| Literature DB >> 24152542 |
Robert Arthur Dudas1, Michael Crocetti.
Abstract
BACKGROUND: Overall usage of email communication between patients and physicians continues to increase, due in part to expanding the adoption of electronic health records and patient portals. Unequal access and acceptance of these technologies has the potential to exacerbate disparities in care. Little is known about the attitudes of pediatric caregivers with regard to their acceptance of email as a means to communicate with their health care providers.Entities:
Keywords: communication; electronic mail; email; health care disparities; pediatrics; primary health care
Mesh:
Year: 2013 PMID: 24152542 PMCID: PMC3806434 DOI: 10.2196/jmir.2738
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Figure 1Survey response flow diagram.
Caregiver demographics by email usage (N=229).
| Variable | Do you ever use email to communicate with others? |
| ||
|
| Yes (n=171) | No (n=58) |
| |
| Mothers surveyed, n (%) | 140 (82.3)a | 41 (70.6) | .06 | |
| Age (years), mean (SD) | 33.3 (9) | 34.1 (12) | .51 | |
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| African-American | 74 (43.2) | 31 (53.4) | .22 |
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| Caucasian | 80 (47.3) | 25 (43.1) | .65 |
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| Other | 17 (9.9) | 2 (3.4) | .17 |
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| < High school | 13 (7.6)a | 10 (18.1)b | .04 |
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| High school (GED) | 72 (42.3)a | 37 (67.3)b | .44 |
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| College or greater | 86 (50.6) a | 8 (14.5) b | <.001 |
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| ≤20,000 | 34 (20.0)a | 28 (50.9)b | <.001 |
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| 20,001 - 40,000 | 44 (25.9)a | 9 (16.4)b | .20 |
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| > 40,000 | 59 (34.7)a | 1 (1.8)b | <.001 |
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| Don’t know/refuse | 33 (19.4)a | 17 (30.9)b | .09 |
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| Commercial/private | 90 (56.2)c | 18 (32.7)b | .003 |
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| Medicaid | 61 (38.1)c | 27 (49.1)b | .16 |
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| None | 1 (0.6)c | 0 (0.0)b | .99 |
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| Don’t know/refuse | 8 (5.0)c | 10 (18.2)b | .004 |
aPercentages calculated based on 170 responses.
bPercentages calculated based on 55 responses.
cPercentages calculated based on 160 responses.
Practices of email users.
| Variable | Frequency, n (%) | |
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| |
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| Daily or more | 102 (60.0) |
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| Few times weekly | 35 (20.6) |
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| Weekly or less | 33 (19.4) |
| Would like to email child’s doctor (yes)b | 145 (86.3) | |
| Communicates currently with child’s doctor by email (yes)b | 18 (10.7) | |
aPercentages based 170 responses.
bPercentages based on 168 responses.
Email users attitudes toward email communication with doctors (n=171).
| Variable | Frequency of agreement, n (%) |
| More doctors should offer email communication | 135 (78.9) |
| Email would increase contact with my child’s doctora | 131 (77.1) |
| Email would distance us from my child’s doctor | 19 (11.1) |
| Email would improve communication with my child’s doctora | 125 (73.5) |
| Email with my child’s doctor would be satisfying | 131 (76.6) |
| Email would be a good/easy way to make appointmenta | 130 (76.5) |
| Email hackers are a worrya | 58 (34.1) |
aPercentage calculated based on 170 responses.
Email communication to discuss common pediatric conditions (N=171).
| Pediatric condition | Agreement, n (%) |
| Cold symptoms | 141 (82.5) |
| Earache | 139 (81.3) |
| Sleep | 136 (79.5) |
| Weight issues | 136 (79.5) |
| Fever | 135 (78.9) |
| Constipation | 133 (77.8) |
| Diarrhea | 133 (77.8) |
| Vomiting | 129 (75.4) |
| Feeding/diet | 134 (78.4) |
| Safety topicsa | 133 (78.2) |
| Pink eye | 131 (76.7) |
| Toilet trainingb | 129 (76.3) |
| Immunizations | 125 (73.1) |
| Colicb | 121 (71.6) |
| Behavior | 121 (70.8) |
| Developmenta | 120 (70.6) |
aPercentages calculated based on 170 responses.
bPercentages calculated based on 169 responses.
