| Literature DB >> 31440113 |
Kirubel Biruk Shiferaw1, Eden Abetu Mehari2.
Abstract
BACKGROUND: Health-care professionals should be able to identify and use reputable health care-information sources from the Internet and other relevant sources of information, in order to make good medical decisions. The level in health professional eHealth literacy and the extent of Internet use in a resource-constrained setting is not well documented. The aim of this study was to assess the extent of Internet use and eHealth literacy among a cross section of health-care professionals at the University of Gondar Comprehensive Specialized Hospital, northwest Ethiopia.Entities:
Keywords: Ethiopia; Internet use; eHealth literacy; health professionals
Year: 2019 PMID: 31440113 PMCID: PMC6664426 DOI: 10.2147/AMEP.S205414
Source DB: PubMed Journal: Adv Med Educ Pract ISSN: 1179-7258
Participants’ sociodemographic characteristics
| n | % | n | % | ||
|---|---|---|---|---|---|
| Male | 133 | 46.3% | Medical doctor | 19 | 6.6% |
| Female | 154 | 53.7% | Nurse | 88 | 30.7% |
| Health officer | 9 | 3.1% | |||
| 21–29 | 171 | 59.6% | Lab technician | 50 | 17.4% |
| 30–39 | 94 | 32.8% | Midwife | 64 | 22.3% |
| >39 | 22 | 7.7% | Pharmacist | 57 | 19.9 |
| Diploma (certificate) | 55 | 19.2% | <5 | 167 | 58.2% |
| Degree (BSc) | 220 | 76.7% | 5–10 | 86 | 30.0% |
| Master's (MPH/MSc) | 12 | 4.2% | >10 | 34 | 11.8% |
| 1,500–3,500 | 54 | 18.8% | |||
| 3,500–5,500 | 203 | 70.7% | |||
| >5,500 | 30 | 10.5% |
Internet access and use
| Questions | n | % | |
|---|---|---|---|
| Do you have Internet access? | Yes | 287 | 100 |
| No | — | — | |
| If yes, select the type of connection | DSL/cable | 78 | 27.2 |
| Wi-fi | 155 | 54.0 | |
| Mobile data | 54 | 18.8 | |
| If you have Internet access, where do you have it? | Office | 120 | 41.8 |
| Cafés/hotels | 28 | 9.8 | |
| Campus lab/wi-fi | 100 | 34.8 | |
| Home | 39 | 13.6 | |
| If you use the Internet, how frequently do you use it? | Daily | 67 | 23.3 |
| Several days a week | 121 | 42.2 | |
| Weekly | 61 | 21.3 | |
| <One day a week | 38 | 13.2 | |
| By what means do you access the Internet? | Smartphone | 119 | 41.5 |
| Laptop | 113 | 39.4 | |
| Tablet | 14 | 4.9 | |
| Desktop | 41 | 14.3 | |
| Do you use the Internet regularly for medical/professional updates? | Yes | 136 | 47.4 |
| No | 151 | 52.6 | |
| Does information from websites influence your decision-making? | Yes | 173 | 60.3 |
| No | 114 | 39.7 | |
| Have you ever advised a website for a patient? | Yes | 7 | 2.4 |
| No | 280 | 97.6 | |
| Has a patient ever asked for the name of a website for more information on their condition? | Yes | — | — |
| No | 287 | 100 | |
| If yes, have you ever recommended any? | Yes | — | — |
| No | — | — | |
| Do you trust the general quality of medical websites? | Yes | 96 | 33.4 |
| No | 191 | 66.6 |
eHealth literacy–response frequency and percentage
| High eHealth literacy (%) | Low eHealth literacy (%) | |
|---|---|---|
| Male | 95 (33.1%) | 38 (13.2%) |
| Female | 104 (36.2%) | 50 (17.4%) |
| 21–29 | 127 (44.3%) | 44 (15.3%) |
| 30–39 | 62 (21.6%) | 32 (11.1%) |
| >39 | 10 (3.5%) | 12 (4.2%) |
| Diploma | 31 (10.8%) | 24 (8.4%) |
| Degree | 159 (55.4%) | 61 (21.3%) |
| Master's | 9 (3.1%) | 3 (1.0%) |
| Medical doctor | 19 (6.6%) | — |
| Nurse | 65 (22.6%) | 23 (8.0%) |
| Health officer | 9 (3.1%) | — |
| Medical lab technician | 35 (12.2%) | 13 (4.5%) |
| Pharmacist | 35 (12.2%) | 22 (7.7%) |
| Midwife | 36 (12.4%) | 28 (9.8%) |
| <5 | 128 (44.6%) | 39 (13.6%) |
| 5–10 | 56 (19.5%) | 30 (10.4%) |
| >10 | 15 (5.2%) | 19 (6.6%) |
| 1,500–3,500 | 31 (10.8%) | 23 (8.0%) |
| 3,500–5,500 | 141 (49.1%) | 62 (21.6%) |
| >5,500 | 27 (9.4%) | 3 (1.0%) |
Multivariable logistic regression for eHealth literacy
| Independent variables | Dependent variables(eHealth literacy) | |||
|---|---|---|---|---|
| Coefficient estimate | Lower confidence level | Upper confidence level | ||
| 21–29 | 1.182 | 1.320 | 8.058 | 0.010* |
| 30–39 | 0.844 | 0.907 | 5.960 | 0.079 |
| Male | 0.243 | 0.771 | 2.108 | 0.345 |
| Degree | 0.657 | 1.051 | 3.543 | 0.034* |
| Master's | 0.843 | 0.566 | 9.524 | 0.242 |
| Physician | 1.889 | 1.409 | 31.029 | 0.017* |
| Nurse | 0.788 | 1.107 | 4.363 | 0.024* |
| Health officer | 0.820 | 1.368 | 6.025 | 0.084 |
| Medical lab technician | 0.596 | 0.831 | 3.962 | 0.135 |
| Pharmacist | 0.213 | 0.598 | 2.560 | 0.566 |
| 3,500–5,500 | 0.523 | 0.911 | 3.126 | 0.096 |
| >5,500 | 1.311 | 0.166 | 1.243 | 0.020* |
| <5 | 1.392 | 1.872 | 8.639 | 0.000* |
| 5–10 | 0.810 | 1.002 | 5.039 | 0.049* |
Notes: Reference groups: age (>39 years), sex (female), education (diploma), profession (midwife), salary (ETB1,500–3,500), years of experience (>10). *P<0.05).