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Further validation of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) in the UK veterinary profession: Rasch analysis

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Abstract

Purpose

To examine the psychometric properties of the 14-item Warwick-Edinburgh Mental Well-being Scale (WEMWBS) in the UK veterinary profession by the application of Rasch analysis, and to assess the external construct validity of the derived interval scale measurements.

Methods

Data sets were derived from two independent cross-sectional surveys of the veterinary profession (n = 8,829 and n = 1,796). Rasch analysis (n = 500) included response option thresholds ordering, tests of fit, differential item functioning, targeting, response dependency, and person separation index (PSI). Unidimensionality was evaluated by principal component analysis of residuals. The findings were validated across further subsamples from both data sets. The external construct validity of the Rasch-fitting item set was evaluated by associations with other measures of psychological health or psychosocial work characteristics.

Results

Data for the original 14 items deviated significantly from Rasch model expectations (chi-square = 558.2, df = 112, P = <0.001, PSI = 0.918). A unidimensional 7-item scale (Short WEMWBS, SWEMWBS) with acceptable fit to the model (chi-square = 58.8, df = 56, P = 0.104, PSI = 0.832) was derived by sequential removal of the most misfitting items. The external construct validity of SWEMWBS was supported.

Conclusions

SWEMWBS has robust interval-level measurement properties which support its suitability as an indicator of population mental health and well-being in this occupational group with elevated suicide risk.

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Abbreviations

CI:

Confidence interval

DIF:

Differential item functioning

HADS:

Hospital Anxiety and Depression Scale

HADS-A:

Anxiety subscale of Hospital Anxiety and Depression Scale

HADS-D:

Depression subscale of Hospital Anxiety and Depression Scale

HSE MSIT:

Health and Safety Executive Management Standards Indicator Tool

ICC:

Item characteristic curve

PSI:

Person separation index

RCVS:

Royal College of Veterinary Surgeons

SD:

Standard deviation

SWEMWBS:

Short Warwick-Edinburgh Mental Well-being Scale

WEMWBS:

Warwick-Edinburgh Mental Well-being Scale

WHI_N:

Negative work–home interaction

References

  1. Bartram, D. J., & Baldwin, D. S. (2010). Veterinary surgeons and suicide: A structured review of possible influences on increased risk. Veterinary Record, 166, 388–397.

    Article  PubMed  CAS  Google Scholar 

  2. Platt, B., Hawton, K., Simkin, S., & Mellanby, R. J. (2010). Systematic review of the prevalence of suicide in veterinary surgeons. Occupational Medicine, 60, 436–446.

    Article  PubMed  CAS  Google Scholar 

  3. Charlton, J. (1995). Trends and patterns in suicide in England and Wales. International Journal of Epidemiology, 24(Suppl. 1), S45–S52.

    Article  PubMed  Google Scholar 

  4. Tennant, R., Hiller, L., Fishwick, R., Platt, S., Joseph, S., Weich, S., et al. (2007). The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): development and UK validation. Health and Quality of Life Outcomes, 5, 63.

    Article  PubMed  Google Scholar 

  5. Clarke, A., Friede, T., Putz, R., Ashdown, J., Martin, S., Blake, A., et al. (2011). Warwick-Edinburgh Mental Well-being Scale (WEMWBS): validated for teenage school students in England and Scotland. A mixed methods assessment. BMC Public Health, 11, 487.

    Article  PubMed  Google Scholar 

  6. Bartram, D. J., Yadegarfar, G., Sinclair, J. M. A., & Baldwin, D. S. (2011). Validation of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) as an overall indicator of population mental health and well-being in the UK veterinary profession. The Veterinary Journal, 187, 397–398.

    Article  PubMed  Google Scholar 

  7. Hobart, J., & Cano, S. (2009). Improving the evaluation of therapeutic interventions in multiple sclerosis: The role of new psychometric methods. Health Technology Assessment, 13(12), iii, ix–x, 1–177.

    Google Scholar 

  8. Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen: Danish Institute for Educational Research.

