceptualization, Data curation, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Department of Education and Psychology, Freie Universitaet Berlin, Berlin, Germany

    ⨯
  • Daniel Schulze ,

    Contributed equally to this work with: Kathrin Heinitz, Timo Lorenz, Daniel Schulze

    Roles Data curation, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Department of Education and Psychology, Freie Universitaet Berlin, Berlin, Germany

    ⨯
  • Julia Schorlemmer

    Roles Conceptualization, Writing – original draft

    Affiliation Department of Occupational Medicine, Charité Berlin, Berlin, Germany

    ⨯

Abstract

Increasing individual subjective well-being has various positive outcomes, knowledge about its antecedents and the mediators of this relationship can therefore help to increase subjective well-being and the accompanying positive effects. The more future oriented facets of psychological capital, i.e. optimism, hope and self-efficacy have been shown in several studies to be positively related to subjective well-being and negatively to ill-being. Furthermore, recent studies suggest coping strategies as mediators for these relationships. In our study, we examined the longitudinal relation of optimism, hope and self-efficacy with subjective well-being and ill-being in a German panel dataset and tested the mediating effect of flexible goal adjustment in a path model. Our results show a statistically significant positive effect of self-efficacy and optimism on subjective well-being as well as a statistically significant negative effect of optimism on depression over three years. All three predictors show a statistically significant relation with flexible goal adjustment, but flexible goal adjustment did not mediate the effect on subjective well-being or depression.

Citation: Heinitz K, Lorenz T, Schulze D, Schorlemmer J (2018) Positive organizational behavior: Longitudinal effects on subjective well-being. PLoS ONE 13(6): e0198588. https://doi.org/10.1371/journal.pone.0198588

Editor: Amelia Manuti, Universita degli Studi di Bari Aldo Moro, ITALY

Received: March 21, 2017; Accepted: May 22, 2018; Published: June 22, 2018

Copyright: © 2018 Heinitz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data for this study comes from the 2008 wave of the German Ageing Survey (DEAS). The data is not owned by the authors but property of the Research Data Centre (FDZ-DZA). Data from the Research Data Centre (FDZ-DZA; https://www.dza.de/en/fdz.html) is available free of charge to scientific researchers for non-profitable purposes. The FDZ-DZA provides access and support to scholars interested in using DEAS data for their research. Data from completed waves are available for the scientific community free of charge. However, for reasons of data protection, signing a data distribution contract is required before data can be obtained. The FDZ-DZA can be contacted via an application form: https://www.dza.de/en/fdz/access-to-data/formular-deas-en-english.html For this study the data waves 2008 and 2011 were used.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that not competing interests exist.

Introduction

Happy workers will be more productive workers—as Cropanzano and Wright [1] acknowledge, this relation has been supported if happiness was operationalized as well-being, although the happy-productive worker hypothesis [2] has been subjected to much debate and produced controversial empirical results [3]. To learn about mechanisms that increase well-being is relevant in the work context as well as independent of the context [4]. It is relevant for the individual itself, but also, according to the happy productive worker hypothesis, for organizations.

Numerous theories have set out to explain how various individual or job characteristics influence well-being (for an overview see [5]), e.g. the conservation of resources theory [6], the job-demands-resources theory [7] or the stressor-detachment model [8]. According to the conservation of resources theory [6], individuals seek to acquire and maintain resources. Their gain or maintenance results in well-being [9]. Hobfoll [6] distinguishes four types of resources that have the potential to increase well-being: physical objects, conditions, energies or personal characteristics [9]. In our study we focus on personal characteristics and more specifically on characteristics proposed by positive psychology, as well-being can be enhanced by interventions targeting on these constructs [10]. More specifically we examine the longitudinal effects of self-efficacy, optimism and hope on well-being. Coping strategies are being discussed to function as mediating mechanisms of this relation [11]. Flexible goal adjustment as one coping strategy has been shown to mediate the relationship between optimism and well-being in a concurrent sample [11]. We therefore also examine if flexible goal adjustment mediates the relation between the three facets optimism, hope and self-efficacy with well-being over time.

Positive organizational behavior: Self-efficacy, optimism and hope

Positive psychology in the workplace encompasses various concepts [12] such as positive organizational behavior or positive organizational scholarship. They are united in their focus on strengths and flourishing [13, 14] but have differing perspectives. The focus of positive organizational behavior is on the individual within the organization. Luthans [15] defines micro-level positive organizational behavior as the “study and application of positively oriented human resource strengths and psychological capacities”(p59). Positive organizational behavior in this sense is measurable and meets the open-to-development criterion. It is therefore open to individual learning and change [15–17]. Three of these positive organizational behavior capacities are self-efficacy, optimism, and hope. They all “fit the specific criteria of being positive, unique, measurable, capable of being learned and developed, and manageable for performance improvement”([15] p70). All three are part of the overarching concept of Psychological Capital (PsyCap) [18, 17], including resiliency besides self-efficacy, optimism, and hope. PsyCap was developed as a work-related concept and, as a whole, is defined as “a core psychological factor of positivity in general, and POB criteria meeting states in particular, that go beyond human and social capital to gain a competitive advantage through investment/development of ‘who you are’” ([18] p253). PsyCap influences a variety of outcomes, such as job satisfaction and commitment [19, 20] or reduced absenteeism [21]. Furthermore, individuals high in PsyCap perform better than those low in PsyCap since they can draw upon more resources to pursue goals [22, 23]. Furthermore, PsyCap is linked to an improved psychological and physical well-being [24]. Of the four PsyCap components especially self-efficacy, optimism and hope are goal- and future oriented.

