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Original Investigation

Implementation of a Referral Scheme to Text Messaging Programs for Physical Activity and Healthy Eating in Underserved Hispanics

Portacio, Francia G.1; Corvalan, Deborah2; Stoutenberg, Mark1,3

Author Information
Translational Journal of the ACSM: Winter 2021 - Volume 6 - Issue 1 - e000144
doi: 10.1249/TJX.0000000000000144

Abstract

Hispanics are the largest minority ethnic group in the United States and are at a higher risk for diabetes, uncontrolled hypertension, and obesity compared with non-Hispanic Whites and/or African Americans (1). Only 17.0% of Hispanic adults met both the national guidelines for aerobic activity and muscle strengthening, whereas 52.5% met neither aerobic activity nor muscle strengthening guidelines (2). Similarly, mean daily caloric intake among Hispanic adults is higher than non-Hispanic Whites and consists of a greater levels of fast food (3).

Strategies to engage Hispanic individuals in physical activity and healthy eating are essential for decreasing the rising rates of obesity and chronic diseases seen in this population. One method for delivering health information on physical activity and dietary habits is through the use of mobile technology (4–6). Research has found higher rates of text messaging among Hispanics compared with non-Hispanic Whites (7). Text messages are well suited for health promotion as they can be written in simple text, personalized based on the health literacy levels, and facilitate interactive communication between patients and their providers (8). Text messages are effective in improving health behaviors, as seen in smoking cessation and weight reduction programs (9), and there is growing evidence of text messaging programs successfully improving physical activity and dietary habits in Hispanic adults (4,10–12). The challenge is to effectively connect Hispanic individuals to text messaging interventions and prevention programs in a manner that is accessible to the user (13).

One setting with significant potential for connecting Hispanic adults to text messaging interventions is through primary care. Health care settings provide a unique setting to connect patients to physical activity and healthy eating programs for multiple reasons. First, clinic settings present an ideal opportunity for health care providers to interact and communicate with their patients. Second, health care providers are thought to be a very credible source and thus more likely to be influential in behavior change (14). Examples of providers connecting their patients to healthy lifestyle resources are best illustrated through the physical activity referral schemes common in the United Kingdom (15), other parts of Europe (16), and advocated by the Exercise is Medicine® in the United States (17). Typically, these referral schemes involve providers engaging their patients in brief counseling, followed by a written or electronic “prescription” to encourage them to be active, finishing with a referral that connects them to available physical activity resources for ongoing support.

Providing Hispanic patients with a referral to text messaging programs via their health care provider may increase patient engagement (8). However, little is known about linking underserved Hispanic populations to text messaging programs in a health care setting. To address this gap, the goals of this study were to use a mixed methods approach 1) to evaluate the implementation of a health care provider referral scheme linking patients to a text message program for physical activity or healthy eating, and 2) to understand the barriers implementing the referral scheme in a community health clinic serving a predominantly underserved Hispanic population.

METHODS

The implementation of a referral scheme to connect low-income Hispanic patients to one of two text messaging programs, offered by CareMessage™, a mobile technology software company, was pilot tested at a community health clinic. Providers were encouraged to refer their patients to text messaging programs designed to increase physical activity levels or improve dietary habits during an 8-wk referral period. Patients who did not self-initiate enrollment received a reminder phone call from clinic staff 1 wk later. Provider referral rates and patient enrollment in the programs were tracked to assess the implementation of the referral scheme. Semistructured interviews assessed barriers and facilitators experienced by the providers.

Setting

The text messaging referral scheme was implemented at a local community health clinic in South Florida that provides free primary and specialty care to uninsured individuals below the 200% federal poverty level, particularly in assisting uninsured and undocumented individuals with their medical needs. The clinic serves primarily Hispanic patients, both Spanish and non-Spanish speaking, as well as a small number of non-Hispanics English speaking patients.

