Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-22T18:58:43.645Z Has data issue: false hasContentIssue false
  • English
  • Français

Visual analogue mood scale scores in healthy young versus older adults

Published online by Cambridge University Press:  11 July 2018

Liana Machado Open the ORCID record for Liana Machado [Opens in a new window] ,
Laura M. Thompson  and
Christopher H. R. Brett
Liana Machado*
Affiliation:
Department of Psychology, Brain Health Research Centre, University of Otago, Dunedin, New Zealand Brain Research New Zealand, Auckland, New Zealand
Laura M. Thompson
Affiliation:
Department of Psychology, Brain Health Research Centre, University of Otago, Dunedin, New Zealand Brain Research New Zealand, Auckland, New Zealand
Christopher H. R. Brett
Affiliation:
Department of Psychology, Brain Health Research Centre, University of Otago, Dunedin, New Zealand Brain Research New Zealand, Auckland, New Zealand
*
Correspondence should be addressed to: Dr. Liana Machado, Department of Psychology, Brain Health Research Centre, University of Otago, William James Building, 275 Leith Walk, Dunedin 9054, New Zealand. Phone: 0064 3 479 7622. Email: [email protected].
Get access

Abstract

Background:

The current research sought to characterize current mood state profiles in healthy young versus older adults using 100-point visual analogue mood scales (VAMS), provide within-sample and new sample replication of age-group differences, assess sex differences, and compare with commonly used standardized symptom measures.

Methods:

In two studies, six word-only VAMS (happy, sad, calm, tense, energetic, and sleepy) were administered in a laboratory setting. In Study 1, 22 young and 29 older males completed the VAMS six times (twice per day at weekly intervals). In Study 2, 60 young (30 males) and 60 older (30 males) adults completed on one occasion the VAMS, Beck Depression Inventory-II, State-Trait Anxiety Inventory, and Pittsburgh Sleep Quality Index.

Results:

VAMS scores showed that older adults had a tendency to indicate feeling happier, less sad, calmer, less tense, more energetic, and less sleepy than young adults. This pattern occurred across assessment points and irrespective of sex, except for the tense VAMS, which showed higher scores in females than males in young but not older adults. The standardized measures showed significant age-group differences for Trait Anxiety only (lower in older than young adults).

Conclusions:

These findings establish current mood state differences in young versus older adults. The absence of age-group differences in past studies may relate to the limited precision of the scales (only 7 points, in contrast to the 100-point scales used here).