Self-efficacy is a dispositional resource used for coping with all kinds of demands and challenges [25, 26] and can be defined as “one’s beliefs about his or her ability to mobilize the motivation, cognitive resources, and courses of action necessary to execute a specific action within a given context”([27] p66). Optimism as conceptualized within the concept of PsyCap [28] includes not only the dispositional optimistic look towards the future, but also global positive expectations [29, 30]. Following Seligman [14], not only this positive outlook but also the personal reflection of positive and negative events in the past, present and future relevantly influence optimism [30]. Optimistic persons expect positive things to happen and therefore believe in a positive future [31, 32]. Hope is “a positive motivational state that is based on an interactively derived sense of successful agency (goal directed energy) and pathways (planning to meet goals)”([33] p287). Hopeful individuals are able to generate alternative routes in an adaptive way [34, 35]. Goal-directed thoughts lead to positive and active emotions (e.g. curiosity) or negative and passive emotions, depending on past experiences with goal pursuits [36, 35]. Hopeful individuals use the ‘willpower’ to generate personal goals and resolutely follow them and the ‘waypower’ to adapt alternatives while obstacles occur on their way [37]. There has been a lot of research regarding the distinction of optimism and hope [38–42], and while being overlapping and having trait-like thoughts about goals in common [41], their differential relations with outcomes suggest that they are still distinct constructs [39, 43].

Subjective well-being, ill-being and positive organizational behavior

All three, self-efficacy, hope, and optimism have shown to be related to or predict well-being as well as ill-being. One way of operationalizing well-being is via subjective well-being, which is a multifaceted construct, consisting of affective and cognitive components [44]. It is not only associated with but can also lead to health and longevity [3, 45, 46], increase work-related productivity and success [47], and positively influence social relationships [45, 48]. In contrast to well-being is the term ill-being, which refers to negative psychological constructs such as depression [49]. For the examination of the effects of positive organizational behavior both aspects seem to be relevant, the prevention of ill-being as well as the promotion of subjective well-being, as the absence of ill-being does not automatically lead to subjective well-being and vice versa [50].

Self-efficacy as “the power of believing you can” [51] correlates to and influences well-being positively [25, 52–56], and reduces depression [57–59]. Optimism influences the way people feel and how they actively try to solve problems when being confronted with obstacles and hence influences subjective well-being [60–62]. Practicing optimism leads to increased well-being [63]. Hopeful individuals are motivated to energetically pursue goals and to consider alternative routes to achieve them [37]. They “generate more effective coping strategies to setbacks due to pathways thinking, and thus experience more positive emotions which”([37] p295) and this enhances their well-being. Accordingly, in their meta-analysis and review, Reichard et al. [37] found statistically significant effect sizes between hope and job satisfaction and well-being and negative effect sizes between hope, stress, and burnout.

So far, no study compared the effects of these three central constructs of positive psychology. PsyCap is the only exception, but it is mostly examined as g-factor, effects of its subfacets are seldom shown. PsyCap also has statistically significant relations to well-being [64] and predicts subjective well-being within a three-week period [65]. According to previous research on self-efficacy, optimism and hope with well-being and ill-being, we propose:

  1. (1). Self-efficacy (a), optimism (b) and hope (c) at T0 positively predict subjective well-being at T1.
  2. (2). Self-efficacy (a), optimism (b) and hope (c) at T0 negatively predict depression scores at T1.

Flexible goal-adjustment as a mediator

Goal regulation strategies have been frequently discussed as possible mediators between optimism and well-being [11, 66, 67]. The results of Hanssen et al. [11] suggest that especially flexible goal adjustment applies as a mediator in this relationship. Flexible goal adjustment can be seen as passive accommodative coping, as changing personal preferences due to situational restrictions, which seems to be especially relevant in later life [68]. It is complementary to tenacious goal pursuit, an assimilative coping strategy, in which life circumstances are adjusted to obtain a desired condition [68]. The flexible management of personal goals is associated with well-being [69–73]. Goal regulation strategies such as flexible goal adjustment were found to affect the quality of life and general well-being of patients with chronic illnesses [74, 75]. Furthermore, in older age flexible people report higher levels of self-esteem [76] and are more likely to look at their biographical past in a self-enhancing way [77]. By disengaging old goals when necessary, reengaging new goals and accepting this change by adjusting to the situation, people can stay optimistic and hopeful despite witnessed difficulties and are more satisfied with their lives [68, 71]. At first sight, high self-efficacy should inhibit flexible goal adjustment, in a sense that if one is certain about one’s possibilities, there is no need to change a goal. But as Brandtstädter ([78] p143) argued, it might not be that simple, as “if getting what one wants is central to the concept of power, it follows that a way to retain a sense of efficacy may be to adjust one’s preferences to the range of the feasible”. Following this argumentation, the relation of self-efficacy and subjective well-being as well as depression, should also be mediated by flexible goal adjustment.

We therefore propose:

  1. (3). Flexible goal adjustment mediates the effect of self-efficacy (a), optimism (b) and hope (c) at T0 on subjective well-being at T1.
  2. (4). Flexible goal adjustment mediates the effect of self-efficacy (a), optimism (b) and hope (c) at T0 on depression at T1.

Method

Participants and procedure

Data for this study comes from the German Ageing Survey [79], an ongoing register-based, cohort-sequential, nationwide representative survey of the German population aged 40 to 85. The present study used the sample of 2008 (6205 participants) and 2011. In 2011, 2858 participants of the original sample were re-interviewed with a response rate of 64.4%. The response rate corresponds to that of other longitudinal studies with comparable age groups [80]. Participants completed face-to-face interviews and a self-administered questionnaire. Due to the longitudinal data analysis only people who were interviewed 2008 and 2011, with employment status working and maximum age 65 (maximum retirement age in Germany) were included. These criteria excluded 1858 persons from the data analysis. Furthermore, 408 were excluded due to missing data (345 due to declined answers on relevant variables, 63 due to high amount (> 50%) of missing data scale wise). The total sample included 592 people between 39–62 years of age in 2008 (M = 49.43, SD = 5.60), and nearly half of them (47%) were men.

Measures

Self-Efficacy was measured using the Generalized Self-Efficacy Scale [81]. The scale consists of 5 items (e.g. “I can usually handle whatever comes my way”) with a 4-point Likert response format (Cronbach’s α2008 = .79; α2011 = .79).

Optimism was measured using the ‘Affective valence of future time perspective’ scale [82]. The scale consists of five items (e.g. “I look to the future with confidence”) with a 4-point Likert response format (Cronbach’s α2008 = .86; α2011 = .86).

Hope was measured using the Hope Scale [83]. The scale consists of 8 items (e.g. “There are lots of ways around any problem”) with a 4-point Likert response format (Cronbach’s α2008 = .83; α2011 = .83).

