The effect of an information and communication technology (ICT) on older adults' quality of life: study protocol for a randomized control trial

David H Gustafson Sr, Fiona McTavish, David H Gustafson Jr, Jane E Mahoney, Roberta A Johnson, John D Lee, Andrew Quanbeck, Amy K Atwood, Andrew Isham, Raj Veeramani, Lindy Clemson, Dhavan Shah, David H Gustafson Sr, Fiona McTavish, David H Gustafson Jr, Jane E Mahoney, Roberta A Johnson, John D Lee, Andrew Quanbeck, Amy K Atwood, Andrew Isham, Raj Veeramani, Lindy Clemson, Dhavan Shah

Abstract

Background: This study investigates the use of an information and communication technology (Elder Tree) designed for older adults and their informal caregivers to improve older adult quality of life and address challenges older adults face in maintaining their independence (for example, loneliness and isolation, falling, managing medications, driving and transportation).

Methods/design: This study, an unblinded randomized controlled trial, will evaluate the effectiveness and cost of Elder Tree. Older adults who are at risk for losing their independence - along with their informal caregivers, if they name them - are randomized to two groups. The intervention group has access to their usual sources of information and communication as well as to Elder Tree for 18 months while the control group uses only their usual sources of information and communication. The primary outcome of the study is older adult quality of life. Secondary outcomes are cost per Quality-Adjusted Life Year and the impact of the technology on independence, loneliness, falls, medication management, driving and transportation, and caregiver appraisal and mastery. We will also examine the mediating effect of self-determination theory. We will evaluate the effectiveness of Elder Tree by comparing intervention- and control-group participants at baseline and months 6, 12, and 18. We will use mixed-effect models to evaluate the primary and secondary outcomes, where pretest score functions as a covariate, treatment condition is a between-subjects factor, and the multivariate outcome reflects scores for a given assessment at the three time points. Separate analyses will be conducted for each outcome. Cost per Quality-Adjusted Life Year will be compared between the intervention and control groups. Additional analyses will examine the mediating effect of self-determination theory on each outcome.

Discussion: Elder Tree is a multifaceted intervention, making it a challenge to assess which services or combinations of services account for outcomes in which subsets of older adults. If Elder Tree can improve quality of life and reduce healthcare costs among older adults, it could suggest a promising way to ease the burden that advancing age can place on older adults, their families, and the healthcare system.

Trial registration: ClinicalTrials.gov NCT02128789 . Registered on 26 March 2014.

Figures

Figure 1
Figure 1
Participant flow.
Figure 2
Figure 2
Timeline.

