Skip to main content

Validity of a Voice-Based Evaluation Method for Effectiveness of Behavioural Therapy

  • Conference paper
  • First Online:

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 604))

Abstract

In this study, we used General Health Questionnaire 30 (GHQ30) and voice to evaluate the stress reduction effect of a stress resilience program, and examined the validity of stress evaluation by voice. We divided the subjects who participated in the program into two groups by the number of training sessions. The results showed a stress-reduction effect only in the group with more training sessions (more than 13 sessions) for both GHQ30 and voice-based indexes. Moreover, both indexes showed a highly negative correlation between the pre-training value and the difference between the post-training and pre-training values. This implies that the effect of the training is more evident for subjects with higher stress levels. The voice-based evaluation showed trends similar to those displayed by GHQ30.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    We used 12 as cut-off criteria of two groups, because the value was the median of their training sessions.

  2. 2.

    We assumed that increases and decreases in the score would occur with the same probability if the S-Gim were not performed.

  3. 3.

    We used the test function in Microsoft Excel 2010 for the tests.

  4. 4.

    Since vitality scores are continuous values, there was no subjects whose vitality score did not change.

References

  1. World Health Organization: The Global Burden of Disease: 2004 Update, pp. 46–49. WHO Press, Geneva, Switzerland (2004)

    Google Scholar 

  2. Kessler, R.C., Akiskal, H.S., Ames, M., Birnbaum, H., Greenberg, P., Hirschfeld, R.M.A., Jin, R., Merikangas, K.R., Simon, G.E., Wang, P.S.: Prevalence and effects of mood disorders on work performance in a nationally representative sample of U.S. workers. Am. J. Psychiatry 163(9), 1561–1568 (2006)

    Article  Google Scholar 

  3. Goldberg, D.P., Blackwell, B.: Psychiatric illness in general practice: a detailed study using a new method of case identification. BMJ 2(5707), 439–443 (1970)

    Article  Google Scholar 

  4. Beck, A.T.: A systematic investigation of depression. Compr. Psychiatry 2(3), 163–170 (1961)

    Article  Google Scholar 

  5. Beck, A.T., Ward, C.H., Mendelson, M., Mock, J., Erbaugh, J.: An inventory for measuring depression. Arch. Gen. Psychiatry 4(6), 561–571 (1961)

    Article  Google Scholar 

  6. Suzuki, G., Tokuno, S., Nibuya, M., Ishida, T., Yamamoto, T., Mukai, Y., Mitani, K., Tsumatori, G., Scott, D., Shimizu, K.: Decreased plasma brain-derived neurotrophic factor and vascular endothelial growth factor concentrations during military training. PLoS ONE 9(2), e89455 (2014)

    Article  Google Scholar 

  7. Arora, S., Venkataraman, V., Zhan, A., Donohue, S., Biglan, K.M., Dorsey, E.R., Little, M.A.: Detecting and monitoring the symptoms of Parkinson’s disease using smartphones: a pilot study. Parkinsonism Relat. D. 21(6), 650–653 (2015)

    Article  Google Scholar 

  8. Rachuri, K. K., Musolesi, M., Mascolo, C., Rentfrow, P.J., Longworth, C., Aucinas. A.: EmotionSense: a mobile phones based adaptive platform for experimental social psychology research. In: Proceedings of the 12th ACM International Conference on Ubiquitous Computing, pp. 281–290 (2010)

    Google Scholar 

  9. Lu, H., Rabbi, M., Chittaranjan, G.T., Frauendorfer, D., Mast, M.S., Campbell, A.T., Gatica-Perez, D., Choudhury, T.: Stresssense: detecting stress in unconstrained acoustic environments using smartphones. In: Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pp. 351–360 (2012)

    Google Scholar 

  10. Cannizzaro, M., Harel, B., Reilly, N., Chappell, P., Snyder, P.J.: Voice acoustical measurement of the severity of major depression. Brain Cogn. 56, 30–35 (2004)

    Article  Google Scholar 

  11. Moore, E., Clements, M., Peifert, J., Weisser, L.: Analysis of prosodic variation in speech for clinical depression. In: Proceedings of the 25th Annual International Conference of the IEEE EMBS, vol. 3, pp. 2925–2928. IEEE Press, New York (2003)

    Google Scholar 

  12. Mundt, J.C., Snyder, P.J., Cannizzaro, M.S., Chappie, K., Geralts, D.S.: Voice acoustic measures of depression severity and treatment response collected via interactive voice response (IVR) technology. J. Neurolinguist. 20(1), 50–64 (2007)

    Article  Google Scholar 

  13. Yang, Y., Fairbairn, C., Cohn, J.F.: Detecting depression severity from vocal prosody. IEEE Trans. Affect. Comput. 4(2), 142–150 (2013)

    Article  Google Scholar 

  14. Shimizu, T., Furuse, N., Yamazaki, T., Ueta, Y., Sato, T., Nagata, S.: Chaos of vowel /a/ in Japanese patients with depression: a preliminary study. J. Occup. Health. 47(3), 267–269 (2005)

    Article  Google Scholar 

  15. Vicsi, K., Sztaho, D.: Examination of the sensitivity of acoustic-phonetic parameters of speech to depression. In: IEEE 3rd International Conference on Cognitive Infocommunications, pp. 511–515. IEEE Press, New York (2012)

    Google Scholar 

  16. Zhou, G., Hansen, J.H.L., Kaiser, J.F.: Nonlinear feature based classification of speech under stress. IEEE Trans. Speech Audio Process. 9(3), 201–216 (2001)

    Article  Google Scholar 

  17. Shinohara, S., et al.: A mental health evaluation method using prosody information of voice. (in preparation)

    Google Scholar 

  18. Tokuno, S., et. al.: Usage of emotion recognition in stress resilience program. In: Proceedings of 40th ICMM World Congress on Military Medicine (2013)

    Google Scholar 

  19. Merry, S.N., Stasiak, K., Shepherd, M.: The effectiveness of SPARX, a computerised self help intervention for adolescents seeking help for depression: randomised controlled non-inferiority trial. BMJ 344, 1–16 (2012)

    Article  Google Scholar 

  20. Fleming, T., Dixson, R.: A pragmatic randomized controlled trial of computerized CBT (SPARX) for symptoms of depression among adolescents excluded from mainstream education. Behav. Cogn. Psychoth. 40, 529–541 (2012)

    Article  Google Scholar 

  21. Tokuno, S., Mitsuyoshi, S., Suzuki, G., Tsumatori, G.: Stress evaluation using voice emotion recognition technology: A novel stress evaluation technology for disaster responders. Proc. XVI World Congress of Psychiatry 2, 301 (2014)

    Google Scholar 

Download references

Acknowledgements

We would like to express our sincere appreciation to Colonel Sota Shimozono of JGSDF Medical School and his staff members for their cooperation in sharing S-Gim and collecting data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shuji Shinohara .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Shinohara, S., Mitsuyoshi, S., Nakamura, M., Omiya, Y., Tsumatori, G., Tokuno, S. (2016). Validity of a Voice-Based Evaluation Method for Effectiveness of Behavioural Therapy. In: Serino, S., Matic, A., Giakoumis, D., Lopez, G., Cipresso, P. (eds) Pervasive Computing Paradigms for Mental Health. MindCare 2015. Communications in Computer and Information Science, vol 604. Springer, Cham. https://doi.org/10.1007/978-3-319-32270-4_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-32270-4_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32269-8

  • Online ISBN: 978-3-319-32270-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics