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Using mobile health to improve social support for low-income Latino patients with diabetes: a randomized mixed methods feasibility trial of TExT-MED FANS

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Using mobile health to improve social support for low-income Latino patients with diabetes: a randomized mixed methods feasibility trial of TExT-MED FANS

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Content RUNNING HEAD: SOCIAL SUPPORT FOR LOW-INCOME LATINO PATIENTS WITH
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Using mobile health to improve social support for low-income Latino patients with
diabetes: a randomized mixed methods feasibility trial of TExT-MED FANS

Elizabeth Rhea Erwin Burner
University of Southern California, Keck School of Medicine
Masters of Science Degree in
Clinical, Translational and Biologic Investigations
Degree conferred on: December 13
th
, 2017
SOCIAL SUPPORT FOR LOW-INCOME LATINO PATIENTS WITH DIABETES
Table of Contents:
Acknowledgements………………………………Page 3
Abstract………………………………………….……Page 4
Introduction…………………………………………Page 6
Methods…………………………………………….…Page 8
Results……………………...……………………….…Page 15
Conclusions………………...………….………….…Page 22
Conflicts of Interest.…..……………………….…Page 27
Works Cited……………...……………………….…Page 28
Tables……….……………...……………………….…Page 32
Supplemental Tables………………...…………..Page 34
Interview guides………………...…………………Page 36

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Acknowledgements:
I would like to acknowledge the generosity of time and spirit of the patients and family
members who took part in this study, my committee, Drs. Sanjay Arora, Michael Menchine
and Cecelia Patino-Sutton, and the larger KL2 community who encouraged me during my
studies. I would also like thank my husband, Dale Burner, and our children, Caroline and
Andrew, whose patience with my continuing education is endless and admirable.

My time and the project were supported by a KL2 from the SC CTSI (NIH/NCRR/NCATS
Grant # KL2TR000131). My time was also supported by an NIH Grant #1K23DK106538.

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Abstract:
Background:
Social support interventions can improve diabetes self-care, particularly for Latinos, but
are time and resource intensive. Mobile health may overcome these barriers by engaging
and training supporters remotely.

Methods:
We conducted a randomized controlled feasibility trial of Emergency Department patients
with diabetes to determine feasibility of enrolling patients and supporters, acceptability of
the intervention and preliminary efficacy results to power a larger trial. All patients
received an existing mHealth curriculum (TExT-MED). After identifying a supporter,
patients were randomized to intervention: supporters receiving FANS (Family And friends
Network Support), a text message support curriculum synchronized to patient messages,
or control: supporters receiving a mailed pamphlet of the same information. Participant
followed-up at three months. FANS intervention participants came to post-intervention
interviews as part of a qualitative analysis.

Results:
We enrolled 44 patients (22 per arm) and followed-up 36 at three months. Participants
were positive about the program. FANS intervention improved HbA1c (intervention mean
decreased 10.4% to 9.0% vs 10.1% to 9.5%, delta -0.8%, CI -0.4 to 2, p=0.30), self-
monitoring of glucose (intervention increased 1.6 days per week vs control decreased 2
days per week, delta 2.3 days per week, CI 4 to 0.6, p=0.02) and physical activity (mean
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Godin Leisure Time Activity score improved 16.1 vs decreased 9.6 for control, delta 25.7, CI
49.2 to 2.3, p=0.10). In qualitative analysis, patients reported improved motivation,
behaviors, and relationships. Supporters reported making healthier decisions for
themselves.

Conclusions:
mHealth is a feasible, acceptable and promising avenue to improve social support and
diabetes outcomes.

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Introduction:
Low income Latinos have higher rates of diabetes and complications than the national
average.(Beckles & Chou, 2016; Geiss et al., 2014) This is likely multifactorial, related to
genetics and socioeconomic status, as well as language barriers and difficulty with access to
primary care. (Caballero, 2005; Daniulaityte, 2004; Piccolo, Subramanian, Pearce, Florez, &
McKinlay, 2016) Mobile health (mHealth) interventions to improve diabetes self-care have
promising results in several disparity populations, including low income English and
Spanish speaking Latinos.(Fortmann et al., 2017) Automated text message based mobile
health interventions offer an attractive solution to some of these barriers as they are
relatively inexpensive, highly scalable and most low income Latinos have mobile phones
capable of receiving basic SMS (Short-message service) text messages based on national
estimates.(G. Livingston, Minushkin, & Cohn, 2008) However, mHealth interventions have
great heterogeneity in outcomes, and most have had modest treatment effect. (Bell, Fonda,
Walker, Schmidt, & Vigersky, 2012; de Jongh, Gurol-Urganci, Vodopivec-Jamsek, Car, &
Atun, 2012; Hou, Carter, Hewitt, Francisa, & Mayor, 2016; Quinn et al., 2011; Seto et al.,
2012) The TExT-MED trial previously conducted by our group is the only mHealth based
diabetes trial to focus on emergency department patients with poor access to primary care.
We found improvements in glycemic control for Spanish speaking participants in the trial,
and modest overall improvement in patients receiving the TExT-MED intervention vs
usual care.(Arora, Peters, Burner, Lam, & Menchine, 2014) In post-intervention focus
groups, patients identified a need for more personalization and support, and also identified
family members as integral to diabetes management.(Burner, Menchine, Kubicek, Robles, &
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Arora, 2014). Incorporating family members into the intervention could potentially
increase its efficacy.

Social support interventions typically create a new support network among peers with a
shared diagnosis or engage family members in providing disease specific social support to
improve health outcomes.(Aikens, Trivedi, Aron, & Piette, 2015; Ayala et al., 2015; Safford
et al., 2015; Tang, Funnell, Sinco, Spencer, & Heisler, 2015; Trief et al., 2016; Yin et al.,
2015) Among Latino patients, social support interventions have successfully improved
diabetes outcomes and have been viewed favorably, however this has not been studied in
emergency department based interventions.(Teufel-Shone, Drummond, & Rawiel, 2005;
Thompson, Horton, & Flores, 2007; Two Feathers et al., 2005) Social support interventions
tend to be time intensive for family members, requiring travel to clinics for training.
Alternative strategies are to deploy diabetes educators or community health workers to a
family member’s home, however this can be costly to healthcare systems. This can result in
family members who live closest to the patient with the most available free time to travel
participating in support interventions, rather than the potential supporters that might be
more influential or helpful to the patient.

Merging these two types of interventions could generate a solution that has the ease and
scalability of mobile technologies coupled with the personal touch of social support.
mHealth based social support interventions could reduce the need for physical presence
and make social support interventions more accessible to populations in need. By
increasing social support and educating family members about good diabetes self-
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management practices, we may increase activation for behavior change and decrease the
barrier to healthy life choices for these patients. In this study, we conduct and analyze a
randomized controlled feasibility trial to determine the acceptability, feasibility and
efficacy of a novel social support module integrated into an existing mHealth intervention
for low income Latinos with diabetes.

Methods:
Trial Design:
This is a parallel, non-blinded, randomized control trial with 1:1 allocation.

Patient Population, Study Setting and Recruitment Goals:
The study was conducted in the Emergency Department (ED) of Los Angeles County +
University of Southern California Medical Center (LAC+USC). This patient population
(LAC+USC ED patients with diabetes) has been studied previously by our group, and is
predominately Latino, Spanish-speaking and low-income. Our prior work indicates that
diabetes specific knowledge is low in this population, and that the average HbA1c is 10.9%.
Prior work in this group shows that 80% of patients have a text-capable phone, and prior
mHealth interventions in this population have had higher than 80% satisfaction ratings.
(Arora et al., 2013; Arora et al., 2016; Arora, Marzec, Gates, & Menchine, 2011; Arora et al.,
2014) The recruitment goal was to determine the number of patients that could feasibly be
enrolled in a 6 week period; our high estimate of feasibility was 50 patient/family member
pairs.

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Patient and Supporter Recruitment, Enrollment, Randomization and Follow-Up:
IRB approval was obtained prior to study initiation, and the trial was registered with
clinicaltrials.gov (NCT01945996). Research assistants surveyed the ED electronic patient
tracking system for patients with diabetes during daytime hours for six weeks. While in the
ED, patients were screened for eligibility based on this criteria: having a text capable
mobile phone, being comfortable with sending and receiving texts and having a
glycosylated hemoglobin A1c (HbA1c) of ≥ 8, which falls into the ADA “Take Action” range.
The HbA1c-based eligibility requirement was verified using the Afinion AS-100 capillary
point-of-care HbA1c meter. Patients were excluded if they were <18 years old, pregnant, or
were unable to provide consent. During this initial screen, patients identified a family
member or friend to act as a supporter. Patients were excluded if we could not reach the
family member or friend within 1 week of patient screening. One supporter was enrolled
per patient. At enrollment, we collected patients’ self-reported race, ethnicity, age, language
preference and proficiency. Patients returned to the hospital for a baseline assessment.
Once baseline assessment was complete, patients were randomized to receive the
intervention condition (TEXT-MED+FANS intervention) or control condition (TEXT-MED
with un-augmented social support and a pamphlet for supporters) by sequential closed
envelope assignment. Envelopes were created prior to study initiation, and opened at
baseline assessment by the RA enrolling the patient. Neither patients, supporters or
research staff were blinded to allocation. Patients were contacted at one month to ensure
they were still receiving messages. Patients in both arms followed-up in person at three
months (the end of the message curriculum) to complete repeat assessment. Patients in the
intervention arm were invited to stay after this visit to participate in a focus group
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interview. Supporters were contacted by phone or in person at three months to take a brief
survey on change in texting habits and satisfaction with the intervention. Supporters in the
FANS intervention arm were invited to a focus group interview for supporters only.
Patients received a total of $100 in gift cards if they completed follow up at 3 months.

Interventions:
The intervention consisted of two curricula; one for patients and another for supporters.
The patient messages were previously developed for TExT-MED, a uni-directional, fully
automated, text message based program designed to increase knowledge, self-efficacy and
subsequent disease management and glycemic control. These twice-daily text messages for
patients were derived from the National Diabetes Education Program (NDEP), (Arora et al.,
2011) and consisted of: 1) educational/motivational messages (1 per week) 2) medication
reminders (3 per week) 3) trivia questions (2 per week) and 4) healthy living challenges (2
per week).(Arora et al., 2014) Patients in both trial arms received 2 messages daily, one
educational or motivational message in the morning, and one message from one of the
other three categories in the evening.

