Frontiers in Psychological and Behavioral Science          
Frontiers in Psychological and Behavioral Science(FPBS)
ISSN:2309-012X(Print)       ISSN:2309-0138(Online)
Factor Structure of an Internet-Based Symptom Checklist and Correlation with Conventional Rating Scales
Full Paper(PDF, 89KB)
The Neuropsych Questionnaire (NPQ) addresses two important clinical issues: how to screen patients from a wide range of neuropsychiatric disorders quickly and efficiently; and how to acquire independent verification of a patient’s complaints. The NPQ is available on the Internet in both adult and pediatric versions, and its adult version consists of 207 simple questions about common symptoms of neuropsychiatric disorders. The NPQ reports give the scores of the patient’s and/or observer’s responses in terms of 20 symptom clusters: inattention, hyperactivity-impulsivity, learning problems, memory, anxiety, panic, agoraphobia, obsessions and compulsions, social anxiety, depression, mood instability, mania, aggression, psychosis, somatization, fatigue, sleep, suicide, pain and substance abuse. In this paper, the factor analysis with a large number of patients are carried out to investigate the factor structure of the NPQ and report the correspondence between the NPQ and other clinical RSs in common use. This analysis generates three distinct factors: cognitive, somatic and manic– and anxiety- depression. The symptoms scales composed of the anxiety-depression factor load equally with those of the mania and somatic factors but not those of the cognitive factor. In summary, the NPQ is a useful tool in neuropsychiatric practice. It also generates interesting data about the nature of symptom self-report and its relationship with specific psychiatric diagnoses.
Keywords:Neuropsych Questionnaire; Symptom Questionnaire; Self-Rating
Author: C. Thomas Gualtieri1
1.NC Neuropsychiatry, 400 Franklin Square, 1829 East Franklin Street, Chapel Hill NC 27514, USA
  1. M. Slade, P. McCrone, E. Kuipers, et al, “Use of standardised outcome measures in adult mental health services: randomised controlled trial,” Br J Psychiatry, vol. 189, pp. 330-336, 2006.
  2. A. S. Kesselheim, T. G. Ferris and D. M. Studdert, “Will physician-level measures of clinical performance be used in medical malpractice litigation?” JAMA, vol. 295 (15), pp. 1831-1834, 2006.
  3. R. M. Bagby, A. G. Ryder, D. R. Schuller and M. B. Marshall, “The hamilton depression rating scale: has the gold standard become a lead weight?” Am J Psychiatry, vol. 161(12), pp. 2163-2177, 2004.
  4. Streiner D. Norman, Health Measurement Scales A Practical Guide to Their Development and Use, 2nd ed., New York: Oxford University Press, 1995.
  5. C. Gualtieri, “An Internet-based symptom questionnaire that is reliable, valid, and available to psychiatrists, neurologists, and psychologists,” MedGenMed., vol. 9(4), p.3, 2007.
  6. D. J. Slick, E. M. Sherman, G. L. Iverson, “Diagnostic criteria for malingered neurocognitive dysfunction: proposed standards for clinical practice and research,” Clin Neuropsychol., vol. 13(4), pp. 545-561, 1999.
  7. R. Berzon, R. D. Hays, “Shumaker SA. international use, application and performance of health-related quality of life instruments,” Qual Life Res., vol. 2(6), pp. 367-368, 1993.
  8. J. Hedlund and B. Vieweg, “The hamilton rating scale for depression: a comprehensive review,” J Operational Psychiatry, vol. 10, pp. 149-165, 1979.
  9. I. McDowell and C .Newell, Measuring Health, A Gude to Rating Scales and Questionnaires, 2nd ed. New York: Oxford Univ Press, 1996.
  10. R. E. Nisbett and T. D. Wilson, “The halo effect: evidence for unconscious alteration of judgments,” Journal of Personality and Social Psychology, vol. 35(4), pp. 250-256, 1977.
  11. J. B. Dowd and M. Todd, “Does self-reported health bias the measurement of health inequalities in U.S. adults? Evidence using anchoring vignettes from the health and retirement study,” J Gerontol B Psychol Sci Soc Sci., vol. 66(4), pp. 478-489, 2011.
  12. P. Symonds, “On the loss of reliability in ratings due to the coarseness of the scale,” Journal of Experimental Psychology, vol. 17, pp. 456-461, 1924.
  13. W. R. Garner, “Rating scales, discriminability, and information transmission,” Psychol Rev., vol. 67, pp. 343-352, 1960.
  14. C. C. Preston and A. M. Colman, “Optimal number of response categories in rating scales: reliability, validity, discriminating power, and respondent preferences,” Acta Psychol (Amst)., vol. 104(1), pp. 1-15, 2000.
  15. H. Schutz and M. Rucker, “Variable configurations across scale lengths: an empirical study,” Educ Psychol Measurement, vol. 35, pp. 319-24, 1975.
  16. K. A. Kobak, J. H. Greist, J. W. Jefferson and D. J. Katzelnick, “Computer-administered clinical rating scales, a review,” Psychopharmacology (Berl.)., vol. 127(4), pp. 291-301, 1996.
  17. N. Smits, F. G. Zitman, P. Cuijpers, M. E. Den Hollander-Gijsman and I. V. E. Carlier, “A proof of principle for using adaptive testing in routine outcome monitoring: the efficiency of the mood and anxiety symptoms questionnaire -anhedonic depression CAT,” BMC Med Res Methodol., vol. 12, p. 4, 2012.
  18. R. D. Gibbons, D. J. Weiss, P. A. Pilkonis, et al, “Development of a computerized adaptive test for depression,” Arch. Gen. Psychiatry, vol. 69(11), pp. 1104-1112, 2012.
  19. J. Cummings, H. Gould and K. Zhong, “Advances in designs for Alzheimer’s disease clinical trials,” Am J Neurodegener Dis., vol. 1(3), pp. 205-216, 2012.
  20. M. Inoue, D. Jimbo, M. Taniguchi and K. Urakami, “Touch panel-type dementia assessment scale: a new computer-based rating scale for Alzheimer’s disease, Psychogeriatrics, vol. 11(1), pp. 28-33, 2011.
  21. G. Wolford, S. D. Rosenberg, H. J. Rosenberg, et al, “A clinical trial comparing interviewer and computer-assisted assessment among clients with severe mental illness,” Psychiatr Serv., vol. 59(7), pp. 769-775, 2008.
  22. J. A. Fein, M. E. Pailler, F. K. Barg, et al, “Feasibility and effects of a web-based adolescent psychiatric assessment administered by clinical staff in the pediatric emergency department,” Arch Pediatr Adolesc Med., vol. 164(12), pp. 1112-1117, 2010.
  23. L. A. Goldstein, M. B. Connolly Gibbons, S. M. Thompson, et al, “Outcome assessment via handheld computer in community mental health: consumer satisfaction and reliability,” J Behav Health Serv Res., vol. 38(3), pp. 414-423, 2011.
  24. J. Rucker, S. Newman, J. Gray, et al, “OPCRIT+: an electronic system for psychiatric diagnosis and data collection in clinical and research settings,” Br J Psychiatry, vol. 199(2), pp. 151-155, 2011.
  25. M. Chinman, A. S. Young, T. Schell, J. Hassell and J. Mintz, “Computer-assisted self-assessment in persons with severe mental illness,” J Clin Psychiatry, vol. 65(10), pp. 1343-1351, 2004.