nach oben

Quality of Life Research

Erschienen in:

12.04.2016

The meaning of vaguely quantified frequency response options on a quality of life scale depends on respondents’ medical status and age

verfasst von: Stefan Schneider, Arthur A. Stone

Erschienen in: Quality of Life Research | Ausgabe 10/2016

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Purpose

Self-report items in quality of life (QoL) scales commonly use vague quantifiers like “sometimes” or “often” to measure the frequency of health-related experiences. This study examined whether the meaning of such vaguely quantified response options differs depending on people’s medical status and age, which may undermine the validity of QoL group comparisons.

Methods

Respondents (n = 600) rated the frequency of positive and negative QoL experiences using vague quantifiers (never, rarely, sometimes, often, always) and provided open-ended numeric frequency counts for the same items. Negative binomial regression analyses examined whether the numeric frequencies associated with each vague quantifier differed between medical status (no vs. one or more medical conditions) and age (18–40 vs. 60+ years) groups.

Results

Compared to respondents without a chronic condition, those with a medical condition assigned a higher numeric frequency to the same vague quantifiers for negative QoL experiences; this effect was not evident for positive QoL experiences. Older respondents’ numeric frequencies were more extreme (i.e., lower at the low end and somewhat higher at the high end of the response range) than those of younger respondents. After adjusting for these effects, differences in QoL became somewhat more pronounced between medical status groups, but not between age groups.

Conclusions

The results suggest that people with different medical backgrounds and age do not interpret vague frequency quantifiers on a QoL scale in the same way. Open-ended numeric frequency reports may be useful to detect and potentially correct for differences in the meaning of vague quantifiers.

Vorheriger Artikel Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated health, and subjective life expectancy in survey instruments

Nächster Artikel Comparability of the Patient-Reported Outcomes Measurement Information System Pediatric short form symptom measures across culture: examination between Chinese and American children with cancer

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

PROMIS wave 1 testing included 24 health conditions; the 16 most prevalent were used here.

The model could also have been specified using the vague quantifiers as categorical dependent variable and the numeric frequencies as continuous predictor variable. The selected model had the advantage that we could use the vague quantifier categories as dummy-coded predictors, thereby not imposing any assumptions about the functional form (linear, quadratic, etc.) of the relationship between numeric frequencies and vague quantifier categories.

Schwarz, N., & Oyserman, D. (2001). Asking questions about behavior: Cognition, communication, and questionnaire construction. American Journal of Evaluation, 22, 127–160.CrossRef

Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response. Cambridge: Cambridge University Press.CrossRef

Volkman, J. (1951). Scales of judgment and their implications for social psychology. In J. H. Rohrer & M. Sherif (Eds.), Social psychology at the crossroads (pp. 273–294). New York: Harper.

Hakel, M. D. (1968). How often is often? American Psychologist, 23, 533–534.CrossRefPubMed

Ahmed, S., Mayo, N. E., Corbiere, M., Wood-Dauphinee, S., Hanley, J., & Cohen, R. (2005). Change in quality of life of people with stroke over time: True change or response shift? Quality of Life Research, 14, 611–627.CrossRefPubMed

Andrykowski, M. A., & Hunt, J. W. (1993). Positive psychosocial adjustment in potential bone marrow transplant recipients: Cancer as a psychosocial transition. Psycho-Oncology, 2, 261–276.CrossRef

Sieff, E. M., Dawes, R. M., & Loewenstein, G. (1999). Anticipated versus actual reaction to HIV test results. The American journal of psychology, 112, 297–311.CrossRefPubMed

Carstensen, L. L., Pasupathi, M., Mayr, U., & Nesselroade, J. R. (2000). Emotional experience in everyday life across the adult life span. Journal of Personality and Social Psychology, 79, 644–655.CrossRefPubMed

Stone, A. A., Schwartz, J. E., Broderick, J. E., & Deaton, A. (2010). A snapshot of the age distribution of psychological well-being in the United States. Proc Natl Acad Sci U S A, 107, 9985–9990.CrossRefPubMedPubMedCentral

10.

Lacey, H. P., Fagerlin, A., Loewenstein, G., Smith, D. M., Riis, J., & Ubel, P. A. (2008). Are they really that happy? Exploring scale recalibration in estimates of well-being. Health Psychology, 27, 669–675.CrossRefPubMedPubMedCentral

11.

Schwarz, N. (2006). Measurement: Aging and the psychology of self-report. In L. L. Carstensen & C. R. Hartel (Eds.), When I’m 64 (pp. 219–230). Washington, DC: The National Academies Press.

12.

Ubel, P. A., Loewenstein, G., & Jepson, C. (2003). Whose quality of life? A commentary exploring discrepancies between health state evaluations of patients and the general public. Quality of Life Research, 12, 599–607.CrossRefPubMed

13.

Schwartz, C. E., Andresen, E. M., Nosek, M. A., & Krahn, G. L. (2007). Response shift theory: Important implications for measuring quality of life in people with disability. Archives of Physical Medicine and Rehabilitation, 88, 529–536.CrossRefPubMed

14.

Sprangers, M. A., & Schwartz, C. E. (1999). Integrating response shift into health-related quality of life research: A theoretical model. Social Science and Medicine, 48, 1507–1515.CrossRefPubMed

15.

Kaplan, G., & Baron-Epel, O. (2003). What lies behind the subjective evaluation of health status? Social Science and Medicine, 56, 1669–1676.CrossRefPubMed

16.

Gibbons, F. X. (1999). Social comparison as a mediator of response shift. Social Science and Medicine, 48, 1517–1530.CrossRefPubMed

17.

Carver, C. S., & Scheier, M. F. (2000). Scaling back goals and recalibration of the affect system are processes in normal adaptive self-regulation: Understanding ‘response shift’ phenomena. Social Science and Medicine, 50, 1715–1722.CrossRefPubMed

18.

Daltroy, L. H., Larson, M. G., Eaton, H. M., Phillips, C. B., & Liang, M. H. (1999). Discrepancies between self-reported and observed physical function in the elderly: The influence of response shift and other factors. Social Science and Medicine, 48, 1549–1561.CrossRefPubMed

19.

Ubel, P. A., Jankovic, A., Smith, D., Langa, K. M., & Fagerlin, A. (2005). What is perfect health to an 85-year-old? Evidence for scale recalibration in subjective health ratings. Medical Care, 43, 1054–1057.CrossRefPubMed

20.

Biernat, M., Manis, M., & Nelson, T. E. (1991). Stereotypes and standards of judgment. Journal of Personality and Social Psychology, 60, 485–499.CrossRef

21.

Bartoshuk, L. M., Fast, K., & Snyder, D. J. (2005). Differences in our sensory worlds: Invalid comparisons with labeled scales. Current Directions in Psychological Science, 14, 122–125.CrossRef

22.

Knäuper, B., Schwarz, N., & Park, D. (2004). Frequency reports across age groups. Journal of Official Statistics, 20, 91–96.

23.

Wänke, M. (2002). Conversational norms and the interpretation of vague quantifiers. Applied Cognitive Psychology, 16, 301–307.CrossRef

24.

Wright, D. B., Gaskell, G. D., & O’Muircheartaigh, C. A. (1994). How much is ‘Quite a bit’? Mapping between numerical values and vague quantifiers. Applied Cognitive Psychology, 8, 479–496.CrossRef

25.

Schneider, S., & Stone, A. A. (2016). Ambulatory and diary methods can facilitate the measurement of patient-reported outcomes. Quality of Life Research, 25, 497–506.CrossRefPubMed

26.

Christodoulou, C., Junghaenel, D. U., DeWalt, D. A., Rothrock, N., & Stone, A. A. (2008). Cognitive interviewing in the evaluation of fatigue items: Results from the patient-reported outcomes measurement information system (PROMIS). Quality of Life Research, 17, 1239–1246.CrossRefPubMedPubMedCentral

27.

DeWalt, D. A., Rothrock, N., Yount, S., & Stone, A. A. (2007). Evaluation of item candidates: The PROMIS qualitative item review. Medical Care, 45, S12–S21.CrossRefPubMedPubMedCentral

28.

Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., et al. (2010). The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63, 1179–1194.CrossRefPubMedPubMedCentral

29.

Cook, K. F., Bamer, A. M., Amtmann, D., Molton, I. R., & Jensen, M. P. (2012). Six patient-reported outcome measurement information system short form measures have negligible age-or diagnosis-related differential item functioning in individuals with disabilities. Archives of Physical Medicine and Rehabilitation, 93, 1289–1291.CrossRefPubMed

30.

Gershon, R. C., Lai, J. S., Bode, R., Choi, S., Moy, C., Bleck, T., et al. (2012). Neuro-QOL: Quality of life item banks for adults with neurological disorders: Item development and calibrations based upon clinical and general population testing. Quality of Life Research, 21, 475–486.CrossRefPubMed

31.

Rothrock, N. E., Hays, R. D., Spritzer, K., Yount, S. E., Riley, W., & Cella, D. (2010). Relative to the general US population, chronic diseases are associated with poorer health-related quality of life as measured by the patient-reported outcomes measurement information system (PROMIS). Journal of Clinical Epidemiology, 63, 1195–1204.CrossRefPubMedPubMedCentral

32.

Gardner, W., Mulvey, E. P., & Shaw, E. C. (1995). Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models. Psychological Bulletin, 118, 392–404.CrossRefPubMed

33.

Fahrmeir, L., & Tutz, G. (2013). Multivariate statistical modelling based on generalized linear models. New York: Springer.

34.

Nagelkerke, N. J. (1991). A note on a general definition of the coefficient of determination. Biometrika, 78, 691–692.CrossRef

35.

Harder, V. S., Stuart, E. A., & Anthony, J. C. (2010). Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research. Psychological Methods, 15, 234–249.CrossRefPubMedPubMedCentral

36.