Flexible goal adjustment was measured using the Flexible Goal Adjustment Scale [84]. The scale consists of 10 items (e.g. “I adapt quite easily to changes in plans or circumstances”) with a 5-point Likert response format (Cronbach’s α2008 = .77; α2011 = .77).

Subjective well-being was composed of the three factors positive affect, negative affect, and life satisfaction [44]. The affective component of subjective well-being was measured using the German version [85] of the brief Positive Affect Negative Affect Scale (PANAS) [86]. The scale consists of 10 items, 5 negative adjectives (e.g. “ashamed”, Cronbach’s α2008 = .87; α2011 = .86) and 5 positive adjectives (e.g. “enthusiastic”, Cronbach’s α2008 = .85; α2011 = .86) with a 5-point Likert response format.

The cognitive component of subjective well-being was measured using Satisfaction with Life Scale [87]. The scale consists of 5 items (e.g. “I am satisfied with my life”) with a 5-point Likert response format (Cronbach’s α2008 = .84; α2011 = .85).

Depressive symptoms were measured using the General Depression Scale (Allgemeine Depressions Skala) [88]. The scale consists of 15 items (e.g. “I felt that everything I did was an effort”) with a 4-point Likert response format (Cronbach’s α2008 = .85; α2011 = .87).

More details on the questionnaires used can be found at www.dza.de/en/research/deas/research-instruments.html.

Covariates / Control variables

Sex is an important covariate for subjective well-being, as it has been revealed that especially older women reported lower subjective well-being [89] and there are differential relations for sex between our predictors and subjective well-being [37]. Income and education are positively related to subjective well-being [90]. The socio-economic status (SES) in general affects physical and psychological health negatively [91, 92]. SES is assessed by the individual´s occupation and classified with the International Socio-Economic Index of Occupational Status (ISEI), which scales occupations by relating them to education and income [93]. SES influences subjective well-being and health through different ways: Low SES groups show higher health risk behavior [94], have less access to health care and receive qualitatively poorer health care [95], the material deprivation is higher and the psychosocial environment is more stressful over the life course [96]. Further we included the occurrence of special health events such as an accident or a serious illness due to the possible impact of these events on subjective well-being and depression [97].

Data analysis

We checked the demographic data for effects of systematic drop-outs due to the large gap between complete and final data set for our analysis. Only minimal changes in age, sex and the distribution of individuals in East and West Germany could be found.

As subjective well-being consisted of three independently measured constructs, we tested for the unidimensionality of the compound variable using confirmatory factor analysis. The Satorra-Bentler adjusted χ2 was calculated to adjust for non-normal distributions of the variables [98]. The fit was inspected using the criteria proposed by Hu and Bentler [99]. According to these indices the model for subjective well-being in 2008 (Satorra-Bentler-χ2 (1, 592) = .025, p = .874, CFI = 1.00, SRMR = .003, RMSEA = .00, CIRMSEA = .00 - .06) as well as the model for SWB in 2011 (Satorra-Bentler-χ2 (1, 592) = .052, p = .820, CFI = 1.00, SRMR < .001, RMSEA < .001, CIRMSEA = .00 - .06) showed a good model fit. To test our hypotheses we used a structural equation model (SEM). The data analysis was run using the statistical software R [100]. The confirmatory factor analyses and SEM were conducted using the “lavaan” package [101].

Results

Table 1 offers a general overview over the bivariate correlations of all variables used in this study. The path model to test our hypotheses shows an acceptable model fit, Satorra-Bentler-χ2 (5, 592) = 17.952, p = .003, CFI = .979, SRMR = .015, RMSEA = .066, CIRMSEA = .037 - .098. Fig 1 shows the tested model with highlighted statistically significant paths while all direct regression paths of the model are displayed in Table 2. Self-efficacy and optimism at T0 both statistically significantly predict subjective well-being at T1, but only optimism at T0 shows statistically significant negative relations to depression at T1. Hope at T0 shows no statistically significant relation to either subjective well-being or depression at T1. Hypotheses 1(c) and 2(c) therefore have to be rejected.

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Fig 1. Path model of the longitudinal relation of self-efficacy, optimism and hope with well-being and depression, mediated by flexible goal-adjustment.

Regression weights are standardized beta-weights, a critical health event is coded no/yes; b sex is coded male/female;.* p < .05, ** p < .01, *** p < .001.

https://doi.org/10.1371/journal.pone.0198588.g001

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Table 1. Summary of the bivariate correlations of all variables.

https://doi.org/10.1371/journal.pone.0198588.t001

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Table 2. Regression paths using MLM estimator.

https://doi.org/10.1371/journal.pone.0198588.t002

Whereas all three predictors are statistically significantly related to flexible goal adjustment at T0, no indirect path is statistically significant with standardized regression paths between .002-.01. These results are not in favor of hypotheses 3 and 4.

Discussion

Positive organizational behavior focuses on individual strengths and resources [15], optimism, hope and self-efficacy being prominent examples. All three are related to positive aspects from an individual perspective but also from an organizational perspective. We therefore wanted to examine if those three aspects have a longitudinal relation with subjective well-being and ill-being and if this relation is mediated by the coping strategy flexible goal adjustment. For our study we used a working subsample of the German Ageing Survey [79].

In accordance with other studies, our results show that all three facets are correlated to subjective well-being and depression concurrently [38, 102, 103]. According to the results of our path model, hope seems not to be relevant for time-lagged subjective well-being nor depression, but optimism predicts both and self-efficacy predicts subjective well-being after a three year period. Hence, in a direct comparison, optimism seems to be the most relevant for subjective well-being and depression of the three constructs.

