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Effect of a Telecare Case Management Program for Older Adults Who Are Homebound During the COVID-19 PandemicA Pilot Randomized Clinical Trial

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME
Key Points

Question  Can a telecare case management program delivered by a nurse case manager supported by a health-social team improve self-efficacy, health-related measures, and health care service utilization outcomes among older adults who are homebound?

Findings  In this randomized clinical trial with 68 participants, there was no statistical difference in self-efficacy between the telecare group and control group at 3 months according to the Chinese version of the 10-item, 4-point General Self-efficacy Scale. Scores for self-efficacy improved in both groups over time.

Meaning  While the intervention did not increase self-efficacy, the findings suggest that telecare case management may increase quality of life and rates of medication adherence among older adults who are homebound.

Abstract

Importance  Older adults who are homebound can be difficult to reach owing to their functional limitations and social distancing during the COVID-19 pandemic, leaving their health needs unrecognized at an earlier stage.

Objective  To determine the effectiveness of a telecare case management program for older adults who are homebound during the COVID-19 pandemic.

Design, Setting, and Participants  This randomized clinical trial was conducted among 68 older adults in Hong Kong from May 21 to July 20, 2020, with a last follow-up date of October 20, 2020. Inclusion criteria were being 60 years or older, owning a smartphone, and going outside less than once a week in the previous 6 months.

Interventions  Participants in the telecare group received weekly case management from a nurse supported by a social service team via telephone call and weekly video messages covering self-care topics delivered via smartphone for 3 months. Participants in the control group received monthly social telephone calls.

Main Outcomes and Measures  The primary outcome was the change in general self-efficacy from before the intervention to after the intervention at 3 months. Self-efficacy was measured by the Chinese version of the 10-item, 4-point General Self-efficacy Scale, with higher scores representing higher self-efficacy levels. Analysis was performed on an intention-to-treat basis.

Results  A total of 68 participants who fulfilled the criteria were enrolled (34 in the control group and 34 in the intervention group; 56 [82.4%] were women; and mean [SD] age, 71.8 [6.1] years). At 3 months, there was no statistical difference in self-efficacy between the telecare group and the control group. Scores for self-efficacy improved in both groups (β = 1.68; 95% CI, −0.68 to 4.03; P = .16). No significant differences were found in basic and instrumental activities of daily living, depression, and use of health care services. However, the telecare group showed statistically significant interactions of group and time effects on medication adherence (β = −8.30; 95% CI, −13.14 to −3.47; P = .001) and quality of life (physical component score: β = 4.99; 95% CI, 0.29-9.69; P = .04).

Conclusions and Relevance  In this randomized clinical trial, participants who received the telecare program were statistically no different from the control group with respect to changes in self-efficacy, although scores in both groups improved. After the intervention, the telecare group had better medication adherence and quality of life than the control group, although the small sample size may limit generalizability. A large-scale study is needed to confirm these results.

Trial Registration  ClinicalTrials.gov Identifier: NCT04304989

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Article Information

Accepted for Publication: June 27, 2021.

Published: September 9, 2021. doi:10.1001/jamanetworkopen.2021.23453

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Wong AKC et al. JAMA Network Open.

Corresponding Author: Arkers Kwan Ching Wong, PhD, RN, School of Nursing, The Hong Kong Polytechnic University, One Cheong Wan Road, Hung Hom, Hong Kong (arkers.wong@polyu.edu.hk).

Author Contributions: Drs A. K. C. Wong and F. K. Y. Wong had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: A. K. C. Wong, F. K. Y. Wong, Chow, S. M. Wong.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: A. K. C. Wong.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: A. K. C. Wong, Lee.

Obtained funding: A. K. C. Wong, F. K. Y. Wong, Chow.

Administrative, technical, or material support: S. M. Wong.

Supervision: F. K. Y. Wong, Chow.

Conflict of Interest Disclosures: Drs A. K. C. Wong, F. K. Y. Wong, and S. M. Wong and Ms Chow reported receiving grants from the Nethersole Institute of Continuing Holistic Health Education (NICHE) during the conduct of the study. Dr A. K. C. Wong reported receiving grants from the NICHE outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported by grant P0031004 from the NICHE (Dr A. K. C. Wong).

Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

Additional Contributions: We thank all of the community centers for their collaboration with the research team.