United States Census Bureau. (2014). Current population survey data on educational attainment. http://www.census.gov/hhes/socdemo/education/data/cps/index.html. Accessed February 22, 2016.

37.

Yost, K. J., Eton, D. T., Garcia, S. F., & Cella, D. (2011). Minimally important differences were estimated for six PROMIS-cancer scales in advanced-stage cancer patients. Journal of Clinical Epidemiology, 64, 507–516.CrossRefPubMedPubMedCentral

38.

Junghaenel, D. U., Christodoulou, C., Lai, J.-S., & Stone, A. A. (2011). Demographic correlates of fatigue in the US general population: Results from the patient-reported outcomes measurement information system (PROMIS) initiative. Journal of Psychosomatic Research, 71, 117–123.CrossRefPubMedPubMedCentral

39.

Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28, 193–213.CrossRefPubMed

40.

Schneider, S., & Stone, A. A. (2015). Mixed emotions across the adult life span in the United States. Psychology and Aging, 30, 369–382.CrossRefPubMedPubMedCentral

41.

Barlow, J., Turner, A., & Wright, C. (1998). Comparison of clinical and self-reported diagnoses for participants on a community-based arthritis self-management programme. Rheumatology, 37, 985–987.CrossRef

42.

El Fakiri, F., Bruijnzeels, M. A., & Hoes, A. W. (2007). No evidence for marked ethnic differences in accuracy of self-reported diabetes, hypertension, and hypercholesterolemia. Journal of Clinical Epidemiology, 60, 1271–1279.CrossRefPubMed

43.

Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N., & Stone, A. A. (2004). A survey method for characterizing daily life experience: The day reconstruction method. Science, 306, 1776–1780.CrossRefPubMed

44.

Belli, R. F. (1998). The structure of autobiographical memory and the event history calendar: Potential improvements in the quality of retrospective reports in surveys. Memory, 6, 383–406.CrossRefPubMed

45.

Schneider, S., & Stone, A. A. (2014). Distinguishing between frequency and intensity of health-related symptoms from diary assessments. Journal of Psychosomatic Research, 77, 205–212.CrossRefPubMedPubMedCentral

46.

Keding, A., Böhnke, J. R., Croudace, T. J., Richmond, S. J., & MacPherson, H. (2015). Validity of single item responses to short message service texts to monitor depression: An mHealth sub-study of the UK ACUDep trial. BMC Medical Research Methodology, 15, 56.CrossRefPubMedPubMedCentral

47.

Cameron, I. M., Scott, N. W., Adler, M., & Reid, I. C. (2014). A comparison of three methods of assessing differential item functioning (DIF) in the Hospital Anxiety Depression Scale: Ordinal logistic regression, Rasch analysis and the Mantel Chi square procedure. Quality of Life Research, 23, 2883–2888.CrossRefPubMed

48.

Crane, M., Rissel, C., Greaves, S., & Gebel, K. (2016). Correcting bias in self-rated quality of life: An application of anchoring vignettes and ordinal regression models to better understand QoL differences across commuting modes. Quality of Life Research, 25, 257–266.CrossRefPubMed

49.

Salomon, J. A., Tandon, A., & Murray, C. J. (2004). Comparability of self rated health: Cross sectional multi-country survey using anchoring vignettes. BMJ, 328, 258.CrossRefPubMedPubMedCentral

50.

Hsee, C. K., & Tang, J. N. (2007). Sun and water: On a modulus-based measurement of happiness. Emotion, 7, 213.CrossRefPubMed

51.

Lacey, H. P., Loewenstein, G., & Ubel, P. A. (2011). Compared to what? A joint evaluation method for assessing quality of life. Quality of Life Research, 20, 1169–1177.CrossRefPubMed

52.

Visser, M. R., Oort, F. J., & Sprangers, M. A. (2005). Methods to detect response shift in quality of life data: A convergent validity study. Quality of Life Research, 14, 629–639.CrossRefPubMed

Titel: The meaning of vaguely quantified frequency response options on a quality of life scale depends on respondents’ medical status and age
verfasst von: Stefan Schneider
Arthur A. Stone
Publikationsdatum: 12.04.2016
Verlag: Springer International Publishing
Erschienen in: Quality of Life Research / Ausgabe 10/2016
Print ISSN: 0962-9343
Elektronische ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-016-1293-7

Springer Professional

Abstract

Purpose

Methods

Results

Conclusions

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 10/2016

The Swedish SCOPA-SLEEP for assessment of sleep disorders in Parkinson’s disease and healthy controls

Assessing health-related quality of life in patients with breast cancer: a systematic and standardized comparison of available instruments using the EMPRO tool

Skin toxicity and quality of life during treatment with panitumumab for RAS wild-type metastatic colorectal carcinoma: results from three randomised clinical trials

The development of a new computer adaptive test to evaluate chorea in Huntington disease: HDQLIFE Chorea

Association of physical fitness with health-related quality of life in early postmenopause

The relative impact of chronic conditions and multimorbidity on health-related quality of life in Ontario long-stay home care clients

Premium Partner