Evaluating Access to Cellphones for Telehealth Among People Experiencing Homelessness

Abstract

Background:

Telehealth has expanded access to health care services, yet its effectiveness relies heavily on access to communication technology, particularly cellphones. People experiencing homelessness (PEH) face significant barriers to technological access, which may limit their ability to engage in telehealth.

Materials and Methods:

This pilot study evaluated cellphone access and barriers to use for telehealth among sheltered and unsheltered PEH at free community clinics in Virginia Beach, Virginia, through an orally administered survey. Differences in the use of telehealth between government-issued cellphone users and nongovernment-issued cellphone users in this population were examined, as well as differences in perceived barriers to cellphone access and telehealth utilization between sheltered PEH and unsheltered PEH.

Results:

Of the 74 participants, 53% reported being sheltered PEH and 47% were unsheltered. Of the sheltered PEH, 97% reported having a cellphone, whereas only 74% of the unsheltered PEH reported having one. Significant barriers to utilization included the cost of devices (p = 0.013), inability to charge phones (p = 0.048), and a lack of mobile data (p < 0.001). Nongovernment cellphone users were more likely to use their cellphones for audio-only telehealth than government cellphone users. The study findings provide insights but, given sample size, they cannot be generalized.

Conclusion:

PEH may have access to a cellphone; however, utilization for telehealth may be limited due to cost and technological barriers, as well as prioritization of texting and phone calls to preserve data. Overcoming these barriers is crucial to making telehealth an equitable health care tool for PEH.

Keywords

telemedicine telehealth ill-housed persons cellphone health services accessibility health equity

Introduction

In the United States, there are over 771,000 people experiencing homelessness (PEH) on any given day.¹ This number represents an 18% increase in homelessness in 1 year.¹ The percentage of the population that experiences homelessness varies by geography, including state, population size, and community demographics. Trend analysis over recent years indicates that this rate continues to rise yearly.¹ In the state of Virginia, it is estimated that over 7,000 individuals experience homelessness.² The fastest growing demographic of the unhoused in the United States and Virginia is those over 60 years of age. This population tends to have the greatest health needs, especially among those who are insecurely housed.³ Access to quality health care is a significant barrier for this population. Unique barriers that impact PEH from achieving equitable health care include negative prior health care experiences, poor health literacy, and a perceived stigma from health care providers.⁴ When compared with low-income and poorly insured populations with stable housing, PEH have a higher prevalence of acute and chronic conditions, poor mental health, and higher mortality rates.³ PEH face higher rates of mental health conditions, substance abuse disorders, sexually transmitted diseases, wound infections, and chronic illnesses like liver disease and hepatitis, diabetes, hypertension, and pulmonary disease.⁵

Telehealth can be a promising solution to enhance health care access for vulnerable populations, including PEH and individuals affected by social determinants of health. It has been shown to be an effective modality of health care delivery, associated with positive outcomes for both patients and providers⁶ while broadening the reach of care, decreasing cost, and improving community health outcomes.^6,7

Studies have shown that up to 94% of PEH have access to cellphones and other digital devices.^8,9 Therefore, utilizing telehealth to increase access to care for PEH may be an option.

Despite telehealth’s success and implementation across regions and populations, PEH often lack adequate access and/or the proper digital knowledge to use telehealth services.¹⁰

Digital literacy considered a “super social determinant of health,” involves skills that help people interact successfully in today’s digital environment.¹¹ It is crucial to equip individuals with necessary skills to access information, obtain essential health care services, and secure employment opportunities. Having a cellphone does not guarantee active involvement in digital activities. Essential tasks, including telehealth visits, employment applications, and access to government services, are difficult to complete on mobile-only devices.¹² Individuals experiencing digital exclusion frequently rely on outdated, basic phones or shared devices, limiting functionality and privacy.¹³

Effective use of technology requires digital skills, including navigating online platforms, evaluating information, and protecting personal data. Limited digital skills are associated with reduced access to health care and other essential services.¹⁰ Access to technical support is critical, as disruptions in device or connectivity functions can rapidly impede care and service access.¹⁴