The clinic director was approached by CareMessage™ with an offer to use their text messaging programs to better assist their patients with lifestyle modification. In adopting the CareMessage™ text messaging programs, she believed that the programs would be beneficial to their patients and well received by the clinic providers. The resulting pilot study was proposed to test this approach. All five primary health care providers (physicians, n = 2; nurse practitioners, n = 3) working at the clinic agreed to participate in the referral scheme. The providers participated in a 30-min training and received a written manual that included information regarding CareMessage™, details about the program (i.e., content, duration), and a step-by-step process on connecting their patients to the text messaging programs and documenting it on the electronic health record (EHR).

Potentially Eligible Participants

All Spanish-speaking, Hispanic adult patients who visited the clinic during the study period were potentially eligible to receive a referral. Health care providers were encouraged to provide potentially eligible patients to the text messaging program if the patient 1) is 18 yr of age or older, 2) is Hispanic, 3) is Spanish speaking, and 4) owns and uses a cell phone. A final criteria, collaboratively refined with the health care providers before implementation, was added to allow them to designate patients as ineligible to receive a referral based on their medical condition. Children, adolescents, and patients visiting subspecialty practitioners also were not eligible to receive a referral. The Institutional Review Board at the University of Miami approved all study procedures and materials.

Text Messaging Programs

The text messaging programs used in this study were developed by CareMessage™, a mobile technology and the largest patient engagement nonprofit organization in the United States for underserved populations. Although their services are offered at low cost to health care organizations, CareMessage™ provided their text messaging service free to the community health clinic as part of their philanthropic activities. CareMessage™ offers a cloud-based platform with options for several text messaging programs in English or Spanish on various health behavior topics designed to increase individual knowledge and self-efficacy. CareMessage™ health education text messaging programs have demonstrated significant improvement in health behaviors, such as significant weight loss in a population of patients with chronic liver disease (14). In our study, patients had the option of enrolling in text messaging programs designed to either increase physical activity levels or improve dietary habits. Both programs consisted of three weekly, automated, culturally adapted, and interactive text messages over a period of 16 wk. Before implementation, the research team and the clinic staff reviewed the text messages to ensure appropriateness and make minor cultural adaptations for the target patient population.

Implementation of the Referral Scheme

Potentially eligible patients seen at the community health clinic over an 8-wk period between mid-January and mid-March 2016 had the opportunity to receive a referral to the text messaging program. Health care providers initiated the referral process by giving patients a referral card containing information on enrolling into either of the text messaging programs and encouraged them to self-initiate enrollment by texting the number on the referral card. Providers also informed the patient that this was part of a study with the University of Miami and that a research team member would call them to complete enrollment shortly after the initial text message. Finally, patients were provided with a “clinic” consent form to be completed and turned in by clinic checkout, absolving the clinic of liability regarding participation in the text messaging program. Potentially eligible patients were excluded from the study if they did not turn in a completed clinic consent form.

Health care providers were asked to document a “note” in the patient’s EHR on whether they provided a referral or if they deemed a patient ineligible to receive a referral based on their medical condition. To ensure consistency in documenting referrals, providers accessed a Word document saved on their desktop, copied a scripted entry on whether a referral was given or if the patient was deemed ineligible, and pasted it into the EHR. No assistance was provided by the clinic staff at the time of the referral to assist patients who enroll in the text messaging programs.

Enrollment Process

Referred patients were enrolled in the study in one of two ways. Patients who received a referral and completed the clinic consent form were encouraged to self-initiate the enrollment process by texting the number on the referral card. Patients who did not self-initiate the enrollment process received a follow-up phone call from a Spanish-speaking clinic intern 7–10 d after the referral. During this call, patients were reminded about receiving the referral card and encouraged to participate. If they expressed interest in participating, their contact information was forwarded to a research team member. Follow-up calls were documented in the notes section of each patient’s EHR.

