Skip to main content
Log in

The Positive Functioning at Work Scale: Psychometric Assessment, Validation, and Measurement Invariance

  • Original Research
  • Published:
Journal of Well-Being Assessment

Abstract

The PERMA framework (Seligman 2011) presents five building blocks of well-being: positive emotion, engagement, relationships, meaning, and accomplishment. However, Seligman (2018) suggested the original five building blocks are highly predictive of well-being but certainly not exhaustive. This research attempted to expand the PERMA model in the workplace with four new building blocks of well-being: physical health, mindset, environment, and economic security. Study 1 utilized nine subject matter experts (SMEs) to content analyze and evaluate an item pool for scale development. In Study 2 (N = 300), an exploratory factor analysis (EFA) extrapolated nine dimensions of positive functioning at work (PF-W) with a random sample of full-time employees recruited on Amazon’s Mechanical Turk (MTurk). The purpose of Study 3 was to validate the PF-W scale and test its ability to predict work outcomes. Findings from 727 full-time employees supported a general factor of PF-W with nine lower-order dimensions. The measure exhibited convergent, discriminant, criterion, predictive, and incremental forms of validity with other well-being (Diener 1985; Luthans, Youssef and Avolio 2007) and performance measures (Griffin, Neal and Parker 2007), as well as measurement invariance across job function. The Positive Functioning at Work Scale provides a comprehensive measurement tool that can inform future workplace programs and interventions. It also predicts important work outcomes, such as turnover intentions, job-related affective well-being, plus individual, team, and organizational adaptivity, proactivity, and organizational proficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Ackerman, C. E., Warren, M. A., & Donaldson, S. I. (2018). Scaling the heights of positive psychology: A systematic review of measurement scales. International Journal of Wellbeing, 8(2), 1–21.

  • Adelmann, P. K., Antonucci, T. C., Crohan, S. E., & Coleman, L. M. (1989). Empty nest, cohort, and employment in the well-being of midlife women. Sex Roles: A Journal of Research, 20, 173–189.

    Article  Google Scholar 

  • Avey, J., Reichard, R., Luthans, F., & Mhatre, K. (2011). Meta-analysis of the impact of positive psychological capital on employee attitudes, behaviors, and performance. Human Resource Development Quarterly, 22(2), 127–152.

    Article  Google Scholar 

  • Azzam, T., & Jacobson, M. R. (2013). Finding a comparison group: Is online crowdsourcing a viable option? American Journal of Evaluation, 34(3), 372–384.

    Article  Google Scholar 

  • Bennett, N., & Lemoine, J. G. (2014). What VUCA really means for you. Retrieved from https://hbr.org/2014/01/what-vuca-really-means-for-you

    Google Scholar 

  • Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606.

    Article  Google Scholar 

  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.

  • Bollen, K. (1989). Structural equations with latent variables. Choice Reviews Online, 27(02), 27–0974.

    Google Scholar 

  • Braeken, J., & van Assen, M. A. L. M. (2017). An empirical Kaiser criterion. Psychological Methods, 22(3), 450–466.

    Article  Google Scholar 

  • Brown, T. A. (2012). Confirmatory factor analysis for applied research. New York: Guilford Press.

  • Brown, T. A. (2015). Methodology in the social sciences. Confirmatory factor analysis for applied research (2nd ed.). The Guilford Press.

  • Buhrmester, M., Kwang, T., & Gosling, S. D. (2016). Amazon’s mechanical Turk: A new source of inexpensive, yet high-quality data? In A. E. Kazdin (Ed.), Methodological issues and strategies in clinical research (4th ed., pp. 133–139).

    Chapter  Google Scholar 

  • Butler, J., & Kern, M. L. (2016). The PERMA-profiler: A brief multidimensional measure of flourishing. International Journal of Well-Being, 6(3).

  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105.

    Article  Google Scholar 

  • Caniels, M. C. J., Semeijn, J. H., & Renders, I. H. M. (2018). Mind the mindset! The interaction of proactive personality, transformational leadership and growth mindset for engagement at work. Career Development International, 23(1), 48–66.

    Article  Google Scholar 

  • Carlson, M., Wilcox, R., Chou, C.-P., Chang, M., Yang, F., Blanchard, J., & Clark, F. (2011). Psychometric properties of reverse-scored items on the CES-D in a sample of ethnically diverse older adults. Psychological Assessment, 23(2), 558–562.

    Article  Google Scholar 

  • Chen, F., Jing, Y., Hayes, A., & Lee, J. (2013). Two concepts or two approaches? A bifactor analysis of psychological and subjective well-being. Journal of Happiness Studies, 14(3), 1033–1068.