References

    1. Farber N, Shinkle D, Lynott J, Fox-Grage W, Harrell R. Aging in place: a state survey of livability policies and practices. Washington, DC: AARP Public Policy Institute; 2011.
    1. Perissinotto CM, Stijacic Cenzer I, Covinsky KE. Loneliness in older persons: a predictor of functional decline and death. Arch Intern Med. 2012;172:1078–83. doi: 10.1001/archinternmed.2012.1993.
    1. Lord SR, Sherrington C, Menz HB, Close JCT. Falls in older people: risk factors and strategies for prevention. 2. New York: Cambridge University Press; 2007.
    1. Marek KD, Antle L. Medication management of the community-dwelling older adult. In: Hughes RG, editor. Patient safety and quality: an evidence-based handbook for nurses. Rockville, MD: Agency for Healthcare Research and Quality; 2008.
    1. Baldwin G. Director, Division of Unintentional Injury Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention. Aging, transportation and health. Testimony before the Special Committee on Aging, U.S. Senate. U.S. Department of Health and Human Services: Washington, DC; 2013.
    1. Davis JC, Robertson MC, Ashe MC, Liu-Ambrose T, Khan KM, Marra CA. International comparison of cost of falls in older adults living in the community: a systematic review. Osteoporos Int. 2010;21:1295–306. doi: 10.1007/s00198-009-1162-0.
    1. Ward BW, Schiller JS. Prevalence of multiple chronic conditions among US adults: estimates from the National Health Interview Survey, 2010. Prev Chronic Dis. 2013;10 doi: 10.5888/pcd10.120203.
    1. Vogeli C, Shields AE, Lee TA, Gibson TB, Marder WD, Weiss KB, et al. Multiple chronic conditions: prevalence, health consequences, and implications for quality, care management, and costs. J Gen Intern Med. 2007;22(Suppl 3):391–5. doi: 10.1007/s11606-007-0322-1.
    1. Institute of Medicine of the National Academies . Retooling for an aging America: building the health care workforce. Washington, D.C.: The National Academies Press; 2008.
    1. Vedel I, Akhlaghpour S, Vaghefi I, Bergman H, Lapointe L. Health information technologies in geriatrics and gerontology: a mixed systematic review. J Am Med Inform Assoc. 2013;20:1109–19. doi: 10.1136/amiajnl-2013-001705.
    1. Tse MM, Choi KC, Leung RS. E-health for older people: the use of technology in health promotion. Cyberpsychol Behav. 2008;11:475–9. doi: 10.1089/cpb.2007.0151.
    1. Sum S, Mathews RM, Hughes I, Campbell A. Internet use and loneliness in older adults. Cyberpsychol Behav. 2008;11:208–11. doi: 10.1089/cpb.2007.0010.
    1. Wahl HW, Iwarsson S, Oswald F. Aging well and the environment: toward an integrative model and research agenda for the future. Gerontologist. 2012;52:306–16. doi: 10.1093/geront/gnr154.
    1. Czaja SJ, Lee CC. The impact of aging on access to technology. Univ Access Inf Soc. 2007;5:341–9. doi: 10.1007/s10209-006-0060-x.
    1. Hou SI, Charlery SAR, Roberson K. Systematic literature review of Internet interventions across health behaviors. Health Psychol Behav Med. 2014;2:455–81. doi: 10.1080/21642850.2014.895368.
    1. Gustafson DH, McTavish FM, Chih MY, Atwood AK, Johnson RA, Boyle MG, et al. A smartphone application to support recovery from alcoholism: a randomized clinical trial. JAMA Psychiatry. 2014;71:566–72. doi: 10.1001/jamapsychiatry.2013.4642.
    1. Gustafson DH, DuBenske LL, Namkoong K, Hawkins R, Chih MY, Atwood AK, et al. An eHealth system supporting palliative care for patients with non-small cell lung cancer: a randomized trial. Cancer. 2013;119:1744–51. doi: 10.1002/cncr.27939.
    1. Dubenske LL, Gustafson DH, Namkoong K, Hawkins RP, Atwood AK, Brown RL, et al. CHESS improves cancer caregivers’ burden and mood: results from an eHealth RCT. Health Psychol. 2013;33:1261–72. doi: 10.1037/a0034216.
    1. Gustafson D, Wise M, Bhattacharya A, Pulvermacher A, Shanovich K, Phillips B, et al. The effects of combining Web-based eHealth with telephone nurse case management for pediatric asthma control: a randomized controlled trial. J Med Internet Res. 2012;14 doi: 10.2196/jmir.1964.
    1. Gustafson DH, Hawkins R, Pingree S, McTavish F, Arora NK, Mendenhall J. Effect of computer support on younger women with breast cancer. J Gen Intern Med. 2001;16:435–45. doi: 10.1046/j.1525-1497.2001.016007435.x.