Broadband access must be sufficient in speed, reliability, and capacity to support activities such as telehealth. Affordability remains a primary barrier to adoption, particularly in low-income households, perpetuating disparities in health and economic opportunity.¹⁵

PEH encounter distinct barriers to digital access that limit the practicality of telehealth and other online health services. Although cellphone ownership is common, access is often unstable due to frequent device loss or theft, limited charging options, reliance on public Wi-Fi, and use of government-issued phones with restricted data and functionality.^16,17 These challenges are further exacerbated by lack of private space for telehealth visits and by limited digital skills and access to technical support.^18,19 As a result, PEH are significantly less likely to engage in internet-based health care services despite elevated health needs, demonstrating that device ownership alone is an inadequate indicator of meaningful digital access.^16,19 Addressing digital inequities for PEH requires interventions that account for housing instability, device sustainability, privacy, and ongoing support rather than narrowly focusing on cellphone distribution.^17,19

Although telehealth has been reported to improve access to health care, it also has the potential to increase health care disparities. This is particularly true for PEH who have cell phones but do not have access to smartphones or data plans. PEH own one of three types of phones: smartphones, basic phones, or prepaid phones.^8,20 The smartphones are often issued through government assistance programs and provide limited data plans.²¹ Basic phones allow primarily for phone calls and texts, and prepaid phones purchased at retail stores have a fixed number of prepaid minutes.²⁰ Recent research shows that although many PEH have mobile devices, there are still digital accessibility issues, with many struggling with affordable data plans, relying on public access to the internet, and public charging stations.²² Vulnerable populations are less likely to own a device with adequate data plans and smartphone applications; some may lack trust in the delivery of health care via telehealth.^23,24 Additionally, studies have demonstrated that vulnerable populations lack the skills needed to effectively use phones beyond calls and text messaging. This includes difficulty navigating applications, setting up email accounts, and managing data plans.²⁵

While prior studies have examined cellphone ownership among PEH, few have evaluated access to mobile data plans or the implications for health care and telehealth engagement. Previous studies have been limited by small samples, single-site designs, and focused on device ownership, ignoring connectivity and digital literacy. Studying PEH is further complicated by housing instability and challenges with recruitment and retention, contributing to a limited evidence base. This study expands on prior studies of cellphone ownership among PEH to evaluate factors that impact the utilization of cellphones for telehealth, including data plan access, cellphone type, private versus government-provided devices, and patterns of health care-related use among sheltered and unsheltered PEH, providing empirical data to inform strategies for equitable telehealth implementation.

Theoretical Framework

This study applied Andersen’s Behavioral Model of Health Services (Phase 4), which takes a dynamic view of health care use.²⁶ The model identifies three key influences: predisposing factors (demographics, social structure, health beliefs), enabling factors (resources, access), and perceived need for services. Here, predisposing factors refer to housing status; enabling factors include access to cellphones/Wi-Fi, data, and digital literacy; perceived need focuses on participants’ views of technology-based health services.

Materials and Methods

STUDY DESIGN

This pilot study utilized a cross-sectional survey conducted between January 2025 and April 2025, with a convenience sample of clients receiving services in two community clinics that provide free health care services to PEH in Virginia Beach, VA.

SETTING

The study took place in Virginia Beach, VA, at free community clinics located in the Housing Resource Center (HRC) and People in Need Ministry (PiN). HRC, funded by the city since 2018, offers shelter, a health clinic, dining, and educational services for those experiencing homelessness.²⁷ PiN, a faith-based nonprofit started in 2002, provides support and job training, with a free clinic added in 2015.²⁸ HRC serves city-housed clients; PiN caters to those insecurely housed or street homeless. Old Dominion University (ODU) faculty and students operate both clinics. These sites were selected due to their connection with ODU. Approximately 300 unique individuals received care during the study period.