Although CareMessage™ allows patients to self-enroll directly in their programs via text message, for research purposes, an additional step was added to obtain patient informed consent before enrollment in the research study. Eligible patients who expressed interest in participating in the text messaging program, by either self-initiated enrollment or during the follow-up call, received a telephone call from a research team member who provided an explanation of the text messaging program, obtained their verbal consent to participate in the study, and conducted baseline assessments. The research member accessed the CareMessage™ portal and manually enrolled the patient in the text messaging program of their choice (physical activity or healthy eating). Enrolled patients started receiving text messages in Spanish the following week for a total of 16 wk.

Evaluation

The present study used a mixed methods approach built on 1) components of the RE-AIM framework and 2) a general inductive approach to explain and understand the barriers in the attempt of implementing a referral scheme for a text messaging program within a community health clinic.

Quantitative Analysis—Adoption and Implementation of the Text Messaging Referral Scheme

At the end of the 8-wk referral period, clinic administration provided a deidentified spreadsheet with data extracted from their EHR of all eligible patients served during the referral period. The deidentified data included information on patient 1) age, 2) gender, 3) nationality, 4) body mass index, and 5) medical condition(s). The adoption of the referral scheme was assessed as the number of providers who gave a referral to at least one patient. The implementation of the referral scheme was assessed by notes made in the EHR that tracked 1) patient referrals or those deemed ineligible by the provider, 2) follow-up calls, and 3) enrollment of patients in the text messaging programs. The proportion of referrals by health care providers was calculated based on the number of patients they served during the referral period.

Qualitative Analysis—Individual Interviews with Clinic Administrators and Providers

At the conclusion of the 8-wk referral period, open-ended interviews were conducted in English with clinic administrators and health care providers involved in the referral scheme. The interviews assessed overall perceptions of the referral scheme (i.e., barriers and facilitators) and were conducted at the clinic during a prearranged time. Interview questions were sent to the clinic staff ahead of time. The interview guides (see Supplemental Digital Content, http://links.lww.com/TJACSM/A116) were developed based on the predetermined steps involved in the referral process (i.e., design of the referral process and implementation barriers). Follow-up prompts elicited more detailed responses. The duration of the interviews ranged from 15 to 30 min. All interviews were audio recorded and later transcribed by a professional transcription agency.

A general inductive approach was used to analyze the qualitative data. An inductive approach consists of “gathering data and making sense of them by grouping data segments into codes, themes, and larger perspectives” (18). Each transcript was read thoroughly while listening to the corresponding audio-recorded interview to familiarize the research team with the content of each interview, as well as to verify the accuracy of the professional transcription agency. An Excel spreadsheet was created to summarize codes and quotations for the codebook.

RESULTS

Quantitative Results—Implementation of Text Messaging Referral Scheme

During the 8-wk referral period, a total of 291 patients visited one of the five participating health care providers at the community health clinic. The use of the referral scheme was adopted by all five health care providers, who all referred at least one potentially eligible patient to the text messaging programs. Health care provider referrals reached only 8.9% of potentially eligible patients (26 of the 291 total patients seen). Nine individuals who received referrals were not enrolled in the study (six declined or refused to submit consent forms and three were non-Hispanics). Of the referred patients who provided consent (n = 17; 5.8% of all patients seen), only one self-initiated the enrollment process. The remaining 16 referred patients received follow-up phone calls from a clinic intern. Eleven of these patients expressed interest in enrolling in the study, three declined to participate, and two others were unreachable. A total of 12 patients (4.1% of all patients seen during the referral period) enrolled in the text messaging programs (Fig. 1).

Figure 1
Figure 1:
Eligible patients to enrolled participant flow chart.

