| Literature DB >> 29549074 |
Eun Ji Kim1, Yiyang Yuan2, Jane Liebschutz3, Howard Cabral4, Lewis Kazis4.
Abstract
BACKGROUND: Disabilities affect more than 1 in 5 US adults, and those with disabilities face multiple barriers in accessing health care. A digital gap, defined as the disparity caused by differences in the ability to use advanced technologies, is assumed to be prevalent among individuals with disabilities.Entities:
Keywords: Internet; disability; health care provider; health information; psychosocial factors; trust
Year: 2018 PMID: 29549074 PMCID: PMC5878361 DOI: 10.2196/rehab.8783
Source DB: PubMed Journal: JMIR Rehabil Assist Technol ISSN: 2369-2529
Sociodemographic characteristics of the study sample.
| Characteristic | Total (n=3185), %a | Any disability (n=796), %a | No disability (n=2274), %a | ||
| Excellent, very good, or good | 86.1 | 66.7 | 90.9 | <.001 | |
| Fair or poor | 13.9 | 33.3 | 9.1 | — | |
| Male | 48.4 | 46.3 | 49.2 | .43 | |
| Female | 51.6 | 53.7 | 50.9 | — | |
| Younger than 65 | 82.8 | 65.7 | 87.4 | <.001 | |
| 65 or older | 17.2 | 34.3 | 12.6 | — | |
| Married or living as married | 58.8 | 47.0 | 61.8 | <.001 | |
| Singlec | 41.2 | 53.0 | 38.2 | — | |
| Non-Hispanic white | 66.9 | 63.7 | 68.1 | <.001 | |
| Hispanic | 15.4 | 15.7 | 14.7 | — | |
| Non-Hispanic black or African American | 10.5 | 16.4 | 9.3 | — | |
| Non-Hispanic Asian | 5.1 | 2.7 | 5.6 | — | |
| Other | 2.1 | 1.5 | 2.3 | — | |
| Less or complete high school | 34.1 | 50.0 | 29.4 | <.001 | |
| Some college | 32.7 | 33.0 | 32.8 | — | |
| College graduate | 33.2 | 17.0 | 37.7 | — | |
| High | 55.5 | 49.8 | 57.3 | 0.02 | |
| Low | 44.5 | 50.2 | 42.7 | — | |
| Have insurance | 83.0 | 83.2 | 82.6 | — | |
| No insurance | 17.0 | 16.8 | 17.4 | 0.85 | |
| Less than $20,000 | 20.9 | 40.9 | 15.9 | <.001 | |
| $20,000 to $34,999 | 14.3 | 16.4 | 13.8 | — | |
| $35,000 to $49,999 | 14.6 | 14.5 | 14.6 | — | |
| $50,000 to $74,999 | 17.7 | 12.2 | 19.1 | — | |
| $75,000 or more | 32.6 | 16.0 | 36.7 | — | |
aWeighted percentage. Missing value was excluded.
bRao-Scott chi-square test. Missing value was excluded.
cSingle included divorced, widowed, separated, single, or never been married.
dAll monetary values presented in USD.
Characteristics associated with electronic health information communication.
| Characteristic | Totala (n=3185) | Any disabilitya (n=796) | No disabilitya (n=2274) | ||
| Yes | 63.6 | 71.2 | 61.7 | .003 | |
| No | 36.4 | 28.8 | 38.3 | — | |
| Yes | 87.7 | 89.0 | 87.2 | .47 | |
| No | 12.3 | 11.0 | 12.8 | — | |
| Have one or more than 1 electronic mobile device (eg, mobile phone) | 91.7 | 82.5 | 94.1 | <.001 | |
| No mobile device | 8.3 | 17.5 | 5.9 | — | |
| Very important | 64.9 | 58.2 | 66.5 | .009 | |
| Somewhat/not at all important | 35.1 | 41.8 | 33.5 | — | |
| Willingness to exchange medical information with provider, mean (SD) | 2.57 (0.03) | 2.39 (0.07) | 2.62 (0.03) | <.001 | |
aWeighted percentage. Missing value was excluded.
bRao-Scott chi-square test for categorical variables and t test for continuous variables. Missing value was excluded.
