Patterns and Correlates of Internet Use,Cell Phone Use,and Attitudes Toward Patient Portals Among a Predominantly Mexican-American Clinic Population

Abstract

Objectives:

The purpose of this study was to describe access and health-related use of the Internet and cell phones, and attitudes toward patient portals among a predominantly Hispanic patient population residing along the U.S.-Mexico border.

Methods:

A bilingual cross-sectional survey was conducted in two clinics to describe use and attitudes toward use of Web 2.0 technology for health-related activities. Univariate and multivariable analyses were conducted to identify factors associated with past Web 2.0 use and willingness to use these technologies in the future.

Results:

Two hundred and one participants were recruited (response rate: 53.3%). Respondents had an average age of 61.5 years, were predominantly female (63.2%), Hispanic (71.6%), of low income (93.0% <$25,000), and low educational attainment (49.8% <high school). 44.8% reported Internet access and 39.3% reported Internet use. Barriers identified included access (80%) and not knowing how to use the Internet (76.5%). A majority (98.5%) reported having a cell phone available in their house and 76.5% had used a cell phone. 16.3% had heard of a patient portal; 94.5% agreed it was a good idea to review medical records, but only 49.2% thought it was a good idea to review medical records online. In multivariable analyses, younger age (p < 0.001) and higher health literacy were associated with willingness to use patient portals and younger age with text messaging.

Conclusion:

Significant barriers to use of Web 2.0 exist; incorporating Web 2.0 strategies into healthcare may still leave certain populations underserved.

Background

Web 2.0 is Internet capability with a dynamic interface such that anyone accessing a Webpage can change the page, and has been proposed as a strategy to address health disparities.¹ National data at the time of the study revealed that 81% of Americans used the Internet. However, there were differences in use by racial/ethnic group: 84% of white, non-Hispanics, 73% of black, non-Hispanics, and 74% of Hispanics used the Internet.² Type of health insurance has been associated with Internet use, with 50% of private pay individuals, 41% of Medicaid patients, and 20% of Medicare patients using the Internet.³ Among Hispanics, differences are seen by birth country (81% of U.S.-born Latinos use the Internet compared to 54% of foreign-born Latinos), and by language (47% of Spanish Language-dominant Latinos use the Internet compared to 74% of bilingual Latinos and 81% of English-dominant Latinos).⁴ In addition, age, income, and education all play a significant role in the use of Internet among Hispanics.^4,5 A higher proportion of the population use cell phones to access the Internet, but disparities in use still remain (85% of white non-Hispanics, 79% of black non-Hispanics, and 76% of Hispanics use a cell phone for Internet access).⁴ This phenomenon of differential use by different groups calls into question the likely success of Web 2.0 technology in addressing disparities in healthcare. Hispanics do depend more on their cell phones, since a higher proportion forgo a landline (35% of Hispanics do not have a landline in their homes compared to 23% of whites and 29% of blacks).⁴

Despite the concerns of a growing “digital divide,” there is still an emphasis for increased Internet capabilities within healthcare. While patient portals are still in their infancy, evidence has shown mixed attitudes of patients and physicians for portal use, as well as barriers to use.^6

–10 Text messaging has been used on a small scale and might be comparable to portal capabilities.³ There are relatively few studies reporting outcomes for health promotion interventions using Web 2.0, and even fewer have been implemented in minority populations.¹ While Internet and Web 2.0 technology show some promise in potentially improving the health of patients and communities, more information is needed regarding attitudes and barriers to access and use of Internet, cell phone, and patient portals, particularly among minority patients and those of lower socioeconomic status. The purpose of this study was to better understand the prevalence of Internet technology use, identify barriers to use, and describe attitudes toward a patient portal and healthcare interventions incorporating interactive Internet technology in a low-income, predominantly Hispanic population along the United States-Mexico border.

Materials and Methods

Study Population and Setting

The study was conducted in two university-based outpatient clinics situated in a county with Hispanics comprising 81% of the population. Prior Institutional Review Board approval was obtained. The participants were individuals who walked in or had an appointment at either the university-based Family Medicine clinic or the Internal Medicine clinic. Inclusion criteria were any person in the clinic waiting room older than 18 years, who was of sufficient mental capacity to answer questions.

Procedure

Participants were approached for the study in waiting areas of the Texas Tech University Health Sciences Center clinics. Study personnel were trained on delivery of the survey and on assisting subjects to complete the survey, if needed, in either English or Spanish. After obtaining oral informed consent, the patient completed the survey themselves or with the help of the study personnel.

