Top

Published in:

Open Access 01-12-2016

Quality-of-life assessment in dementia: the use of DEMQOL and DEMQOL-Proxy total scores

Authors: Kia-Chong Chua, Anna Brown, Ryan Little, David Matthews, Liam Morton, Vanessa Loftus, Caroline Watchurst, Rhian Tait, Renee Romeo, Sube Banerjee

Published in: Quality of Life Research | Issue 12/2016

Purpose

There is a need to determine whether health-related quality-of-life (HRQL) assessments in dementia capture what is important, to form a coherent basis for guiding research and clinical and policy decisions. This study investigated structural validity of HRQL assessments made using the DEMQOL system, with particular interest in studying domains that might be central to HRQL, and the external validity of these HRQL measurements.

Methods

HRQL of people with dementia was evaluated by 868 self-reports (DEMQOL) and 909 proxy reports (DEMQOL-Proxy) at a community memory service. Exploratory and confirmatory factor analyses (EFA and CFA) were conducted using bifactor models to investigate domains that might be central to general HRQL. Reliability of the general and specific factors measured by the bifactor models was examined using omega (ω) and omega hierarchical (ω _h) coefficients. Multiple-indicators multiple-causes models were used to explore the external validity of these HRQL measurements in terms of their associations with other clinical assessments.

Results

Bifactor models showed adequate goodness of fit, supporting HRQL in dementia as a general construct that underlies a diverse range of health indicators. At the same time, additional factors were necessary to explain residual covariation of items within specific health domains identified from the literature. Based on these models, DEMQOL and DEMQOL-Proxy overall total scores showed excellent reliability (ω _h > 0.8). After accounting for common variance due to a general factor, subscale scores were less reliable (ω _h < 0.7) for informing on individual differences in specific HRQL domains. Depression was more strongly associated with general HRQL based on DEMQOL than on DEMQOL-Proxy (−0.55 vs −0.22). Cognitive impairment had no reliable association with general HRQL based on DEMQOL or DEMQOL-Proxy.

Conclusions

The tenability of a bifactor model of HRQL in dementia suggests that it is possible to retain theoretical focus on the assessment of a general phenomenon, while exploring variation in specific HRQL domains for insights on what may lie at the ‘heart’ of HRQL for people with dementia. These data suggest that DEMQOL and DEMQOL-Proxy total scores are likely to be accurate measures of individual differences in HRQL, but that subscale scores should not be used. No specific domain was solely responsible for general HRQL at dementia diagnosis. Better HRQL was moderately associated with less depressive symptoms, but this was less apparent based on informant reports. HRQL was not associated with severity of cognitive impairment.

Available only for authorised users

Clark, P. G. (1995). Quality of life, values, and teamwork in geriatric care: Do we communicate what we mean? Gerontologist, 35(3), 402–411.CrossRefPubMed

Banerjee, S. (2007). Commentary on “Health economics and the value of therapy in Alzheimer’s disease.” Quality of life in dementia: Development and use of a disease-specific measure of health-related quality of life in dementia. Alzheimers Dementia, 3(3), 166–171.CrossRef

Rabins, P. V., & Black, B. S. (2007). Measuring quality of life in dementia: Purposes, goals, challenges and progress. International Psychogeriatrics, 19(3), 401–407.CrossRefPubMed

Banerjee, S., Smith, S. C., Lamping, D. L., Harwood, R. H., Foley, B., Smith, P., et al. (2006). Quality of life in dementia: More than just cognition. An analysis of associations with quality of life in dementia. Journal of Neurology, Neurosurgery and Psychiatry, 77(2), 146–148.CrossRefPubMedPubMedCentral

Perales, J., Cosco, T. D., Stephan, B. C., Haro, J. M., & Brayne, C. (2013). Health-related quality-of-life instruments for Alzheimer’s disease and mixed dementia. International Psychogeriatrics, 25(5), 691–706.CrossRefPubMed

Halvorsrud, L., & Kalfoss, M. (2007). The conceptualization and measurement of quality of life in older adults: A review of empirical studies published during 1994–2006. European Journal of Ageing, 4(4), 229–246.CrossRef

Bakas, T., McLennon, S. M., Carpenter, J. S., Buelow, J. M., Otte, J. L., Hanna, K. M., et al. (2012). Systematic review of health-related quality of life models. Health and Quality of Life Outcomes, 10(1), 134.CrossRefPubMedPubMedCentral

Smith, S. C., Lamping, D. L., Banerjee, S., Harwood, R. H., Foley, B., Smith, P., et al. (2007). Development of a new measure of health-related quality of life for people with dementia: DEMQOL. Psychological Medicine, 37(5), 737–746.CrossRefPubMed

Mulhern, B., Rowen, D., Brazier, J., Smith, S., Romeo, R., Tait, R., Watchurst, C., Chua, K. C., Loftus, V., Young, T., Lamping, D., Knapp, M., Howard, R., & Banerjee, S. (2013). Development of DEMQOL-U and DEMQOL-PROXY-U: Generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation. Health Technology Assessment, 17(5), v–xv, 1–140.