Logistic regression of email users’ attitudes as a function of age, education level, insurance type, family income, and race.
| Covariate (n) | Agreement | ||
|
| OR (95% CI) | Adjusteda OR (95% CI) | |
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| Caregiver age | 1.05 (1.00-1.09) | 1.00 (0.94-1.08) |
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| Completed > high school | 3.45 (1.54-7.72) | 2.28 (0.88-5.91) |
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| Medicaid insurance | 0.47 (0.22-1.02) | 0.75 (0.30-1.9) |
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| Income ≤ US $30,000 | 0.17 (0.07-0.43) | 0.26 (0.09-0.74) |
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| African-American race | 0.40 (0.19-0.85) | 0.34 (0.14-0.82) |
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| Caregiver age | 1.02 (0.98-1.06) | 1.02 (0.96-1.09) |
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| Completed > high school | 1.92 (0.92-3.99) | 1.33 (0.56-3.17) |
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| Medicaid insurance | 0.64 (0.30-1.35) | 0.73 (0.31-1.72) |
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| Income ≤ US $30,000 | 0.43 (0.20-0.92) | 0.59 (0.24-1.45) |
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| African-American race | 0.38 (0.18-0.79) | 0.41 (0.19-0.91) |
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| Caregiver age | 0.95 (0.89-1.01) | 0.95 (0.87-1.05) |
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| Completed > high school | 0.40 (0.15-1.12) | 0.49 (0.13-1.82) |
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| Medicaid insurance | 2.16 (0.79-5.9) | 1.96 (0.56-6.91) |
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| Income ≤ US $30,000 | 3.65 (1.15-11.51) | 1.51 (0.39-5.88) |
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| African-American race | 1.53 (0.59-3.98) | 1.40 (0.46-4.27) |
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| Caregiver age | 1.03 (0.99-1.07) | 1.05 (0.99-1.12) |
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| Completed > high school | 1.82 (0.91-3.63) | 1.37 (0.59-3.20) |
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| Medicaid insurance | 0.83 (0.41-1.68) | 1.10 (0.48-2.52) |
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| Income ≤ US $30,000 | 0.48 (0.24-0.99) | 0.57 (0.24-1.38) |
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| African-American race | 0.45 (0.23-0.90) | 0.49 (0.23-1.04) |
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| Caregiver age | 1.01 (0.97-1.05) | 1.00 (0.95-1.07) |
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| Completed > high school | 2.34 (1.12-4.88) | 1.67 (0.68-4.12) |
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| Medicaid insurance | 0.55 (0.26-1.17) | 0.79 (0.33-1.91) |
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| Income ≤ $30,000 | 0.21 (0.09-0.49) | 0.25 (0.09-0.66) |
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| African-American race | 0.31 (0.15-0.65) | 0.32 (0.14-0.75) |
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| Caregiver age | 1.02 (0.98-1.06) | 0.99 (0.94-1.06) |
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| Completed > high school | 1.78 (0.86-3.65) | 1.90 (0.79-4.58) |
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| Medicaid insurance | 0.91 (0.44-1.90) | 1.39 (0.59-3.29) |
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| Income ≤ US $30,000 | 0.47 (0.23-0.99) | 0.53 (0.21-1.33) |
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| African-American race | 0.41 (0.20-0.85) | 0.40 (0.18-0.88) |
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| Caregiver age | 0.97 (0.94-1.01) | 0.98 (0.93-1.04) |
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| Completed > high school | 0.53 (0.28-1.01) | 0.83 (0.38-1.81) |
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| Medicaid insurance | 1.78 (0.92-3.44) | 1.35 (0.62-2.95) |
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| Income ≤ US $30,000 | 3.06 (1.56-6.02) | 2.21 (0.97-5.02) |
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| African-American race | 1.60 (0.85-3.02) | 1.34 (0.65-2.73) |
aAdjusted for all other covariates in a multiple logistic regression model.