A Dyadic e-Health System on Enhancing Healthy Lifestyles of Older Adults With Sarcopenia
Study Details
Study Description
Brief Summary
Sarcopenia is defined as a reduction in muscle mass, muscle strength, and physical performance. Without proper management, sarcopenia may result in adverse health outcomes. Continuously maintain healthy lifestyle, such as being physically active, taking adequate protein in daily diet, are effective in preventing and managing sarcopenia. e-Health has been used successfully to translate evidence-based lifestyle interventions into daily practice by enhancing self-awareness, promoting self-monitor and sustaining self-management for other populations with different health problems.
This project aims to develop, implement and evaluate the preliminary effects of an e-Health System to encourage older adults with sarcopenia to maintain healthy lifestyles (i.e. regular exercise and adequate intake of high-quality protein). Combining the concepts of smart health, the System aims to enhance users' self-monitoring (Level 1) and self-management (Level 2) of sarcopenia.
Level 1 aims to enhance participants' and their family members' awareness of the risks of sarcopenia through continued monitoring. The System will perform baseline and regular subjective (such as self-administered questionnaires) and objective (such as activity levels by an embedded accelerometer) assessments on the participants. The embedded risk calculator in the System will analyze the scores obtained from different assessments and then recommend participants to follow the healthy lifestyle interventions in Level 2.
Level 2 aims to enhance participants' and their family members' ability to manage the health problems related sarcopenia. The System will recommend two major evidence-based lifestyle interventions, including physical exercise and nutritional advice, based on the analysis of the assessment data in Level 1. These interventions will be conducted during the four face-to-face sessions and continuously self-practised at home. The interventions will provide interactive, immediate feedback to the participants and their family members to improve their involvement. The participants and their family members can monitor their progress via the System.
The investigators hypothesize that the experimental group who has adopted the e-Health system in their daily life to manage sarcopenia will exhibit milder symptoms of sarcopenia and more sustainable self-management ability than participants in the control group who has received usual care.
Condition or Disease | Intervention/Treatment | Phase |
---|---|---|
|
N/A |
Detailed Description
Sarcopenia is defined as a reduction in appendicular skeletal muscle mass, muscle strength, and physical performance. The prevalence of sarcopenia is high, and it appears in about 25% of local older adults. Without proper management, sarcopenia may result in adverse health outcomes leading to poor quality of life and premature institutionalization. It also causes a burden on their family members. The current evidence shows that preventing and managing sarcopenia with healthy lifestyle interventions, which include maintaining a physically active lifestyle, ideal body weight, adequate protein intake and social participation, tend to produce positive outcomes if older adults can continuously maintain these healthy lifestyles.
e-Health was defined as "the cost-effective and secure use of information and communications technologies in support of health". e-Health has been used successfully to translate evidence-based lifestyle interventions into daily practice by enhancing self-awareness, promoting self-monitor and sustaining self-management for addressing obesity in young people, smoking cessation in adults and promoting physical activities in older adults with sedentary lifestyle. For example, a systematic review of 15 papers with 1967 participants compared the e-Health based interventions with the control groups to reduce sedentary behaviour and increase physical activity levels. The results showed that the group that received e-Health based interventions had a significantly increased level of physical activity compared with the control groups.
Despite all these potential benefits of using e-Health to manage health, studies indicated that older adults tend to be reluctant to use new technologies due to the inability to integrate them into their daily lives. Consequently, it has been posited that older adults may be less capable or willing to adopt e-Health strategies to manage their health. One possible explanation for this low adaptation rate is that older adults cannot integrate the technologies into their daily lives. Studies have argued that the motivation of participants to sustain the use of the new technologies depends on the extent to which the participants feel that the technologies can fulfil their needs, align with their goals, and meet their expectations. In addition, older adults often attempt to adopt new habits, such as using a new electronic device, maintaining a physically active lifestyle, while being embedded in social networks comprising, amongst others, friends and family. However, current e-Health-based interventions are usually focused on individuals. Given that empirical evidence highlights the role of family members in influencing older adults' behaviour, including an adaptation of technologies and healthy lifestyles, there is a need to consider the potential benefits of involving family support when delivering an e-Health based intervention to older adults.