References
1.
Xiang  X , Chen  J , Kim  M .  Trajectories of homebound status in Medicare beneficiaries aged 65 and older.   Gerontologist. 2020;60(1):101-111. doi:10.1093/geront/gnz023 PubMedGoogle ScholarCrossref
2.
Sterling-Fox  C.   Access to five nonprimary health care services by homebound older adults: an integrative review.   Home Health Care Manag Pract. 2019;31(1):55-69. doi:10.1177/1084822318810384Google ScholarCrossref
3.
Zhao  YL , Alderden  J , Lind  B , Stibrany  J .  Risk factors for falls in homebound community-dwelling older adults.   Public Health Nurs. 2019;36(6):772-778. doi:10.1111/phn.12651PubMedGoogle ScholarCrossref
4.
Xiang  X , Brooks  J .  Correlates of depressive symptoms among homebound and semi-homebound older adults.   J Gerontol Soc Work. 2017;60(3):201-214. doi:10.1080/01634372.2017.1286625 PubMedGoogle ScholarCrossref
5.
Qiu  WQ , Dean  M , Liu  T ,  et al.  Physical and mental health of homebound older adults: an overlooked population.   J Am Geriatr Soc. 2010;58(12):2423-2428. doi:10.1111/j.1532-5415.2010.03161.x PubMedGoogle ScholarCrossref
6.
Kim  CO , Jang  SN .  Home-based primary care for homebound older adults: literature review.   Ann Geriatr Med Res. 2018;22(2):62-72. doi:10.4235/agmr.2018.22.2.62 PubMedGoogle ScholarCrossref
7.
Norman  GJ , Wade  AJ , Morris  AM , Slaboda  JC .  Home and community-based services coordination for homebound older adults in home-based primary care.   BMC Geriatr. 2018;18(1):241. doi:10.1186/s12877-018-0931-z PubMedGoogle ScholarCrossref
8.
Stall  N , Nowaczynski  M , Sinha  SK .  Systematic review of outcomes from home-based primary care programs for homebound older adults.   J Am Geriatr Soc. 2014;62(12):2243-2251. doi:10.1111/jgs.13088 PubMedGoogle ScholarCrossref
9.
Ninnis  K , van den Berg  M , Lannin  NA ,  et al.  Information and communication technology use within occupational therapy home assessments: a scoping review.   Br J Occup Ther. 2019;82(3):141-152. doi:10.1177/0308022618786928Google ScholarCrossref
10.
Read  J , Jones  N , Fegan  C ,  et al.  Remote home visit: exploring the feasibility, acceptability and potential benefits of using digital technology to undertake occupational therapy home assessments.   Br J Occup Ther. 2020;83(10):648-658. doi:10.1177/0308022620921111Google ScholarCrossref
11.
Hawley  CE , Genovese  N , Owsiany  MT ,  et al.  Rapid integration of home telehealth visits amidst COVID-19: what do older adults need to succeed?   J Am Geriatr Soc. 2020;68(11):2431-2439. doi:10.1111/jgs.16845 PubMedGoogle ScholarCrossref
12.
Kim  EH , Gellis  ZD , Bradway  CK , Kenaley  B .  Depression care services and telehealth technology use for homebound elderly in the United States.   Aging Ment Health. 2019;23(9):1164-1173. doi:10.1080/13607863.2018.1481925 PubMedGoogle ScholarCrossref
13.
Gellis  ZD , Kenaley  B , McGinty  J , Bardelli  E , Davitt  J , Ten Have  T .  Outcomes of a telehealth intervention for homebound older adults with heart or chronic respiratory failure: a randomized controlled trial.   Gerontologist. 2012;52(4):541-552. doi:10.1093/geront/gnr134 PubMedGoogle ScholarCrossref
14.
Abrashkin  KA , Zhang  J , Poku  A .  Acute, post-acute, and primary care utilization in a home-based primary care program during COVID-19.   Gerontologist. 2021;61(1):78-85. doi:10.1093/geront/gnaa158 PubMedGoogle ScholarCrossref
15.
Tomioka  K , Kurumatani  N , Hosoi  H .  Social participation and cognitive decline among community-dwelling older adults: a community-based longitudinal study.   J Gerontol B Psychol Sci Soc Sci. 2018;73(5):799-806. doi:10.1093/geronb/gbw059PubMedGoogle Scholar
16.
