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Reliability of the NEO Five Factor Inventory short form for assessing personality after stroke

Published online by Cambridge University Press:  28 March 2017

Toni Dwan Open the ORCID record for Toni Dwan [Opens in a new window] ,
Tamara Ownsworth ,
Caroline Donovan  and
Ada Ho Yan Lo
Toni Dwan*
Affiliation:
School of Applied Psychology and Menzies Health Institute Queensland, Griffith University, Brisbane, Australia
Tamara Ownsworth
Affiliation:
School of Applied Psychology and Menzies Health Institute Queensland, Griffith University, Brisbane, Australia
Caroline Donovan
Affiliation:
School of Applied Psychology and Menzies Health Institute Queensland, Griffith University, Brisbane, Australia
Ada Ho Yan Lo
Affiliation:
Princess Alexandra Hospital, Brisbane, Australia
*
Correspondence should be addressed to: Toni Dwan, School of Applied Psychology, Griffith University, Mount Gravatt Campus, Mount Gravatt 4122, Australia. Phone: +61 73735 3305; Fax: +61 73735 3388. Email: t.dwan@griffith.edu.au.
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Abstract

Background:

It is well recognized that an individual's personality characteristics influence their psychological adjustment after stroke. However, there is a lack of research on the reliability of personality inventories for stroke. This study primarily aimed to evaluate the reliability of the Neuroticism, Extroversion, Openness to Experience (NEO)-Five Factor Inventory (NEO-FFI) for assessing pre-morbid personality and personality changes after stroke. Further aims were to investigate changes in personality during the hospital-to-home transition period and examine associations between personality and mood.

Methods:

Forty participants with stroke (52.5% male, M age=65.55 years) were recruited at time of hospital discharge and completed the NEO-FFI, Centre for Epidemiologic Studies – Depression and Geriatric Anxiety Inventory. Significant others completed an informant version of the NEO-FFI. Stroke participants were re-assessed on the NEO-FFI at 1-month and 4-months post-discharge. Forty matched controls also completed the NEO-FFI.

Results:

Internal consistency was adequate for the NEO-FFI (α=0.57–0.86), although low for agreeableness. There was fair to excellent concordance between self-rated and informant versions of the NEO-FFI (ICC=0.58–0.78). Significant positive associations were found between neuroticism and mood (r=0.50–0.68), and significant negative associations were found between extraversion and mood (r=−0.33–0.36) and agreeableness and anxiety (r=−0.43). Self-ratings of stroke participants on the NEO-FFI at discharge did not significantly differ from matched controls. Extraversion levels significantly decreased, and agreeableness levels significantly increased between discharge and 1- and 4-months post-discharge.

Conclusions:

Overall, the results support the reliability of the NEO-FFI for assessing personality characteristics in the context of stroke.

Keywords

StrokepersonalityNEO-FFIdepressionanxiety
Type
Research Article
Information
International Psychogeriatrics , Volume 29 , Issue 7 , July 2017 , pp. 1157 - 1168
Copyright
Copyright © International Psychogeriatric Association 2017 