Characteristics of individuals reached were evaluated using the deidentified spreadsheet of eligible patients who received a referral compared with all potentially eligible patients. Of the eligible, referred patients (n = 17), the mean age was 48.7 yr, 82% were female, and the average body mass index was 33.1 kg·m−2 (Table 1). Most referred patients had existing health conditions, such as hypertension (18%) and high cholesterol (17%). The top two nationalities of the referred patients were Nicaraguan (35%) and Honduran (23%). Patients referred to the text messaging programs differed significantly by nationality (P < 0.001) and body mass index (P = 0.015), but not by medical condition (P = 0.786) or gender (P = 0.769). During the referral period, individual health care providers referred between 3% and 25% of their patients (Table 2).

TABLE 1 - Characteristics of Nonreferred versus Referred Patients to the Text Messaging Programs.
Nonreferred (n = 245) Referred (n = 17) Between-Group Differences (P)
Nationality, n (%) P < 0.001
 Nicaraguan 70 (29) 6 (35)
 Honduran 63 (26) 4 (23)
 Cuban 41 (17) 2 (12)
 Other 34 (14) 0 (0)
 Colombian 21 (8) 1 (6)
 Guatemalan 8 (3) 2 (12)
 Venezuelan 8 (3) 2 (12)
Medical Conditions, n (%) P = 0.786
 HTN 28 (11) 3 (18)
 CHOL 36 (15) 3 (18)
 DM 18 (7) 2 (12)
 CHOL/DM 14 (6) 2 (12)
 HTN/DM 18 (7) 0 (0)
 HTN/CHOL 21 (9) 1 (6)
 HTN/CHOL/DM 25 (10) 1 (6)
 None 85 (35) 5 (29)
Gender, n (%) P = 0.769
 Female 186 (76) 14 (82)
 Male 59 (24) 3 (18)
BMI (kg·m−2), n (%) P = 0.015
 Underweight (<18.5) 1 (0.4) 0 (0)
 Normal (18.5 to <25) 48 (19.6) 0 (0)
 Overweight (25.0 to <30) 102 (42) 5 (29)
 Obese (>30.0) 94 (38) 12 (71)
Data are not provided for 29 patients who were not referred to the text messaging program.
BMI, body mass index; CHOL, cholesterol; DM, diabetes; HTN, hypertension.

TABLE 2 - Proportion of Patients Referred by Each Provider to Text Messaging Program during Referral Period.
Provider Percent
1 7
2 23
3 12
4 3
5 25
Proportions are calculated by the total number of patients seen by a provider, divided by the number they referred to the text messaging program.

Of the 12 patients who enrolled in the text messaging program, 9 (75%) selected the nutrition program and 3 (25%) selected the physical activity program. Nine participants completed the text messaging program, one could not be contacted at the end of the text messaging program, and two participants opted out during the text messaging program. Response rates to the interactive components of the text messaging programs included 85% in the physical activity program and 82% in the nutrition program, nearly double the average response rate (42%) across all CareMessage™ programs (19).

Qualitative Results—Individual Interviews with Clinic Administrators and Providers

All clinic staff (administrators and health care providers) involved in the referral scheme were individually interviewed (two administrators and five health care providers). The majority were female (85.7%), had an average job experience of 17.4 yr, and had worked at the clinic for an average of 5.8 yr.

Four prominent themes emerged from the interviews, primarily reflecting the barriers that the providers faced implementing the referral scheme: 1) time, how long the overall referral process took; 2) resources, the need for additional volunteers or interns to assist with the referral after the consultation; 3) communication, the need for better communication between administrators and providers, and 4) technology, lack of patient cell phone knowledge as well as barriers in using the EHR for documenting referrals.

First, providers expressed that although it appeared to be a simple referral process, they did not have enough time to answer patient questions. One provider commented, “It’s a lack of time. I tried, and then people would start asking me questions about the program, and I’m going—inside of me, you know, this is not my role. I cannot be spending time on this. I need to be spending time teaching them about high blood pressure or diabetes or how to apply insulin or, you know, all this stuff, and I cannot be spending more time—as it is, we only have, like, 15 min to do all that.”