Keywords

agingmood statecurrent mood stateaffective stateaffective symptoms
Type
Original Research Article
Information
International Psychogeriatrics , Volume 31 , Issue 3: Issue Theme: Caregiving for People with Dementia , March 2019 , pp. 417 - 424
Copyright
Copyright © International Psychogeriatric Association 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aitken, R. C. B. (1969). Measurement of feelings using visual analogue scales. Proceedings of the Royal Society of Medicine-London, 62, 989–993.Google Scholar
Barrows, P. D. and Thomas, S. A. (2017). Assessment of mood in aphasia following stroke: validation of the dynamic visual analogue mood scales (D-VAMS). Clinical Rehabilitation, 32, 94–102. DOI: 10.1177/0269215517714590.Google Scholar
Beck, A., Steer, R. and Brown, G. (1996). Manual for Beck Depression Inventory II (BDI-II). San Antonio, TX: Psychology Corporation.Google Scholar
Bliwise, D. L. (1993). Sleep in normal aging and dementia. Sleep, 16, 40–81.Google Scholar
Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433–436.Google Scholar
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R. and Kupfer, D. J. (1989). The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Research, 28, 193–213.Google Scholar
Buysse, D. J., Reynolds, C. F. 3rd, Monk, T. H., Hoch, C. C., Yeager, A. L. and Kupfer, D. J. (1991). Quantification of subjective sleep quality in healthy elderly men and women using the Pittsburgh sleep quality index (PSQI). Sleep, 14, 331–338.Google Scholar
Carstensen, L. L. et al. (2011). Emotional experience improves with age: evidence based on over 10 years of experience sampling. Psychology and Aging, 26, 21–33.Google Scholar
Carstensen, L. L., Pasupathi, M., Mayr, U. and Nesselroade, J. R. (2000). Emotional experience in everyday life across the adult life span. Journal of Personality and Social Psychology, 79, 644–655.Google Scholar
Chang, R. and Little, T. D. (2018). Innovations for evaluation research: multiform protocols, visual analog scaling, and the retrospective pretest-posttest design. Evaluation and the Health Professions, 41, 246–269. DOI: 10.1177/163278718759396.Google Scholar
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.Google Scholar
Forsyth, B. et al. (2016). Effects of low dose ibogaine on subjective mood state and psychological performance. Journal of Ethnopharmacology, 189, 10–13.Google Scholar
Gorrall, B. K., Curtis, J. D., Little, T. D. and Panko, P. (2016). Innovations in measurement: visual analog scales and retrospective pretest self-report designs. Actualidades en Psicología, 30, 2–7.Google Scholar
Groeger, J. A., Stanley, N., Deacon, S. and Dijk, D. J. (2014). Dissociating effects of global SWS disruption and healthy aging on waking performance and daytime sleepiness. Sleep, 37, 1127–1142.Google Scholar
Hayley, A. C., Williams, L. J., Kennedy, G. A., Berk, M., Brennan, S. L. and Pasco, J. A. (2014). Prevalence of excessive daytime sleepiness in a sample of the Australian adult population. Sleep Medicine, 15, 348–354.Google Scholar
Henderson, A. S., Jorm, A. F., Korten, A. E., Jacomb, P., Christensen, H. and Rodgers, B. (1998). Symptoms of depression and anxiety during adult life: evidence for a decline in prevalence with age. Psychological Medicine, 28, 1321–1328.Google Scholar
Jorm, A. F. (2000). Does old age reduce the risk of anxiety and depression? A review of epidemiological studies across the adult life span. Psychological Medicine, 30, 11–22.Google Scholar
Kontou, E., Thomas, S. A. and Lincoln, N. B. (2012). Psychometric properties of a revised version of the visual analog mood scales. Clinical Rehabilitation, 26, 1133–1140.Google Scholar
Leach, L. S., Christensen, H., Mackinnon, A. J., Windsor, T. D. and Butterworth, P. (2008). Gender differences in depression and anxiety across the adult lifespan: the role of psychosocial mediators. Social Psychiatry and Psychiatric Epidemiology, 43, 983–998.Google Scholar
Mellor, A., Waters, F., Olaithe, M., McGowan, H. and Bucks, R. S. (2014). Sleep and aging: examining the effect of psychological symptoms and risk of sleep-disordered breathing. Behavioral Sleep Medicine, 12, 222–234.Google Scholar
Nyenhuis, D. L., Stern, R. A., Yamamoto, C., Luchetta, T. and Arruda, J. E. (1997). Standardization and validation of the visual analog mood scales. The Clinical Neuropsychologist, 11, 407–415.Google Scholar
Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spatial Vision, 10, 437–442.Google Scholar
Rausch, M. and Zehetleitner, M. (2014). A comparison between a visual analogue scale and a four point scale as measures of conscious experience of motion. Consciousness and Cognition, 28, 126–140.Google Scholar
Reynolds, C. F. 3rd et al. (1991). Daytime sleepiness in the healthy “old old”: a comparison with young adults. Journal of the American Geriatrics Society, 39, 957–962.Google Scholar
Rybarczyk, B., Lund, H. G., Garroway, A. M. and Mack, L. (2013). Cognitive behavioral therapy for insomnia in older adults: background, evidence, and overview of treatment protocol. Clinical Gerontologist, 36, 70–93.Google Scholar
Spielberger, C. D., Gorsuch, R. L., Jacobs, G. A., Lushene, R. and Vagg, P. R. (1983). State-Trait Anxiety Inventory For Adults. Mind Garden.Google Scholar
Stein, M. B., Belik, S. L., Jacobi, F. and Sareen, J. (2008). Impairment associated with sleep problems in the community: relationship to physical and mental health comorbidity. Psychosomatic Medicine, 70, 913–919.Google Scholar
Stern, R. A., Arruda, J. E., Hooper, C. R., Wolfner, G. D. and Morey, C. E. (1997). Visual analogue mood scales to measure internal mood state in neurologically impaired patients: description and initial validity evidence. Aphasiology, 11, 59–71.Google Scholar
Suri, G. and Gross, J. J. (2012). Emotion regulation and successful aging. Trends in Cognitive Sciences, 16, 409–410.Google Scholar
Sutcliffe, R., Rendell, P. G., Henry, J. D., Bailey, P. E. and Ruffman, T. (2017). Music to my ears: age-related decline in musical and facial emotion recognition. Psychology and Aging, 32, 698–709.Google Scholar
Temple, R. O., Stern, R. A., Latham, J., Ruffolo, J. S., Arruda, J. E. and Tremont, G. (2004). Assessment of mood state in dementia by use of the visual analog mood scales (VAMS). American Journal of Geriatric Psychiatry, 12, 527–530.Google Scholar
Theorell-Haglöw, J., Åkerstedt, T., Schwarz, J. and Lindberg, E. (2015). Predictors for development of excessive daytime sleepiness in women: a population-based 10-Year follow-up. Sleep, 38, 1995–2003.Google Scholar
Vitiello, M. V. (1997). Sleep disorders and aging: understanding the causes. Journals of Gerontology. Series A: Biological Sciences and Medical Sciences, 52, M189–M191.Google Scholar
Vitiello, M. V. (2006). Sleep in normal aging. Sleep Medicine Clinics, 1, 171–176.Google Scholar
Ward, A. M. et al. (2013). Daytime sleepiness is associated with decreased default mode network connectivity in both young and cognitively intact elderly subjects. Sleep, 36, 1609–1615.Google Scholar
White, N., Forsyth, B., Lee, A. and Machado, L. (2018). Repeated computerized cognitive testing: performance shifts and test-retest reliability in healthy young adults. Psychological Assessment, 30, 539–549.Google Scholar
Wilsmore, B. R., Grunstein, R. R., Fransen, M., Woodward, M., Norton, R. and Ameratunga, S. (2013). Sleep habits, insomnia, and daytime sleepiness in a large and healthy community-based sample of New Zealanders. Journal of Clinical Sleep Medicine, 9, 559–566.Google Scholar
Wong, W. S. and Fielding, R. (2011). Prevalence of insomnia among Chinese adults in Hong Kong: a population-based study. Journal of Sleep Research, 20, 117–126.Google Scholar
Zhao, M. F., Zimmer, H. D., Shen, X., Chen, W. and Fu, X. (2016). Exploring the cognitive processes causing the age-related categorization deficit in the recognition of facial expressions. Experimental Aging Research, 42, 348–364.Google Scholar