PARTICIPANTS

Participants were chosen through convenience sampling from PEH utilizing services at either HRC or PiN over 18-weeks. While waiting for health care or other services, front office staff invited clients to participate in an anonymous survey. Interested individuals were directed to the researchers. To mitigate potential comprehension challenges, the researcher read each consent form aloud to participants, providing explanations and addressing all questions before obtaining written informed consent. The study was conducted using a digital survey on a secure university-issued tablet. To address literacy issues, each survey was read aloud to participants. After obtaining consent, the survey was carried out in a secure environment to preserve privacy. Inclusion criteria included PEH utilizing services at HRC or PiN, aged 18 to 90 years, and English-speaking. Participants did not need to receive health care services in the clinics to meet criteria. Those not meeting inclusion criteria were excluded. After completing the survey, each participant received a 1-day bus pass. The ODU Social and Behavioral Institutional Review Board approved the study.

INSTRUMENTS AND MEASURES

The researcher-developed survey contained 43 questions and took 15–30 min to complete. The first eight questions focused on participant demographics. Nine questions assessed access to cellphones and related access to service and data plans. Eleven Likert scale questions focused on identified barriers to access and use of cellphones. The first four questions focused on digital literacy and assessed confidence in using the cellphone, downloading mobile applications, connecting to Wi-Fi, and troubleshooting the device. Ratings for each item ranged from very confident (1) to not confident at all (3). The next seven questions focused on barriers, including cost, access to mobile data, access to charging the phone, lack of understanding of its use, and feeling unsafe. Each of these items was rated on a 5-point Likert scale ranging between always (1) and never (5). Lower scores indicated a higher frequency of the barrier. The final 15 questions evaluated the purposes for which cellphones were used and included a variety of health care services in addition to texting, phone calls, and email. A subset of these questions evaluated how often the cellphone was used for specific purposes in the form of a 5-point Likert scale ranging from always (1) to never (5).

Face and content validity were established through expert review. Two content experts and one tool development expert reviewed the survey. Before deployment, the survey was also tested with clients of the sites. Changes were made after receiving feedback regarding ease of use and understanding. The digital literacy Likert question set regarding confidence in cellphone use and the Likert question set regarding barriers to use showed good reliability with a Cronbach’s α of 0.808 and 0.815, respectively.

ANALYSIS

Data were analyzed with SPSS 29.0.²⁹ Descriptive statistics summarized the sample’s demographics. To facilitate analysis, variables were recoded to create categories that permitted analysis of nominal data for two groups. The category “government phones” included those who reported Medicaid-eligible or prepaid, while the category “nongovernment phones” included those who reported purchasing their phones and data plans without government assistance.

Results

DEMOGRAPHICS

The study sample included 74 men and women, with the majority (68.9%) being male. The ages ranged from 18 to 68 years, with the mean being 47.8 years. Most participants were white (51.4%), while 40.5% were black, 1.4% were American Indian/Alaska Native, and 6.8% other. The highest levels of education reported included 64.9% high school, 21.6% community college, 5.4% master’s degree, 4.1% middle school, and 4.1% bachelor’s degree. Most of the participants (87.8%) reported having Medicaid/Medicare insurance, while 1.4% had Tricare, and 10.8% reported having no insurance. The participants were all homeless, with 39 reporting being sheltered and 35 reporting being unsheltered (Table 1).

Table 1.