10.

Reise, S. P., Waller, N. G., & Comrey, A. L. (2000). Factor analysis and scale revision. Psychological Assessment, 12(3), 287–297.CrossRefPubMed

11.

Reise, S. P. (2012). Invited paper: The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47(5), 667–696.CrossRefPubMedPubMedCentral

12.

Reise, S. P., Bonifay, W. E., & Haviland, M. G. (2013). Scoring and modeling psychological measures in the presence of multidimensionality. Journal of Personality Assessment, 95(2), 129–140.CrossRefPubMed

13.

Reise, S. P., Moore, T. M., & Haviland, M. G. (2010). Bifactor models and rotations: Exploring the extent to which multidimensional data yield univocal scale scores. Journal of Personality Assessment, 92(6), 544–559.CrossRefPubMedPubMedCentral

14.

Chen, F. F., West, S. G., & Sousa, K. H. (2006). A comparison of bifactor and second-order models of quality of life. Multivariate Behavioral Research, 41(2), 189–225.CrossRefPubMed

15.

Mokkink, L. B., Terwee, C. B., Knol, D. L., Stratford, P. W., Alonso, J., Patrick, D. L., et al. (2010). The COSMIN checklist for evaluating the methodological quality of studies on measurement properties: a clarification of its content. BMC Medical Research Methodology, 10, 22.CrossRefPubMedPubMedCentral

16.

Mokkink, L. B., Terwee, C. B., Patrick, D. L., Alonso, J., Stratford, P. W., Knol, D. L., et al. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Quality of Life Research, 19(4), 539–549.CrossRefPubMedPubMedCentral

17.

Smith, S. C., Lamping, D. L., Banerjee, S., Harwood, R., Foley, B., Smith, P., Cook, J. C., Murray, J., Prince, M., Levin, E., Mann, A., & Knapp, M. (2005). Measurement of health-related quality of life for people with dementia: Development of a new instrument (DEMQOL) and an evaluation of current methodology. Health Technology Assessment, 9(10), 1–93, iii–iv.

18.

Brunner, M., Nagy, G., & Wilhelm, O. (2012). A tutorial on hierarchically structured constructs. Journal of Personality, 80(4), 796–846.CrossRefPubMed

19.

Banerjee, S., & Wittenberg, R. (2009). Clinical and cost effectiveness of services for early diagnosis and intervention in dementia. International Journal of Geriatric Psychiatry, 24(7), 748–754.CrossRefPubMed

20.

Willis, R., Chan, J., Murray, J., Matthews, D., & Banerjee, S. (2009). People with dementia and their family carers’ satisfaction with a memory service: A qualitative evaluation generating quality Indicators for dementia care. Journal of Mental Health, 18(1), 26–37.CrossRef

21.

Banerjee, S., Willis, R., Matthews, D., Contell, F., Chan, J., & Murray, J. (2007). Improving the quality of care for mild to moderate dementia: An evaluation of the Croydon Memory Service Model. International Journal of Geriatric Psychiatry, 22(8), 782–788.CrossRefPubMed

22.

Folstein, M. F., Folstein, S. E., & 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(3), 189–198.CrossRefPubMed

23.

Rubright, J. D., Nandakumar, R., & Karlawish, J. (2015). Identifying an appropriate measurement modeling approach for the mini-mental state examination. Psychological Assessment, 28(2), 125–133.CrossRefPubMed

24.

Blake, H., McKinney, M., Treece, K., Lee, E., & Lincoln, N. B. (2002). An evaluation of screening measures for cognitive impairment after stroke. Age and Ageing, 31(6), 451–456.CrossRefPubMed

25.

Brayne, C. (1998). The mini-mental state examination, will we be using it in 2001? International Journal of Geriatric Psychiatry, 13(5), 285–290.CrossRefPubMed

26.

Tombaugh, T. N., & McIntyre, N. J. (1992). The mini-mental state examination: A comprehensive review. Journal of the American Geriatrics Society, 40(9), 922–935.CrossRefPubMed

27.

Yesavage, J., & Sheikh, J. (1986). Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version. Clinical Gerontologist, 5(1), 165–173.CrossRef

28.

Aikman, G. G., & Oehlert, M. E. (2001). Geriatric Depression Scale. Clinical Gerontologist, 22(3–4), 63–70.CrossRef

29.

Ferraro, F. R., & Chelminski, I. (1996). Preliminary normative data on the Geriatric Depression Scale-Short Form (GDS-SF) in a young adult sample. Journal of Clinical Psychology, 52(4), 443–447.CrossRefPubMed

30.

Herrmann, N., Mittmann, N., Silver, I. L., Shulman, K. I., Busto, U. A., Shear, N. H., & Naranjo, C. A. (1996). A validation study of the geriatric depression scale short form. International Journal of Geriatric Psychiatry, 11(5), 457–460.CrossRef

31.

Almeida, O. P., & Almeida, S. A. (1999). Short versions of the geriatric depression scale: A study of their validity for the diagnosis of a major depressive episode according to ICD-10 and DSM-IV. International Journal of Geriatric Psychiatry, 14(10), 858–865.CrossRefPubMed

32.

Cummings, J. L., Mega, M., Gray, K., Rosenberg-Thompson, S., Carusi, D. A., & Gornbein, J. (1994). The Neuropsychiatric Inventory: Comprehensive assessment of psychopathology in dementia. Neurology, 44(12), 2308–2314.CrossRefPubMed

33.

Cummings, J. L., Ihl, R., Herrschaft, H., Hoerr, R., & Tribanek, M. (2013). Sensitivity to change of composite and frequency scores of the Neuropsychiatric Inventory in mild to moderate dementia. International Psychogeriatrics, 25(3), 431–438.CrossRefPubMed

34.

Cummings, J. L., Tribanek, M., & Hoerr, R. (2014). Sensitivity to change of composite and frequency scores of the neuropsychiatric inventory in mild cognitive impairment. International Psychogeriatrics, 26(11), 1871–1874.CrossRefPubMed

35.

Bucks, R. S., Ashworth, D. L., Wilcock, G. K., & Siegfried, K. (1996). Assessment of activities of daily living in dementia: Development of the Bristol Activities of Daily Living Scale. Age and Ageing, 25(2), 113–120.CrossRefPubMed

36.

Sikkes, S. A., de Lange-de Klerk, E. S., Pijnenburg, Y. A., Scheltens, P., & Uitdehaag, B. M. (2009). A systematic review of Instrumental Activities of Daily Living Scales in dementia: Room for improvement. Journal of Neurology, Neurosurgery and Psychiatry, 80(1), 7–12.CrossRefPubMed

37.

Byrne, L. M., Wilson, P. M., Bucks, R. S., Hughes, A. O., & Wilcock, G. K. (2000). The sensitivity to change over time of the Bristol Activities of Daily Living Scale in Alzheimer’s disease. International Journal of Geriatric Psychiatry, 15(7), 656–661.CrossRefPubMed

38.

Brown, A., & Croudace, T. (2015). Scoring and estimating score precision using multidimensional IRT. In S. P. Reise & D. A. Revicki (Eds.), Handbook of item response theory modeling: Applications to typical performance assessment (a volume in the multivariate applications series). New York: Routledge/Taylor & Francis Group.

39.

Rindskopf, D., & Rose, T. (1988). Some theory and applications of confirmatory second-order factor analysis. Multivariate Behavioral Research, 23(1), 51–67.CrossRefPubMed

40.

Murray, A. L., & Johnson, W. (2013). The limitations of model fit in comparing the bi-factor versus higher-order models of human cognitive ability structure. Intelligence, 41(5), 407–422.CrossRef

41.

Zinbarg, R. E., Yovel, I., Revelle, W., & McDonald, R. P. (2006). Estimating generalizability to a latent variable common to all of a scale’s indicators: A comparison of estimators for omega(h). Applied Psychological Measurement, 30(2), 121–144.CrossRef

42.

Zinbarg, R. E., Revelle, W., Yovel, I., & Li, W. (2005). Cronbach’s α, Revelle’s β, and Mcdonald’s ωH: Their relations with each other and two alternative conceptualizations of reliability. Psychometrika, 70(1), 123–133.CrossRef

43.

Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98–104.CrossRef

44.

Muthén, L., & Muthén, B. (1998–2012). Mplus user’s guide. In L. Muthén & B. Muthén (Eds.) (7th ed.). Los Angeles, CA. http://www.statmodel.com/ugexcerpts.shtml.

45.

Rhemtulla, M., Brosseau-Liard, P. E., & Savalei, V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychological Methods, 17(3), 354–373.CrossRefPubMed

46.

Holgado-Tello, F. P., Chacón-Moscoso, S., Barbero-García, I., & Vila-Abad, E. (2008). Polychoric versus Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables. Quality & Quantity, 44(1), 153–166.CrossRef

47.

Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491.CrossRefPubMedPubMedCentral

48.

Muthén, B., du Toit, S., & Spisic, D. (1997). Robust inference using weighted least squares and quadratic estimating equations in latent variable modeling with categorical and continuous outcomes. http://www.statmodel.com/wlscv.shtml.

49.

Savalei, V., & Rhemtulla, M. (2013). The performance of robust test statistics with categorical data. British Journal of Mathematical and Statistical Psychology, 66(2), 201–223.CrossRefPubMed

50.

Kline, R. B. (2010). Hypothesis testing. In T. Little (Ed.), Principles and practice of structural equation modeling (3rd ed., pp. 189–229). New York: Guilford Press.

51.

Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25(2), 173–180.CrossRefPubMed

52.

Browne, M., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. Bollen & J. Long (Eds.), Testing structural equation models (pp. 136–162). Beverly Hills, CA: Sage.

53.

Reininghaus, U., McCabe, R., Burns, T., Croudace, T., & Priebe, S. (2011). Measuring patients’ views: A bifactor model of distinct patient-reported outcomes in psychosis. Psychological Medicine, 41(2), 277–289.CrossRefPubMed

54.

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.CrossRefPubMed

55.

Muthén, B. O. (1989). Latent variable modeling in heterogeneous populations. Psychometrika, 54(4), 557–585.CrossRef

56.

Reise, S. P., & Haviland, M. G. (2005). Item response theory and the measurement of clinical change. Journal of Personality Assessment, 84(3), 228–238.CrossRefPubMed

57.

Lucas-Carrasco, R., Lamping, D. L., Banerjee, S., Rejas, J., Smith, S. C., & Gomez-Benito, J. (2010). Validation of the Spanish version of the DEMQOL system. International Psychogeriatrics, 22(4), 589–597.CrossRefPubMed

58.

Reise, S. P., Morizot, J., & Hays, R. D. (2007). The role of the bifactor model in resolving dimensionality issues in health outcomes measures. Quality of Life Research, 16(Suppl 1), 19–31.CrossRefPubMed

59.

Kifley, A., Heller, G. Z., Beath, K. J., Bulger, D., Ma, J., & Gebski, V. (2012). Multilevel latent variable models for global health-related quality of life assessment. Statistics in Medicine, 31(11–12), 1249–1264.CrossRefPubMed

60.

Ebesutani, C., Reise, S. P., Chorpita, B. F., Ale, C., Regan, J., Young, J., Higa-McMillan, C., & Weisz, J. R. (2012). The Revised Child Anxiety and Depression Scale-Short Version: Scale reduction via exploratory bifactor modeling of the broad anxiety factor. Psychological Assessment, 24(4), 833–845.CrossRefPubMed

61.

Marsh, H. W. (1986). Negative item bias in ratings scales for preadolescent children—A cognitive developmental phenomenon. Developmental Psychology, 22(1), 37–49.CrossRef

62.

Binder, M., & Coad, A. (2013). “I’m afraid I have bad news for you…” Estimating the impact of different health impairments on subjective well-being. Social Science and Medicine, 87, 155–167.CrossRefPubMed

63.

Ebesutani, C., Drescher, C. F., Reise, S. P., Heiden, L., Hight, T. L., Damon, J. D., & Young, J. (2012). The loneliness questionnaire-short version: An evaluation of reverse-worded and non-reverse-worded items via item response theory. Journal of Personality Assessment, 94(4), 427–437.CrossRefPubMed

64.

Ebesutani, C., Drescher, C. F., Reise, S. P., Heiden, L., Hight, T. L., Damon, J. D., & Young, J. (2012). The importance of modeling method effects: Resolving the (uni)dimensionality of the loneliness questionnaire. Journal of Personality Assessment, 94(2), 186–195.CrossRefPubMed

65.

Ray, J. V., Frick, P. J., Thornton, L. C., Steinberg, L., & Cauffman, E. (2016). Positive and negative item wording and its influence on the assessment of callous-unemotional traits. Psychological Assessment, 28(4), 394–404.CrossRefPubMed

66.

