Table 2.
Study characteristics
| Study | Study design | Age (range, mean) | Gender (female) |
Education (college degree or higher) |
Computer-related experience | Sample size | Country | Application descriptions | Health domain |
|---|---|---|---|---|---|---|---|---|---|
| Disease prevention and self-management (N = 28) | |||||||||
| Alsswey et al25 | Quantitative research (Survey) |
60+, Mean (M): not reported. |
15.70% | 23.90% | All had at least 1 year of experience in using mobile applications. | 134 | Not reported | A mobile app designed to manage physical health needs for Arab elderly users (eg, medication-related information and instructions) | Medication adherence |
| Alvarez et al26 |
Quantitative research (Pilot study: usability study, feasibility study) |
Usability: 65+, M = 73.2; Feasibility: 65+, M = 76 |
Usability: 67.6%; Feasibility: 59.5% |
Usability: 9 years of education; Feasibility: 10.53 years of education |
Usability: 32.3% had previous experience with technology. | Usability: 34; Feasibility: 62 | Chile | A mobile app that provides interventions to prevent delirium for bedside use for hospitalized elderly patients | Delirium prevention |
| Bakogiannis et al27 | Quantitative research (Usability study, pilot study) |
Usability: M = 64.9; Pilot: M = 68.7 |
Usability: 21%; Pilot: 13% |
Not reported. | Not reported. |
Usability: 14; Pilot: 30 |
Greece | ThessHF app, a mobile app that supports heart failure self-care for elderly patients with heart failure | Heart failure self-management |
| Balsa et al28 | Quantitative research (Usability study) | 67–80, M = 70.91 | 72.2% | 63.6% | Not reported. | 11 | Portugal | VASelfCare, a mobile-based intelligent assistant (in the form of an anthropomorphic virtual assistant) that supports older adults with Type 2 Diabetes Mellitus (T2DM) in medication adherence and lifestyle changes | T2DM self-management |
| Baric et al29 |
Qualitative research (Focus groups) |
66–85, M = 73 | 45% | 40% | 55% had daily or weekly computer use; 85% had daily or weekly phone use. | 20 | Sweden | RemindMe, an interactive digital calendar that provides active reminders for senior people with cognitive impairment | Cognitive impairment self-management |
| Chen et al30 |
Qualitative research (Usability study) |
64 | 100% | Not reported. | Not reported. | 1 | China | Win-Win aSleep (WWAS), a mobile app to assist cognitive behavioral therapy for older adults with insomnia | Insomnia self-management |
| Chen et al31 |
Quantitative research (Pre-post intervention study) |
60+, M = 86.68 |
77% | Not reported. | Not reported. | 57 | Hong Kong | Lok Chi, a home-based tablet-based intervention designed to improve cognitive and emotional health for community-dwelling older adults with mild cognitive impairment (MCI) | MCI self-management |
| Chung et al32 |
Quantitative research (Pre-post intervention study) |
65–78, M = 71.56 |
100% | 0% |
38 had Android smartphones; 2 had feature phones on which mobile apps were not available. |
40 | South Korea | MIND MORE, a mobile app for insomnia self-management in community-dwelling older adults | Insomnia self-management |
| Cunningham et al33 | Quantitative research (Cohort study) | 69–97, M = 84.6 | 64% | Not reported. | Not reported. | 14 | United Kingdom | Memory Tracks, a music mobile platform that provides song-task association training for elderly people with dementia | Dementia self-management |
| Djabelkhir et al34 |
Quantitative research (RCT) |
60+, M = 79 |
60%–70% | 44.4%–60% | Not reported | 14 | France | Two tablet-based cognitive training apps (cognitive stimulation, cognitive engagement) for elderly patients with MCI | MCI self-management |
| Fortuna et al35 | Quantitative research (Feasibility study) |
60+, M = 68.8 |
87.50% | 12.50% | 62.5% had smartphones. | 8 | United States | PeerTECH, a tablet-delivered psychiatric self-management intervention for older adults with mental illnesses | Psychiatric self-management |
| Hackett et al36 |
Quantitative research (Pilot study, within-subject, cross-over experiment) |
65+, M = 80.3 |
70% | Not reported. | Participants were able to use computers and had positive attitudes toward computers. | 10 | United States | SmartPrompt, a mobile reminder app for older adults with dementia and MCI | Self-management of dementia and MCI |