Sample Demographics

VARIABLES	TOTAL
VARIABLES	N	%
Age
18–27 years	3	4
28–37 years	15	20.3
38–48 years	17	23
49–58 years	19	25.7
59–68 years	20	27
Gender
Male	51	68.9
Female	23	31.1
Race/ethnicity
American Indian or Alaska Native	1	1.4
Black or African American	30	40.5
White	38	51.4
Other	5	6.8
Level of education
Middle school (grade 7)	3	4.1
High school (grade 12)	48	64.9
Community or technical college (2-year degree)	16	21.6
Bachelor’s degree (4-year college degree)	3	4.1
Master’s degree	4	5.4
Insurance
Medicare/Medicaid	65	87.8
Tricare	1	1.4
No insurance	8	10.8
Housing arrangement
Sheltered (shelter, transition apartment/home)	39	52.7
Unsheltered (tent, woods, street)	35	47.3
Employment status
Employed	10	13.5
Unemployed, seeking employment	28	37.8
Unemployed, not seeking employment	15	20.3
Disabled	17	5.4
Retired	4	23
Do you have a phone?
Yes	64	86
No	10	14

CELLPHONE ACCESS

Of the 74 participants, 64 reported they had a phone, and 10 reported not having a phone. Among sheltered PEH (n = 39), there were 38 (97%) who reported having a cellphone and 1 (2%) who reported having no cellphone. Among unsheltered PEH (n = 35), there were 26 (74%) who reported having a cellphone and 9 (26%) who reported having no cellphone (Fig. 1). Using the chi-square test, this was a statistically significant difference with a p value of 0.004 (p < 0.01). In this sample, sheltered PEH were more likely to have a cellphone than unsheltered.

Of the sheltered PEH (n = 38), 53% (n = 20) reported having a nongovernment cellphone, while 47% (n = 18) reported having a government cellphone. Of the unsheltered PEH (n = 26), 39% (n = 10) reported having a nongovernment cellphone, while 61% (n = 16) reported having a government cellphone (Fig. 2). There was no significant difference between sheltered and unsheltered PEH and the type of cellphone they had using the chi-square test (p = 0.265).

Of the 38 sheltered PEH who reported having a cellphone, 35 (92%) reported having access to cellular service and 3 (8%) reported having no access to cellular service. Of the 26 unsheltered PEH who reported having a cellphone, there were only 25 responses when asked about having access to cellular service, 21 (84%) reported having access to cellular service, and 4 (16%) responded no to having service (Fig. 3). Using the chi-square test, there was no statistically significant difference in having access to cellular service between sheltered and unsheltered PEH (p = 0.317).

BARRIERS TO CELLPHONE ACCESS AND USE

Most participants report being very confident in using their cellphones (71.6%), downloading apps (64.9%), and connecting to Wi-Fi (74.3%). Participants reported lower levels of confidence related to troubleshooting their devices, with 51.4% being very confident, 23% being somewhat confident, and 12.2% being not confident at all in troubleshooting. The mean total score for cell phone use confidence, encompassing all these factors, was 5.37. The range of possible scores was 4–12, with lower scores indicating a higher level of confidence.

Of the 38 sheltered PEH, participants reported that they were rarely or never unable to use their cellphones because of the cost of device (4.39), cost of apps (4.42), cost of mobile plan (4.24), lack of data (4.18), inability to charge (4.37), knowledge gap (4.58), or feeling unsafe (4.71).

Of the 26 unsheltered PEH, participants reported they were rarely or never unable to use their cellphones because of the cost of apps (4.42), lack of knowledge (4.92), or feeling unsafe (4.58). Participants reported that they were sometimes or rarely unable to use their cellphones because of the cost of device (3.54), cost of mobile plan (3.54), and inability to charge the device (3.62). No mobile data (2.92) was the biggest barrier for the unsheltered PEH.

Using the Mann–Whitney U, there was a significant difference between sheltered and unsheltered PEH related to barriers, including the cost of the device (p = 0.013), no mobile data (p ≤ 0.001), and inability to charge the device (p = 0.048) with unsheltered PEH more likely to report barriers to the use of cellphones than sheltered PEH (Table 2).

Table 2.