The World Health Organization's global strategy for digital health emphasizes the importance of empowering older adults to integrate technology into their daily life. Family members who have a close relationship with older adults can support them in adopting the e-Health based interventions for self-management of the health problems. Dyads are defined as two individuals (such as, family caregiver and care recipient) maintaining a socially close relationship. There has been some evidence suggesting that e-Health based interventions targeting the promotion of psychosocial wellbeing through a dyadic approach benefit both care recipients and caregivers. However, most positive findings were from studies targeting children/adolescent-parents dyads or young adult dyads. In addition, behavioural change (such as adopting a new healthy diet habit) is interdependent between care recipients and family caregivers. With the support of family, older adults can easily familiarise themselves with the technical design and functions of the e-Health platform, overcome barriers to adopting the technology and sustain healthy lifestyles in their daily routine. Through the dyadic approach, family members may co-develop an action plan to target the health goals, receive personalized feedback on participants' performance and obtain encouragement from the family members via the e-health platform. Family support may facilitate and motivate older adults (participants) to continue using the e-Health platform and sustain healthy lifestyles. Promising evidence suggests that dyadic interventions can deliver synergistic benefits to both family caregivers and care recipients. However, a limited empirical study has adopted a dyadic approach for older adults to use e-Health platforms to enhance their healthy lifestyles for managing sarcopenia.
Aims and objectives
An e-Health system which comprises of the concept of smart health (i.e. refer to individual demographic and health data) will be developed. This project aims to evaluate the effectiveness of an e-Health System delivered in a dyadic approach to encourage older adults with sarcopenia to maintain healthy lifestyles (i.e. adequate intake of high-quality protein and regular exercises). Two objectives of this study include:
-
to develop a two-level e-Health system to enhance self-monitoring and self-management of sarcopenia
-
to evaluate the immediate effects (4 weeks) and the mid-term effects (after engaging in the e-Health system for 12 weeks).
The investigators hypothesize that the experimental group who has adopted the e-Health system in their daily life to manage sarcopenia will exhibit milder symptoms of sarcopenia, better mobility and physical function and better quantity and quality of protein intake, greater self-efficacy and more sustainable self-management ability than participants in the control group who has received usual care.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
---|---|
Experimental: The Experimental Group Participants in the Experimental Group will attend an implementation program guided by the Self-Determination Theory (SDT). The 12-week intervention consists of a 4-week, group-based, face-to-face supervised sessions conducted by a well-trained Research Assistant, plus an 8-week self-management phase. |
Behavioral: e-Health System with nutritional advice
A 12-week intervention consisting of a 4-weekly group-based, face-to-face supervised sessions, and an 8-week self-management phase will be arranged to the experimental group. The features of the System will be introduced to the users and their family members in the first two face-to-face sessions. The users and their family members will then be able to start using the System with the mobile app. In the other two sessions, all participants in the experimental group will learn how to accurately complete their dietary records in the e-Health System and will be provided with nutritional advice.
For the 8-week self-management phase, the participants will be recommended to follow the lifestyle interventions to relieve their problems related to sarcopenia. The participants are required to fill in their dietary record in the e-Health System every day, and will be provided with nutritional advice to improve high-quality protein and leucine intake, which is essential for muscle building.
Behavioral: The Exercise Training
For the 8-week self-management phase, the participants will be recommended to follow the lifestyle interventions to relieve their problems related to sarcopenia. The participants in the experimental group will also be suggested to continually practise exercise training at home for 30 minutes at least 5 times per week. Participants can review the self-learning exercise videos embedded in the System. The exercise trainings include: a) progressive resistance training to improve muscle strength; and b) brisk walking exercise to maintain walkability.
|
No Intervention: The Control Group Participants in The Control Group will attend 4-weekly, group-based, regular face-to-face health talks about managing sarcopenia with the exact dosage provided to the intervention group. |
Outcome Measures
Primary Outcome Measures
- Changes of muscle strength [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
Handgrip strength (kg) will be measured by using the hand dynamometer.
- Changes of muscle mass [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
Muscle mass (kg) will be measured by using bioelectrical impedance analysis.
- Changes of body mass index [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The weight and height will be combined to report BMI in kg/m^2.
- Changes of waist circumference [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
Waist circumference was taken as the minimum circumference between the umbilicus and xiphoid process and measured to the nearest 0.5 cm.
- Changes of fat mass [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
Fat mass (kg) will be measured by using bioelectrical impedance analysis.