    1. Gustafson DH, Hawkins R, Boberg E, Pingree S, Serlin RE, Graziano F, et al. Impact of a patient-centered, computer-based health information/support system. Am J Prev Med. 1999;16:1–9. doi: 10.1016/S0749-3797(98)00108-1.
    1. Gustafson DH, Greist JH, Stauss FF, Erdman H, Laughren T. A probabilistic system for identifying suicide attemptors. Comput Biomed Res. 1977;10:83–9. doi: 10.1016/0010-4809(77)90026-X.
    1. Shaw BR, McTavish F, Hawkins R, Gustafson DH, Pingree S. Experiences of women with breast cancer: exchanging social support over the CHESS computer network. J Health Commun. 2000;5:135–59. doi: 10.1080/108107300406866.
    1. McTavish FM, Pingree S, Hawkins R, Gustafson D. Cultural differences in use of an electronic discussion group. J Health Psychol. 2003;8:105–17. doi: 10.1177/1359105303008001447.
    1. Meis T, Gaie M, Pingree S, Boberg EW, Patten CA, Offord KP, et al. Development of a tailored, Internet‐based smoking cessation intervention for adolescents. J Comput Mediat Commun. 2002;7:1–7.
    1. Clemson L, Cumming RG, Kendig H, Swann M, Heard R, Taylor K. The effectiveness of a community-based program for reducing the incidence of falls in the elderly: a randomized trial. J Am Geriatr Soc. 2004;52:1487–94. doi: 10.1111/j.1532-5415.2004.52411.x.
    1. Pingree S, Hawkins R, Baker T, DuBenske L, Roberts LJ, Gustafson DH. The value of theory for enhancing and understanding e-health interventions. Am J Prev Med. 2010;38:103–9. doi: 10.1016/j.amepre.2009.09.035.
    1. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55:68–78. doi: 10.1037/0003-066X.55.1.68.
    1. Ryan RM, Patrick H, Deci EL, Williams GC. Facilitating health behaviour change and its maintenance: interventions based on self-determination theory. Eur Health Psychol. 2008;10:2–5.
    1. Shaw BR, Hawkins R, McTavish F, Pingree S, Gustafson DH. Effects of insightful disclosure within computer mediated support groups on women with breast cancer. Health Commun. 2006;19:133–42. doi: 10.1207/s15327027hc1902_5.
    1. Kim E, Han JY, Shah D, Shaw B, McTavish F, Gustafson DH. Predictors of supportive message expression and reception in an interactive cancer communication system. J Health Commun. 2011;16:1106–21. doi: 10.1080/10810730.2011.571337.
    1. Yoo W, Chih MY, Kwon MW, Yang J, Cho E, McLaughlin B, et al. Predictors of the change in the expression of emotional support within an online breast cancer support group: a longitudinal study. Patient Educ Couns. 2013;90:88–95. doi: 10.1016/j.pec.2012.10.001.
    1. Frattaroli J. Experimental disclosure and its moderators: a meta-analysis. Psychol Bull. 2006;132:823–65. doi: 10.1037/0033-2909.132.6.823.
    1. Gaugler JE, Duval S, Anderson KA, Kane RL. Predicting nursing home admission in the US: a meta-analysis. BMC Geriatr. 2007;7:13. doi: 10.1186/1471-2318-7-13.
    1. Onder G, Liperoti R, Soldato M, Carpenter I, Steel K, Bernabei R, et al. Case management and risk of nursing home admission for older adults in home care: results of the AgeD in HOme Care Study. J Am Geriatr Soc. 2007;55:439–44. doi: 10.1111/j.1532-5415.2007.01079.x.
    1. Luppa M, Luck T, Weyerer S, Konig HH, Brahler E, Riedel-Heller SG. Prediction of institutionalization in the elderly. A systematic review. Age Ageing. 2010;39:31–8. doi: 10.1093/ageing/afp202.
    1. Meldon SW, Mion LC, Palmer RM, Drew BL, Connor JT, Lewicki LJ, et al. A brief risk-stratification tool to predict repeat emergency department visits and hospitalizations in older patients discharged from the emergency department. Acad Emerg Med. 2003;10:224–32. doi: 10.1111/j.1553-2712.2003.tb01996.x.
    1. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap) - a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81. doi: 10.1016/j.jbi.2008.08.010.
    1. Hays RD, Bjorner JB, Revicki DA, Spritzer KL, Cella D. Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items. Qual Life Res. 2009;18:873–80. doi: 10.1007/s11136-009-9496-9.
    1. Revicki DA, Kawata AK, Harnam N, Chen WH, Hays RD, Cella D. Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample. Qual Life Res. 2009;18:783–91. doi: 10.1007/s11136-009-9489-8.