    Article  Google Scholar 

  • Coffey, J. K., Wray-Lake, L., Mashek, D., & Branand, B. (2016). A multi-study examination of well-being theory in college and community samples. Journal of Happiness Studies: An Interdisciplinary Forum on Subjective Well-Being, 17(1), 187–211.

    Article  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.

    Google Scholar 

  • Crank, J., Regoli, R., Hewitt, J., & Culbertson, R. (1995). Institutional and organizational antecedents of role stress, work alienation, and anomie among police executives. Criminal Justice and Behavior, 22, 152–171.

    Article  Google Scholar 

  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.

    Article  Google Scholar 

  • Cronbach, L. J. (1970). Essentials of psychological testing. New York: Harper & Row.

    Google Scholar 

  • DeSimone, J., Harms, P., & DeSimone, A. (2015). Best practice recommendations for data screening. Journal of Organizational Behavior, 36(2), 171–181.

    Article  Google Scholar 

  • DeVellis, R. F. (2017). Scale development: Theory and applications (4th ed). In Los Angeles, CA. Sage: Publications.

    Google Scholar 

  • Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71–75.

  • Diener, E. (2005). Income and happiness. Retrieved from https://www.psychologicalscience.org/observer/income-and-happiness

    Google Scholar 

  • Diener, E., & Seligman, M. E. P. (2004). Beyond money: Toward an economy of well-being. Psychological Science in the Public Interest, 5(1), 1–31.

    Article  Google Scholar 

  • Donaldson, S. I. (2019). Evaluating positive functioning and performance: A positive work and organizations approach (Doctoral dissertation). Retrieved from PQDT-Global.

  • Donaldson, S. I., Chen, C., & Donaldson, S. I. (in press). Designing positive organizational psychology interventions. In S. I. Donaldson & C. Chen (Eds.), Positive organizational psychology interventions: Design and evaluation. New Jersey: Wiley.

  • Donaldson, S. I., Heshmati, S., Lee, J. Y., & Donaldson, S. I. (2020). Examining building blocks of well-being beyond perma and self-report bias. The Journal of Positive Psychology, 1–8.

  • Donaldson, S. I., Lee, J. Y., & Donaldson, S. I. (2019a). Evaluating positive psychology interventions at work: A systematic review and meta-analysis. International Journal of Applied Positive Psychology, 4, 113–134.

    Article  Google Scholar 

  • Donaldson, S. I., Lee, J. Y., & Donaldson, S. I. (2019b). The effectiveness of positive psychology interventions in the workplace: A theory-driven evaluation approach. In V. Z. Llewellyn & S. Rothmann (Eds.), Theoretical approaches to multi-cultural positive psychology interventions (pp. 115–159). Cham, Switzerland: Springer International.

    Chapter  Google Scholar 

  • Donaldson, S. I., Heshmati, S., Lee, J. Y., & Donaldson, S. I. (2020). Examining building blocks of well-being beyond PERMA and self-report bias. The Journal of Positive Psychology: Advanced online publication.

  • Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92(6), 1087–1101.

    Article  Google Scholar 

  • Dweck, C. S. (2006). Mindset: The new psychology of success. New York: Random House.

    Google Scholar 

  • Easterlin, R. A. (2003). Explaining happiness. Proceedings of the National Academy of Science, 100(19), 11176–11183.

    Article  Google Scholar 

  • Fox, S., Spector, P. E., Goh, A., & Bruursema, K. (2007). Does your coworker know what you're doing? Convergence of self- and peer-reports of counterproductive work behavior. International Journal of Stress Management, 14(1), 41–60.

    Article  Google Scholar 

  • Fredrickson, B. (2003). The value of positive emotions. American Scientist, 91(4).

  • Friedlander, F., & Brown, L. D. (1974). Organization development. Annual Review of Psychology, 25, 313–341.

  • Goodman, J. K., Cryder, C. E., & Cheema, A. (2013). Data collection in a flat world: The strengths and weaknesses of mechanical Turk samples. Journal of Behavioral Decision Making, 26(3), 213–224.

    Article  Google Scholar 

  • Goodman, F., Disabato, D., Kashdan, T., & Kauffman, S. (2018). Measuring well-being: A comparison of subjective well-being and PERMA. The Journal of Positive Psychology, 13(4), 321–332.

    Article  Google Scholar 

  • Griffin, M., Neal, A., & Parker, S. (2007). A new model of work role performance: Positive behavior in uncertain and interdependent contexts. The. Academy of Management Journal, 50(2), 327–347.