Instrument

The bilingual survey contained 84 questions and assessed 10 interrelated constructs. Internet access was evaluated with “Do you have access to the Internet (this can be at home, your work, a library, your cell phone or anywhere)?”¹¹ Internet use was evaluated with 15 questions that evaluated frequency of use, the language of searches, and the types of activities it is used for.^3,4,9,12 Barriers to access were evaluated with the question, “If you do not access the Internet, which of the following are reasons for this?” and they selected from a range of seven options (e.g., lack of interest, cost, complexity, trust, knowledge, etc.).⁹ Cell phone use was evaluated with seven questions covering frequency of use, type of use (e.g., Internet, texting, apps, video calling, etc.), and type of use related to health.^3,4 Attitudes toward sharing medical records in general and online were evaluated with the question, “Now I'm going to ask you some questions about how you would feel if your doctors routinely shared your clinic medical records with you … Answer how much you agree with the following statements (do you strongly disagree, disagree, agree, or strongly agree),” and then they were presented with 19 statements to consider, for example, “I would find the lab and X ray reports confusing, or I would better understand my medical conditions, etc.”¹⁰

For patient portal assessment, we presented the following brief description: “Patient Portals are healthcare-related online applications that allow patients to interact and communicate with their healthcare providers. Patients can make appointments, ask questions, request refills, receive messages and reminders, view lab results and parts of their medical record securely over the Internet,” and then asked patients whether they had previously heard of a portal and elicited whether they would use a patient portal or text messaging for each of the following activities: communicating with their healthcare provider, medication management, send home readings, appointment scheduling, requesting refills, or viewing test results.^3,4,13 Health literacy was evaluated with three questions from a previous survey.^14,15 Computer literacy was evaluated with one adapted question.¹⁶ Acculturation was evaluated with the brief acculturation scale for Hispanics.¹⁷ Demographic information was evaluated, including gender, age, self-reported race and ethnicity, income, and level of education. All items were translated into Spanish and then back translated by a certified translator to ensure accuracy; any differences were resolved by discussion.

Analysis

The results were summarized using descriptive statistics. Health literacy was scored from three items in which the responses were scored from 1 to 5. A composite score from the items was determined so that the final score was 3–15. Any score that summed to <12 was deemed inadequate.¹⁵ The computer literacy score was calculated by self-reported confidence in computer skills from 1 to 10.¹⁶ Acculturation was calculated using the acculturation Index. The score is created by summing the values of the item responses and dividing the sum by the number of items with response. The items summarized four factors: the linguistic capabilities of the participant in English and in Spanish, that is, (1) speaking and reading capabilities in general, (2) speaking language at home, (3) in which language they think, and (4) the language the person speaks with their current friends.¹⁷

The survey data were collected using Microsoft Infopath 2010 survey collection software and inputted into Excel, and subsequently analyzed using IBM SPSS version 22.0. Bivariate analyses were conducted to understand factors (e.g., gender, age, education, income, primary language, nativity, and chronic health conditions) associated with Web 2.0 use and barriers to the uptake of this technology. Any variable significant at p < 0.2 was included in the multiple regression model.

Results

Of 375 patients approached, 201 completed the survey for a 53.3% response rate. The average age of the 201 participants was 61.5 years with the range being 18–94 years (Table 1).

Table 1.

Demographic Profile of Participants

N = 201	FREQUENCY, n (%)
Age mean (years), (SD)	61.4 (17.3)
Gender
Female	127 (63.2)
Male	74 (36.8)
Race/ethnicity
Asian	2 (1.0)
Hispanic	144 (71.6)
Non-Hispanics Black	26 (12.9)
Non-Hispanics White	29 (14.5)
Income
<$10,000	57 (28.3)
$10,000–$15,000	49 (24.4)
$15,000–$20,000	50 (24.9)
>$20,000	45 (22.4)
Education
Less than high school diploma	100 (49.7)
At least a high school diploma	101 (50.3)
Acculturation status
Low acculturation <3	109 (54.8)
High acculturation >3	89 (45.2)
Health literacy mean score (0–12)	3.48 (2.56)
Computer literacy, mean, SD (1–10)	3.98 (3.53)
Health status
Excellent	3 (1.5)
Very good	42 (20.9)
Good	105 (52.2)
Fair	50 (24.9)
Poor	1 (0.5)
Chronic diseases
High BP	128 (63.7)
High cholesterol	116 (57.7)
Osteoarthritis	65 (32.3)
Diabetes	53 (26.4)
Asthma	52 (26.1)
Obesity	46 (23.0)
Depression	46 (22.9)
Gastric reflux	44 (22.0)
Anxiety	41 (20.4)
Thyroid disease	33 (16.5)
Cancer	15 (7.5)
Heart disease	5 (2.5)
Heart attack	5 (2.5)
Stroke	3 (1.5)
Other	55 (28.1)

BP, blood pressure; SD, standard deviation.