One reason for the diminishing effect of hope could be the chosen outcome criterion. Bryant and Cvengros [39] argue that optimism focuses more on broader quality of future outcomes whereas hope focuses more on specific goals. As well-being in our study with the two components of affect and general life satisfaction presents rather a general positive than a goal-specific outcome, our results are in accordance with their argument. This applies accordingly for our second outcome variable depression. On the other hand, our results also raise the question if the impact of hope diminishes because optimism and self-efficacy have too much overlap with the waypower and willpower components of hope [33]. In the study of Bryant and Cvengros [39] for example, as well as in other studies [103] the three variables are highly correlated. Bryant and Cvengros [39] argue that hope and optimism have discriminant relations with other variables, but can also be considered as having a common g-factor. The meta-analytical results in the study of Alarcon et al. [38] accordingly point out, that optimism and hope are distinguishable but related and that they have discriminant relations with outcome variables, with optimism being more relevant in situations with low personal control and hope being more relevant in situations with higher personal control. Further research with different outcome variables is therefore needed to clarify if hope in comparison to optimism has more impact on time-lagged rather goal specific outcomes.

Our results are also in line with Benyamini and Roziner [104] who found a statistically significant relation between optimism and self-rated health on life satisfaction after a five year period. In their study this relation was eliminated when affectivity was included in the analysis. In our study, however, affect is a part of the outcome as the broader concept of subjective well-being includes life satisfaction as well as positive and negative affect. Optimism might therefore be more responsible for the variance in the affective part of our subjective well-being measure.

Self-efficacy was also related to subjective well-being over a three year period in our sample. This is in support of previous studies that see self-efficacy as an important factor for well-being [53]. However, we found no relation with ill-being. Although depression goes in hand with lower levels of self-efficacy [105], higher levels of self-efficacy seem not to impact levels of depression significantly. This result contradicts the findings of Holahan and Holahan [58] and Maciejewski et al. [59]. It should be stated though, that the study of Holahan and Holahan [58] focuses on self-efficacy for social support. Social support on the other hand also has an impact on depression [58, 106]. Maciejewski et al. [59] examined general self-efficacy. Their effect size for the indirect effect of baseline self-efficacy on follow-up depression for the subsample without prior depression (βindirect = -0.114, s.e. = 0.033, p < 0.001) resembles ours (βindirect = -0.095, s.e. = 0.066, p = 0.153), but Maciejewski et al. [59] have a much larger sample. Furthermore, overlaps between hope, optimism and self-efficacy have been controlled for in our sample, which might reduce the effect of self-efficacy. Taken together, the results suggest that there is a possible small effect of self-efficacy on later depression.

Concurrently, optimism, hope and self-efficacy were all correlated with flexible goal adjustment. Contrary to the results of Hanssen et al. [11] however, flexible goal adjustment did not mediate the relation between optimism and self-efficacy with well-being nor with depression over a three-year period. Hence, flexible goal adjustment might have cross-sectional assocations with well-being [11] but no long-time mediating effect.

The substantially long period of time (three years in our study) might be a drawback as adjusted goals might rather be accepted as new goals. In order to examine the mediating effects of flexible goal adjustment in the relation of positive organizational behavior and subjective well-being respectively ill-being, longitudinal designs with shorter time periods could therefore be appropriate. Furthermore, tenacious goal pursuit [66] might be an alternative for the long-time mediation, as the modification of behavior or the situation in order to fit with one’s goals might rather be the appropriate long-term strategy resulting in higher levels of subjective well-being and lower levels of ill-being. Following the argumentation of Heyl, Wahl, and Mollenkopf [72] both flexible goal adjustment and tenacious goal pursuit are necessary for an adaptive self-regulation and both have differential effects on the affective aspects of subjective well-being. In order to get a complete picture, both aspects as well as their interactions should be considered.

Practical implications

Subjective well-being has many desirable effects on a personal but also on the organizational level (e.g. health and longevity, [45], or work-related productivity, [47]). Knowing about antecedents of subjective well-being, and especially about developable factors is therefore helpful in many ways. Positive organizational behavior subsumes developable factors that have an effect on organizational well-being, optimism, hope and self-efficacy being among them. There are intervention programs, even online interventions, in order to develop these facets, e.g. the interventions to strengthen psychological capital [107, 20], that can support subjective well-being and reduce ill-being. Focussing especially on optimism and self-efficacy can help to develop easy to handle and little time-consuming interventions and strengthen the organizations following a people-based approch as e.g. described by Manuti and de Palma [108].

Furthermore, subjective well-being has an impact on the retention intentions of older workers [109]. Supporting an optimistic outlook and self-efficacy in older workers might therefore be one part of the puzzle to retain them in the active workforce in order to face the demographic change. One has to bear in mind, however, that optimism and self-efficacy do not inherently have a positive effect, but that this effect depends on the context [110]. Therefore, “the best interventions to promote well-being may thus be those that teach people different skills […] and the best time and place to use each one” ([111] p577).

Limitations

As we used the panel data of the German Ageing Survey [79], we were restricted in our measures as well as in the age range of our participants. We had to rely on the measures used in the German Ageing Survey and they proved to have satisfying internal consistency scores, but we have to point out, that our results only hold for the measures used. Other measures that focus on different aspects might yield different results [38]. Furthermore, our results are specific for an older population. As we mentioned, certain coping strategies might be more relevant in later life [78, 68], implications for younger populations therefore cannot be deviated and need further research.

Also we used context-free measures of well-being. Referring to the happy-productive worker hypothesis, and the remarks made by Cropanzano and Wright [1], these overall measures of well-being have an impact on work outcomes. This relation is empirically supported e.g. by Tsai, Chen, and Liu [112] or Fritz and Sonnentag [113] (see also [114]). One has to note, however, that the effects are smaller than those between context-specific measures and work performance. All in all, context-specific and context-free measures of well-being are overlapping to a large extent [44], which is especially the case for the working context as work takes a large amount of time. Investing in possibilities to enhance general well-being should pay off for organizations. Furthermore, the work context can be a place full of opportunities in order to enhance self-efficacy.

Another possible limitation of this study is the issue of self-report measures and common method variance [115]. This issue is heavily debated in work and organizational psychology with unclear results if common method is in fact a problem to the results in this field or how big the problem might be [116–119]. Even with the open debate we think that it is worth mentioning that it could be a possible limitation.