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References

Afshar, H., Roohafza, H., Hassanzadeh-Keshteli, A., Sharbafchi, M. R., Feizi, A. and Adibi, P. (2015). Association of personality traits with psychological factors of depression, anxiety, and psychological distress: a community based study. International Journal of Body, Mind and Culture, 2, 105–114.Google Scholar
Ahn, D.-H., Lee, Y.-J., Jeong, J.-H., Kim, Y.-R. and Park, J.-B. (2015). The effect of post-stroke depression on rehabilitation outcome and the impact of caregiver type as a factor of post-stroke depression. Annals of Rehabilitation Medicine, 39, 74–80. doi: org/10.5535/arm.2015.39.1.74 Google Scholar
Ayerbe, L., Ayis, S., Wolfe, C. D. A. and Rudd, A. G. (2013). Natural history, predictors and outcomes of depression after stroke: systematic review and meta-analysis. The British Journal of Psychiatry, 202, 14–21. doi:10.1192/bjp.bp.111.107664.CrossRefGoogle ScholarPubMed
Broomfield, N. M., Quinn, T. J., Abdul-Rahim, A. H., Walters, M. R. and Evans, J. J. (2014). Depression and anxiety symptoms post-stroke/TIA: prevalence and associations in cross-sectional data from a regional stroke registry. BMC Neurology, 14, 1–9. doi: 10.1186/s12883-014-0198-8 CrossRefGoogle ScholarPubMed
Caruso, J. C. (2000). Reliability generalization of the NEO personality scales. Educational and Psychological Measurement, 60, 236–254. doi:10.1177/00131640021970484 Google Scholar
Costa, P. T. and McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO PI-R) and NEO Five-Factor Inventory (NEO FFI): Professional Manual. Odessa, FL: Psychological Assessment Resources.Google Scholar
Foltz, C., Morse, J. Q., Calvo, N. and Barber, J. P. (1997). Self- and observer ratings on the NEO-FFI in couples: initial evidence of the psychometric properties of an observer form. Assessment, 4, 287–295. doi:10.1177/107319119700400308.Google Scholar
Glinski, K. and Page, A. C. (2012). Modifiability of neuroticism, extraversion, and agreeableness by group cognitive behaviour therapy for social anxiety disorder. Behaviour Change, 27, 42–52. doi: https://doi.org/10.1375/bech.27.1.42.Google Scholar
Godwin, K. M., Ostwald, S. K., Cron, S. G. and Wasserman, J. (2013). Long-term health related quality of life of survivors of stroke and their spousal caregivers. The Journal of Neuroscience Nursing, 45, 147–154. doi:10.1097/JNN.0b013e31828a410b Google Scholar
Goldberg, L. R., Sweeney, D., Merenda, P. F. and Hughes, J. E. (1998). Demographic variables and personality: the effects of gender, age, education, and ethnic/racial status on self-descriptions of personality attributes. Personality and Individual Differences, 24, 393–403. doi:10.1016/S0191-8869(97)00110-4.CrossRefGoogle Scholar
Greenop, K. R., Almeida, O. P., Hankey, G. J., van Bockxmeer, F. and Lautenschlager, N. T. (2009). Premorbid personality traits are associated with post-stroke behavioral and psychological symptoms: a three-month follow-up study in Perth, Western Australia. International Psychogeriatrics, 21, 1063–1071. doi:10.1017/S1041610209990457.Google Scholar
Hackett, M. L., Anderson, C. S., House, A. O. and Xia, J. (2008). Interventions for treating depression after stroke. Cochrane Database of Systematic Reviews, 4, CD003437. doi:10.1002/14651858.CD003437.pub3 Google Scholar
Hackett, M. L. and Pickles, K. (2014). Part I: frequency of depression after stroke: an updated systematic review and meta-analysis of observational studies. International Journal of Stroke, 9, 1017–1025. doi:10.1111/ijs.12357 Google Scholar
Hann, D., Winter, K. and Jacobsen, P. (1999). Measurement of depressive symptoms in cancer patients: evaluation of the Center for Epidemiological Studies Depression scale (CES-D). Journal of Psychosomatic Research, 46, 437–443. doi:10.1016/S0022-3999(99)00004-5.CrossRefGoogle ScholarPubMed
Haslam, C., Holme, A., Haslam, S. A., Iyer, A., Jetten, J. and Williams, W. H. (2008). Maintaining group memberships: social identity continuity predicts well-being after stroke. Neuropsychological Rehabilitation, 18, 671–691. doi:10.1080/09602010701643449 Google Scholar
