| Literature DB >> 32917171 |
Xinran Sun1, Wenxin Yan1, Hao Zhou2, Zhaoqing Wang1, Xueying Zhang1, Shuang Huang1, Li Li3.
Abstract
BACKGROUND: China is becoming an aging society at the fastest pace in history, and there are a large number of empty nesters in the country. With economic and social development, internal support systems among families are gradually weakening. Supporting the elderly is thus emerging as a significant issue, and promoting digital health technologies is an effective way to help address it. Encouraging the application of Internet to elderly care and Internet use among the elderly are important means of promoting digital health technologies. This paper examines the current state of the use of the Internet by the elderly and factors influencing it (including physical, psychological, and social) as well as demand among the elderly for smart services.Entities:
Keywords: Digital health technologies; Elderly; Influential factor; Internet use
Mesh:
Year: 2020 PMID: 32917171 PMCID: PMC7488462 DOI: 10.1186/s12889-020-09448-0
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Socioeconomic and demographic characteristics of the respondents (N = 669)
| Variables | Total (669) | Internet users (258) | |
|---|---|---|---|
| n1 | n2 | % | |
| Sex | |||
| Male | 232 | 75 | 32.3 |
| Female | 437 | 183 | 41.9 |
| Χ2 | 5.832* | ||
| Age | |||
| 60–69 | 376 | 193 | 51.3 |
| 70–79 | 228 | 62 | 27.2 |
| ≥ 80 | 65 | 3 | 4.6 |
| Mean ± SD | 69.23 ± 6.90 | 66.00 ± 5.03 | |
| Χ2 | 69.925** | ||
| Education | |||
| Primary school or below | 224 | 31 | 13.8 |
| Secondary education | 377 | 186 | 49.3 |
| University degree | 68 | 41 | 60.3 |
| Χ2 | 89.816** | ||
| Marriage status | |||
| Single/widowed/divorced | 164 | 46 | 28.0 |
| Married | 505 | 212 | 42.0 |
| Χ2 | 10.141* | ||
| Living arrangements | |||
| Alone | 63 | 27 | 42.9 |
| With children or others | 606 | 231 | 38.1 |
| Χ2 | 0.541 | ||
| Monthly income (¥) | |||
| < 1500 | 177 | 43 | 24.3 |
| 1500–2999 | 397 | 165 | 41.6 |
| ≥ 3000 | 95 | 50 | 52.6 |
| Χ2 | 24.654** | ||
| House as property | |||
| Yes | 515 | 220 | 42.7 |
| No | 154 | 38 | 24.7 |
| Χ2 | 16.290** | ||
| Chronic diseases | |||
| Yes | 481 | 189 | 39.3 |
| No | 188 | 69 | 36.7 |
| Χ2 | 0.383 | ||
*p < 0.05;**p < 0.01
The percentage of Internet users = n2/n1
State of Internet use by the elderly (N = 258)
| Variables | n | % |
|---|---|---|
| Number of Internet users | 258 | 38.6 |
| Daily online time | ||
| < 2 h | 139 | 53.9 |
| 2–5 h | 91 | 35.3 |
| > 5 h | 28 | 10.9 |
| Weekly online days | ||
| < 3 days | 27 | 10.5 |
| 3–5 days | 37 | 14.3 |
| 5–7 days | 194 | 75.2 |
| Internet activitya | ||
| Chatting online | 190 | 74.2 |
| Reading news | 151 | 59.0 |
| Watching videos and listening to music | 81 | 32.7 |
| Searching for health information | 56 | 22.5 |
| Playing games | 37 | 15.0 |
| Shopping | 17 | 6.8 |
| Specific health information contenta | ||
| Diet care knowledge | 159 | 63.1 |
| Fitness knowledge | 113 | 47.1 |
| Medication condition | 75 | 29.8 |
| Food safety news | 72 | 28.6 |
| Disease-related information | 33 | 13.1 |
aMultiple-choice questions
Demand for digital health technologies
| Service items | Range | M ± SDa |
|---|---|---|
| Smart bracelet | 1–5 | 2.80 ± 1.07 |
| Emergency caller | 1–5 | 2.77 ± 1.01 |
| Telemedicine | 1–5 | 2.63 ± 0.94 |
| Online health consultation | 1–5 | 2.58 ± 0.95 |
| Online appointment registration | 1–5 | 2.52 ± 1.00 |
| Pay for medical expenses online | 1–5 | 2.45 ± 0.87 |
aM Mean, SD Standard deviation
Assignment description: The numbers 1–5 represent the range of responses from “not at all” to “significantly needed.”
Factors influencing Internet use
| Variables | B | OR | 95% CI | ||
|---|---|---|---|---|---|
| Sex (ref = Female) | 0.659 | 0.003 | 1.933 | 1.260 | 2.695 |
| Age | −0.119 | 0.000 | 0.888 | 0.851 | 0.926 |
| Education (ref = Primary school or below) | 0.000 | ||||
| Secondary education | 1.279 | 0.000 | 3.591 | 2.141 | 6.024 |
| University degree | 1.943 | 0.000 | 6.978 | 3.080 | 15.806 |
| Marriage status (ref = Married) | 0.332 | 0.269 | 1.393 | 0.774 | 2.507 |
| Monthly income (¥) (ref ≥ 3000) | 0.035 | ||||
| < 1500 | −0.987 | 0.011 | 0.373 | 0.174 | 0.800 |
| 1500–3000 | −0.485 | 0.122 | 0.616 | 0.333 | 1.138 |
| Number of children | −0.134 | 0.230 | 0.874 | 0.703 | 1.088 |
| Chronic diseases (ref = No) | −0.353 | 0.117 | 1.423 | 0.916 | 2.210 |
| House property (ref = No) | −0.030 | 0.911 | 0.970 | 0.572 | 1.645 |
| Living arrangements (ref = With children or others) | −0.697 | 0.078 | 0.498 | 0.229 | 1.082 |
| Quality of life | 2.241 | 0.036 | 9.404 | 1.161 | 76.176 |
| Loneliness | −0.031 | 0.263 | 0.969 | 0.917 | 1.024 |
| Social participation | 0.255 | 0.025 | 1.290 | 1.032 | 1.614 |
| Number of friends | 0.262 | 0.021 | 1.299 | 1.040 | 1.623 |
B: Regression coefficient
CI CI code, OR ratio of odds