| Holden et al37 | Quantitative research (Usability study) | 60–85, M = 67.6 | 61.00% | 23.00% | Some participants had never used a smartphone before. | 23 | United States | Brain Buddy, a mobile app to reduce unsafe medication use by older adults | Medication use |
| Jongstra et al38 |
Quantitative research (RCT) |
65+, M = 69 |
56% | 29% | Not reported. | 41 | Finland, France, The Netherlands | An interactive counseling platform for healthy aging (ie, cardiovascular risk profiling and prevention) | Cardiovascular diseases prevention |
| Jung et al39 |
Qualitative study (Usability study, interviews) |
65–80, M: not reported. |
78.57% | 57.14% | All participants had experience with smartphones. | 14 | United States | FRADA, a food record app that provides dietary assessments for older adults with Type 2 Diabetes | Diabetes self-management |
| Kim et al40 |
Mixed methods research (Pilot study) |
65+, M = 75.7 |
91% | 18.2% | Participants had 3.5 years of smart device usage experience on average. | 11 | South Korea | 365 Healthy Swallowing Coach, a mobile app that delivers swallowing training for elderly dysphagia patients | Swallowing training |
| Loh et al41 |
Mixed methods research (Pilot study) |
68–87, M = 76.8 | 17% | 67% | 44% (17%) had access to a mobile phone (a tablet or iPad). | 18 | United States | TouchStream, a mHealth app that provides geriatric assessment-driven interventions for older adults with cancer | Cancer treatment |
| Madill et al42 | Quantitative research (Usability study) |
60+, M = 75.5 |
23.30% | Not reported. | Not reported. | 30 | United States | “Take Back Your Back”, an iPad-based educational tool for older adults with chronic lower back pain | Back pain treatment |
| Manca et al43 | Quantitative research (Between-subject experiment) |
69–84, M = 75.3 |
64.3% | 7.14% | 50% were familiar with technologies and devices. | 14 | Italy | A music-based game (robot version and tablet version) for older adults with MCI | MCI self-management |
| Manera et al44 |
Quantitative research (Pilot study) |
60–90, M = 78.3 | 71% | Not reported. | Not reported. | 21 | Not reported. | “Kitchen and cooking”, a tablet-based serious game for elderly people with MCI and Alzheimer’s Disease (AD) | Self-management of MCI and AD |
| Mertens et al45 | Quantitative research (Crossover design) |
60+, M = 73.8 |
50% | 25% | 16.7% expert in computer literacy | 24 | Germany | Medication Plan, a mobile app designed to improve therapy adherence for elderly patients undergoing rehabilitation | Rehabilitation self-management |
| Mira et al46 |
Quantitative research (RCT) |
65+, M = 72.9 |
Not reported. | Not reported. | 45% had smartphone experience. | 99 | Spain | ALICE, a tablet-based app for medication self-management | Medication self-management |
| Portz et al47 |
Quantitative research (Pilot study) |
60+, M = 66 |
60% | Not reported. | Not reported. | 30 | United States | HF app, a mobile app that tracks heart failure symptoms in elderly users | Heart failure self-management |
| Puig et al48 |
Quantitative research (RCT) |
60+, Median = 66 |
28% | Not reported. | Not reported. | 100 | Finland | +Approp, a mobile app for HIV prevention and self-management for older HIV-infected patients | HIV prevention and self-management |
| Quinn et al49 |
Quantitative research (Pilot study) |
65+ M = 70.3 |
57% | Not reported. | 71.4% had Internet at home. | 7 | United States | Patient coaching system (PCS), a mobile software for diabetes management for older adults | Diabetes management |
| Reading Turchioe et al50 | Quantitative research (Feasibility study) |
60+, M: not reported. |
37% | 47% | 30.4% did not have a computer and 26.2% did not have the internet. | 168 | United States | mi.Symptoms, a mobile app that facilitates symptom reporting and patient outcome reporting in older adults | Chronic disease self-management |
| Scase et al51 |
Qualitative research (Focus groups) |
65–80, M = 75.0 | 88% | Not reported. | Not reported. | 25 | United Kingdom | 4 tablet-based cognitive games (ie, “Find it,” “Match it,” “Solve it,” and “Complete it”) for older adults with mild cognitive impairment | MCI self-management |
| Sun et al52 |
Quantitative research (RCT) |
66–72 M = 68 |
59.34% | Not reported. | Not reported. | 91 | China | A mobile-based telemedicine app for T2DM self-management for older adults | T2DM self-management |
| Physical and cognitive function improvement (N = 27) | |||||||||
| Albergoni et al53 |
Quantitative research (Pilot study) |