Tomás, J. M., Oliver, A., Galiana, L., Sancho, P., & Lila, M. (2013). Explaining method effects associated with negatively worded items in trait and state global and domain-specific self-esteem scales. Structural Equation Modeling: A Multidisciplinary Journal, 20(2), 299–313.CrossRef

67.

Lindwall, M., Barkoukis, V., Grano, C., Lucidi, F., Raudsepp, L., Liukkonen, J., & Thogersen-Ntoumani, C. (2012). Method effects: The problem with negatively versus positively keyed items. Journal of Personality Assessment, 94(2), 196–204.CrossRefPubMed

68.

Horan, P. M., DiStefano, C., & Motl, R. W. (2003). Wording effects in self-esteem scales: Methodological artifact or response style? Structural Equation Modeling, 10(3), 435–455.CrossRef

69.

Marsh, H. W. (1996). Positive and negative global self-esteem: A substantively meaningful distinction or artifactors? Journal of Personality and Social Psychology, 70(4), 810–819.CrossRefPubMed

70.

Black, B. S., Johnston, D., Morrison, A., Rabins, P. V., Lyketsos, C. G., & Samus, Q. M. (2012). Quality of life of community-residing persons with dementia based on self-rated and caregiver-rated measures. Quality of Life Research, 21(8), 1379–1389.CrossRefPubMed

71.

Moyle, W., Murfield, J. E., Griffiths, S. G., & Venturato, L. (2012). Assessing quality of life of older people with dementia: A comparison of quantitative self-report and proxy accounts. Journal of Advanced Nursing, 68(10), 2237–2246.CrossRefPubMed

72.

Novella, J. L., Jochum, C., Jolly, D., Morrone, I., Ankri, J., Bureau, F., & Blanchard, F. (2001). Agreement between patients’ and proxies’ reports of quality of life in Alzheimer’s disease. Quality of Life Research, 10(5), 443–452.CrossRefPubMed

73.

Vogel, A., Mortensen, E. L., Hasselbalch, S. G., Andersen, B. B., & Waldemar, G. (2006). Patient versus informant reported quality of life in the earliest phases of Alzheimer’s disease. International Journal of Geriatric Psychiatry, 21(12), 1132–1138.CrossRefPubMed

74.

Lawton, M. P. (1994). Quality of life in Alzheimer disease. Alzheimer Disease and Associated Disorders, 8(Suppl 3), 138–150.CrossRefPubMed

75.

Frick, U., Irving, H., & Rehm, J. (2012). Social relationships as a major determinant in the valuation of health states. Quality of Life Research, 21(2), 209–213.CrossRefPubMed

76.

Hughes, T. F., Flatt, J. D., Fu, B., Chang, C. C., & Ganguli, M. (2013). Engagement in social activities and progression from mild to severe cognitive impairment: The MYHAT study. International Psychogeriatrics, 25(4), 587–595.CrossRefPubMed

77.

Lou, V. W., Chi, I., Kwan, C. W., & Leung, A. Y. (2013). Trajectories of social engagement and depressive symptoms among long-term care facility residents in Hong Kong. Age and Ageing, 42(2), 215–222.CrossRefPubMed

78.

MacRae, H. (2011). Self and other: The importance of social interaction and social relationships in shaping the experience of early-stage Alzheimer’s disease. Journal of Aging Studies, 25(4), 445–456.CrossRef

79.

Coyle, C. E., & Dugan, E. (2012). Social isolation, loneliness and health among older adults. Journal of Aging Health, 24(8), 1346–1363.CrossRefPubMed

80.

Huxhold, O., Fiori, K. L., & Windsor, T. D. (2013). The dynamic interplay of social network characteristics, subjective well-being, and health: The costs and benefits of socio-emotional selectivity. Psychology and Aging, 28(1), 3–16.CrossRefPubMed

81.

Ichida, Y., Hirai, H., Kondo, K., Kawachi, I., Takeda, T., & Endo, H. (2013). Does social participation improve self-rated health in the older population? A quasi-experimental intervention study. Social Science and Medicine, 94, 83–90.CrossRefPubMed

82.

Rook, K. S., Luong, G., Sorkin, D. H., Newsom, J. T., & Krause, N. (2012). Ambivalent versus problematic social ties: Implications for psychological health, functional health, and interpersonal coping. Psychology and Aging, 27(4), 912–923.CrossRefPubMed

83.