Internet Access and Use

Of the 201 surveyed, 44.8% (n = 90) said they had access to the Internet, and only 39.3% (n = 79) said that they use the Internet. In univariate analysis, factors associated with greater Internet use were younger age (p < 0.001), female gender (p < 0.01), higher income (p < 0.001), education above high school (p < 0.001), high acculturation status (p < 0.001), higher self-reported health status (p < 0.001), and greater health literacy (p < 0.001) (Table 2). Of those using the Internet (n = 79), 60.8% (n = 48) searched the Internet in English, 19.0% (n = 15) in Spanish, and 20.3% (n = 16) in both Spanish and English. The majority, 91.1–93.7%, used it for e-mail, news, or researching a product, service, or a map. Health-related activities it was used for included finding information about specific diseases (96.2%, 76/79), treatment or procedure (88.3%, n = 68/77), a doctor (74.7%, n = 59/79), hospitals (63.3%, n = 50/79), insurance (52.6%, n = 41/79), and test results (50.6%, n = 40/79). Participants also used the Internet to view online videos (70.9%, n = 56/79) related to health and medical issues, and 58.2% (n = 46/79) read about other people's health experiences. In this survey, 69.6% (n = 55/79) of Internet users participate in social networking, and of these, 29.1% (n = 16/55) use it to get health information, 23.6% (n = 13/55) use it to follow an acquaintance's health, and 30.9% (n = 17/55) have used it to memorialize others.

Table 2.

Univariate Analysis: Demographic Characteristics and Internet Use

	USE INTERNET
N = 201	YES, n (%)	NO, n (%)	FISHER EXACT TEST p-VALUE
Gender			0.007
Male	20 (27.0)	54 (73.0)
Female	59 (46.5)	68 (53.5)
Age			<0.001^a
18–45 Years	41 (95.3)	2 (4.7)
46–75 Years	37 (33.6)	73 (66.4)
>75 Years	0 (0)	47 (100)
Race/ethnicity			0.522
Hispanic	59 (41.0)	85 (59.0)
Non-Hispanic	20 (35.1)	37 (64.9)
Education			<0.001^a
Less than high school	15 (15.0)	85 (85.0)
High school or more	64 (63.4)	37 (36.6)
Acculturation status			<0.001
Low acculturation (<3)	28 (25.9)	80 (74.1)
High acculturation (>3)	50 (56.2)	39 (43.8)
Health status			<0.001
Poor/fair	8 (15.7)	43 (84.3)
Very good/good/excellent	71 (47.3)	79 (52.7)
Health literacy status			<0.001
Adequate	62 (81.6)	14 (18.4)
Inadequate	17 (13.6)	108 (86.4)

Pearson's chi-square analysis.

Barriers to Internet Use

When participants not using the Internet (N = 122) were asked for reasons why they did not use the Internet, 80% (n = 96/122) reported not having a computer and 76.5% (n = 91/119) reported not knowing how to use the Internet. Other barriers included it was too complicated (39.2%, n = 47/120), did not trust the information (16.0%, n = 19/119), or have no interest in using it (26.7%, n = 32/120). Finally, all participants who participated in the survey (n = 201) were asked whether they would schedule appointments using the Internet; only 31.8% (n = 64/201) said they would.

Cell Phone Access and Use

A majority, 98.5% (n = 198/201), of participants reported to have a cell phone in their home, and 76.5% (n = 153/201) had used the cell phone. Of those using a cell phone, 41.8% (n = 64/153) used it for e-mail, for text messaging (64.2%, n = 97/151), to access Internet (46.1%, n = 70/152), for instant messaging (39.9%, n = 61/153), for video call (14.4%, n = 22/153), and to access health applications (22.9%, n = 35/153). Out of the total number of participants, 33.7% (n = 65/193) reported they would schedule an appointment by text messaging, and 44.6% (N = 195, n = 87/195) said they would use text messaging to communicate with the doctor.