    Google Scholar 

  9. Tennant, A., & Conaghan, P. G. (2007). The Rasch measurement model in rheumatology: What is it and why use it? When should it be applied, and what should one look for in a Rasch paper. Arthritis and Rheumatism, 57, 1358–1362.

    Article  PubMed  Google Scholar 

  10. Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44, S69–S77.

    Article  PubMed  Google Scholar 

  11. Terwee, C. B., Bot, S. D. M., de Boer, M. R., van der Windt, D. A. W. M., Knol, D. L., Dekker, J., et al. (2007). Quality criteria were proposed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology, 60, 34–42.

    Article  PubMed  Google Scholar 

  12. Gregorich, S. E. (2006). Do self-report instruments allow meaningful comparisons across diverse population groups? Testing measurement invariance using the confirmatory factor analysis framework. Medical Care, 44, S78–S94.

    Article  PubMed  Google Scholar 

  13. Leiter, M. P., & Schaufeli, W. B. (1996). Consistency of the burnout structure across occupations. Anxiety, Stress and Coping, 9, 229–243.

    Article  Google Scholar 

  14. Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3, 4–70.

    Article  Google Scholar 

  15. Robertson-Smith, G., Robinson, D., Hicks, B., Khambhaita, P., & Hayday, S. (2010). The 2010 RCVS survey of the UK veterinary and veterinary nursing professions. Brighton: Institute for Employment Studies. http://www.rcvs.org.uk/publications/rcvs-survey-of-the-professions-2010/surveyprofessions2010.pdf. Accessed February 13, 2012.

  16. Bartram, D. J., Yadegarfar, G., & Baldwin, D. S. (2009). A cross-sectional study of mental heath and well-being and their associations in the UK veterinary profession. Social Psychiatry and Psychiatric Epidemiology, 44, 1075–1085.

    Article  PubMed  Google Scholar 

  17. Zigmond, A. S., & Snaith, R. P. (1983). The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica, 67, 361–370.

    Article  PubMed  CAS  Google Scholar 

  18. Geurts, S. A. E., Taris, T. W., Kompier, M. A. J., Dikkers, J. S. E., van Hooff, M. L. M., & Kinnunen, U. M. (2005). Work-home interaction from a work psychological perspective: Development and validation of a new questionnaire, the SWING. Work & Stress, 19, 319–339.

    Article  Google Scholar 

  19. Cousins, R., Mackay, C. J., Clarke, S. D., Kelly, C., Kelly, P. J., & McCaig, R. H. (2004). ‘Management standards’ and work related stress in the UK: Practical development. Work & Stress, 18, 113–136.

    Article  Google Scholar 

  20. Singleton, N., Bumpstead, R., O’brien, M., Lee, A., & Meltzer, H. (2001). Psychiatric morbidity among adults living in private households, 2000. London: The Stationery Office.

    Google Scholar 

  21. Lamoureux, E. L., Pesudovs, K., Thumboo, J., Saw, S.-M., & Wong, T. Y. (2009). An evaluation of the reliability and validity of the visual functioning questionnaire (VF-11) using Rasch analysis in an Asian population. Investigative Ophthalmology & Visual Science, 50, 2607–2613.

    Article  Google Scholar 

  22. Cano, S. J., Barrett, L. E., Zajicek, J. P., & Hobart, J. C. (2011). Beyond the reach of traditional analyses: Using Rasch to evaluate the DASH in people with multiple sclerosis. Multiple Sclerosis Journal, 17, 214–222.

    Article  PubMed  CAS  Google Scholar 

  23. Smith, A. B., Rush, R., Fallowfield, L. J., Velikova, G., & Sharpe, M. (2008). Rasch fit statistics and sample size considerations for polytomous data. BMC Medical Research Methodology, 8, 33.

    Article  PubMed  Google Scholar 

  24. Linacre, J. M. (1994). Sample size and item calibration stability. Rasch Measurement Transactions, 7, 328.

    Google Scholar 

  25. Lundgren-Nilsson, Å., & Tennant, A. (2011). Past and present issues in Rasch analysis: The Functional Independence Measure (FIM) revisited. Journal of Rehabilitation Medicine, 43, 884–891.