Broderick  L , McCullagh  R , White  EB , Savage  E , Timmons  S .  Perceptions, expectations, and informal supports influence exercise activity in frail older adults.   SAGE Open. 2015;5(2):1-10. doi:10.1177/2158244015580850Google ScholarCrossref
17.
Wong  AKC , Wong  FKY , Chang  K .  Effectiveness of a community-based self-care promoting program for community-dwelling older adults: a randomized controlled trial.   Age Ageing. 2019;48(6):852-858. doi:10.1093/ageing/afz095 PubMedGoogle ScholarCrossref
18.
Farley  H .  Promoting self-efficacy in patients with chronic disease beyond traditional education: a literature review.   Nurs Open. 2019;7(1):30-41. doi:10.1002/nop2.382 PubMedGoogle ScholarCrossref
19.
Lau  SCL , Bhattacharjya  S , Fong  MWM ,  et al.  Effectiveness of theory-based digital self-management interventions for improving depression, anxiety, fatigue and self-efficacy in people with neurological disorders: a systematic review and meta-analysis.   J Telemed Telecare. Published online October 24, 2020. doi:10.1177/1357633X20955122PubMedGoogle Scholar
20.
Yamazaki  S , Fujita  K , Imuta  H .  Development of a scale measuring barriers to going out among community-dwelling older adults.   Geriatr Gerontol Int. 2021;21(2):238-244. doi:10.1111/ggi.14111 PubMedGoogle ScholarCrossref
21.
Yao  NA , Ritchie  C , Cornwell  T , Leff  B .  Use of home-based medical care and disparities.   J Am Geriatr Soc. 2018;66(9):1716-1720. doi:10.1111/jgs.15444 PubMedGoogle ScholarCrossref
22.
Urbaniak  GC , Plous  S . Research Randomizer. Accessed July 19, 2021. https://www.randomizer.org/
23.
Martin  KS .  The Omaha System: A Key to Practice, Documentation, and Information Management. 2nd ed. Health Connections Press; 2005.
24.
Leung  DYP , Leung  AYM .  Factor structure and gender invariance of the Chinese General Self-efficacy Scale among soon-to-be-aged adults.   J Adv Nurs. 2011;67(6):1383-1392. doi:10.1111/j.1365-2648.2010.05529.x PubMedGoogle ScholarCrossref
25.
Leung  SOC , Chan  CCH , Shah  S .  Development of a Chinese version of the Modified Barthel Index—validity and reliability.   Clin Rehabil. 2007;21(10):912-922. doi:10.1177/0269215507077286 PubMedGoogle ScholarCrossref
26.
Tong  AYC , Man  DWK .  The validation of the Hong Kong Chinese version of the Lawton Instrumental Activities of Daily Living scale for institutionalized elderly persons.   OTJR: Occupation, Participation and Health. 2002;22(4):132-142. doi:10.1177/153944920202200402Google Scholar
27.
Jin  H , Kim  Y , Rhie  SJ .  Factors affecting medication adherence in elderly people.   Patient Prefer Adherence. 2016;10:2117-2125. doi:10.2147/PPA.S118121 PubMedGoogle ScholarCrossref
28.
Lam  CLK , Wong  CKH , Lam  ETP , Lo  YYC , Huang  WW .  Population norm of Chinese (HK) SF-12 Health Survey Version 2 of Chinese adults in Hong Kong.   Hong Kong Practitioner. 2010;32(2):77-86. Accessed July 28, 2021. http://hdl.handle.net/10722/157222Google Scholar
29.
Pocklington  C , Gilbody  S , Manea  L , McMillan  D .  The diagnostic accuracy of brief versions of the Geriatric Depression Scale: a systematic review and meta-analysis.   Int J Geriatr Psychiatry. 2016;31(8):837-857. doi:10.1002/gps.4407 PubMedGoogle ScholarCrossref
30.
Laforest  S , Nour  K , Gignac  M , Gauvin  L , Parisien  M , Poirier  MC .  Short-term effects of a self-management intervention on health status of housebound older adults with arthritis.   J Appl Gerontol. 2008;27(5):539-567. doi:10.1177/0733464808319712Google ScholarCrossref
31.
Cocks  K , Torgerson  DJ .  Sample size calculations for pilot randomized trials: a confidence interval approach.   J Clin Epidemiol. 2013;66(2):197-201. doi:10.1016/j.jclinepi.2012.09.002 PubMedGoogle ScholarCrossref