Providers expressed a need for additional support to alleviate this time constraint and to help patients better understand the purpose of the text messaging programs. One provider commented, “It’s not like I’m asking the clinic to hire somebody brand new, I mean, somebody full time for this, but maybe if there was a way to get maybe an extra volunteer in for that duration … and have that person in charge of walking our patients through this, that would have doubled our enrollment rate easily.” Another provider stated, “Some of our patients are very skeptical about programs they don’t really understand because of their immigration status. If you have somebody who can be dedicated to answer their questions and to really explain it more fully, the program, I think they might be willing to do it.”

Communication between administrators and providers was mentioned as a significant barrier. Providers desired more inclusion during the developmental stages of the referral scheme. Although the administration was viewed as very supportive and reliable, one provider indicated, “I had not been given a heads up about this program at all,” and added, “It would have been nice for the director to give us plenty of notice of what’s coming down the pike.” Another provider commented, “I wasn’t informed about us participating in this program, I was a little bit, uh—you know, I kind of took a big sigh because we’re really overwhelmed with, uh, how much stuff we have to do with our patients.”

Providers also suggested the need for a simplified but more advanced method of documenting the referral process in the EHR. One provider commented, “We use an electronic medical record to document our visits, but we don’t actually use it for prescribing, so when a patient needs a simple prescription, not only do I have to document it electronically. I also have to write a paper prescription the old-school way, so I’m actually doing double the work because we don’t have that technology in place.” Another provider stated, “My only complaint was with the electronic record, that there’s no easy—there was no easier way of doing it but have to open the encounter, and since we’re involved in other programs, it was one extra step, and it kind of did delay the documentation for the patient.”

On the other hand, the clinic administrators were excited to introduce the text messaging programs at the clinic and spoke about the importance of providing patients with additional health education resources. Although most patients had previously reported using text messaging, their concerns centered around the tech “savviness” of the patients, time constraints the providers faced, and protection of patients’ health information privacy. One administrator stated, “I think maybe we did underestimate a little bit the ability of our patient, of our specific patient population to use their cell phones.” Regarding to time limitations, one administrator acknowledged, “They (providers) had to give the patient the consent form, then they had to do a special documentation in EHR, that took extra time. I think it frustrated them a little bit.” Finally, another administrator shared, “We needed to make sure that the patients’ privacy and the clinic’s, liability and that we did things right, not the clinical design of it, but more of the administrative design of it.” Overall, the administrators hoped for higher referral rates but acknowledged that providers did the best they could with limited time and resources and were encouraged by the success of using a volunteer to conduct follow-up calls after receiving the referral.

DISCUSSION

This study examined the implementations of a referral scheme linking underserved Hispanics to text messaging programs focused on lifestyle behavior change. Understanding barriers to implementing a referral scheme in a clinic setting may be useful in guiding administrators in adopting and implementing referral schemes, increasing health care providers’ willingness to provide referrals, and enhancing patient engagement in future efforts.

Despite working with clinic administration in the design of the referral scheme, streamlining the referral process, and offering standardized training to the clinic staff, a low percent (8.9%) of patients received referrals. This low rate indicates that the referral scheme was not successful in reaching patients seen during the referral period. In comparison, a referral scheme connecting patients to a weight management program engaged 42.3% of their patients using a variety of strategies (18). First, their referral period lasted 7 months, which allowed more time to broadly promote the referral process through presentations, clinic brochures, and posters. Second, feedback from patients resulted in changes to maximize patient and health care provider awareness and acceptance of the program.

Further compounding the low provider referral rates, only one patient (5.8% of eligible patients who received referrals) self-enrolled in the text messaging program. However, it was encouraging that, upon receiving a follow-up call by a clinic intern, 68.8% of referred patients enrolled in the text messaging programs, highlighting the importance of active follow-up with patients after a referral. Our findings are similar to those of Beidas et al. (20) in their work with breast cancer survivors postsurgery. They found that follow-up calls by a clinic staff member increased engagement of referred breast cancer survivors in a rehabilitative exercise program from 39% to 65%. The importance of this intermediary between providers and wellness resources may be a key component in the overall effectiveness in a referral scheme and an important area for future study.