Attitudes to Sharing Medical Information

When all participants were asked about attitudes for viewing medical information, 94.5% (n = 190/201) agreed it is a good idea to review medical records and 93.5% (n = 188/201) of participants were interested in reviewing their own medical records, whereas 49.2% (n = 98/199) of participants believed it is a good idea to review their own medical record online and 47.7% (n = 95/199) of participants have an interest in reviewing their own medical record online. Hispanic subjects were more likely to have favorable attitudes to viewing their own records in general (48.6% vs. 42.1%, p < 0.02) and online (49.3% vs. 44.4%, p < 0.05).

When participants with Internet access (N = 79) were asked about attitudes toward sharing medical records, 94.9% (n = 75/79) felt that it is a good idea to routinely review their own medical records and 94.9% (n = 75/79) were interested in reviewing own medical records. Other commonly reported attitudes were feeling they would better understand their medical conditions (93.7%, n = 74/79), feeling they would be more in control of medical care (92.4%, n = 73/79), and feeling more reassured (91.2%, n = 72/79) (Table 3).

Table 3.

Attitudes About Sharing Medical Information

N = 79	AGREEMENT, N (%)
I would find the doctors' notes in the medical records confusing	61 (77.2)
I would find the lab and X-ray reports confusing	63 (79.7)
I would be better prepared for my doctor visits	71 (89.9)
I would trust my doctor more	69 (87.4)
I would contact my doctors' offices with more questions between visits	45 (56.9)
I would read things that would make me worry more	55 (69.6)
I would better understand my medical conditions	74 (93.7)
I would better understand my doctors' instructions	69 (87.3)
I would be embarrassed or offended by some of the things that my doctors wrote about me	8 (10.7)
I would help to identify significant factual errors in the medical record	61 (77.2)
I would feel more reassured	78 (91.2)
I would be better at following my doctors' recommendations	65 (82.3)
I would feel more in control of my medical care	73 (92.4)
I would be more satisfied with my medical care	72 (91.1)
I would be able to find mistakes that my doctors could correct in the records	61 (77.3)
Overall, I think it is a good idea for patients to be able to routinely review their clinic medical records	75 (94.9)
I would be interested in reviewing my own clinic medical records	75 (94.9)

When all participants were asked about barriers to accessing medical records online, participants stated the following: no computer at home (50.8%, n = 98/193), did not know how to use it (46.4%, n = 89/192), it is too complicated (25.9%, n = 50/193), do not trust the information (15.5%, n = 30/193), and they have no interest in using it (14.1%, n = 27/192).

Attitudes to Patient Portal Use

After a brief description of patient portals, all participants were asked if they had ever heard of them previous to the description and only 16.3% (n = 32/196) reported that they had. 35.8% (n = 80/201) agreed that they would use a patient portal through the Internet or for managing their healthcare, with a range of 35.8–39.8% for different healthcare-related tasks (Table 4).

Table 4.

Likelihood of Patient Portal Use in the Future

	PATIENT PORTAL	TEXT MESSAGING
n = 201	YES, n (%)	YES, n (%)
Communicate with doctor (n = 196)	78 (38.8)	83 (41.3)
Manage medications (n = 201)	78 (38.8)	81 (40.3)
Send health information (n = 201)	77 (38.3)	78 (38.8)
Get health information (n = 201)	80 (39.8)	83 (41.3)
Appointment scheduling (n = 201)	72 (35.8)	75 (37.3)
Request refills (n = 201)	79 (39.3)	85 (42.3)
View test results (n = 199)	76 (38.2)	76 (37.8)

Factors associated with willingness to use patient portals in univariate analyses were younger age (p < 0.001), higher income (p < 0.001), education above high school diploma (p < 0.001), higher acculturation status (p < 0.001), better self-reported health status (p = 0.001) and adequate health literacy status (p < 0.001), and higher computer literacy, and in multivariable analyses were age between 18 and 45 years (p < 0.001), income higher than $10,000, and adequate health literacy (p < 0.001) (Table 5).

Table 5.