References

  1. 1. Cropanzano R, Wright TA. When a "happy" worker is really a "productive" worker: A review and further refinement of the happy-productive worker thesis. Consulting Psychology Journal: Practice and Research. 2001;53(3):182–199.
  2. 2. Lucas RE, Diener E. The happy worker: Hypotheses about the role of positive affect in worker productivity. In: Barrick MR, Ryan AM, editors. Personality and work: Reconsidering the role of personality in organizations. San Francisco, CA: Jossey-Bass; 2002. P.30–59.
    • 3. Zelenski JM, Murphy SA, Jenkins DA. The happy-productive worker thesis revisited. J HAPPINESS STUD. 2008;9(4):521–537.
    • 4. Diener E, Chan MY. Happy people live longer: Subjective well-being contributes to health and longevity. Applied Psychology: Health and Well-Being. 2011;3(1):1–43.
    • 5. Ilies R, Aw SS, Pluut H. Intraindividual models of employee well-being: What have we learned and where do we go from here? EUR J WORK ORGAN PSY. 2015;24(6):827–838.
    • 6. Hobfoll SE. Conservation of resources: A new attempt at conceptualizing stress. AM PSYCHOL. 1989[cited Nov 2016];44(3):513–524. Available from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.452.8014&rep=rep1&type=pdf pmid:2648906
    • 7. Demerouti E, Bakker AB, Nachreiner F, Schaufeli WB. The job demands-resources model of burnout. J APPL PSYCHOL. 2001;86(3):499–512 pmid:11419809
    • 8. Sonnentag S, Fritz C. Recovery from job stress: The stressor—detachment model as an integrative framework. J ORGAN BEHAV. 2015;36(S1):72–103.
    • 9. Culbertson SS, Fullagar CJ, Mills MJ. Feeling good and doing great: The relationship between psychological capital and well-being. J OCCUP HEALTH PSYCH. 2010;15(4):421–433. pmid:21058856
    • 10. Sin NL, Lyubomirsky S. Enhancing well-being and alleviating depressive symptoms with positive psychology interventions: A practice-friendly meta-analysis. J CLIN PSYCHOL. 2015;65(5):467–487.
    • 11. Hanssen MM, Vancleef LMG, Vlaeyen JWS, Hayes AF, Schouten EGW, Peters ML. Optimism, motivational coping and well-being: Evidence supporting the importance of flexible goal adjustment. J HAPPINESS STUD. 2015;16(6):1525–1537
    • 12. Mills MJ, Fleck CR, Kozikowski A. Positive psychology at work: A conceptual review, state-of-practice assessment, and a look ahead. The Journal of Positive Psychology. 2013;8(2):153–164
    • 13. Diener E. Culture and subjective well-being. Champaign, IL: Springer; 2009
      • 14. Seligman ME, Csikszentmihalyi M. Positive psychology: An introduction. Netherlands: Springer; 2014. 279–298p.
        • 15. Luthans F. Positive organizational behavior: Developing and managing psychological strengths. ACAD MANAGE EXEC. 2002;16(1):57–72.
        • 16. Luthans F, Youssef CM. Emerging positive organizational behavior. J MANAGE. 2007;33(3):321–349.
        • 17. Luthans F, Youssef CM. Human, social, and now positive psychological capital management: Investing in people for competitive advantage. ORGAN DYM. 2004;33(2):143–160.
        • 18. Luthans F, Avolio BJ, Walumbwa FO, Li W. The psychological capital of Chinese workers: Exploring the relationship with performance. MANAGE ORGAN REV. 2005;1(2):249–271
        • 19. Larson M, Luthans F. Potential added value of psychological capital in predicting work attitudes. Journal of Leadership & Organizational Studies. 2006;13(1):45–62.
        • 20. Luthans F, Avey JB, Patera JL. Experimental analysis of a web-based training intervention to develop positive psychological capital. ACAD MANAG LEARN EDU. 2008;7(2):209–221.
        • 21. Avey JB, Patera JL, West BJ. (2006). The implications of positive psychological capital on employee absenteeism. Journal of Leadership & Organizational Studies. 2006;13(2):42–60.
        • 22. Hobfoll SE. Social and psychological resources and adaptation. REV GEN PSYCHOL. 2002[cited Nov 2016];6(4):307–324. Available from: https://www.researchgate.net/profile/Stevan_Hobfoll/publication/232556057_Social_aan_Psychological_Resources_and_Adaptation/links/5446aca40cf2f14fb810b98e/SociSo-and-Psychological-Resources-and-Adaptation.pdf 10.1037//1089-2680.6.4.307
        • 23. Luthans F, Avolio BJ, Avey JB, Norman SM. Positive psychological capital: Measurement and relationship with performance and satisfaction. PERS PSYCHOL. 2007;60(3):541–572.
        • 24. Baron RA, Franklin RJ, Hmieleski KM. Why entrepreneurs often experience low, not high, levels of stress: The joint effects of selection and psychological capital. Journal of Management. 2016;42(3):742–768.
        • 25. Bandura A. Self-Efficacy: The exercise of control. New York, NY: W.H. Freeman and Co; 1997.
          • 26. Jerusalem M, Schwarzer R. Self-efficacy as a resource factor in stress appraisal processes. In: Schwarzer R, editor. Self-efficacy: Thought Control of Action. New York, NY: Taylor & Francis, 1992. p.195–213
            • 27. Stajkovic AD, Luthans F. Self-efficacy and work-related performance: A meta-analysis. PSYCHOL BULL. 1998;124(2):240.
            • 28. Luthans F, Youssef CM, Avolio BJ. Psychological capital: Investing and developing positive organizational behavior. Positive Organizational Behavior. 2007;1(2):9–24.
            • 29. Carver CS, Scheier MF, Miller CJ, Fulford D. Optimism. In: Snyder CR, Lopez SJ, editors. The Oxford handbook of positive psychology. 2nd ed. New York, NY: Oxford University Press; 2009. p.303–311.
              • 30. Luthans F, Avolio BJ, Youssef-Morgan CM. Psychological Capital and beyond. New York, NY: Oxford University Press. 2015. p.305
                • 31. Scheier ME, Carver CS. Optimism, coping, and health: assessment and implications of generalized outcome expectancies. HEALTH PSYCHOL. 1985;4(3);219–247 pmid:4029106
                • 32. Scheier ME, Carver CS. Dispositional optimism and physical well-being: The influence of generalized outcome expectancies on health. J PERS. 1987;55(2):169–210. pmid:3497256
                • 33. Snyder CR, Irving LM, Anderson JR. Hope and health. In: Snyder CR, Forsyth DR, editors. Handbook of social and clinical psychology: The health perspective. New York, NY: Pergamon Press; 1991. p.285–305.