The FANS (Family And friends Network Supporters) messages for supporters was a newly
developed curricula that mirrored the patient messages. Supporters in the FANS arm
received one or two text messages a day; an educational or motivational message in the
morning, and a trivia or support challenge in the evening, which corresponded to the
patient messages. Challenge messages were modified to be inspire social support for the
patient. Trivia questions were identical to patient trivia questions. Supporters did not
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receive a message when the patient received a medication reminder. The pair of messages
was sent to the patient and the supporter synchronously (see Figure 1 for example of
patient and supporter messages that would correspond). This synchronous message
delivery was designed to promote conversation between the patient and the supporter,
increasing the impact of the message. The FANS messages are based on the module of
social support developed by Hinson-Langford, et al., which recognizes four arenas of social
support: 1. Instrumental support (tangible goods and actions), 2. Informational support
(knowledge sharing), 3. Emotional support, 4. Appraisal support (feedback on accuracy of
beliefs and appropriateness of actions). (Langford, Bowsher, Maloney, & Lillis, 1997) To
ensure that positive and appropriate support behaviors were emphasized in family
members, the FANS support curriculum included basic educational information in addition
to motivational messages and challenges to provide specific acts of support. The FANS
curriculum was translated into Spanish by a professional translator, and back translated by
two native Spanish speakers to ensure retention of meaning.

Figure 1: Examples of corresponding TEXT-MED patient and FANS supporter messages
Type of
message
Patient TExT-MED message FANS corresponding message
Educational/
Motivational
message
30 minutes of exercise a day
(even walking!) will give you
MORE energy not less. Make it
part of your routine!
30 minutes of exercise a day (even
walking!) will give your loved one
MORE energy not less. Help make it
part of their routine!
Challenge
Message
Challenge: Call a friend or
family member and go on a 30-
minute walk with them today
Challenge: Go on a 30 minute walk
with your loved one, but if you live far,
text them and go for a 30 minute walk
the same time they do.

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In the intervention group, patients received the TExT-MED program, and their supporters
received the FANS intervention daily for three months. In the control group, patients also
received the TExT-MED program daily, but the supporters received a pamphlet mailed at
the time of enrollment only with the same information as the FANS curriculum with
instructions indicating when they should read each message to synchronize with the
patient message.

Outcome Measures:
As this was a preliminary trial designed to inform future trials, we had several types of
outcomes of interest: feasibility, acceptability and preliminary efficacy.

Feasibility outcomes were percent of eligible patients who opted to participate, percent of
willing patients who were able to come to an enrollment visit and for whom we could
contact a supporter by phone to enroll, follow-up rate for patients and supporters, and
percent of invited patients and supporters that attended in-depth interviews at the end of
the study. We collected these outcomes to be able to plan for the enrollment time frame
needed for a larger trial. We also collected whether supporters reported receiving either
the text messages or mailed pamphlet, respective to the arm they were assigned to assess
technical feasibility.

Acceptability outcomes were divided into patient-focused and supporter-focused
outcomes. At the conclusion of the intervention, patients answered yes or no if they 1)
believed the platform was a good way to learn about diabetes, 2) would recommend the
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program to friends or family members and 3) wanted the messages to continue. Supporters
answered yes or no whether they 1) liked being involved as a supporter 2) would
recommend the program to friends or family members and 3) would want the messages to
continue at the end of the trial (FANS intervention arm only). We also sought to record if
and why any patients or supporters withdrew from the intervention.

Preliminary efficacy outcomes were split into 1) diabetes specific outcomes 2) social
support outcomes and 3) communication outcomes. These outcomes were measured at
baseline assessment and 3 month follow-up.

Diabetes specific outcomes: We collected point of care HBA1c; self-efficacy, measured by
Diabetes Empowerment Scale - Short Form (DES-SF); (Anderson, Fitzgerald, Gruppen,
Funnell, & Oh, 2003) diabetes related quality of life, measured by the Problem Areas in
Diabetes (PAID) scale; (Welch, Jacobson, & Polonsky, 1997) healthy behaviors measured
via the Summary of Diabetes Self-Care Activities (SDSCA) (Toobert, Hampson, Glasgow, &
RE, 2000) and the Godin Leisure Time Activity Scale.(Godin & Shephard, 1997) We selected
these measures as intermediary steps to glycemic control at the individual behavioral level
(SDSCA and Godin scale), with potential relationships with behavioral activation/self-
efficacy (DES-SF) and perceived barriers to healthy choices (PAID).

Social support outcomes: We collected measures of social support, measured by the
Norbeck Social Support Questionnaire, which is sub-scored as tangible and emotional
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support; (Norbeck, Lindsey, & Carrieri, 1981) and social connectedness, measured by the
Social Connected Scale –Revised. (Lee & Robbins, 1995)

Communication outcomes: We also collected patient and supporter report of the number of
text messages exchanged with the supporter as well as the percent of messages about
diabetes.

Statistical Analysis:
We generated descriptive statistics for patient demographics, feasibility outcomes, and
acceptability outcomes using STATA version 13.("STATA," 2013) For the preliminary
efficacy data, we generated descriptive statistics, and used t-tests or rank sum tests as
appropriate for variable type to compare outcomes between the groups. We also
completed post-hoc analysis of baseline characteristics of patients who completed follow
up versus those who did not, and outcome analysis for intervention group dyads who
completed the study, based on supporter report of receiving the messages.