- The Short Physical Performance Battery (SPPB) scale [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The Short Physical Performance Battery (SPPB) scale will be used to measure physical function, which is a well-established tool for monitoring function in older people, which contains three kinds of assessments: stand for 10 seconds with feet in 3 different positions, 3-meter or 4-meter walking speed test, and time to rise from a chair for five times. The scores of SPPB range from 0 (worst performance) to 12 (best performance). The minimum and maximum values are 0 and 10 respectively. Higher scores mean a better performance.
Secondary Outcome Measures
- Mini Nutritional Assessment (MNA) Short-form [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
Participants' nutritional status will be assessed through the Mini Nutritional Assessment (MNA). It is a simple and quick tool for assessing older people who are malnourished or at risk of malnutrition. The MNA Short-form contains 6 items. Questions are weighted, 2-3 points per item. Scores are categorised as 0-7 (malnourished), 8-11 (at risk of malnutrition), 12-14 (normal nutritional status). The minimum and maximum values are 0 and 14 respectively. Higher scores mean a better nutritional status.
- Health Action Process Approach (HAPA) Nutrition Self-efficacy Scale [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The nutrition self-efficacy scale is one part of the Health-Specific Self-efficacy Scale which was developed by Ralf Schwarzer and Britta Renner. The nutritional self-efficacy scale is a 5-item scale, and each item is rated on 4-point likert scale from 1= very uncertain, 2=rather uncertain, 3=rather certain, 4=very certain. Higher score means higher self-efficacy. The minimum and maximum values are 0 and 20 respectively. Higher scores mean a higher self-efficacy.
- Dietary quality index-International (DQI-I) [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The DQI-I will be used to estimate the dietary quality of participants. It is a well-used questionnaire without being affected by culture. The total scores range from 0 to 100, with a higher score representing better diet quality. The minimum and maximum values are 0 and 100 respectively .Higher scores mean a better diet quality.
- Diet Adherence [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The adherence to protein intake will be reflected by the protein score in the DQI-I. Total calorie intake will be analyzed by a software program "Food Processor®". If any participant forgets to keep the dietary record, the 7-day food recall method will be used by the experimental group facilitator to check the participant's food intake, an approach commonly used in nutritional studies. The participants' attendance rate in the consultation sessions will be monitored.
- Exercise Adherence [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
Assessed based on the participants' attendance in the weekly exercise training session, as well as on their self-reports on their overall adherence to the exercise regimen.
- Changes of Numeric Rating Scale (NRS) [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The Numeric Pain Scale (NRS) is a self-reported questionnaire consists of 1 question measuring pain intensity. The scores range from 0 to 10, with higher scores indicate greater pain. A cutoff value > 3 indicates greater pain.
- Changes of Brief Fatigue Inventory (BFI) [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The Brief Fatigue Inventory (BFI) measures nine items on 10-point numeric scales for fatigue level and interference with daily life. A global fatigue score can be obtained by averaging all the items on the BFI. The total scores range from 0-10 points, with higher scores indicate greater fatigue. A cutoff value ≥ 4 on the BFI scale indicates intervention for fatigue.
- Changes of Chinese Self-Efficacy for Exercise (CSEE) scale [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The CSEE scale contains of 9 items. Each item is rated on 11-point Liker scale from 0 = no confidence to 10 = full of confidence. All item scores are summed to get the total score which ranges from 0 to 90 with a higher score indicates higher exercise self-efficacy.
- Changes of Fried Frailty Index (FFI) [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
Fried Frailty Index includes: i) an unintentional loss of 10% of body weight in the past year; ii) exhaustion: by answering 'Yes' to either 'I felt that everything I did was an effort', or 'I could not get going in the last week'; iii) a slow walk time: with an average walking speed in the lowest quintile stratified by median body height; iv) reduced handgrip strength: with maximal grip strength in the lowest quintile stratified by body mass index quartile; and v) the Physical Activity Scale for the Elderly-Chinese (PASE-C) score in the lowest quintile (i.e., < 30 for men and < 27.7 for women).
- Changes of the 15-item Chinese version Geriatric Depression Scale (C-GDS) [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The C-GDS consists of 15 yes/no questions. Each negative answer will be given 1 point, with possible scores ranging from 0-15. The higher score indicates more depressive mood. • Respondents with a score more than 8 are identified as having symptoms of depression.