    Article  PubMed  Google Scholar 

  26. Pallant, J. F., Miller, R. L., & Tennant, A. (2006). Evaluation of the Edinburgh Post Natal Depression Scale using Rasch analysis. BMC Psychiatry, 6, 28.

    Article  PubMed  Google Scholar 

  27. Tennant, A., & Pallant, J. F. (2006). Unidimensionality matters! (A tale of two Smiths?). Rasch Measurement Transactions, 20, 1048–1051.

    Google Scholar 

  28. Andrich, D., Sheridan, B. S., & Luo, G. (2010). RUMM2030: A Windows program for the analysis of data according to Rasch unidimensional models for measurement. Perth, Australia: RUMM Laboratory.

    Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  30. Mcmanus, S., Meltzer, H., Brugha, T. S., Bebbington, P. E., & Jenkins, R. (2009). Adult psychiatric morbidity in England, 2007: Results of a household survey. London: National Centre for Social Research. http://www.ic.nhs.uk/cmsincludes/_process_document.asp?sPublicationID=1231750469828&sDocID=5446. Accessed February 13, 2012.

  31. Muller, S., & Roddy, E. (2009). A Rasch analysis of the Manchester foot pain and disability index. Journal of Foot and Ankle Research, 2, 29.

    Article  PubMed  Google Scholar 

  32. Teresi, J. A., & Fleishman, J. A. (2007). Differential item functioning and health assessment. Quality of Life Research, 16, 33–42.

    Article  PubMed  Google Scholar 

  33. Stewart-Brown, S., Tennant, A., Tennant, R., Platt, S., & Parkinson, J. (2009). Internal construct validity of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS): A Rasch analysis using data from the Scottish Health Education Population Survey. Health and Quality of Life Outcomes, 7, 15.

    Article  PubMed  Google Scholar 

  34. Edelen, M. O., & Reeve, B. B. (2007). Applying item response theory (IRT) modeling to questionnaire development, evaluation, and refinement. Quality of Life Research, 16, 5–18.

    Article  PubMed  Google Scholar 

  35. Andrich, D. (2011). Rating scales and measurement. Expert Review of Pharmacoeconomics and Outcomes Research, 11, 571–585.

    Article  PubMed  Google Scholar 

  36. Massof, R. W. (2011). Understanding Rasch and item response theory models: Applications to the estimation and validation of interval latent trait measures from responses to rating scale questionnaires. Ophthalmic Epidemiology, 18, 1–19.

    Article  PubMed  Google Scholar 

  37. Hambleton, R. K., & Swaminathan, H. (1985). Item response theory: Principles and applications. Boston, Massachussets: Kluwer-Nijhoff.

    Google Scholar 

  38. Wright, B. D. (1997). A history of social science and measurement. Educational Measurement: Issues and Practice, 16, 33–45.

    Article  Google Scholar 

  39. Cano, S. J., & Hobart, J. C. (2011). The problem with health measurement. Patient Preference and Adherence, 5, 279–290.

    Article  PubMed  Google Scholar 

  40. Bohlig, M., Fisher, W. P., Masters, G. N., & Bond, T. (1998). Content validity and misfitting items. Rasch Measurement Transactions, 12, 607.

    Google Scholar 

  41. Heinemann, A. W., & Deutsch, A. (2011). Commentary on ‘Past and present issues in Rasch analysis: The FIM revisited’. Journal of Rehabilitation Medicine, 43, 958–960.

    PubMed  Google Scholar 

  42. Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., et al. (2007). Psychometric evaluation and calibration of health-related quality of life item banks: Plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Medical Care, 45(Suppl 1), S22–S31.

    Article  PubMed  Google Scholar 

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Acknowledgments

This research would not have been possible without the support of the veterinarians who invested their time into completing and returning the questionnaires. The RCVS included the WEMWBS in the RCVS Survey of the Profession 2010 and supplied the response data in a suitable format for analysis.

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Correspondence to David J. Bartram.

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Bartram, D.J., Sinclair, J.M. & Baldwin, D.S. Further validation of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) in the UK veterinary profession: Rasch analysis. Qual Life Res 22, 379–391 (2013). https://doi.org/10.1007/s11136-012-0144-4

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