                  • 34. Snyder CR. The psychology of hope: You can get there from here. New York, NY: The Free Press; 1994. 428p.
                    • 35. Snyder CR, Lopez SJ. The future of positive psychology: A declaration of independence. In: Snyder CR, Lopez SJ, editors. Handbook of positive psychology. New York, NY: Oxford University Press; 2002. p. 751–767.
                      • 36. Snyder CR. Hope theory: Rainbows in the mind. PSYCHOL INQ. 2002;13(4):249–275.
                      • 37. Reichard RJ, Avey JB, Lopez S, Dollwet M. Having the will and finding the way: A review and meta-analysis of hope at work. The Journal of Positive Psychology. 2013;8(4):292–304
                      • 38. Alarcon GM, Bowling NA, Khazon S. Great expectations: A meta-analytic examination of optimism and hope. PERS INDIV DIFFER. 2013;54(7):821–827
                      • 39. Bryant FB, Cvengros JA. Distinguishing hope and optimism: Two sides of a coin, or two separate coins? J SOC CLIN PSYCHOL. 2004;23(2):273–302
                      • 40. Gallagher MW, Lopez SJ. Positive expectancies and mental health: Identifying the unique contributions of hope and optimism. The Journal of Positive Psychology. 2009;4(6):548–556
                      • 41. Rand KL. Hope and optimism: Latent structures and influences on grade expectancy and academic performance. J PERS. 2009;77(1):231–260. pmid:19076999
                      • 42. Scioli A, Chamberlin CM, Sammor CM, Lapointe AB, Campbell TL, Macleod AR, et al. A prospective study of hope, optimism, and health. PSYCHOL REP. 1997;81(3):723–733.
                      • 43. Magaletta PR, Oliver JM. The hope construct, will, and ways: Their relations with self—efficacy, optimism, and general well—being. J CLIN PSYCHOL. 1999;55(5):539–551 pmid:10392785
                      • 44. Pavot W. The assessment of subjective well-being: Successes and shortfalls. In: Eid M, Larsen RJ, editors. The science of subjective well-being. New York, NY: The Guilford Press; 2008. p.124–140.
                        • 45. Diener E. The remarkable changes in the science of subjective well-being. PERSPECT PSYCHOL SCI. 2013;8(6):663–666. pmid:26173230
                        • 46. Xu J, Roberts RE. The power of positive emotions: It’s a matter of life or death—Subjective well-being and longevity over 28 years in a general population. HEALTH PSYCHOL. 2010;29(1):9–19. pmid:20063931
                        • 47. Erdogan B, Bauer TN, Truxillo DM, Mansfield LR. Whistle while you work: A review of the life satisfaction literature. J MANAGE. 2012;38(4):1038–1083
                        • 48. Tay L, Diener E. Needs and subjective well-being around the world. J PERS SOC PSYCHOL. 2011;101(2):354–365. pmid:21688922
                        • 49. Howell RT, Kern ML, Lyubomirsky S. Health benefits: Meta-analytically determining the impact of well-being on objective health outcomes. Health Psychology Review. 2007;1(1):83–136.
                        • 50. Keyes CLM. The mental health continuum: From languishing to flourishing in life. J HEALTH SOC BEHAV. 2002;43(2):207–222. pmid:12096700
                        • 51. Maddux JE. (2000). Self-efficacy—The power of believing you can. In: Snyder CR, Lopez SJ, editors. Handbook of Positive Psychology. New York: Oxford University Press; 2009. p.335–345
                          • 52. Barlow J, Wright C, Cullen L. A job-seeking self-efficacy scale for people with physical disabilities: Preliminary development and psychometric testing. BRIT J GUID COUNS. 2002;30(1):37–53.
                          • 53. Caprara GV, Steca P, Gerbino M, Paciello M, Vecchio GM. Looking for adolescents' well-being: Self-efficacy beliefs as determinants of positive thinking and happiness. EPIDEMIOL PSICHIAT S. 2006;15(01):30–43.
                          • 54. Hampton NZ. Subjective well-being among people with spinal cord injuries: The role of self-efficacy, perceived social support, and perceived health. REHABIL COUNS BULL. 2004;48(1):31–37.
                          • 55. Kuijer RG, De Ridder DT. Discrepancy in illness-related goals and quality of life in chronically ill patients: the role of self-efficacy. Psychology and Health. 2003;18(3):313–330.
                          • 56. Lopez SJ, Pedrotti ST, Snyder CR. Positive Psychology. The scientific and practical explorations of human strengths. 2nd ed. Thousad Oaks, CA: SAGE Publications, Inc; 2011. p.598.
                            • 57. Bisschop MI, Kriegsman DM, Beekman AT, Deeg DJ. Chronic diseases and depression: the modifying role of psychosocial resources. SOC SCI MED. 2004;59(4):721–733. pmid:15177830
                            • 58. Holahan CK, Holahan CJ. Self-efficacy, social support, and depression in aging: A longitudinal analysis. Journal of Gerontology. 1987;42(1):65–68. pmid:3794199
                            • 59. Maciejewski PK, Prigerson HG, Mazure CM. Self-efficacy as a mediator between stressful life events and depressive symptoms. BRIT J PSYCHIAT. 2000;176(4):373–378.
                            • 60. Carver CS, Scheier MF, Segerstrom SC. Optimism. CLIN PSYCHOL REV. 2010;30(7):879–889. pmid:20170998
                            • 61. Forgeard MJC, Seligman MEP. Seeing the glass half full: A review of the causes and consequences of optimism. PRAT PSYCHOL. 2012;18(2):107–120.
                            • 62. Nes LS, Segerstrom SC. Dispositional optimism and coping: A meta-analytic review. PERS SOC PSYCHOL REV 2006;10(3):235–251 pmid:16859439
                            • 63. Sheldon KM, Lyubomirsky S. How to increase and sustain positive emotion: The effects of expressing gratitude and visualizing best possible selves. The Journal of Positive Psychology. 2006;1(2):73–82
                            • 64. Avey JB, Reichard RJ, Luthans F, Mhatre KH. Meta—analysis of the impact of positive psychological capital on employee attitudes, behaviors, and performance. Human Resource Development Quarterly. 2011;22(2):127–152.