    Article  Google Scholar 

  • Hacker, J. S., Huber, G. A., Nichols, A., Rehm, P., Schlesinger, M., Valletta, R., & Craig, S. (2014). The economic security index: A new measure for research and policy analysis. Review of Income and Wealth, 60, S5–S32.

    Article  Google Scholar 

  • Harman, E., & Azzam, T. (2018). Towards program theory validation: Crowdsourcing the qualitative analysis of participant experiences. Evaluation and Program Planning, 66, 183–194.

    Article  Google Scholar 

  • Harrison, D., & McLaughlin, M. (1996). Structural properties and psychometric qualities of organizational self-reports: Field tests of connections predicted by cognitive theory. Journal of Management, 22(2), 313–338.

    Article  Google Scholar 

  • Hartig, T., Korpela, K., Evans, G., & Gärling, T. (1997). A measure of restorative quality in environments. Scandinavian Housing and Planning Research, 14(4), 175–194.

    Article  Google Scholar 

  • Hendriks, T., Hassankhan, A., Schotanus-Dijkstra, M., Bohlmeijer, E., & De, J. (2019). The efficacy of multi-component positive psychology interventions: A systematic review and meta-analysis of randomized controlled trials. Journal of Happiness Studies, 21(1), 357–390.

  • Horn, J. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185.

    Article  Google Scholar 

  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.

    Article  Google Scholar 

  • Huff, C., & Tingley, D. (2015). “Who are these people?” evaluating the demographic characteristics and political preferences of MTurk survey respondents. Research & Politics, 2(3).

  • Huppert, F., & So, T. (2013). Flourishing across europe: Application of a new conceptual framework for defining well-being. Social Indicators Research, 110(3), 837–861.

    Article  Google Scholar 

  • Jacobson, M. R., Whyte, C. E., & Azzam, T. (2018). Using crowdsourcing to code open-ended responses: A mixed methods approach. American Journal of Evaluation, 39(3), 413–429.

    Article  Google Scholar 

  • Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., & Rosseel, Y. (2018). SemTools: Useful tools for structural equation modeling. R package version 0.51. Retrieved from https://CRAN.R-project.org/package=semTools

  • Jovanović, V. (2015). A bifactor model of subjective well-being: A re-examination of the structure of subjective well-being. Personality and Individual Differences, 87, 45–49.

    Article  Google Scholar 

  • Judge, T., & Watanabe, S. (1993). Another look at the job satisfaction^life satisfaction relationship. Journal of Applied Psychology, 78(6), 939–948.

    Article  Google Scholar 

  • Kern, M. L. (2014). The workplace PERMA Profiler. Retrieved from https://permahsurvey.com/

  • Kern, M. L., Waters, L. E., Adler, A., & White, M. A. (2015). A multidimensional approach to measuring well-being in students: Application of the PERMA framework. The Journal of Positive Psychology, 10(3), 262–271.

  • Kline, R. B. (2016). Methodology in the social sciences. Principles and practice of structural equation modeling (4th ed.). New York: Guilford Press.

    Google Scholar 

  • Kobau, R., Sniezek, J., Zack, M., Lucas, R., & Burns, A. (2010). Well-being assessment: An evaluation of well-being scales for public health and population estimates of well-being among us adults. Applied Psychology: Health and Well-Being, 2(3), 272–297.

    Google Scholar 

  • Koo, T., & Li, M. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163.

    Article  Google Scholar 

  • Lambert, E., Hogan, N., Camp, S., & Ventura, L. (2006). The impact of work—Family conflict on correctional staff: A Riminary study. Criminology & Criminal Justice: An International Journal, 6(4).

  • Laschinger, H. K. S., Heather, K., Leiter, P. M., Day, A., Gilin-Oore, D., & Mackinnon, P. S. (2012). Building empowering work environments that foster civility and organizational trust: Testing an intervention. Nursing Research, 61(5), 316–325.

  • Ledesma, R. D., & Valero-More, P. (2007). Determining the number of factors to retain in EFA: An easy-to-use computer program for carrying out parallel analysis. Practical Assessment, Research & Evaluation, 12(2), 1–11.

    Google Scholar 

  • Little, T. D., Slegers, D. W., & Card, N. A. (2006). A non-arbitrary method of identifying and scaling latent variables in sem and macs models. Structural Equation Modeling, 13(1), 59–72.

  • Longo, Y., Coyne, I., & Joseph, S. (2017). The scales of general well-being (SGWB). Personality and Individual Differences, 109, 148–159.

    Article  Google Scholar 

  • Luthans, F., Avolio, B., Avey, J., & Norman, S. (2007). Positive psychological capital: Measurement and relationship with performance and satisfaction. Personnel Psychology, 60(3), 541–572.