Post-Intervention Qualitative Analysis:
At the conclusion of the three-month trial, we conducted a series of group and individual
interviews with only intervention group patients and intervention group supporters (half
of the total participants) in order to assess acceptability to patients and family members
and to understand the patient and supporter factors that might impact efficacy. The
question guides (see appendices 1 and 2) focused on how the intervention impacted
behavior motivation, patient perception of their disease, and the role their supporter
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played in their diabetes management. Interviews were conducted on the same day as the
three month follow up visit, after survey instruments were administered. Experienced
interviewers conducted 6 focus groups in Spanish and English with a total of 22
participants (14 patients and 8 family members). We imported verbatim transcripts into a
computerized qualitative analysis program, Dedoose. A rigorous text-based, modified
grounded theory approach was used.(Charmaz, 2006) Transcripts were analyzed in an
iterative process, reexamining the earlier transcripts with the new codes derived from each
round of analysis until saturation was reached. Broad categorical key themes arose from
the initial codes. We reviewed 297 pages of transcripts in the initial line-by-line process.
Through three iterative rounds of co-coding, we developed a set of 32 codes and subcodes.
Intercoder reliability was excellent (pooled Kappa 0.86.)(De Vries, Elliott, Kanouse, &
Teleki, 2008)
Results:
Enrolled patient characteristics:
We enrolled a total of 44 patients. Patients were predominantly Latino (80%), more often
female (57%), and preferred Spanish to English at home (57%). Intervention and control
group patients had similar baseline hemoglobin A1c, social support, social connectedness,
diabetes related self-efficacy, physical activity and diabetes self-care behaviors (see Table
1), with the exception of more frequent foot self-exams among control group patients.

Feasibility outcomes:
Enrollment and Follow-up: (see Figure 2 for consort-style diagram) We screened 745 ED
patients with diabetes for eligibility. 58 were eligible; reasons for ineligibility were: no
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mobile phone (174), Do not know how to text (180), HbA1c in good control (147), did not
speak English nor Spanish (28), critically ill (80), refused screening (28), no support person
identified (4), unable to contact support person (24), identified support person can not text
(15). Of these 65 eligible patients, 11 refused to participate, and 10 did not return for their
enrollment visit, resulting in 44 enrolled patients (68% of eligible patients enrolled). At the
conclusion of the study, 82% (36/44) of patients followed-up at 3 months. We were able to
follow-up with 60% (26/44) of supporters. 100% of patients reported receiving text
messages. 94% of supporters in the FANS intervention arm reported receiving support
messages, and 80% of supporters in the control mailed pamphlet arm reported receiving
the pamphlet.

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Figure 2: Diagram of Screening, Enrollment, Randomization and Follow-up of TExT-
MED+FANS Patients

Acceptability outcomes:
100% of patients who followed up at the end of the intervention stated text messages were
a good way to teach about diabetes, 97% stated they would want the messages to continue
Adults with Diabetes
presenting to LAC+USC
Emergency Department
Total screened for
eligibility = 745 patients
Total eligible = 65 patients,
all invited to Enrollment
visit 2-6 weeks after
screen
Lost to follow up
- Patient lost to follow up = 5
Excluded:
- No mobile phone = 174
- Do not know how to text = 180
- HbA1c <8 = 147
- No English or Spanish = 28
- Critically ill/AMS = 80
- Refused screening = 28
- Unable to identify support person = 4
- Unable to contact support person = 24
- Support person cannot text = 15

Patient: text-messages = 22 dyads
Supporter: text messages

Patient: text-messages = 22 dyads
Supporter: pamphlet by mail

Randomization 44 patient-supporter dyads
Reasons for Patient Not Enrolling:
- Refused to participate = 11
- Did not return for enrollment visit =
10
Lost to follow up
- Patient lost to follow up = 7
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at the conclusion of the intervention, and 97% would recommend the program to a friend
or family member with diabetes. 100% of supporters stated they like being involved as a
supporter, 88% stated they would like the text messages to continue, and 93% stated that
they would recommend the program to friends or family members. No patients or
supporters requested to be dropped from the intervention nor opted out of messages.

Preliminary Efficacy Outcomes:
For diabetes specific outcomes, both groups experienced decreases in HbA1c at three
month follow-up. The intervention group experienced a greater drop in mean HbA1c
(intervention patients’ mean HbA1c decreased from 10.4% to 9.0%, delta 1.4 (95%CI 2.3 to
0.4) compared to control group patients’ mean HbA1c decrease from 10.1% to 9.5%, delta
0.6 (95%CI 1.4 to -0.2), p=0.296). FANS intervention patients also reported increased self-
monitoring of glucose (intervention mean increased 1.6 days per week vs control
decreased 2 days per week, CI 4 to 0.6, p=0.02) and physical activity (mean Godin Leisure
Time Activity score improved 16.1 vs decreased 9.6 for control, delta 25.7, CI 49.2 to 2.3,
p=0.10). There were no differences between intervention and control patients report of
other self-care activities (SD-SCA), diabetes-related quality of life (PAID scale) nor self-
efficacy (DES-SF). Please see Table 2 for full results.

For social support outcomes, we found no difference in patients in the FANS intervention
and control group reported levels of tangible social support, emotional social support and
social connectedness, see Table 2 for full results.

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For communication outcomes, intervention group patient-supporter dyads also reported
increased number of texts per week (51 more texts per week for FANS intervention group
dyads compared to a decrease of two messages per week for control dyads, p=0.06) but no
change in the percent of text messages about diabetes, with 26% (95%CI 0.76% to 52%)
increase in intervention dyads compared to 30% (95%CI 11% to 49%) increase in control
intervention dyads, p=0.82. The correlation between supporter and patient report of
number of text messages exchanged each week was moderate (r=0.57).