Ettema, T. P., Droes, R. M., de Lange, J., Mellenbergh, G. J., & Ribbe, M. W. (2005). A review of quality of life instruments used in dementia. Quality of Life Research, 14(3), 675–686.CrossRefPubMed

84.

Holmbeck, G., Devine, K., & Bruno, E. (2010). Developmental issues and considerations in research and practice. In J. Weisz & A. Kazdin (Eds.), Evidence-based psychotherapies for children and adolescents (2nd ed., pp. 28–39). New York, NY: Guilford Press.

85.

Ebesutani, C., Smith, A., Bernstein, A., Chorpita, B. F., Higa-McMillan, C., & Nakamura, B. (2011). A bifactor model of negative affectivity: Fear and distress components among younger and older youth. Psychological Assessment, 23(3), 679–691.CrossRefPubMed

86.

Banerjee, S., Samsi, K., Petrie, C. D., Alvir, J., Treglia, M., Schwam, E. M., & del Valle, M. (2009). What do we know about quality of life in dementia? A review of the emerging evidence on the predictive and explanatory value of disease specific measures of health related quality of life in people with dementia. International Journal of Geriatric Psychiatry, 24(1), 15–24.CrossRefPubMed

87.

Ozer, D., & Benet-Martinez, V. (2006). Personality and the prediction of consequential outcomes. In S. Fiske, A. Kazdin, & D. Schacter (Eds.), Annual review of psychology (Vol. 57, pp. 401–421). Palo Alto, CA: Annual Reviews.

88.

Chen, F. F., Hayes, A., Carver, C. S., Laurenceau, J. P., & Zhang, Z. (2012). Modeling general and specific variance in multifaceted constructs: A comparison of the bifactor model to other approaches. Journal of Personality, 80(1), 219–251.CrossRefPubMed

89.

Yang, Y., Sun, Y., Zhang, Y., Jiang, Y., Tang, J., Zhu, X., & Miao, D. (2013). Bifactor item response theory model of acute stress response. PLoS ONE, 8(6), e65291.CrossRefPubMedPubMedCentral

90.

Horn, J. L., & McArdle, J. J. (1992). A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research, 18(3–4), 117–144.CrossRefPubMed

91.

Finch, H. (2005). The MIMIC model as a method for detecting DIF comparison with Mantel–Haenszel, SIBTEST, and the IRT likelihood ratio. Applied Psychological Measurement, 29(4), 278–295.CrossRef

92.

Willse, J. T., & Goodman, J. T. (2008). Comparison of multiple-indicators, multiple-causes- and item response theory-based analyses of subgroup differences. Educational and Psychological Measurement, 68(4), 587–602.CrossRef

93.

Woods, C. M. (2009). Evaluation of MIMIC-model methods for DIF testing with comparison to two-group analysis. Multivariate Behavioral Research, 44(1), 1–27.CrossRefPubMed

94.

Banerjee, S., Willis, R., Graham, N., & Gurland, B. J. (2010). The Stroud/ADI dementia quality framework: A cross-national population-level framework for assessing the quality of life impacts of services and policies for people with dementia and their family carers. International Journal of Geriatric Psychiatry, 25(3), 249–257.CrossRefPubMed

Title: Quality-of-life assessment in dementia: the use of DEMQOL and DEMQOL-Proxy total scores
Authors: Kia-Chong Chua
Anna Brown
Ryan Little
David Matthews
Liam Morton
Vanessa Loftus
Caroline Watchurst
Rhian Tait
Renee Romeo
Sube Banerjee
Publication date: 01-12-2016
Publisher: Springer International Publishing
Published in: Quality of Life Research / Issue 12/2016
Print ISSN: 0962-9343
Electronic ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-016-1343-1

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Quality-of-life assessment in dementia: the use of DEMQOL and DEMQOL-Proxy total scores

Purpose

Methods

Results

Conclusions

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Purpose

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 12/2016

Health-related quality of life in haemodialysis patients suffering from chronic itch: results from GEHIS (German Epidemiology Haemodialysis Itch Study)

EQ-5D-derived health utilities and minimally important differences for chronic health conditions: 2011 Commonwealth Fund Survey of Sicker Adults in Canada

Psychometric assessment of the IBS-D Daily Symptom Diary and Symptom Event Log

The role of mindfulness in distress and quality of life for men with advanced prostate cancer

Measurement of utility in asthma: evidence indicating that generic instruments may miss clinically important changes

Reporting and dealing with missing quality of life data in RCTs: has the picture changed in the last decade?