- Changes of the Chinese (Hong Kong) 12-item Short Form Health Survey (SF-12v2) [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
The Chinese (Hong Kong) 12-item SF-12v2 is a shortened form (12 items) of the SF-36v2 Health Survey. This is a generic assessment of health-related quality of life (HR QOL) from the participants' perspective. It consists of 12 questions measuring eight domains of health, including physical functioning, role physical, bodily pain, general health, vitality, social functioning, role emotional and mental health. These health domain scores are aggregated into the physical component summary (PCS) score and the mental component summary (MCS) score. Eight domains of SF-12v2 (HK) are measured on a scale ranging from 0 to 100. A higher domain score indicates a better HRQoL.
- Changes of the Strength, Assistance in walking, Rise from a chair, Climb stairs, and Falls (SARC-F) [Change from baseline to 4 weeks immediately after the completion of all supervised sessions, 12 weeks after the completion of the self-management phase]
SARC-F includes five components: strength, assistance walking, rise from a chair, climb stairs, and falls. SARC-F items are selected to reflect health status changes associated with the consequences of sarcopenia. The scores range from 0 to 10, with 0 to 2 points for each component. A score equal to or greater than 4 is predictive of sarcopenia and poor outcome.
Eligibility Criteria
Criteria
Inclusion Criteria:
-
Community-dwelling older people aged > 60 years;
-
Meeting the diagnostic criteria of sarcopenia according to the Asian Sarcopenia
Working Group (ASWG):
-
Early-stage sarcopenia refers to the fulfillment of one of the following criteria: low handgrip strength < 28 kg for men and < 18 kg for women, low muscle quality as reflected by low appendicular skeletal muscle mass (ASM) /height squared < 7 kg/m2 for men and <5.7 kg/m2 for women, or low physical performance with a Short Physical Performance Battery (SPPB) score of < 9;
-
Able to communicate, read, and write in Chinese without significant hearing and vision problems to ensure that our instructions are understood;
-
Own a smartphone, and able to access the internet at home or elsewhere;
-
Reside with family and have at least one daily shared meal (family is defined as an individual who has a significant personal relationship with the participant, such as next of kin, spouse and the individual must be at aged > 18); and
-
Able to identify a family member who has a smartphone and is willing to support the participant to use the e-Health System.
Exclusion Criteria:
-
With any form of disease or condition that might affect food intake and digestion (such as severe heart or lung diseases, diabetes, cancer, or autoimmune diseases);
-
Currently suffering from acute gouty arthritis or had a gout attack in the past year;
-
Taking medications that may influence eating behaviour, digestion, or metabolism (such as weight loss medication);
-
Being addicted to alcohol, which might affect the effort to change dietary behaviour;
-
Having impaired mobility, which might affect participation in exercise training, as defined by a modified Functional Ambulatory Classification score of < 7;
-
Having renal impairment, based on the renal function blood test which will be screened by a geriatrician;
-
Having depressive symptomatology, defined by a Geriatric Depression Scale score of > 8;
-
Suffering from dementia (i.e., MoCA<20 or clinical dementia rating ≥1);
-
Having any medical implant device such as a pacemaker, because low-level currents will flow through the body when doing the bioelectric impedance analysis (BIA by InBody S10, Korea), which may cause the device to malfunction.
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
---|---|---|---|---|---|
1 | The Hong Kong Polytechnic Universtiy | Hong Kong | Hong Kong |
Sponsors and Collaborators
- The Hong Kong Polytechnic University
Investigators
- Principal Investigator: Justina Liu, PhD, The Hong Kong Polytechnic University
Study Documents (Full-Text)
More Information
Additional Information:
Publications
- Alghadir AH, Anwer S, Iqbal A, Iqbal ZA. Test-retest reliability, validity, and minimum detectable change of visual analog, numerical rating, and verbal rating scales for measurement of osteoarthritic knee pain. J Pain Res. 2018 Apr 26;11:851-856. doi: 10.2147/JPR.S158847. eCollection 2018.
- Bamidis PD, Paraskevopoulos E, Konstantinidis E, Spachos D, Billis A. Multimodal e-Health Services for Smoking Cessation and Public Health: The SmokeFreeBrain Project Approach. Stud Health Technol Inform. 2017;245:5-9.
- Beaudart C, Dawson A, Shaw SC, Harvey NC, Kanis JA, Binkley N, Reginster JY, Chapurlat R, Chan DC, Bruyere O, Rizzoli R, Cooper C, Dennison EM; IOF-ESCEO Sarcopenia Working Group. Nutrition and physical activity in the prevention and treatment of sarcopenia: systematic review. Osteoporos Int. 2017 Jun;28(6):1817-1833. doi: 10.1007/s00198-017-3980-9. Epub 2017 Mar 1.