Univariate and Multivariable Regression: Predictors of Willingness to Use Patient Portal for Healthcare

	UNIVARIATE			MULTIVARIABLE
VARIABLE	ODDS RATIO	95% CI	p	ODDS RATIO	95% CI	p
Gender
Male	1.0			1.0
Female	1.98	1.08–3.65	0.027	1.85	0.70–4.88	0.21
Age
18–45 Years	1.0			48.0	7.45–310.17	<0.001
46–75 Years	0.050	0.01–0.15	<0.001	2.77	0.78–9.80	0.113
>75 Years	0.010	0.00–0.04	<0.001	1.0
Race/ethnicity
Non-Hispanic	1.0
Hispanic	1.32	0.69–2.49	0.391
Income
<$10,000	1.0			1.0
$10,000 to <$25,000	13.66	4.67–39.95	<0.001	7.94	1.76–35.76	0.007
≥$25,000	33.12	7.08–154.8	<0.001	25.18	2.140–264.31	0.007
Education
Less than high school	1.0			1.0
High school or more	8.09	4.18–15.64	<0.001	1.18	0.33–4.17	0.791
Acculturation status
Low acculturation <3	1.0			1.0
High acculturation >3	3.04	1.68–5.49	<0.001	0.50	0.15–1.65	0.256
Health status
Poor/fair	1.0			1.0
Very good/good/excellent	3.58	1.67–7.68	0.001	1.08	0.34–3.41	0.884
Health literacy status
Inadequate	1.0			1.0
Adequate	22.68	10.73–47.87	<0.001	11.09	3.80–32.33	<0.001
Health literacy score	2.29	1.83–2.86	<0.001
Computer literacy score	2.14	1.80–2.55	<0.001

CI, confidence interval.

A slightly higher percentage reported they would use text messaging for the same activities, but this percentage also hovered around 40%. Factors associated with willingness to use text messaging in univariate analyses were younger age (p < 0.001), higher income (p < 0.001), education above high school diploma (p < 0.001), higher acculturation status (p = 0.001), higher self-reported health status (p = 0.001), and adequate health literacy (p < 0.001), and in multivariable analysis was age (p < 0.001) (Tables 6 and 7).

Table 6.

Intention to Use Patient Portal or Text Messages for Patient Care

	WILLING TO USE PATIENT PORTAL, n (%)			WILLING TO USE TEXT MESSAGES, n (%)
n = 201	YES	NO	FISHER EXACT TEST p VALUE	YES	NO	FISHER EXACT TEST p VALUE
Gender			0.010			0.007
Male	20 (27.4)	53 (72.6)		22 (31.0)	49 (69.0)
Female	58 (46.4)	67 (53.6)		62 (51.2)	59 (48.8)
Age			<0.001			<0.001
18–45 Years	39 (90.7)	4 (9.3)		40 (93.0)	3 (7.0)
46–75 Years	36 (32.7)	74 (67.3)		44 (41.1)	63 (58.9)
>75 Years	4 (8.5)	43 (91.5)		2 (4.5)	42 (95.5)
Race/ethnicity			0.427			0.874
Hispanic	60 (41.7)	84 (58.3)		63 (45.3)	76 (54.7)
Non-Hispanic	20 (35.1)	37 (64.9)		24 (42.9)	32 (57.1)
Income			<0.001			<0.001
<$10,000	4 (7.0)	53 (93.0)		7 (12.7)	48 (87.3)
$10,000 to <$25,000	66 (50.8)	64 (49.2)		71 (56.3)	55 (43.7)
≥$25,000	10 (71.4)	4 (28.6)		9 (64.3)	5 (35.7)
Education			<0.001			<0.001
Less than high school	17 (17.0)	83 (83.0)		19 (20.0)	76 (80.0)
High school or more	63 (62.4)	38 (37.6)		68 (68.0)	32 (32.0)
Acculturation status			<0.001			0.001
Low acculturation <3	31 (28.7)	77 (71.3)		35 (34.0)	68 (66.0)
High acculturation >3	49 (55.1)	40 (44.9)		52 (59.1)	36 (40.9)
Health status			0.001			0.001
Poor/fair	10 (19.6)	41 (80.4)		12 (24.0)	38 (76.0)
Very good/good/excellent	70 (46.7)	80 (53.3)		75 (51.7)	70 (48.3)
Health literacy status			<0.001			<0.001
Adequate	61 (80.3)	15 (19.7)		60 (78.9)	16 (21.1)
Inadequate	19 (15.2)	108 (84.8)		27 (22.7)	92 (77.3)

Table 7.