Post hoc sub-analysis: We found no differences in baseline characteristics for patients
who completed follow up versus those who did not, nor in preliminary outcome measures
for patients whose supporters received the messages versus did not.

Qualitative analysis
Through the qualitative analysis, we identified several key themes regarding the
intervention’s acceptability and impact on patients’ motivation for behavior change and
diabetes self-management (See Table 3 for exemplary quotes for the key themes
identified.) Foremost, intervention group participants in the interviews were
overwhelmingly positive about the program. The most impactful messages were those that
had specific calls for action such a dietary goal for a meal or physical activity challenge.
Some patients also felt motivated by messages that called on them to stay healthy and
honor their responsibilities. Patients and family members both noted that their
communication had improved, and that they felt that the communication initiated by the
FANS intervention had strengthened their relationships. Both patients and supporters
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believed there could be more personalization of the messages, both in time of day delivered
and in content tailored to their specific needs. Interestingly, supporters noted they were
more mindful of their own health decisions, and believed that participation had improved
their own health. The FANS curriculum was designed to improve social support behaviors
from family members, but not specifically to improve the health choices supporters made
for themselves, while TExT-MED was designed to improve diabetes related self-efficacy,
specific self-care behaviors and resultant glycemic control among patients.

Table 3. Key themes and Exemplary Quotes of Impact of TExT-MED FANS
Theme Quote from Interview Participants
Positive regard for
the TExT-MED FANS
intervention
“I think it [TExT-MED+FANS] is very good. To motivate people. For
example, the people, the messages that you send. They are good, as long as
the people who receive them read them. Because it's no longer up to you. It
depends on the people that receive them.”
Desire to be healthy
and honor
responsibilities
“I always knew that back in my mind, but didn't come forth… One of the
last few texts that you guys sent, that, uh, you also wanna be there around
your family. You know, your loved ones… I remember that. And I go, ‘yeah,
that's the reason why I'm doing it.’”
Improved
communication and
emotional support
“I thank you very much for this, the messages, because that’s how my
husband would communicate with me. Let me tell you, he and I did not
have a good relationship. But now, he is my support.” (Translated from
Spanish)
“I think emotionally closer we became. Sometimes we would receive a text
that would say, ‘tell them how much you appreciate them.’ And then,
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sometimes, you know, when I’m random and I just go up and I told her like
why I love her and it makes her feel good about herself. Cause sometimes
she goes in a state of like depression. I noticed that I'm like, whoa. Don't
worry, it'll get better. I just try to tell her positive things to help her out,
emotionally. I'm not really good at like expressing how I feel. So I think
reminders, the text messages, help me.”
Desire for more
personalization
“I'm taking [medications] on a regular basis, the times where I should take
them. Not just, forget in the morning. Examples like texting [medication
reminders] at nine o'clock. For me, that's late. So, if I forgot because it was
late. Nine o'clock is late for me. Nine o'clock is my break time.”
Change in supporters
health behaviors
“You have someone that is receiving the same information that you are and
that it’s making, even making the other person a little bit more self
conscious about their own health.”
“[A Challenge] Message would say, ‘don’t eat bread or sweets or
carbohydrates’ or something like that, and tell the person that you are
doing the same thing’… it makes you conscious of your own diet and how
screwed up it is, you know? Like that you really don’t, if you’re not being
forced to actually take a look at what you’re putting in your mouth you
really don’t really think about it.”

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Conclusions:
Patient-centered mHealth interventions for diabetes are generally modestly effective at
improving diabetes outcomes.(Hou et al., 2016) Improving the quality and quantity of
social support provided by patient’s family members also improves intentions and diabetes
self-care behaviors,(Kirk, Ebert, Gamble, & Ebert, 2013; Mansyur, Rustveld, Nash, & Jibaja-
Weiss, 2015; Strom & Egede, 2012) but is difficult to scale up for larger populations. We
created the TExT-MED+FANS intervention to add a mobile social support intervention to a
previously successful patient centered mHealth intervention, and tested if this could
feasibly enhance clinical outcomes in a scalable manner. In this study, we found that such a
novel mobile social support intervention was feasible, acceptable to patients and their
family members, and produced promising results for diabetes-specific outcomes.

The chief reason to conduct this study was to determine the time frame necessary to enroll
patient in a fully powered trial and to determine the scalability of the intervention. The
enrollment procedures for family members and the requirement for patients and family
members be able to text could limit eligibility and future scalability. While these additional
inclusion criteria (willing and available family member to serve as a supporter, owning a
mobile phone and knowing how to text) did limit percent of eligible patients who were
successfully enrolled, we were able to enroll 44 patients and their family members in a 6-
week time frame, indicating a fully-powered trial is feasible in this setting. The primary
limitation to enrollment was mobile phone ownership and use of text messaging. However,
multiple studies have shown that cell phone ownership and use of text messaging by low-
income Latino patients is increasing, so this potential limit to scalability is decreasing
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rapidly.(Arora et al., 2013; Gretchen Livingston, 2011) Additionally, there is value in an
intervention that can change behavior for a segment of this underserved population, even if
mobile phone ownership does not reach 100%. An additional issue for a few patients was
the lack of a support person to enroll; this intervention is designed as an induction
intervention, where we activate existing social connections, rather than an alternation
intervention in which we would attempt to create new connections. (Valente, 2012) We
chose this kind of induction intervention, because while social support is generally believed
to improve diabetes self -management, in some populations there is evidence that some
family behaviors can be obstructive to good health decisions.(L. S. Mayberry, Egede,
Wagner, & Osborn, 2015; Lindsay S. Mayberry & Osborn, 2012; Lindsay Satterwhite
Mayberry & Osborn, 2014; Lindsay S. Mayberry, Rothman, & Osborn, 2014) To encourage
positive support behaviors from family members, the FANS support curriculum included
basic educational information rather than solely “pushes” to provide specific acts of
support. In larger iterations of this intervention, the intricacies of helpful and obstructive
behaviors will need to be better elucidated. This intervention can increase support, but we
must ensure that the support provided is appropriate and helpful.

