| Literature DB >> 32873273 |
Shiqun Chen1, Guoli Sun1, Xiaolin Cen1,2, Jin Liu1, Jianfeng Ye3, Jiyan Chen1, Li Lei1, Yibo He1, Feier Song1, Wei Guo1, Yan Liang4, Yuying Hu5, Kaihong Chen6, Liling Chen6, Ning Tan1, Yong Liu7.
Abstract
BACKGROUND: Digital health tools (WeChat or mobile health apps) provide opportunities for new methods of hypertension management for hypertensive patients. However, the willingness of these patients to use social media and mobile health apps for hypertension management remains unclear. This study explored the characteristics and requirements of patients willing to use digital health (WDH) tools to manage hypertension.Entities:
Keywords: Blood pressure management; Community; Digital health tools; Hypertension; Willingness
Mesh:
Year: 2020 PMID: 32873273 PMCID: PMC7465797 DOI: 10.1186/s12889-020-09462-2
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Sample characteristics of WDH patients
| Item | Total sample | WDH | No WDH |
|---|---|---|---|
| 100% (1089/1089) | 42.7% (465/1089) | 57.3% (506/1089) | |
| Male (vs female), n (%) | 549 (50.4) | 218 (60.3) | 331 (39.7) |
| Age (SD) | 60 (13) | 58 (12) | 61 (13) |
| Age > 75 years, n (%) | 160 (15.4) | 112 (24.1) | 48 (7.7) |
| BMI (SD) | 24.5 (4.3) | 24.45 (4.8) | 24.48 (3.9) |
| Educational level, n (%) | |||
| High school or above | 816 (79) | 286 (35.1) | 530 (64.9) |
| Junior high school or less | 217 (21) | 129 (59.5) | 88 (40.5) |
| Employment status, n (%) | |||
| working | 590 (57.2) | 270 (45.8) | 320 (54.2) |
| not working | 441 (42.8) | 144 (32.6) | 297 (67.4) |
| Medical insurance, n (%) | |||
| medical care | 916 (89.5) | 362 (39.5) | 554 (60.5) |
| no medical care | 108 (10.5) | 47 (43.5) | 61 (57.5) |
| Mean SBP fluctuation, n (%) | |||
| < 140 mmHg | 587 (57.6) | 227 (38.7) | 360 (61.3) |
| ≥ 140 mmHg | 432 (42.4) | 176 (40.7) | 256 (59.3) |
| Knowledge of diagnostic criteria, n (%) | |||
| ≥ 140/90 mmHg | 501 (46) | 224 (44.7) | 227 (55.3) |
| other | 588 (54) | 241 (41) | 347 (59) |
| Acknowledgement of complications of hypertension (diseases caused by hypertension), n (%) | |||
| myocardial infarction | 528 (51.3) | 267 (50.6) | 261 (49.4) |
| stroke | 529 (51.5) | 270 (51) | 259 (49) |
| renal impairment | 470 (45.8) | 247 (52.6) | 223 (47.4) |
| BP monitoring, n (%) | |||
| good BP monitoring | 564 (51.8) | 243 (43.1) | 321 (56.9) |
| poor BP monitoring | 525 (48.2) | 222 (42.9) | 303 (57.7) |
| Medical adherence, n (%) | |||
| good adherence | 801 (73.5) | 326 (40.7) | 475 (59.3) |
| poor adherence | 288 (26.5) | 139 (48.3) | 149 (51.7) |
| Smoking, n (%) | |||
| never smoked or quit | 836 (76.8) | 367 (43.9) | 469 (56.1) |
| smoked | 253 (23.2) | 98 (38.7) | 155 (61.3) |
| Physical activity, n (%) | |||
| weekly high-intensity exercise | 641 (63) | 262 (40.9) | 379 (59.1) |
| absence of the above exercise intensity | 376 (37) | 137 (36.4) | 239 (63.6) |
Multivariate associations with WDH patients a-b
| Item | WDH a | ||
|---|---|---|---|
| Odds Ratio | 95% CI | ||
| Male (vs female) | 1.17 | 0.83–1.65 | 0.36 |
| Age | 0.99 | 0.98–1.01 | 0.62 |
| BMI | 1.00 | 0.97–1.04 | 0.90 |
| Marriage vs no marriage | 1.14 | 0.73–1.78 | 0.56 |
| Good education vs Poor education | 1.92 b | 1.27–2.94 | 0.002 |
| Unemployment vs employment | 0.72 | 0.47–1.10 | 0.13 |
| Medical insurance vs no medical insurance | 1.04 | 0.61–1.76 | 0.90 |
| Hypertension diagnosis | 1.21 | 0.87–1.70 | 0.26 |
| Usual SBP fluctuation< 140 mmHg vs ≥140 mmHg | 1.11 | 0.78–1.59 | 0.56 |
| Good BP monitoring vs poor BP monitoring | 1.64 b | 1.19–2.26 | 0.002 |
| Good medical adherence vs poor medical adherence | 1.52 b | 1.01–2.28 | 0.044 |
| Smoking vs no smoking | 0.79 | 0.53–1.16 | 0.23 |
| Less physical activity vs more physical activity | 1.04 | 0.74–1.47 | 0.82 |
aWDH refers to non-WDH
bStill significant after correction for multiplicity