Health care providers mentioned several barriers to implementing the referral scheme, including a lack of time to provide referrals, a lack of resources to assist patients with the referral process, the need for more communication between clinic administrators and providers, and better methods for documenting the referrals. Common to most interventions in clinic settings, health care providers in our study listed time as a major impediment to fully implementing the referral scheme (21,22). Providers reported that referrals to the text messaging programs often prompted patients to ask additional questions, taking away time from the consultation. To overcome this barrier, several providers suggested having an additional person (i.e., student volunteer or intern) onsite to assist with patient inquiries. In a previous study, five community health clinics implemented a referral scheme connecting patients to the Take Charge Lite weight management program (22). They concluded that having additional, dedicated support staff helped them achieve higher referral rates (40.0%) and patient participation levels (15.6%).

Although clinic administrators provided initial communication, providers expressed the desire to be involved in the design of the referral scheme before implementation, which may have resulted in greater levels of participation. Various studies highlight the influential role that leadership engagement plays in health care settings to develop an effective communication structure (23–25). Strong communication between administrators and providers leads to positive perceptions that an intervention has high priority, contributing to higher implementation rates (25).

Technological barriers were a final concern for the health care providers. They had to manually document every referral because of limitations within their EHR system. The additional steps were perceived as burdensome, time consuming, and inefficient, decreasing the ability to make the referral a quick and easy process. Adopting an electronic referral and/or consultation (eCR) management system, a powerful tool that allows health care providers to streamline the documentation of referrals into the EHR, may help address such barriers. Interviews with leaders from 16 diverse, health care delivery organizations found that the integration of eCR in EHR systems effectively assisted health care providers streamline and overcome barriers faced with documenting referrals (26). However, this tool may not be feasible for community health clinics that have limited resources and likely lack access to an eCR system.

Strengths and Limitations

A strength of this study was the use of a mixed methods approach to exploring facilitators and barriers associated with the implementation of the referral scheme. This approach allowed for deeper insight into how clinic administrators and health care providers perceived their involvement in the design and implementation of the referral scheme. One study limitation involved the deidentified patient data released by the clinic at the end of the study. Because of concerns about patient confidentiality, information from 29 patients was not released, preventing us from fully comparing enrolled participants to all eligible participants. In addition, only deidentified information on the proportion of patients referred by each provider was given, preventing us from linking specific providers, their referral rates, and qualitative feedback. This limited our ability to examine provider characteristics that may have influenced the implementation of the referral scheme. In addition to challenges importing information into the EHR, clinic administration requested that each referred patient sign a consent form at the time of checkout, which took additional time, occasionally caused confusion among participants, and may have affected referral rates. Lastly, because of the small number of patients who were referred and enrolled in the program, we were unable to examine the effectiveness of the text messaging programs on patient health behaviors.

CONCLUSION

Understanding the specific barriers involved with implementing a referral scheme can identify future areas of improvement to better link patients to available resources. This information is currently lacking in the literature and may be especially important for increasing program participation and maximizing available resources in low resource clinic settings. The barriers identified through our work, time limitations, lack of communication, resources, and technology, are common in most health settings, but even more so in community health clinics. To address these barriers, strategies such as including the health care team before the implementation of a referral scheme, using a tracking system in the EHR that streamlines the referral process, and incorporating intermediaries to assist in the referral process to encourage patient engagement may alleviate these barriers, increase the level of provider adoption and fidelity of implementation, and lead to greater success connecting patients to health promoting programs.

The Institutional Review Board at the University of Miami approved all study procedures and materials. Informed consent was obtained from all participants involved in the study.

Dr. Stoutenberg is a paid consultant for the American College of Sports Medicine, serving as a Program Officer for the Exercise is Medicine® initiative. The results of this study are presented honestly and without fabrication, falsification, or inappropriate data manipulation and do not constitute endorsement by the American College of Sports Medicine.