32.
Whitehead  AL , Julious  SA , Cooper  CL , Campbell  MJ .  Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable.   Stat Methods Med Res. 2016;25(3):1057-1073. doi:10.1177/0962280215588241 PubMedGoogle ScholarCrossref
33.
Musich  S , Wang  SS , Hawkins  K , Yeh  CS .  Homebound older adults: prevalence, characteristics, health care utilization and quality of care.   Geriatr Nurs. 2015;36(6):445-450. doi:10.1016/j.gerinurse.2015.06.013 PubMedGoogle ScholarCrossref
34.
Almathami  HKY , Win  KT , Vlahu-Gjorgievska  E .  Barriers and facilitators that influence telemedicine-based, real-time, online consultation at patients’ homes: systematic literature review.   J Med internet Res. 2020;22(2):e16407. doi:10.2196/16407 PubMedGoogle Scholar
35.
Khechine  H , Lakhal  S , Pascot  D , Bytha  A.   UTAUT model for blended learning: the role of gender and age in the intention to use webinars.   Interdisciplinary Journal of e-Skills and Lifelong Learning. 2014;10(1):33-52. doi:10.28945/1994Google Scholar
36.
Moryson  H , Moeser  G .  Consumer adoption of cloud computing services in Germany: investigation of moderating effects by applying a UTAUT model.   International Journal of Marketing Studies. 2016;8(1):14-32. doi:10.5539/ijms.v8n1p14Google ScholarCrossref
37.
Greenhalgh  T , Shaw  S , Wherton  J ,  et al.  Real-world implementation of video outpatient consultations at macro, meso, and micro levels: mixed-method study.   J Med internet Res. 2018;20(4):e150. doi:10.2196/jmir.9897 PubMedGoogle Scholar
38.
Choi  NG , Wilson  NL , Sirrianni  L , Marinucci  ML , Hegel  MT .  Acceptance of home-based telehealth problem-solving therapy for depressed, low-income homebound older adults: qualitative interviews with the participants and aging-service case managers.   Gerontologist. 2014;54(4):704-713. doi:10.1093/geront/gnt083PubMedGoogle ScholarCrossref
39.
Free  C , Phillips  G , Galli  L ,  et al.  The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review.   PLoS Med. 2013;10(1):e1001362. doi:10.1371/journal.pmed.1001362 PubMedGoogle Scholar
40.
Schooley  B , San Nicolas-Rocca  T , Burkhard  R .  Patient-provider communications in outpatient clinic settings: a clinic-based evaluation of mobile device and multimedia mediated communications for patient education.   JMIR Mhealth Uhealth. 2015;3(1):e2. doi:10.2196/mhealth.3732 PubMedGoogle Scholar
41.
Spring  B , Pellegrini  C , McFadden  HG ,  et al.  Multicomponent mHealth intervention for large, sustained change in multiple diet and activity risk behaviors: the Make Better Choices 2 randomized controlled trial.   J Med internet Res. 2018;20(6):e10528. doi:10.2196/10528 PubMedGoogle Scholar
42.
Direito  A , Carraça  E , Rawstorn  J , Whittaker  R , Maddison  R .  mHealth technologies to influence physical activity and sedentary behaviors: behavior change techniques, systematic review and meta-analysis of randomized controlled trials.   Ann Behav Med. 2017;51(2):226-239. doi:10.1007/s12160-016-9846-0 PubMedGoogle ScholarCrossref
43.
Volk  RJ , Lowenstein  LM , Leal  VB ,  et al.  Effect of a patient decision aid on lung cancer screening decision-making by persons who smoke: a randomized clinical trial.   JAMA Netw Open. 2020;3(1):e1920362. doi:10.1001/jamanetworkopen.2019.20362 PubMedGoogle Scholar
44.
Orgeta  V , Brede  J , Livingston  G .  Behavioural activation for depression in older people: systematic review and meta-analysis.   Br J Psychiatry. 2017;211(5):274-279. doi:10.1192/bjp.bp.117.205021 PubMedGoogle ScholarCrossref
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