Hwang, S. I., Choi, K. I., Park, O. T., Park, S.-W., Choi, E. S. and Yi, S.-H. (2011). Correlations between pre-morbid personality and depression scales in stroke patients. Annals of Rehabilitation Medicine, 35, 328–336. doi:10.5535/arm.2011.35.3.328.Google Scholar
Jokela, M., Hakulinen, C., Singh-Manoux, A. and Kivimäki, M. (2014). Personality change associated with chronic diseases: pooled analysis of four prospective cohort studies. Psychological Medicine, 44, 2629–2640. doi:10.1017/S0033291714000257 CrossRefGoogle ScholarPubMed
Kim, S. et al. (2013). Influences of personality traits on quality of life after stroke. European Neurology, 69, 185–192. doi:10.1159/000345699.Google Scholar
Lincoln, N. B. (1982). The speech questionnaire: an assessment of functional language ability. International Rehabilitation Medicine, 4, 114–117. doi:10.3109/09638288209166893.Google Scholar
Morris, P. L. P., Robinson, R. G. and Samuels, J. (1993). Depression, introversion and mortality following stroke. Australian and New Zealand Journal of Psychiatry, 27, 443–449. doi: 10.3109/00048679309075801.Google Scholar
Nijsse, B., van Heugten, C. M., van Mierlo, M. L., Post, M. W. M., de Kort, P. L. M. and Visser-Meily, J. M. A. (2017). Psychological factors are associated with subjective cognitive complaints 2 months post-stroke. Neuropsychological Rehabilitation, 27, 99–115. doi:10.1080/09602011.2015.1065280 Google Scholar
Pachana, N. A., Byrne, G. J., Siddle, H., Koloski, N., Harley, E. and Arnold, E. (2007). Development and validation of the geriatric anxiety inventory. International Psychogeriatrics, 19, 103–114. doi:10.1017/S1041610206003504 Google Scholar
Radloff, L. S. (1977). The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401. doi:10.1177/014662167700100306 Google Scholar
Robinson, R. G. and Jorge, R. E. (2016). Post-stroke depression: a review. American Journal of Psychiatry, 173, 221–231. doi:10.1176/appi.ajp.2015.15030363. Google Scholar
Roohafza, H. et al. (2016). Path analysis of relationship among personality, perceived stress, coping, social support, and psychological outcomes. World Journal of Psychiatry, 6, 248–256. doi:10.5498/wjp.v6.i2.248 Google Scholar
Storor, D. L. and Byrne, G. J. A. (2006). Pre-morbid personality and depression following stroke. International Psychogeriatrics, 18, 457–469.CrossRefGoogle ScholarPubMed
Tabachnick, B. G. and Fidell, L. S. (2013). Using Multivariate Statistics. USA: Pearson Education.Google Scholar
Tate, R. L. (2003). Impact of pre-injury factors on outcome after severe traumatic brain injury: does post-traumatic personality change represent an exacerbation of premorbid traits?. Neuropsychological Rehabilitation, 13, 43–64. doi: 10.1080/09602010244000372 Google Scholar
Tate, R. L. (2010). A Compendium of Tests, Scales, and Questionnaires: The Practitioner's Guide to Measuring Outcomes After Acquired Brain Impairment. USA: Psychology Press.Google Scholar
Terwee, C. B., Mokkink, L. B., Knol, D. L., Ostelo, R. W. J. G., Bouter, L. M. and de Vet, H. C. W. (2012). Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Quality of Life Research, 21, 651–657. doi: 10.1007/s11136-011-9960-1.Google Scholar
Thrift, A. G. et al. (2014). Global stroke statistics. International Journal of Stroke, 9, 6–18. doi: 10.1111/ijs.12245.Google Scholar
van Mierlo, M. L., Schröder, C., van Heugten, C. M., Post, M. W. M., de Kort, P. L. M. and Visser-Meily, J. M. A. (2014). The influence of psychological factors on health-related quality of life after stroke: a systematic review. International Journal of Stroke, 9, 341–348. doi: 10.1111/ijs.12149.Google Scholar
Villieux, A., Sovet, L., Jung, S.-C. and Guilbert, L. (2016). Psychological flourishing: validation of the French version of the flourishing scale and exploration of its relationships with personality traits. Personality and Individual Differences, 88, 1–5. doi:10.1016/j.paid.2015.08.027.Google Scholar