Multivariable Regression: Predictors of Willingness to Use Text Messages from Health Providers

	UNIVARIATE			MULTIVARIABLE
VARIABLE	ODDS RATIO	95% CI	p	ODDS RATIO	95% CI	p
Gender
Male	1.0			1.0
Female	2.10	1.14–3.84	0.016	1.16	0.48–3.26	0.767
Age	0.857	0.82–0.89	<0.001	0.88	0.83–0.94	<0.001
Race/ethnicity
Non-Hispanic	1.0
Hispanic	1.10	0.59–2.06	0.754
Income
<$10,000	1.0			1.0
$10,000 to <$25,000	8.85	3.71–21.07	<0.001	5.57	1.22–25.38	0.026
≥$25,000	12.34	3.19–47.63	<0.001	3.58	0.33–37.91	0.289
Education
Less than high school	1.0			1.0
High school or more	8.50	4.41–16.36	<0.001	1.50	0.36–6.18	0.571
Acculturation status
Low acculturation <3	1.0			1.0
High acculturation >3	2.80	1.55–5.05	0.001	0.58	0.15–2.27	0.582
Health status
Poor/fair	1.0			1.0
Very good/good/excellent	3.39	1.64–7.01	0.001	0.67	0.20–2.24	0.524
Health literacy status
Inadequate	1.0			1.0
Adequate	12.77	6.35–25.69	<0.001	1.36	0.34–5.43	0.664
Health literacy score	1.86	1.56–2.23	<0.001
Computer literacy score	1.78	1.55–2.04	<0.001	1.12	0.87–1.44	0.370

Discussion

The results of this study reveal that less than half of this socioeconomically challenged population uses the Internet, with no ethnic group differences noted. This is primarily due to lack of access and not knowing how to use it, and less so because of attitudinal barriers. Those who are using the Internet do look up pertinent healthcare-related information; however, the limited audience that uses the technology minimizes the overall effect of the technology on the community. Similar to other studies among Latino populations, we observed a high rate of cell phone use,^1,2,4,5 as well as text messaging and accessing the Internet. The high rates of text messaging expected, and reported in this study, suggest possible utilization of text messaging in future health-related interventions.^4,5 Although we observed very positive attitudes for accessing one's medical record, study participants showed less interest in actually examining their own medical record through the Internet. We observed low awareness of patient portals and less than half indicated wanting to use the Internet or cell phones to access their medical records or to conduct other healthcare activities. Furthermore, patterns of use and attitudes toward future use indicate that the most vulnerable, that is, those of lower educational level, lower socioeconomic status, poorer health and inadequate health literacy, and older participants were least likely to use the Internet, and were less likely to show interest in using patient portals through cell phone or Internet.

Our findings are consistent with other studies for access and use patterns, including decreased access among a vulnerable patient population and increased cell phone access and use among a Latino population.^1,4,7,18 As for patient portals, recent studies suggest limitations within portal designs and usability, which make portals less compatible for patient and provider needs, which might be a contributing factor as to why our population seemed unconvinced by the patient portal capabilities we provided.^7,18 With the increased use of patient portals across healthcare, it is important to understand predictors of willingness to use the portal among all populations. Our assessment of attitudes and barriers to access medical records yielded interesting results. While almost all patients interviewed generally had positive attitudes toward medical records review, they were less inclined to want to review their own records online. Since we observed that lack of awareness and logistic issues were greater barriers than attitudes, it suggests that avenues for future interventions should focus on raising awareness of patient portals, and on enhancing Internet access and skills rather than on attitudinal barriers. Furthermore, since there is an increased use of cell phones to access the Internet, it seems that the patient portal design and usability should be directed to accommodate these modalities, which individuals in this community more commonly use.

The similarity in opinions about future use of Internet-based patient portal access and text messaging to perform all of the listed healthcare tasks was surprising and could be caused by a few things. First, having never used a patient portal, it is difficult to imagine what the technology is like, making the answers similar to the familiar text messaging. Second, the items listed were not things that people were interested in using; so there is a mid-range of positive responses because those responding were uncertain. Last, this shows a true representation, and there is no difference between whether someone would use the patient portal or text messaging for some tasks.

The strengths of our study are that this is one of the first to focus on a largely Hispanic population with a full spectrum of ages included, the questions were available in English and Spanish, and they covered comprehensive array of Web 2.0 modalities, in addition to the patient portal. Limitations of the study are that the cross-sectional design limits inferences about cause and effect, the information was self-reported and may be open to recall bias, and the sampling was by convenience, so may not be representative of the population, although the response rate was above 50%. The study was conducted in two clinics on the border, so provides valuable information about similar populations but may not be generalizable to other populations.

In conclusion, we found that although Web 2.0 holds promise for addressing health disparities, the most vulnerable members of the population may be less likely to access Web 2.0 or to express willingness to use these technologies for their health management, largely because of logistical barriers as opposed to attitudinal barriers. Therefore, to optimize the potential of Web 2.0 for addressing health disparities, future intervention should include a focus on logistical barriers.

Footnotes

Disclosure Statement

No competing financial interests exist.

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