Differences in Barriers to Access Between Sheltered and Unsheltered PEH with Cellphones¹

HOW OFTEN WERE YOU UNABLE TO USE YOUR PHONE BECAUSE OF: ²	SHELTERED PEH (N = 38)		UNSHELTERED PEH (N = 26)		Z-SCORE	p-VALUE
HOW OFTEN WERE YOU UNABLE TO USE YOUR PHONE BECAUSE OF: ²	MEAN	SD	MEAN	SD	Z-SCORE	p-VALUE
Cost of device	4.39	0.946	3.54	1.449	−2.484	0.013
Cost of apps	4.42	1.030	4.42	1.301	−0.458	0.647
Cost of mobile plan	4.24	1.240	3.54	1.606	−1.748	0.080
No mobile data	4.18	1.111	2.92	1.495	−3.429	<0.001
Unable to charge	4.37	1.149	3.62	1.602	−1.976	0.048
Knowledge Gap	4.58	1.056	4.92	0.392	−1.515	0.130
Feeling unsafe	4.71	0.898	4.58	1.065	−0.571	0.568

Bold values indicate statistical significance at p < 0.05.

Mann–Whitney U test used for statistical significance, z-score and p values reported.

Likert Scale used (1 = Always, 2 = Often, 3 = Sometimes,4 = Rarely, 5 = Never).

PEH, people experiencing homelessness.

USES OF CELLPHONES

To evaluate cellphone utilization by PEH, the data were first filtered to only participants who reported having a cellphone (n = 64). Crosstabs were then used to describe participants with government (n = 34) and nongovernment (n = 30) cellphones and their use of cellphones. The recoded categories of government phones versus nongovernment phones were then compared using the chi-square test for the data regarding cellphone use.

Of the total 30 participants with nongovernment cellphones, the highest use of cellphones reported was for telehealth audio (60%), email (87%), text messaging (97%), and phone calls (93%). When asked about their use for health apps, telehealth visual, and EMR access, most participants reported they did not use their phones for those health care-related activities. Of the 34 participants with government cellphones, the highest use of cellphones reported was for email (71%), text messaging (91%), and phone calls (91%). The majority of these participants did not use their cellphones for health care-related activities (Table 3).

Table 3.

Differences in Use of Cellphone Between Nongovernment and Government Cellphones^a,b

WHAT DO YOU USE YOUR CELLPHONE FOR?	NON-GOVERNMENT (N = 30)		GOVERNMENT (N = 34)		p-VALUE
WHAT DO YOU USE YOUR CELLPHONE FOR?	YES	NO	YES	NO	p-VALUE
Health apps	4 (13%)	26 (87%)	2 (6%)	32 (94%)	0.307
Telehealth Video	9 (30%)	21 (70%)	10 (29%)	24 (71%)	0.959
Telehealth Audio	18 (60%)	12 (40%)	9 (27%)	25 (73%)	0.007
EMR access	11 (37%)	19 (63%)	6 (18%)	28 (82%)	0.086
Email	26 (87%)	4 (13%)	24 (71%)	10 (29%)	0.120
Text messaging	29 (97%)	1 (3%)	31 (91%)	3 (9%)	0.365
Phone calls	28 (93%	2 (7%)	31 (91%)	3 (9%)	0.748

Bold values indicate statistical significance at p < 0.05.

Crosstabs used to differentiate the data between type of cellphone and use of cellphone.

Chi-square test used to determine statistical significance in the differences between.

EMR, electronic medical record.

When comparing the two groups (nongovernment versus government), the difference was only statistically significant for telehealth audio with a p value of 0.007 (p < 0.05). Therefore, in this sample, nongovernment cellphone users were more likely to use their cellphones for telehealth audio than those with government cellphones (Table 3).