We found that this kind of social support intervention was highly accepted by patients and
family members, with overwhelming positive regard for the program. It was engaging, as
no supporters or patients stopped the text messages and follow up with patients was
>80%. Through our qualitative analysis, we similarly found that patients and supporters
were highly engaged in the program and enjoyed the experience. We also found evidence
that an mHealth social support strategy may improve diabetes management compared to a
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more traditional pamphlet version. TEXT-MED+FANS resulted in changes in self-efficacy
compared to the control intervention. As this was a feasibility trial and not powered to find
statistical differences in clinical outcomes, we did not anticipate finding differences in
clinical outcomes. However, we found modestly better glycemic control among FANS
intervention patients versus control intervention patients. Both groups significantly
improved glycemic control from baseline, likely because the control group was not a “no-
touch” group, but instead received a previously tested and successful patient-focused
intervention with a basic social support component. Our novel approach of encouraging
family members to engage via a mobile intervention has the potential to make lasting
behavior changes, thus a longer follow-up period should be tested. The promising
improvements in our FANS intervention patients indicate that this augmented intervention
can improve diabetes self-care and resultant glycemic control. By creating this scalable
intervention, we anticipate that we can reach a larger portion of these high-need patients
and engage them in better self-care as well as relink them to diabetes specialists and/or
primary care providers.

This promising three month feasibility trial has several limitations that must be resolved
prior to conducting larger and longer studies. Follow-up with supporters was only 60% at
three months, and this could decline even further with longer trials. The high approval
ratings from supporters could be inflated given that those who did not enjoy the program
may be less likely to complete follow up. Clarifying the expectations of supporters
participating in the trial, regular engagement check with messages requesting a text-back
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and improved incentives for supporter follow-up would likely all improve this. However,
no supporters opted out of messages, indicating they continued in the intervention even if
they were not available for follow-up. Additionally, the focus of this intervention is the
patients’ health and behavior choices, so the suboptimal follow-up among supporters does
not impact the main patient centered objective of this study. We must also decide how to
accurately and appropriately measure the quantity of patient/supporter communication.
Correlation of self-report of text messaging between the patient and supporter dyads in
which both members completed follow-up measures was moderate. Checking phones for
actual number of messages exchanged may be a more objective measure, but invades
privacy, erodes trust and presumes that participants are not deleting messages due to
memory restrictions on their mobile phone. The perception of social support has been
shown to be more important than the actual provision of the support when examining
outcomes.(McDowell & Serovich, 2007) This potential issue in measuring the mechanism of
action of the intervention does not negate the importance of our findings and the potential
benefit of this kind of intervention. The participants in this trial likely have a higher level of
social support at baseline than patients who did not have a family member available to
serve as supporter, which limits the external validity of our findings. Both patient and
supporters who came to the interviews are also more likely to be highly engaged users, and
the qualitative analysis likely reflects a more positive view of the program than the study
population at large. Lastly, although this brief trial was designed to test the feasibility of
this complicated intervention, and was not powered to detect changes in diabetes
outcomes, the positive findings are encouraging.

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TExT-MED+FANS is an entirely automated, text message based, diabetes self-education and
self-management intervention augmented with mobile instigation of social support. In this
feasibility trial in low-income ED patients with diabetes, we found that mHealth is a
feasible, acceptable and promising avenue to increase diabetes self-care and resultant
glycemic control. Interestingly, although the intervention was focused on patients, the
family members believed they made healthier decisions in their own lives. A fully powered
trial is necessary to determine if there are significant changes in diabetes self-care
behaviors and resultant glycemic control. Instigating improved social support through this
scalable mechanism may be an important key to reaching populations who suffer diabetes
disparities and instigating long-term behavior change and improved diabetes outcomes.

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Conflicts of Interest:
The intellectual property rights to the original TExT-MED program have been purchased
from the University of Southern California by Agile Health, LLC. Drs. Arora and Menchine
consult for Agile Health, LLC. Agile Health did not participate in the design of the FANS
curriculum. No other authors reported disclosures.