70–78, M = 73.8 |
40% | Not reported. | Not reported. | 10 | The Netherlands | PACE, a mobile app that visualizes user adherence to physical activity programs | Physical activities |
| Baez et al54 |
Quantitative research (RCT) |
65–87, M = 71.5 | 70%–75% | Not reported. | Not reported. | 40 | Italy | Gymcentral, a tablet-based app for home-based online group exercises under the supervision of a human coach | Home-based exercises |
| Bergquist et al55 |
Mixed methods research (Usability study) |
60–80, M = 66.4 | 48% | Not reported. | 83% had mobile experience. | 343 | Norway, Germany, The Netherlands | 3 mobile apps that deliver physical function self-tests (ie, Self-TUG, Self-STS, Self-Tandem) for older adults | Physical function self-tests |
| Compernolle et al56 |
Mixed methods research (Usability study) |
60–76, M = 64.3 | 54% | 57% | Not reported. | 28 | Belgium | Activator, a mobile self-monitoring tool designed to reduce older adults’ sedentary behavior | Sedentary behavior change |
| Daly et al57 |
Quantitative research (Pilot study) |
65–81, M = 70 |
50% | 60% | Not reported. | 20 | Australia | PhysiApp, a tablet-based app that delivers tailored, home-based exercise programs for community-dwelling older adults | Home-based exercises |
| Dekker-van Weering et al58 |
Quantitative research (RCT) |
65–75, M = 70.2 | 61.1% | 8.3% | Not reported. | 36 | The Netherlands | A tablet or computer-based portal that provides home-based exercise programs for pre-frail older adults | Physical activities |
| Delbaere et al59 |
Quantitative research (RCT) |
70+, M = 77.4 |
67.4% | Not reported. | 85% (88.4%) in the intervention (control) group owned computers. | 503 | Australia | StandingTall, a tablet-based mobile app that delivers home-based, balance exercises to older adults | Balance exercises |
| Geerds et al60 | Mixed methods research (Usability study) | M = 80.5 | 71.80% | Not reported. | 93.8% had more than 5 years of smartphone experience. | 48 | The Netherlands | A mobile app designed to monitor postoperative functional recovery after hip fracture | Functional recovery after hip fracture |
| Geraedts et al61 | Quantitative research (Feasibility study) |
70+, M = 81 |
62.5% | Not reported. | 62.5% had computer experience; 2.5% had a smartphone. | 21 | The Netherlands | A tablet-based app that provides home-based exercise programs for pre-frail old adults | Home-based exercises |
| Haeger et al62 | Quantitative research (Feasibility study, controlled trial) |
70+, M = 76.5 |
50% | Not reported. | Not reported. | 10 | Germany | MIT App Inventor 2, a mobile app that plans trips in hometowns to increase mobility in older adults | Mobility |
| Harte et al63 | Mixed methods research (Usability study) |
61–85, M: not reported. |
Not reported. | Not reported. | Not reported. | 12 | Ireland | A mobile app that integrates fall risk detection for older adults | Fall risk detection and fall prevention |
| Hawley-Hague et al64 | Qualitative research (Usability study, focus groups, interviews) | 64–92, M = 77.1 | Not reported. | Not reported. | Not reported. | 7 | United Kingdom | Two mobile apps that support falls rehabilitation exercises (ie, My Activity Programme for patients, Motivate Me for professionals) | Fall rehabilitation exercises |
| Hill et al65 | Mixed methods research (Feasibility study) |
60+, M = 78.8 |
78% | 56% | Not reported. | 9 | United States | A tablet-based attention training app designed to improve cognitive functioning in older adults | Cognitive training |
| Hill et al66 | Mixed methods research (Usability study) |
60+, M = 79 |
58% | 50% | Not reported. | 12 | United States | A modified tablet-based attention training app designed to improve cognitive functioning in older adults | Cognitive training |
| Hsieh et al67 | Mixed methods research (Usability study) |
70+, M = 80.3 |
81.8% | 27.2% | 54.5% used tablets and 81.1% used smartphones. | 11 | United States | Steady, a mobile app for fall risk screening for older adults | Fall risk screening and prevention |
| Kang et al68 |
Quantitative research (Pre-post experiment) |
65–75, M = 70 |
50% | Not reported. | Not reported. | 4 | South Korea | A mobile app that provides exercise suggestions for older adults with chronic disorders | Exercise suggestions |
| Kwan et al69 |
Quantitative research (RCT) |
60+, Median = 71 | 85.00% | Not reported. | Not reported. | 33 | Hong Kong | Samsung Health, a mobile app that monitors walking behaviors | Walking activities |
| Li et al70 |
Quantitative research (Pre-post between-subjects experiment) |
65+, M = 71.3 |
70% | Not reported. | Not reported. | 30 | Singapore | 5 exergames (ie, Skiing, Hiking, Pikkuli, Chinatown Race, RehaMed Volleyball) that promote physical activities in older adults | Physical activities |
| Li et al71 |
Quantitative research (RCT) |
60+, M = 79.3 |
19.4% | 4.6 years on average | Not reported. | 31 | Hong Kong | Caspar Health e-system and a mobile app designed to provide occupational therapy rehabilitation for elderly outpatients after hip fraction surgery | Physical and functional ability |
| Mehra et al72 | Mixed methods research (Usability study) |
69–99 M: not reported. |
73.3% | Not reported. | Not reported. | 15 | The Netherlands | VITAMIN app, a tablet-based app that supports older adults in home-based exercises | Exercise training |
| Pettersson et al73 | Qualitative research (Feasibility study) |
70+, M = 76 |
52.6% | Not reported. | 71% (72%) had access to tablet/smartphone (computer). | 28 | Sweden | Safe Step, a mHealth app that supports self-managed exercises and behavior changes for older adults with impaired balance | Self-managed exercises and behavior changes |
| Shake et al74 |
Quantitative research (RCT) |
65+, M = 73.4 |
86% | 20% | Not reported. | 105 | United States | Bingocize, a mobile game app designed to provide exercise and health education for older adults | Exercises and health education |
| Silveria et al75 |
Quantitative research (Pre-post intervention study) |
65+, M = 75.2 |
64% | 54.% had trades or professional diploma | 52.3% frequently used cellphones; 68.2% used computers; 59.1% used the Internet. | 44 | Switzerland | ActiveLifestyle, a tablet-based app that delivers home-based strength-balance training to independently living older adults | Strength-balance training |
| Tabak et al76 | Mixed methods research |
65–75, M = 71 |
50% | Not reported. | 40% had daily technology use. | 20 | United States | WordFit, a game-based mobile coaching app that stimulates daily physical activities among older adults | Physical activities |
| Taylor et al77 |
Quantitative research (Feasibility study) |
60+, M = 83 |
53.3% | 11 years of education on average | 33% owned a computer, 20% used a computer. | 15 | Australia | StandingTall, a tablet-based app that delivers tailored exercise programs to elderly people with dementia | Exercise programs |
| Van Het Reve et al78 |
Quantitative research (Pre-post intervention study) |
65+, M = 75 |
63.6% | 13.6% | Not reported. | 44 | Switzerland | ActiveLifestyle, a tablet-based app that delivers strength-balance training to independently living older adults | Strength-balance training |
| Zhong and Rau79 |
Quantitative research (Usability test, mixed design experiment) |
60–90, M = 69.8 | 73% | 18.9% | 73.6% had a smartphone and 60.1% had Internet access. | 148 | China | Pocket Gait, a mobile app designed to provide gait assessment and fall prevention for older adults | Fall prevention |
| Social inclusion and well-being (N = 6) | |||||||||
| Chi et al80 |
Mixed methods research (Pilot study) |
68–89, M = 78.3 |
100% | Not reported. | 70% felt comfortable using technology. | 10 | United States | Digital Pet, a tablet-based conversational agent in the form of an avatar for older adults | Social connectedness |
| Goumopoulos et al81 |
Mixed methods research (Pilot study) |
60+, M = 65.7 |
59% | Not reported. | Not reported. | 22 | Greece | Senior App Suite, a mobile app designed to improve the social well-being and independence of senior people | Social connectedness |
| Jansen-Kosterink et al82 |
Quantitative research (Usability study) |
60+, M = 73.4 |
80% | 41% | 22%, 66%, and 12% of participants had positive, neutral, and negative attitudes toward technology. | 91 | The Netherlands | GezelschApp, a mobile app that encourages social participation in community-dwelling older adults | Social connectedness |
| Judges et al83 | Mixed methods research | 68–92, M = 80.6 | 70% | Not reported. | Most of them had no experience with computers. | 10 | Canada | InTouch, a tablet-based communication app that reduces loneliness and social isolation in the elderly | Social connectedness |
| Neves et al84] | Mixed methods research (Feasibility study) | 74–95, M = 82.5 | 66.7% | Not reported. | Digital literacy: 4 (no); 3 (low); 5 (medium). | 12 | Canada | InTouch, a tablet-based communication app that reduces loneliness and social isolation in the elderly | Social connectedness |
| Similä et al85 | Mixed methods research (Feasibility study) | 66–82, M = 73 | 100% | Not reported. | 5 participants had Internet access; 4 had used a computer in the previous year; 1 had used a smartphone or tablet. | 7 | Finland | Oiva, a mobile app that provides mental wellness training for older adults | Mental wellness training |
| Healthy dieting (N = 5) | |||||||||
| Aure et al86 | Qualitative research (Interviews) | 68–95, M = 81 | 66.7% | Not reported. | 44.4% had experience with touch technology (eg, tablet, smartphone). | 18 | Norway | Appetitus, a mobile nutrition app that supports weight gain or weight maintenance for older adults | Self-monitoring of dieting |
| Aure et al87 |
Mixed methods research (Feasibility study) |
68–95, M = 79.48 |
72% | Not reported. | 40% had experience using tablet or smartphone; 48% used the Internet daily, 16% used Internet weekly, and 36% never used Internet. | 25 | Norway | Appetitus, a mobile nutrition app that supports weight gain or weight maintenance for older adults | Self-monitoring of dieting |
| Farsjø and Moen88 |
Qualitative research (Pilot study, focus group) |
69–76 M: not reported. |
100% | Not reported. | Not reported. | 4 | Norway | APPETITT, a tablet-based app designed to prevent malnutrition and weight loss in the elderly | Guidance for dieting |
| Franco et al89 | Quantitative research (Usability study) |
60–85 M: not reported. |
79.60% | 74.38% | Not reported. | 50 | United Kingdom | eNutri, a mobile app that provides graphical food frequency assessment for older adults | Healthy dieting |
| Liu et al90 |
Quantitative research (RCT) |
60–90, M = 73.9 | 79% | 58% | 68% had used mobile phones or tablets; 7% had used nutrition-related apps. | 57 | Taiwan | Two mobile apps (ie, voice-only reporting, voice-button reporting) for food intake reporting for elderly people | Food intake reporting |
| Health monitoring and health concern reporting (N = 5) | |||||||||
| Algilani et al91 |
Mixed methods research (Feasibility study) |
67–90, M = 77 |
62.50% | Not reported. | Not reported. | 8 | Sweden | A tablet-based app for early assessment and management of elderly patients’ reported concerns | Health concern reporting |
| Göransson et al92 | Qualitative research (Interviews) |
65+, M = 86 |
64.7% | 23.5% | Not reported. | 17 | Sweden | A mobile app designed to report health concerns | Health concern reporting |
| Göransson et al93 | Quantitative research (Quasi-experimental study) |
65+, M = 86 |
64.7% | 23.5% | Not reported. | 17 | Sweden | A mobile app designed to report health concerns | Health concern reporting |
| Göransson et al94 | Quantitative research (Quasi-experimental study) |
65+, M = 86 |
64.7% | 23.5% | Not reported. | 17 | Sweden | A mobile app designed to report health concerns | Health concern reporting |
| Quinn et al95 | Quantitative research (Usability study) |
65+, M = 77.8 |
66.7% | 100% | 25% are skillful with technology and electronics. | 12 | United States | A mobile app designed to improve engagement of the patient-informal caregiver team | Health recording and monitoring |
| General (provides more than 1 type of functions) (N = 3) | |||||||||
| Bott et al96 | Quantitative research (Quasi-experiment) |
65+, M: Not reported. |
54.7% | 19% had less than high school education | Not reported. | 95 | United States | A tablet-based conversational agent (embodied in the form of an animated avatar) designed to provide psychosocial and health care support for hospitalized patients | Social inclusion; delirium prevention; fall prevention |
| Stal et al97 | Quantitative research (Within-subject experiment) | 65+, M = 72.2 | 35% | 50% | Not reported. | 20 | The Netherlands | A conversational agent, which is embedded in a frailty assessment app and provides training in healthy nutrition, physical health, cognitive health for older adults | Healthy dieting; physical and cognitive function improvement |
| Steinert et al98 | Quantitative research (Usability study) | 61–76, M = 68 | Not reported. | Not reported. | None of the participants had smartphone experience. | 30 | Germany | MyTherapy, a mobile app that helps older adults achieve health-related goals | Diverse health-related goals |