    1. French MT, Dunlap LJ, Zarkin GA, McGeary KA, McLellan AT. A structured instrument for estimating the economic cost of drug abuse treatment. The Drug Abuse Treatment Cost Analysis Program (DATCAP) J Subst Abuse Treat. 1997;14:445–55. doi: 10.1016/S0740-5472(97)00132-3.
    1. Gustafson DH, Quanbeck AR, Robinson JM, Ford JH, 2nd, Pulvermacher A, French MT, et al. Which elements of improvement collaboratives are most effective? A cluster-randomized trial. Addiction. 2013;108:1145–57. doi: 10.1111/add.12117.
    1. Polsky D, Glick HA, Yang J, Subramaniam GA, Poole SA, Woody GE. Cost-effectiveness of extended buprenorphine-naloxone treatment for opioid-dependent youth: data from a randomized trial. Addiction. 2010;105:1616–24. doi: 10.1111/j.1360-0443.2010.03001.x.
    1. The Henry J Kaiser Family Foundation. Hospital adjusted expenses per inpatient day. . Accessed 27 May 2014.
    1. MetLife: Market survey of long-term care costs: The 2012 MetLife market survey of nursing home, assisted living, adult day services, and home care costs . Accessed 27 May 2014.
    1. Agency for Healthcare Research and Quality: Medical expenditure panel survey (MEPS) . Accessed 27 May 2014.
    1. Weinick RM, Bristol SJ, DesRoches CM. Urgent care centers in the US: findings from a national survey. BMC Health Serv Res. 2009;9:79. doi: 10.1186/1472-6963-9-79.
    1. Löthgren M, Zethraeus N. Definition, interpretation and calculation of cost‐effectiveness acceptability curves. Health Econ. 2000;9:623–30. doi: 10.1002/1099-1050(200010)9:7<623::AID-HEC539>;2-V.
    1. Dillard JP, Shen L. On the nature of reactance and its role in persuasive health communication. Commun Monogr. 2005;72:144–68. doi: 10.1080/03637750500111815.
    1. Kaplan D. Structural equation modeling: foundations and extensions. Thousand Oaks, CA: Sage Publications; 2009.
    1. Kaplan D. The Sage handbook of quantitative methodology for the social sciences. Thousand Oaks, CA: Sage Publications; 2004.
    1. Kretzmann JP, McKnight JL. Building communities from the inside out: a path toward finding and mobilizing a community’s assets. Chicago, IL: ACTA Publications; 1993.
    1. Cromwell DA, Eagar K, Poulos RG. The performance of instrumental activities of daily living scale in screening for cognitive impairment in elderly community residents. J Clin Epidemiol. 2003;56:131–7. doi: 10.1016/S0895-4356(02)00599-1.
    1. Lawton MP. The functional assessment of elderly people. J Am Geriatr Soc. 1971;19:465–81. doi: 10.1111/j.1532-5415.1971.tb01206.x.
    1. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179–86. doi: 10.1093/geront/9.3_Part_1.179.
    1. Russell DW. UCLA Loneliness Scale (Version 3): reliability, validity, and factor structure. J Pers Assess. 1996;66:20–40. doi: 10.1207/s15327752jpa6601_2.
    1. Clemson L, Cumming RG, Heard R. The development of an assessment to evaluate behavioral factors associated with falling. Am J Occup Ther. 2003;57:380–8. doi: 10.5014/ajot.57.4.380.
    1. Budnitz DS, Lovegrove MC, Shehab N, Richards CL. Emergency hospitalizations for adverse drug events in older Americans. N Engl J Med. 2011;365:2002–12. doi: 10.1056/NEJMsa1103053.
    1. Piette JD. Patient education via automated calls: a study of English and Spanish speakers with diabetes. Am J Prev Med. 1999;17:138–41. doi: 10.1016/S0749-3797(99)00061-6.
    1. Lawton MP, Moss M, Hoffman C, Perkinson M. Two transitions in daughters’ caregiving careers. Gerontologist. 2000;40:437–48. doi: 10.1093/geront/40.4.437.
    1. Pruchno RA, Resch NL. Mental health of caregiving spouses: coping as mediator, moderator, or main effect? Psychol Aging. 1989;4:454–63. doi: 10.1037/0882-7974.4.4.454.
    1. Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991;32:705–14. doi: 10.1016/0277-9536(91)90150-B.
    1. Kroenke K, Strine TW, Spitzer RL, Williams JB, Berry JT, Mokdad AH. The PHQ-8 as a measure of current depression in the general population. J Affect Disord. 2009;114:163–73. doi: 10.1016/j.jad.2008.06.026.

Source: PubMed

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