Discussion

This pilot study evaluated cellphone access and perceived barriers in using their phone for telehealth between sheltered and unsheltered PEH. The data are consistent with other research suggesting that although PEH have access to cellphones, there are barriers limiting their use for health care.⁴ Unlike other studies, we evaluated the differences in access and use between nongovernment cell phones and government-issued cell phones. Sheltered PEH are more likely to have access to cellphones than their unsheltered counterparts, but among those who reported having cellphones, there was no significant difference in whether they had access to cellular service or not. There was no significance in the difference between sheltered and unsheltered PEH, and whether they had a government or nongovernment cellphone. Barriers to cellphone utilization for telehealth among PEH include a lack of mobile data, the inability to charge devices, and cost. Our results indicated that nongovernment cellphone users were more likely than government cellphone users to participate in audio-only telehealth. This difference could suggest that because nongovernment cellphones were purchased or provided by family members, they had more minutes to do audio-only telehealth, while government cellphones had limited minutes, resulting in avoidance of use for health-related activities. While digital literacy has been identified as a factor impacting the use of cellphones for telehealth, this study suggests that PEH who own a cellphone are confident in its utilization. Whether this confidence would extend to its use for telehealth applications should be further explored. Overall, the results of this pilot study suggest that PEH have increased barriers to cellphone access and utilization for telehealth and other medical services.

These findings also raise important ethical considerations related to justice and equity in digital health delivery. Global public health guidance emphasizes a moral responsibility to ensure telehealth expansion does not exacerbate existing inequities for structurally vulnerable populations, including PEH.^30,31 When digital access barriers limit telehealth engagement, responsibility for access is effectively shifted onto individuals least able to overcome structural constraints, underscoring the need for equity-oriented policies that address connectivity, device sustainability, and digital support alongside telehealth implementation.³¹

Limitations of this study included the use of convenience sampling and incentivized participation. Bus passes were provided to participants; this may have positively influenced their desire to complete the survey. Additionally, this study was limited to only PEH who utilized services at PiN ministry and HRC. Other factors, including limited tech skills, health literacy, and general literacy, may also affect cellphone use for health activities, but were not evaluated in this study. The small sample size limits generalizability and may not capture the diverse conditions and barriers encountered by PEH. Data were self-reported, which may introduce recall or social desirability bias, and participants were recruited from specific sites, potentially limiting external validity. Finally, the cross-sectional design precludes assessment of causal relationships or longitudinal changes in digital access and health care engagement.

Conclusion

This study demonstrates that telehealth via cellphones is a viable avenue for health care in PEH provided cost, mobile data, and charging capabilities are addressed. PEH may be more likely to use their cellphones for health care services and telehealth if the use does not impact their mobile data limits. Establishing funding to develop artificial intelligence that allows device use for health care, specifically telehealth, without consuming mobile data may benefit this population, leading to increased access to care, lower cost health care utilization, and improved outcomes in PEH. Further research is needed to assess whether lack of knowledge and digital skills would prevent PEH from accessing mobile health care if these barriers are overcome.

Despite its limitations, this study suggests the importance of enhancing digital accessibility by simplifying access to low-cost cellphones, improving data plans and Wi-Fi access, providing public charging stations, simplifying mobile applications, and ensuring easy access to the electronic health record. Most importantly, we advocate for government-issued cellphones to have unlimited data plans for health care applications, communication, and telehealth. Additionally, providing digital training in shelters could improve digital literacy among this vulnerable population. These steps are crucial to advancing health equity and social support for PEH.

Authors’ Contributions

R.A.: Conceptualization, Methodology, Formal Analysis, Investigation, Data Curation, Writing—Original Draft, Visualization. K.G.: Conceptualization, Methodology, Writing—Review and Editing, Supervision, Project Administration, Formal Analysis. G.B.: Investigation. T.G.: Conceptualization, Methodology, Writing—Review and Editing, Supervision, Project Administration.

Footnotes

Acknowledgments

The authors would like to thank Kathryn Apperson, MSN, APRN, FNP-BC, for her contributions to the development of the survey tool used in the study and Dr. Kathie Zimbro, PhD, RN, for her contributions to data analysis. The authors would also like to acknowledge the Old Dominion University Community Care clinics at the Housing Resource Center and PiN Ministry for their contributions to this study.

Funding Information

The authors received funding from the Ellmer School of Nursing at Old Dominion University for the purchase of the bus passes.

Disclosure Statements

The authors have no conflicts of interest to disclose.

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