REFERENCES

1. Centers for Disease Control and Prevention (CDC). Vital signs: leading causes of death, prevalence of diseases and risk factors, and use of health services among Hispanics in the United States—2009–2013. MMWR Morb Mortal Wkly Rep. 2015;64(17):469–78. Available from: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6417a5.htm?s_cid=mm6417a5_w.
2. National Center for Health Statistics. Participation in leisure-time aerobic and muscle-strengthening activities that meet the federal 2008 Physical Activity Guidelines for Americans among adults aged 18 and over, by selected characteristics: United States, selected years 1998–2017. In: Health, United States, 2018. Hyattsville (MD): National Center for Health Statistics; 2019, Accessed from: https://www.cdc.gov/nchs/hus/contents2018.htm#Table_025.
3. U.S. Department of Agriculture, Agricultural Research Service. Nutrient Intakes from Food and Beverages: Mean Amounts Consumed per Individual by Race/Ethnicity and Age, What We Eat in America, NHANES 2015–2016. Maryland: U.S. Department of Agriculture, Agricultural Research Service; 2018.
4. Buchholz SW, Sandi G, Ingram D, Welch MJ, Ocampo EV. Bilingual text messaging translation: translating text messages from English into Spanish for the Text4Walking Program2015. JMIR Res Protoc. 2015;4(2):e51.
5. Siopis G, Chey T, Allman-Farinelli M. A systematic review and meta-analysis of interventions for weight management using text messaging. J Hum Nutr Diet. 2015;28(Suppl 2):1–15. doi: 10.1111/jhn.12207. Epub 2014 Jan 31.
6. DiFilippo KN, Huang WH, Andrade JE, Chapman-Novakofski KM. The use of mobile apps to improve nutrition outcomes: a systematic literature review. J Telemed Telecare. 2015;21(5):243–53. Epub 2015/02/15.
7. Zickuhr K, Smith A. Digital Differences. Pew Res. 2012. Available at: http://www.pewinternet.org/ 2012/04/13/digital-differences/. Accessed June 14, 2020.
8. Kumar D, Arya M. mHealth is an innovative approach to address health literacy and improve patient–physician communication—an HIV testing exemplar. J Mob Technol Med. 2015;4(1):25–30. Epub 2015/03/03. doi: 10.7309/jmtm.4.1.6. PubMed PMID: 25729441; PubMed Central PMCID: PMCPMC4341897.
9. U.S. Department of Health and Human Services (USDHHS), Health Resources and Services Administration. Using Health Text Messages to Improve Consumer Health Knowledge Behaviors and Outcomes: An Environmental Scan. Rockville (MD): U.S. Department of Health and Human Services; 2014.
10. Kolodziejczyk JK, Norman GJ, Barrera-Ng A, et al. Feasibility and effectiveness of an automated bilingual text message intervention for weight loss: pilot study. JMIR Res Protoc. 2013;2(2):e48. Epub 2013/11/10. doi: 10.2196/resprot.2789. PubMed PMID: 24200517; PubMed Central PMCID: PMCPMC3841356.
11. Collins TC, Dong F, Ablah E, et al. Text messaging to motivate exercise among Latino adults at risk for vascular disease: a pilot study, 2013. Prev Chronic Dis. 2014;11:E192. Epub 2014/10/31. doi: 10.5888/pcd11.140219. PubMed PMID: 25357260; PubMed Central PMCID: PMCPMC4215572.
12. Fischer HH, Fischer IP, Pereira RI, et al. Text message support for weight loss in patients with prediabetes: a randomized clinical trial. Diabetes Care. 2016;39(8):1364–70. Epub 2016/02/11.