    Article  Google Scholar 

  • Mahalanobis, P. C. (1936). On the generalized distance in statistics. Proceedings of the National Institute of Science of India, 2, 49–55.

    Google Scholar 

  • Marsh, H. W. (1996). Positive and negative global self-esteem: A substantively meaningful distinction or artifactors? Journal of Personality and Social Psychology, 70(4), 810–819.

    Article  Google Scholar 

  • Marsh, H. W., & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of self-concept: First- and higher order factor models and their invariance across groups. Psychological Bulletin, 97(3), 562–582.

    Article  Google Scholar 

  • Maslach, C., Jackson, S. E., & Schwab, R. L. (1986). Maslach burnout inventory: manual with a special supplement “burnout in education” [mbi] (2nd ed.). Consulting Psychologists Press.

  • Meade, A., Johnson, E., & Braddy, P. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. The Journal of Applied Psychology, 93(3), 568–592.

    Article  Google Scholar 

  • Meade, A., & Lautenschlager, G. (2004). A comparison of item response theory and confirmatory factor analytic methodologies for establishing measurement equivalence/invariance. Organizational Research Methods, 7(4), 361–388.

  • Meyers, M., Van Woerkom, M., & Bakker, A. (2013). The added value of the positive: A literature review of positive psychology interventions in organizations. European Journal of Work and Organizational Psychology, 22(5), 618–632.

  • Neumeier, L., Brook, L., Ditchburn, G., & Sckopke, P. (2017). Delivering your daily dose of well-being to the workplace: A randomized controlled trial of an online well-being programme for employees. European Journal of Work and Organizational Psychology, 26(4), 555–573.

  • Nicholas, I. J. (1982). Organizational climate and strategic decision-making. Journal of General Management, 7(3), 57–71.

  • Orsila, R., Luukkaala, T., Manka, M., & Nygard, C. (2011). A new approach to measuring work-related well-being. International Journal of Occupational Safety and Ergonomics, 17(4), 341–359. https://doi.org/10.1080/10803548.2011.11076900.

  • Ozduran, A., & Tanova, C. (2017). Manager mindsets and employee organizational citizenship behaviours. International Journal of Contemporary Hospitality Management, 29(1), 589–606.

    Article  Google Scholar 

  • Page, K., & Vella-Brodrick, D. (2013). The working for wellness program: RCT of an employee well-Being intervention. Journal of Happiness Studies, 14(3), 1007–1031.

  • Piasentin, K., & Chapman, D. (2007). Perceived similarity and complementarity as predictors of subjective person-organization fit. Journal of Occupational and Organizational Psychology, 80(2), 341–354.

    Article  Google Scholar 

  • Porath, C., Spreitzer, G., Gibson, C., & Garnett, F. (2012). Thriving at work: Toward its measurement, construct validation, and theoretical refinement. Journal of Organizational Behavior, 33(2), 250–275.

  • Rand, D. G. (2012). The promise of mechanical Turk: How online labor markets can help theorists run behavioral experiments. Journal of Theoretical Biology, 299, 172–179.

    Article  Google Scholar 

  • Revelle, W. (2015). Psych: Procedures for personality and psychological research. Retrieved from ://CRAN.R-project.org/package=psych

  • Revelle, W., & Zinbarg, R. (2009). Coefficients alpha, beta, omega, and the glb: Comments on Sijtsma. Psychometrika, 74(1), 145.

    Article  Google Scholar 

  • Rodriguez, A., Reise, S., & Haviland, M. (2016). Evaluating bifactor models: Calculating and interpreting statistical indices. Psychological Methods, 21(2), 137–150.

    Article  Google Scholar 

  • Roodt, G., & Bothma, C. (2013). The validation of the turnover intention scale: Original research. SA Journal of Human Resource Management, 11(1), 1–12.

    Google Scholar 

  • Rosseel, Y. (2012). Lavaan: An r package for structural equation modeling. Journal of Statistical Software, 48(2).

  • Russell, E., & Daniels, K. (2018). Measuring affective well-being at work using short-form scales: Implications for affective structures and participant instructions. Human Relations, 71(11), 1478–1507.

  • Ryan, R. M., & Deci, E. L. (2001). On happiness and human potentials: A review of research on hedonic and eudaimonic well-being. Annual Review of Psychology, 52, 141–166.

    Article  Google Scholar 

  • Ryff, C., & Keyes, C. (1995). The structure of psychological well-being revisited. Journal of Personality and Social Psychology, 69(4), 719–727.

    Article  Google Scholar 

  • Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their relationship with burnout and engagement: A multi-sample study. Journal of Organizational Behavior, 25(3), 293–315.