                            • 65. Avey JB, Luthans F, Smith RM, Palmer NF. (2010). Impact of positive psychological capital on well-being over time. J OCCUP HEALTH PSYCH. 2010;15(1):17–28.
                            • 66. Coffey L, Gallagher P, Desmond D, Ryall N. Goal pursuit, goal adjustment, and affective well-being following lower limb amputation. BRIT J HEALTH PSYCH. 2014;19(2):409–424.
                            • 67. Rasmussen HN, Wrosch C, Scheier MF, Carver CS. Self-regulation processes and health: the importance of optimism and goal adjustment. Journal of Personality. 2006;74(6):1721–1748. pmid:17083664
                            • 68. Brandtstädter J, Renner G. Tenacious goal pursuit and flexible goal adjustment: explication and age-related analysis of assimilative and accommodative strategies of coping. PSYCHOL AGING. 1990;5(1):58–67 pmid:2317302
                            • 69. Bailly N, Joulain M, Hervé C, Alaphilippe D. Coping with negative life events in old age: The role of tenacious goal pursuit and flexible goal adjustment. AGING MENT HEALTH. 2012;16(4):431–437. pmid:22128858
                            • 70. Bailly N, Gana K, Hervé C, Joulain M, Alaphilippe D. Does flexible goal adjustment predict life satisfaction in older adults? A six-year longitudinal study. AGING MENT HEALTH. 2014;18(5):662–670. pmid:24479829
                            • 71. Brandtstädter J, Rothermund K. The life-course dynamics of goal pursuit and goal adjustment: A two-process framework. DEV REV. 2002;22(1):117–150.
                            • 72. Heyl V, Wahl HW, Mollenkopf H. Affective well-being in old age: The role of tenacious goal pursuit and flexible goal adjustment. EUR PSYCHOL, 2007;12(2):119–129
                            • 73. Kelly RE, Wood AM, Mansell W. Flexible and tenacious goal pursuit lead to improving well-being in an aging population: a ten-year cohort study. INT PSYCHOGERIATR. 2013;25(01):16–24.
                            • 74. Janse M, Sprangers MA, Ranchor AV, Fleer J. Long-term effects of goal disturbance and adjustment on well-being in cancer patients. QUAL LIFE RES. 2016;25(4):1017–1027. pmid:26446093
                            • 75. Van Damme S, De Waegeneer A, Debruyne J. (2016). Do flexible goal adjustment and acceptance help preserve quality of life in atients with multiple sclerosis? INT J BEHAV MED. 2016;23(3):333–339. pmid:26590139
                            • 76. Trépanier L, Lapierre S, Baillargeon J, Bouffard L. Ténacité et flexibilité dans la poursuite de projets personnels: Impact sur le bien-être à la retraite. CAN J AGING. 2001;20(04):557–576
                            • 77. Brandtstädter J, Rothermund K, Kranz D, Kühn W. Final decentrations. EUR PSYCHOL. 2010;15(2):152–163.
                            • 78. Brandtstädter J. Personal control over development: Some developmental implications of self-efficacy. In: Schwarzer R, editor. Self-efficacy: Thought control of action London, UK: Routledge; 1992. p. 127–145.
                              • 79. Engstler H, Motel-Klingebiel A. Datengrundlagen und Methoden des deutschen Alterssurveys (DEAS). In: Motel-Klingebiel A, Wurm S, Tesch-Römer C, editors. Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart, GER: Kohlhammer; 2010. p.34–60.
                                • 80. Blom AG, Schröder M. Sample composition 4 years on: retention in SHARE Wave 3. In: Schröder M, editor. SHARELIFE Methodology. Mannheim, GER: Mannheim Research Institute fort he Economics of Ageing (MEA); 2011. p.55–61
                                  • 81. Schwarzer R, Jerusalem M. Generalized self-efficacy scale. In: Weinman J, Wright S, Johnston M, editors. Measures in health psychology: A user’s portfolio. Causal and control beliefs. Windsor, UK: NFER-NELSON; 1995. p.35–37.
                                    • 82. Brandtstädter J, Wentura D. Veränderungen der Zeit- und Zukunftsperspektive im Übergang zum höheren Erwachsenenalter: Entwicklungspsychologische und differentielle Aspekte. Z ENTWICKL PADAGOGIS. 1994;26(1):2–21.
                                    • 83. Snyder CR, Harris C, Anderson JR, Holleran SA, Irving LM, Sigmon ST, et al. The will and the ways: Development and validation of an individual-differences measure of hope. J PERS SOC PSYCHOL. 1991;60(4):570–585. pmid:2037968
                                    • 84. Brandtstädter J, Renner G. Tenacious goal pursuit and flexible goal adjustment: Explication and age-related analysis of assimilative and accommodative strategies of coping. PSYCHOL AGING. 1990;5(1):58–67. pmid:2317302
                                    • 85. Schumacher J. SWLS. Satisfaction with life scale. Göttingen, GER: Hogrefe für Psychologie; 2003. p.329.
                                      • 86. Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J PERS SOC PSYCHOL. 1988;54(6):1063–1070. pmid:3397865
                                      • 87. Pavot W, Diener E. Review of the satisfaction with life scale. PSYCHOL ASSESSMENT. 1993;5(2):164–172.
                                      • 88. Hautzinger M, Bailer M, Hofmeister D, Keller F. Allgemeine Depressionsskala (ADS). PSYCHIAT PRAX. 2012;39(06):302–304.
                                      • 89. Pinquart M, Sörensen S. Gender differences in self-concept and psychological well-being in old age: a meta-analysis. J GERONTOL B-PSYCHOL. 2011;56(4):195–213.
                                      • 90. Pinquart M, Sörensen S. Influences of socioeconomic status, social network, and competence on subjective well-being in later life: a meta-analysis. PSYCHOL AGING. 2000;15(2):187–224. pmid:10879576
                                      • 91. Mackenbach JP, Kunst AE, Cavelaars AE, Groenhof F, Geurts JJ, EU Working Group on Socioeconomic Inequalities in Health. Socioeconomic inequalities in morbidity and mortality in Western Europe. LANCET. 319997;49(9066):1655–1659.