Predictors of seeking information from health care provider and internet as health information source.
| Predictors | Internet | Provider | |||||||||||||||
| As actual sourcea,b | As hypothetical sourceb,c | As actual sourcea,b | As hypothetical sourceb,c | ||||||||||||||
| AORd | 95% CI | AORd | 95% CI | AORd | 95% CI | AORd | 95% CI | ||||||||||
| Disability (ref: no disability) | 0.65 | 0.43-0.98 | .048 | 0.66 | 0.41-1.06 | — | 1.24 | 0.76-2.04 | — | 1.25 | 0.77-2.03 | — | |||||
| Aged 65 years or older (ref: younger than 65 years) | 0.30 | 0.21-0.45 | <.001 | 0.45 | 0.30-0.68 | <.001 | 2.07 | 1.36-3.14 | <.001 | 1.88 | 1.28-2.75 | <.001 | |||||
| Internet | 3.62 | 2.07-6.33 | <.001 | 2.53 | 1.63-3.92 | <.001 | 0.38 | 0.19-0.78 | <.001 | 0.47 | 0.32-0.69 | <.001 | |||||
| Provider | 1.23 | 0.82-1.84 | — | 0.54 | 0.40-0.71 | .001 | 1.50 | 0.93-2.40 | — | 2.26 | 1.71-2.99 | <.001 | |||||
| Family and friends | 0.38 | 0.20-0.70 | .003 | 0.74 | 0.40-1.36 | — | 1.41 | 0.62-3.21 | — | 0.88 | 0.49-1.57 | — | |||||
| High health literacy (ref: low health literacy) | 0.71 | 0.48-1.06 | — | 1.31 | 0.94-1.83 | — | 1.47 | 0.87-2.49 | — | 0.84 | 0.59-1.18 | — | |||||
aStudy outcome actual source (provider and internet) for health information was measured by HINTS A2.
bc-statistic was used to evaluate the goodness of fit of the models. We reported the range of c-statistics for each set of the models using 10 imputed datasets: (1) internet as the actual source: 0.788-0.804; (2) internet as the hypothetical source: 0.729-0.743; (3) provider as the actual source: 0.721-0.751; (4) provider as the hypothetical source: 0.685-0.696.
cStudy outcome hypothetical source (provider and internet) for health information was measured by HINTS A8.
dAOR (adjusted odds ratios): logistic regression model adjusted for gender, age group, marital status, education, perception on the importance of patient accessing personal health record, income, health insurance, having a regular provider, owning any mobile device, general health status, and electronic medical record system.
Association between disability types and use of health information.
| Type of disability | Seeking information from internet as actual source | Seeking information from provider as actual source | Exchanging health information with provider | ||||||
| AORa | 95% CI | AORa | 95% CI | AORa | 95% CI | ||||
| Hearing | 0.58 | 0.32-1.06 | — | 1.75 | 0.78-3.90 | — | 1.09 | 0.76-1.56 | — |
| Vision | 0.27 | 0.11-0.65 | .003 | 1.62 | 0.51-5.10 | — | 1.55 | 0.99-2.43 | — |
| Cognition | 0.69 | 0.37-1.27 | — | 1.21 | 0.58-2.52 | — | 1.15 | 0.89-1.48 | — |
| Mobility | 0.51 | 0.30-0.88 | .02 | 1.60 | 0.89-2.85 | — | 1.16 | 0.87-1.53 | — |
| Self-care | 0.46 | 0.17-1.27 | — | 2.50 | 0.80-7.86 | — | 1.27 | 0.77-2.10 | — |
| Independent living | 0.55 | 0.25-1.25 | — | 1.67 | 0.67-4.14 | — | 1.47 | 0.94-2.29 | — |
aAOR (adjusted odds ratios): logistic regression model for each disability subgroup, with reference group as participants without any disability, adjusted for gender, age group, marital status, education, health literacy, trust toward information sources (provider, family and friends, internet, media, government health agencies, charitable or religious organizations), perception on the importance of patient accessing personal health record, income, health insurance, having a regular provider, owning any mobile device, general health status, and electronic medical record system.