- Bloom I, Shand C, Cooper C, Robinson S, Baird J. Diet Quality and Sarcopenia in Older Adults: A Systematic Review. Nutrients. 2018 Mar 5;10(3):308. doi: 10.3390/nu10030308.
- Bruyere O, Reginster JY, Beaudart C. Lifestyle approaches to prevent and retard sarcopenia: A narrative review. Maturitas. 2022 Jul;161:44-48. doi: 10.1016/j.maturitas.2022.02.004. Epub 2022 Feb 25.
- Cao L, Chen S, Zou C, Ding X, Gao L, Liao Z, Liu G, Malmstrom TK, Morley JE, Flaherty JH, An Y, Dong B. A pilot study of the SARC-F scale on screening sarcopenia and physical disability in the Chinese older people. J Nutr Health Aging. 2014 Mar;18(3):277-83. doi: 10.1007/s12603-013-0410-3.
- Carr RM, Prestwich A, Kwasnicka D, Thogersen-Ntoumani C, Gucciardi DF, Quested E, Hall LH, Ntoumanis N. Dyadic interventions to promote physical activity and reduce sedentary behaviour: systematic review and meta-analysis. Health Psychol Rev. 2019 Mar;13(1):91-109. doi: 10.1080/17437199.2018.1532312. Epub 2018 Oct 14.
- Chan AC. Clinical validation of the Geriatric Depression Scale (GDS): Chinese version. J Aging Health. 1996 May;8(2):238-53. doi: 10.1177/089826439600800205.
- CHAU, Mei Wa Rosanna, et al. Reliability and validity of the Modified Functional Ambulation Classification in patients with hip fracture. Hong Kong Physiotherapy Journal, 2013; 31(1): 41-44.
- Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, Jang HC, Kang L, Kim M, Kim S, Kojima T, Kuzuya M, Lee JSW, Lee SY, Lee WJ, Lee Y, Liang CK, Lim JY, Lim WS, Peng LN, Sugimoto K, Tanaka T, Won CW, Yamada M, Zhang T, Akishita M, Arai H. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020 Mar;21(3):300-307.e2. doi: 10.1016/j.jamda.2019.12.012. Epub 2020 Feb 4.
- Chi I, Yip PS, Chiu HF, Chou KL, Chan KS, Kwan CW, Conwell Y, Caine E. Prevalence of depression and its correlates in Hong Kong's Chinese older adults. Am J Geriatr Psychiatry. 2005 May;13(5):409-16. doi: 10.1176/appi.ajgp.13.5.409.
- Cocks K, Torgerson DJ. Sample size calculations for pilot randomized trials: a confidence interval approach. J Clin Epidemiol. 2013 Feb;66(2):197-201. doi: 10.1016/j.jclinepi.2012.09.002. Epub 2012 Nov 27.
- Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, Cooper C, Landi F, Rolland Y, Sayer AA, Schneider SM, Sieber CC, Topinkova E, Vandewoude M, Visser M, Zamboni M; Writing Group for the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), and the Extended Group for EWGSOP2. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019 Jan 1;48(1):16-31. doi: 10.1093/ageing/afy169. Erratum In: Age Ageing. 2019 Jul 1;48(4):601.
- Fox, G., & Connolly, R. Mobile health technology adoption across generations: Narrowing the digital divide. Information Systems Journal. 2018; 28(6): 995-1019.
- Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-56. doi: 10.1093/gerona/56.3.m146.
- Gulotta, R., Forlizzi, J., Yang, R., & Newman, M. W. Fostering engagement with personal informatics systems. In Proceedings of the 2016 ACM Conference on Designing Interactive Systems (pp. 286-300). 2016; 286-300.
- Guralnik JM, Ferrucci L, Pieper CF, Leveille SG, Markides KS, Ostir GV, Studenski S, Berkman LF, Wallace RB. Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci. 2000 Apr;55(4):M221-31. doi: 10.1093/gerona/55.4.m221.
- He, X., & Liu, X. Evaluation of reliability and validity of Mini-nutritional assessment and Chinese nutrition screen. Nurs J Chin People's Lib Army 2010; 27(6B): 894-896.
- Kim S, Haines PS, Siega-Riz AM, Popkin BM. The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. J Nutr. 2003 Nov;133(11):3476-84. doi: 10.1093/jn/133.11.3476.
- Kwan RYC, Liu JYW, Yin YH, Lee PH, Ng SY, Cheung DSK, Kor PPK, Lam SC, Lo SKL, Yang L, Chan SK, Chiang VCL. Sarcopenia and its association with objectively measured life-space mobility and moderate-to-vigorous physical activity in the oldest-old amid the COVID-19 pandemic when a physical distancing policy is in force. BMC Geriatr. 2022 Mar 25;22(1):250. doi: 10.1186/s12877-022-02861-7.
- Kwan RYC, Salihu D, Lee PH, Tse M, Cheung DSK, Roopsawang I, Choi KS. The effect of e-health interventions promoting physical activity in older people: a systematic review and meta-analysis. Eur Rev Aging Phys Act. 2020 Apr 21;17:7. doi: 10.1186/s11556-020-00239-5. eCollection 2020.
- Lam, C. L. K., Wong, C. K. H., Lam, E. T. P., Lo, Y. Y. C., & Huang, W. W. 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.
- Lee LL, Arthur A, Avis M. Using self-efficacy theory to develop interventions that help older people overcome psychological barriers to physical activity: a discussion paper. Int J Nurs Stud. 2008 Nov;45(11):1690-9. doi: 10.1016/j.ijnurstu.2008.02.012. Epub 2008 May 22.
- Marzetti E, Calvani R, Tosato M, Cesari M, Di Bari M, Cherubini A, Collamati A, D'Angelo E, Pahor M, Bernabei R, Landi F; SPRINTT Consortium. Sarcopenia: an overview. Aging Clin Exp Res. 2017 Feb;29(1):11-17. doi: 10.1007/s40520-016-0704-5. Epub 2017 Feb 2.
- McTigue KM, Conroy MB, Hess R, Bryce CL, Fiorillo AB, Fischer GS, Milas NC, Simkin-Silverman LR. Using the internet to translate an evidence-based lifestyle intervention into practice. Telemed J E Health. 2009 Nov;15(9):851-8. doi: 10.1089/tmj.2009.0036.
- Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000 Jan;55(1):68-78. doi: 10.1037//0003-066x.55.1.68.
- Shaffer KM, Tigershtrom A, Badr H, Benvengo S, Hernandez M, Ritterband LM. Dyadic Psychosocial eHealth Interventions: Systematic Scoping Review. J Med Internet Res. 2020 Mar 4;22(3):e15509. doi: 10.2196/15509.
- Stephenson A, McDonough SM, Murphy MH, Nugent CD, Mair JL. Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017 Aug 11;14(1):105. doi: 10.1186/s12966-017-0561-4.
- Tan JP, Li N, Gao J, Wang LN, Zhao YM, Yu BC, Du W, Zhang WJ, Cui LQ, Wang QS, Li JJ, Yang JS, Yu JM, Xia XN, Zhou PY. Optimal cutoff scores for dementia and mild cognitive impairment of the Montreal Cognitive Assessment among elderly and oldest-old Chinese population. J Alzheimers Dis. 2015;43(4):1403-12. doi: 10.3233/JAD-141278.
- Wang XS, Hao XS, Wang Y, Guo H, Jiang YQ, Mendoza TR, Cleeland CS. Validation study of the Chinese version of the Brief Fatigue Inventory (BFI-C). J Pain Symptom Manage. 2004 Apr;27(4):322-32. doi: 10.1016/j.jpainsymman.2003.09.008.
- WHO guideline Recommendations on Digital Interventions for Health System Strengthening. Geneva: World Health Organization; 2019. Available from http://www.ncbi.nlm.nih.gov/books/NBK541902/
- Woo J, Cheung B, Ho S, Sham A, Lam TH. Influence of dietary pattern on the development of overweight in a Chinese population. Eur J Clin Nutr. 2008 Apr;62(4):480-7. doi: 10.1038/sj.ejcn.1602702. Epub 2007 Feb 28.
- Yoshimura Y, Wakabayashi H, Yamada M, Kim H, Harada A, Arai H. Interventions for Treating Sarcopenia: A Systematic Review and Meta-Analysis of Randomized Controlled Studies. J Am Med Dir Assoc. 2017 Jun 1;18(6):553.e1-553.e16. doi: 10.1016/j.jamda.2017.03.019.
- Zhou G, Jiang T, Knoll N, Schwarzer R. Improving hand hygiene behaviour among adolescents by a planning intervention. Psychol Health Med. 2015;20(7):824-31. doi: 10.1080/13548506.2015.1024138. Epub 2015 Mar 16.
- HSEARS20230817002