                                      • 92. Von dem Knesebeck O, Lüschen G, Cockerham WC, Siegrist J. Socioeconomic status and health among the aged in the United States and Germany: a comparative cross-sectional study. SOC SCI MED. 2003;57(9):643–1652.
                                      • 93. Ganzeboom HB, De Graaf PM, Treiman DJ. A standard international socio-economic index of occupational status. SOC SCI RES. 1992;21(1):1–56.
                                      • 94. Lantz PM, Lynch JW, House JS, Lepkowski JM, Mero RP, Musick MA, et al. Socioeconomic disparities in health change in a longitudinal study of US adults: the role of health-risk behaviors. SOC SCI MED. 2001;53(1):29–40. pmid:11380160
                                      • 95. Feinstein JS. The relationship between socioeconomic status and health: a review of the literature. The Milbank Quarterly. 1993;71(2):279–322. pmid:8510603
                                      • 96. Baum A, Garofalo JP, Yali A. Socioeconomic status and chronic stress: does stress account for SES effects on health? ANN NY ACAD SCI. 1999;896(1):131–144.
                                      • 97. Wurm S, Tomasik MJ, Tesch-Römer C. Serious health events and their impact on changes in subjective health and life satisfaction: The role of age and a positive view on ageing. EUR J AGEING. 2008;5(2):117–127. pmid:28798566
                                      • 98. Finney SJ, DiStefano C. Non-normal and categorical data in structural equation modeling. In: Hancock GR, Mueller RO, editors. Structural equation modeling: A second course. Charlotte, NC: Information Age Publishing; 2013. p.269–314.
                                        • 99. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. STRUCT EQU MODELING. 1999;6(1):1–55.
                                        • 100. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. [updated 2014, cited Nov 2016]. Available from: http://www.R-project.org/.
                                          • 101. Rosseel Y. lavaan: An R package for structural equation modeling. J STAT SOFTW. 2012;48(2):1–36.
                                          • 102. Clum GA, Rice JC, Broussard M, Johnson CC, Webber LS. (2014). Associations between depressive symptoms, self-efficacy, eating styles, exercise and body mass index in women. J BEHAV MED. 2014;37(4):577–586. pmid:23934179
                                          • 103. Lorenz T, Beer C, Pütz J, Heinitz K. (2016). Measuring psychological capital: Construction and validation of the compound PsyCap scale (CPC-12). PloS one. [Internet]. 2016 Apr [cited Nov 2016];11(4). Available from: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152892
                                          • 104. Benyamini Y, Roziner I. The predictive validity of optimism and affectivity in a longitudinal study of older adults. PERS INDIV DIFFER. 2008;44(4):853–864.
                                          • 105. Muris P. Relationships between self-efficacy and symptoms of anxiety disorders and depression in a normal adolescent sample. PERS INDIV DIFFER. 2002;32(2):337–348.
                                          • 106. Liu L, Gou Z, Zuo J. Social support mediates loneliness and depression in elderly people. J HEALTH PSYCHOL. 2014;21(5):750–758 pmid:24925547
                                          • 107. Luthans F, Avey JB, Avolio BJ, Peterson SJ. The development and resulting performance impact of positive psychological capital. Human Resource Development Quarterly. 2010;21(1):41–67.
                                          • 108. Manuti A, de Palma PD. Digital HR. Cham, CH: Palgrave Macmillan; 2018 [cited 2018 March 07]. 85 p. Available from: https://www.palgrave.com/gb/book/9783319602097. https://doi.org/10.1007/978-3-319-60210-3
                                            • 109. Siegrist J, Wahrendorf M, Von Dem Knesebeck O, Jürges H, Börsch-Supan A. Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study. EUR J PUBLIC HEALTH. 2007;17(1):62–68. pmid:16777840
                                            • 110. McNulty JK, Fincham FD. Beyond positive psychology? Toward a contextual view of psychological processes and well-being. AM PSYCHOL. 2012;67(2):101–110. pmid:21787036
                                            • 111. McNulty JK, Fincham FD. The pitfalls of valenced labels and the benefits of properly calibrated psychological flexibility. AM PSYCHOL. 2012;67(7):576–577.
                                            • 112. Tsai W-C, Chen C-C, Liu H-L. Test of a model linking employee positive moods and task performance. J APPL PSYCHOL. 2007;92(6):1570–1583. pmid:18020797
                                            • 113. Fritz C, Sonnentag S. Antecedents of day-level proactive behavior: A look at job stressors and positive affect during the day. J MANAGE. 2009;35(1):94–110.
                                            • 114. Warr P, Nielsen K. (2018). Wellbeing and work performance. In: Diener E, Oishi S. Tay L, editors. Handbook of well-being. [Internet] Salt Lake City, UT: DEF Publishers; 2018. [cited 2018 March 07] 960p. Available from: https://www.nobascholar.com/books/1
                                              • 115. Podsakoff PM, MacKenzie SB, Lee J-Y, Podsakoff NP. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J APPL PSYCHOL. 2003;88(5):879–903. pmid:14516251
                                              • 116. Lance CE, Dawson B, Birkelbach D, Hoffman BJ. Method effects, measurement error, and substantive conclusions. ORGAN RES METHODS. 2010;13(3):435–455.
                                              • 117. Pace VL. Method variance from the perspectives of reviewers: Poorly understood problem or overemphasized complaint? ORGAN RES METHODS. 2010;13(3):421–434.
                                              • 118. Spector PE. Method variance in organizational research truth or urban legend? ORGAN RES METHODS. 2006;9(2):221–232.
                                              • 119. Spector PE, Brannick MT. Common method issues: An introduction to the feature topic in organizational research methods. ORGAN RES METHODS. 2010;13(3):403–406.