13. Victorson D, Banas J, Smith J, et al. eSalud: designing and implementing culturally competent ehealth research with latino patient populations. Am J Public Health. 2014;104(12):2259–65. Epub 2014/10/17. doi: 10.2105/ajph.2014.302187. PubMed PMID: 25320901; PubMed Central PMCID: PMCPMC4232154.
14. Keyworth C, Epton T, Goldthorpe J, Calam R, Armitage CJ. Perceptions of receiving behaviour change interventions from GPs during routine consultations: a qualitative study. PLoS One. 2020;15(5):e0233399. Epub 2020/05/22.
15. Campbell F, Holmes M, Everson-Hock E, et al. A systematic review and economic evaluation of exercise referral schemes in primary care: a short report. Health Technol Assess. 2015;19(60):1–110. Epub 2015/07/30. doi: 10.3310/hta19600. PubMed PMID: 26222987; PubMed Central PMCID: PMCPMC4781341.
16. Leijon ME, Bendtsen P, Nilsen P, Ekberg K, Ståhle A. Physical activity referrals in Swedish primary health care—prescriber and patient characteristics, reasons for prescriptions, and prescribed activities. BMC Health Serv Res. 2008;8:201. Epub 2008/10/03. doi: 10.1186/1472-6963-8-201. PubMed PMID: 18828898; PubMed Central PMCID: PMCPMC2567971.
17. Lobelo F, Stoutenberg M, Hutber A. The exercise is medicine global health initiative: a 2014 update. Br J Sports Med. 2014;48(22):1627–33.
18. Creswell JW. Essential Skills for the Qualitative Researcher. Thousand Oaks (CA): Sage Publications; 2015.
19. Landon C. Evaluation of mHealth intervention in COPD: caremessage. Chest. 2017;152(4):A553. doi: 10.1016/j.chest.2017.08.583.
20. Beidas RS, Paciotti B, Barg F, et al. A hybrid effectiveness-implementation trial of an evidence-based exercise intervention for breast cancer survivors. J Natl Cancer Inst Monogr. 2014;2014(50):338–45. Epub 2015/03/10. doi: 10.1093/jncimonographs/lgu033. PubMed PMID: 25749601; PubMed Central PMCID: PMCPMC4411538.
21. Agerwala SM, McCance-Katz EF. Integrating screening, brief intervention, and referral to treatment (SBIRT) into clinical practice settings: a brief review. J Psychoactive Drugs. 2012;44(4):307–17. Epub 2012/12/06. doi: 10.1080/02791072.2012.720169. PubMed PMID: 23210379; PubMed Central PMCID: PMCPMC3801194.
22. Hebert ET, Caughy MO, Shuval K. Primary care providers’ perceptions of physical activity counselling in a clinical setting: a systematic review. Br J Sports Med. 2012;46(9):625–31. Epub 2012/06/20.
23. Klein KJ, Conn AB, Sorra JS. Implementing computerized technology: an organizational analysis. J Appl Psychol. 2001;86(5):811–24. Epub 2001/10/13. PubMed PMID: 11596799.
24. Weiner BJ, Haynes-Maslow L, Kahwati LC, Kinsinger LS, Campbell MK. Implementing the MOVE! weight-management program in the Veterans Health Administration, 2007–2010: a qualitative study. Prev Chronic Dis. 2012;9:E16. Epub 2011/12/17. PubMed PMID: 22172183; PubMed Central PMCID: PMCPMC3277396.
25. Damschroder LJ, Goodrich DE, Robinson CH, Fletcher CE, Lowery JC. A systematic exploration of differences in contextual factors related to implementing the MOVE! weight management program in VA: a mixed methods study. BMC Health Serv Res. 2011;11:248. Epub 2011/10/04. doi: 10.1186/1472-6963-11-248. PubMed PMID: 21961925; PubMed Central PMCID: PMCPMC3206421.
26. Tuot DS, Leeds K, Murphy EJ, et al. Facilitators and barriers to implementing electronic referral and/or consultation systems: a qualitative study of 16 health organizations. BMC Health Serv Res. 2015;15:568.

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