    Article  Google Scholar 

  • Seligman, M. E. P. (2008). Positive health. Applied Psychology, 57, 3–18.

    Article  Google Scholar 

  • Seligman, M. E. P. (2011). Flourishing: A visionary new understanding of happiness and well-being. New York, NY: Free Press.

    Google Scholar 

  • Seligman, M. (2018). PERMA and the building blocks of well-being. The Journal of Positive Psychology, 13(4), 333–335.

  • Seligman, M. E. P., & Csikszentmihalyi, M. (2000). Positive psychology: An introduction. American Psychologist, 55(1), 5–14.

    Article  Google Scholar 

  • Seligman, M. E., Railton, P., Baumeister, R. F., & Sripada, C. (2013). Navigating into the future or driven by the past. Perspectives on Psychological Science, 8(2), 119–141.

  • Shaffer, J. A., DeGeest, D., & Li, A. (2016). Tackling the problem of construct proliferation: A guide to assessing the discriminant validity of conceptually related constructs. Organizational Research Methods, 19(1), 80–110.

    Article  Google Scholar 

  • Spector, P. (2007). Instructions for scoring the job-related affective well-being scale, Jaws. Retrieved from http://shell.cas.usf.edu/~pspector/scales/jawsscor.html

  • Spector, P., Bauer, J., & Fox, S. (2010). Measurement artifacts in the assessment of counterproductive work behavior and organizational citizenship behavior: Do we know what we think we know? The Journal of Applied Psychology, 95(4), 781–790.

  • Spitzer, R., Williams, J., Kroenke, K., Hornyak, R., & McMurray, J. (2000). Validity and utility of the prime-md patient health questionnaire in assessment of 3000 obstetric-gynecologic patients: The prime-md patient health questionnaire obstetrics-gynecology study. American Journal of Obstetrics and Gynecology, 183(3), 759–769.

  • Tail, M., Padgett, M. Y., & Baldwin, T. T. (1989). Job and life satisfaction: A reexamination of the strength of the relationship and gender effects as a function of the date of the study. Journal of Applied Psychology, 74, 502–507.

    Article  Google Scholar 

  • Van Katwyk, P., Fox, S., Spector, P., & Kelloway, E. (2000). Using the job-related affective well-being scale (jaws) to investigate affective responses to work stressors. Journal of Occupational Health Psychology, 5(2), 219–230.

    Article  Google Scholar 

  • Wallston, K. A. (2005). The validity of the multidimensional health locus of control scales. Journal of Health Psychology, 10(5), 623–632.

    Article  Google Scholar 

  • Warren, M. A., Donaldson, S. I., & Luthans, F. (2017). Taking positive psychology to the workplace: Positive organizational psychology, positive organizational behavior, and positive organizational scholarship. In M. A. Warren & S. I. Donaldson (Eds.), Scientific Advances in Positive Psychology (pp. 195–227). Westport, CT: Praeger.

  • Waterman, A. (2008). Reconsidering happiness: A eudaimonist’s perspective. Journal Of Positive Psychology, 3(4), 234–252.

    Article  Google Scholar 

  • Waterman, A., Schwartz, S., Zamboanga, B., Ravert, R., Williams, M., Bede Agocha, V., Yeong Kim, S., & Brent Donnellan, M. (2010). The questionnaire for eudaimonic well-being: Psychometric properties, demographic comparisons, and evidence of validity. Journal of Positive Psychology, 5(1), 41–61.

    Article  Google Scholar 

  • Wheaton, B., Muthen, B., Alwin, D. F., & Summers, G. (1977). Assessing reliability and stability in panel models. Sociological Methodology, 8(1), 84–136.

    Article  Google Scholar 

  • Willis Towers Watson (2017). Global benefits attitudes survey. Retrieved from https://www.willistowerswatson.com/en-US/insights/2017/11/2017-global-benefits-attitudes-survey

  • Yong, A. G., & Pearce, S. (2013). A beginner’s guide to factor analysis: Focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79–94.

    Article  Google Scholar 

  • Yuan, K., & Bentler, P. (2000). Three likelihood-based methods for mean and covariance structure analysis with nonnormal missing data. Sociological Methodology, 30(1), 165–200.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Scott I. Donaldson.

Ethics declarations

Conflict of Interest

All the authors declare no conflicts of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki.

Declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

ESM 1

(DOCX 19 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Donaldson, S.I., Donaldson, S.I. The Positive Functioning at Work Scale: Psychometric Assessment, Validation, and Measurement Invariance. J well-being assess 4, 181–215 (2020). https://doi.org/10.1007/s41543-020-00033-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41543-020-00033-1

Keywords

Navigation