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Tables:

Table 1. Characteristics of TExT-MED+FANS Patients (N=44)
Intervention (n=22) Control (n=22)
Characteristics n % n % p-value
Gender 0.361
Female 11 50% 14 64%
Male 11 50% 8 36%
Race/Ethnicity 0.670
Non-Latino White 1 5% 1 5%
Latino 17 77% 18 82%
African American 1 5% 2 9%
Asian 1 5% 1 5%
Other 2 9% 0 0%
Language preference 0.833
Both equally 1 5% 1 5%
More English than Spanish 4 18% 2 9%
More Spanish than English 3 14% 4 18%
Only English 2 9% 2 9%
Only Spanish 7 32% 11 50%
mean 95% CI mean 95% CI
HbA1c 10.4 9.6 11.3 10.1 9.5 10.8 0.725
Self-Efficacy: DES-SF 4.3 4.0 4.6 4.1 3.9 4.4 0.480
Perception of Problems: PAID 49.0 35.8 62.3 45.9 33.0 58.9 0.742
Self-Care Behaviors: SDSDCA
General diet 3.8 2.8 4.8 4.0 2.8 5.2 0.670
Specific diet 4.3 3.4 5.2 3.9 3.1 4.8 0.532
Exercise 2.8 1.7 3.9 2.4 1.3 3.4 0.560
Blood glucose 3.7 2.5 4.8 5.3 4.2 6.4 0.037
Foot care 4.0 2.8 5.2 4.3 3.1 5.4 0.913
Carb space 2.7 1.8 3.7 3.4 2.2 4.5 0.552
Godin leisure time activity 37.5 23.0 52.1 38.3 23.7 52.9 0.897
Social Support: SSQ Emotional 14.9 13.7 16.1 15.5 15.0 16.0 0.382
Social Support: SSQ Tangible 6.6 5.7 7.6 7.5 7.1 7.9 0.216
Social Connectedness: SCS 18.9 13.9 23.9 16.8 12.1 21.5 0.470
Texts sent per week by patient 76.3 23.8 128.9 91.6 24.3 158.9 0.953
Texts received per week by patient 87.4 30.2 144.6 88.3 22.3 154.2 0.953
SSQ= Norbeck Social Support Questionnaire, SCS=Social Connectedness Scale, PAID=Problem Areas in Diabetes measure, SDSCA=Summary of Diabetes Self-Care Activities measure, DES-SF=Diabetes Efficacy Scale- Short Form
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Table 2. Change-Score Analysis for TExT-MED+FANS Patients who completed follow up, n=36

Intervention (n=17)
Control (n=19) Difference (C-I)
Characteristics mean 95% CI mean 95% CI mean 95% CI p-value
HbA1c -1.4 -2.3 -0.4 -0.6 -1.4 0.2 0.8 -0.4 2.0 0.296
Self-Efficacy: DES-SF 0.1 -0.2 0.4 0.3 -0.1 0.7 0.2 -0.3 0.7 0.295
Perception of Problems: PAID -6.8 -16.0 2.4 -0.9 -15.0 13.2 5.8 -10.8 22.5 0.568
Self-Care Behaviors: SDSDCA
General diet
0.9 -0.3 2.0 0.1 -1.0 1.3 -0.7 -2.3 0.9 0.324
Specific diet 1.2 0.2 2.0 0.9 -0.1 1.9 -0.3 -0.9 1.5 0.690
Exercise 0.4 -0.6 1.3 0.7 -0.6 2.0 0.3 -1.3 1.9 0.588
Blood glucose 1.6 0.5 2.7 -0.7 -2.0 0.7 -2.3 -4.0 -0.6 0.024
Foot care 1.0 -0.5 2.6 0.9 -0.3 2.1 -0.1 -2.0 1.8 0.870
Carb space 0.5 -0.7 1.6 0.5 -0.6 1.5 0.0 -1.5 1.5 0.911
Godin leisure time activity 16.1 33.5 -1.3 -9.6 7.3 -26.6 -25.7 -2.3 -49.2 0.096
Social Support: SSQ
Emotional -1.4 -2.7 0.0 -1.5 -2.8 -0.3 -0.2 -1.9 1.6 0.722
Tangible -0.2 -1.2 0.7 -0.4 -1.2 0.4 -0.1 -1.3 1.1 0.709
Social Connectedness: SCS 0.8 -6.1 7.8 -1.9 -6.5 2.7 5.8 -10.8 22.5 0.568
*ranksum test was used for p-value; SSQ= Norbeck Social Support Questionnaire, SCS=Social Connectedness Scale, PAID=Problem Areas in Diabetes measure, SDSCA=Summary of Diabetes Self-Care Activities measure, DES-
SF=Diabetes Efficacy Scale- Short Form

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Supplemental Tables:

Supplemental Table 1: Comparison of baseline for participants with successful and non successful follow up
Follow-up (n=36) No Follow-up (n=8)
Characteristics n % n % p-value
Gender 0.251
Female 19 53% 6 75%
Male 17 47% 2 25%
Race/Ethnicity 0.642
White 2 6% 0 0%
Latino 27 75% 8 100%
African American 3 8% 0 0%
Asian 2 6% 0 0%
Other 2 6% 0 0%
Language preference 0.393
Both equally 1 3% 1 13%
More English than Spanish 5 14% 1 13%
More Spanish than English 4 11% 3 38%
Only English 3 8% 1 13%
Only Spanish 16 44% 2 25%
mean median mean median
Texts sent per week 79.5 37.5 104.1 36.5 0.939
Texts received per week 79.8 37.5 124.3 75.0 0.286
HbA1c 10.4 10.2 9.8 9.1 0.287
SSQ Emotional 15.1 16.0 15.8 16.0 0.545
SSQ Tangible 7.1 8.0 7.0 8.0 0.705
SCS 17.8 13.0 18.3 16.0 0.674
PAID 46.6 46.9 51.3 57.5 0.715
SDSDCA
General diet 3.8 3.5 4.3 4.0 0.645
Specific diet 5.3 5.3 3.9 4.0 0.056
Exercise 2.6 2.5 2.7 2.0 0.926
Blood glucose 4.8 7.0 3.1 4.0 0.067
Foot care 3.9 3.5 2.3 5.8 0.301
Carb space 3.0 3.0 3.1 3.0 0.622
DES-SF 4.2 4.3 4.3 4.4 0.713
Godin leisure time activity 34.1 35.0 26.4 16.5 0.273
SSQ= Norbeck Social Support Questionnaire, SCS=Social Connectedness Scale, PAID=Problem Areas in Diabetes measure, SDSCA=Summary of Diabetes Self-Care Activities measure, DES-SF=Diabetes Efficacy Scale- Short Form
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Supplemental Table 2: Change-Score Analysis for Completed Follow-up Participants, by Supporter Reported
Receiving Text and/or Pamphlet

Received Text/Pamphlet
(n=21) Not Received (n=2)
Characteristics
mean median mean median
p-value
HbA1c
-1.4 -0.9 0.1 0.1 0.102
SSQ

Emotional
-1.8 0.0 -0.5 -0.5 0.732
Tangible
-0.6 0.0 -0.5 -0.5 0.281
SCS
-1.8 0.0 3.0 3.0 0.296
PAID
-6.6 -3.8 0.0 0.0 0.548
SDSDCA

General diet
0.6 0.0 -0.5 -0.5 0.546
Specific diet
1.0 0.5 0.0 0.0 0.379
Exercise
1.0 1.5 -1.3 -1.3 0.228
Blood glucose
0.8 0.0 -3.0 -3.0 0.143
Foot care
0.9 0.0 3.3 3.3 0.171
Carb space
0.4 0.0 0.5 0.5 0.825
DES-SF
0.2 0.1 0.3 0.3 0.743
Godin leisure time
activity
6.2 0.0 -26.5 -26.5 0.156
*ranksum test was used for p-value
SSQ= Norbeck Social Support Questionnaire, SCS=Social Connectedness Scale, PAID=Problem Areas in Diabetes
measure, SDSCA=Summary of Diabetes Self-Care Activities measure, DES-SF=Diabetes Efficacy Scale- Short
Form

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Interview Guides

APPENDIX 1: Patient question guide

Introductory/Ice breaker questions: Name and….
-How many years have you had diabetes? How many years have you been coming to LAC+USC for care?

Main questions:
1. Thinking back to before Text-MED FANS, and now after the program, how have you changed the
way you take care of yourself?

a. Sub-prompts if not addressed:
i. Who did you see to help you take care of it?
ii. (prompts if necessary: Medications, doctors, alternative medicine)
1. What has been the hardest part?
2. How do you learn about what you need to do to take care of yourself?
(if necessary, prompt on diet, exercise, taking medicines)

2. Thinking back to before the program, what kinds of things inspired you to take control of your
diabetes?
a. Sub-prompts if not addressed:
i. What made it easier to manage it well?
ii. What made it more difficult to manage it well?

3. Before you participated in the program, what did you think would happen if you didn’t manage
your diabetes?
a. How about now? Reword if necessary: What did you think would happen if you did not
control your diabetes?

4. What kinds of things have helped you to change how you manage your diabetes?

a. Sub-prompts:
i. Has it worked for you?
ii. Does it actually get you to change your behavior?
iii. What else have you tried?
1. How successful have these strategies been for you?

5. How has TextMED FANS affected how you manage your diabetes?

6. How did you decide on the supporter you selected to work with you in TexT-MED FANS?
a. Has TExT-MED FANS changed your relationship with your supporter?

7. -What was your favorite part?

8. If not addressed earlier in session -How could TExT-MED be better?

9. -What types of messages made you think the most?
a. Prompt if not addressed:
i. About your diabetes,
RUNNING HEAD: SOCIAL SUPPORT FOR LOW-INCOME LATINO PATIENTS WITH DIABETES
37
ii. about how you manage your diabetes,
iii. and about your health in general
RUNNING HEAD: SOCIAL SUPPORT FOR LOW-INCOME LATINO PATIENTS WITH
DIABETES
38
APPENDIX 2: Supporter question guide

What was your favorite message from the program?

Before the program, what did you know about diabetes? Did you know your loved
one had diabetes?

Before the program, how did you offer support to your loved one?

How has this changed with TExT-MED FANS?

What messages did you like the best? Why?

Abstract (if available)

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Asset Metadata

Creator Burner, Elizabeth Rhea Erwin (author)

Core Title Using mobile health to improve social support for low-income Latino patients with diabetes: a randomized mixed methods feasibility trial of TExT-MED FANS

School Keck School of Medicine

Degree Master of Science

Degree Program Clinical, Biomedical and Translational Investigations

Publication Date 09/26/2017

Defense Date 09/25/2017

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Diabetes Mellitus,disease management,Latinos,OAI-PMH Harvest,social support,text messaging

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Arora, Sanjay (committee chair), Menchine, Michael (committee member), Patino Sutton, Cecilia (committee member)

Creator Email eburner@lacounty.gov,eburner@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-436606

Unique identifier UC11264051

Identifier etd-BurnerEliz-5775.pdf (filename),usctheses-c40-436606 (legacy record id)

Legacy Identifier etd-BurnerEliz-5775.pdf

Dmrecord 436606

Document Type Thesis

Rights Burner, Elizabeth Rhea Erwin

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA