Recruiting low-income postpartum women into two weight loss interventions: in-person versus Facebook delivery

Recruiting low-income postpartum women into two weight loss interventions: in-person versus... Abstract Several studies, such as the Diabetes Prevention Program (DPP), have provided foundational evidence for the efficacy of lifestyle interventions on weight loss and cardiometabolic prevention. However, translating these interventions to real-world settings and engaging at-risk populations has proven difficult. Social media-delivered interventions have high potential for reaching high-risk populations, but there remains a need to understand the extent to which these groups are interested in social media as a delivery mode. One potential way to this is by examining recruitment rates as a proxy for interest in the intervention delivery format. The aim of this study was to describe the recruitment rates of overweight and obese low-income postpartum women into two asynchronous behavioral weight loss interventions: one delivered in-person and the other delivered via Facebook. Both interventions used the same recruitment methods: participants were overweight low-income postpartum women who were clients of Women, Infants, and Children (WIC) clinics in Worcester, MA, screened for the study by nutritionists during routine WIC visits. Similarly, eligibility criteria were the same for both interventions except for a requirement for the Facebook-delivered intervention to currently use Facebook at least once per week. Among women pre-eligible for the in-person intervention, 42.6% gave permission to be contacted to determine full eligibility and 24.1% of eligible women enrolled. Among women pre-eligible for the Facebook intervention, 31.8% gave permission to be contacted and 28.5% of eligible women enrolled. Recruitment rates for a Facebook-based weight loss intervention were similar to recruitment rates for an in-person intervention, suggesting similar interest in the two program delivery modes among low-income postpartum women. Implications Practice: Social media delivery may be used to increase the interest and enrollment of socioeconomically disadvantaged groups in behavioral weight loss interventions. Policy: Policymakers who want to decrease the cost of real-world behavioral interventions should explore the extent to which weight loss intervention can be delivered via social media. Research: Future research should aim at understanding the intervention delivery modalities that increase interest and uptake of behavioral weight loss interventions among postpartum women. INTRODUCTION Several milestone studies, such as the Finnish Diabetes Prevention Study and the Diabetes Prevention Program (DPP), have demonstrated the efficacy of behavioral lifestyle interventions for weight loss and cardiometabolic risk reduction [1–3]. However, these interventions have been highly intensive and costly, and employed highly skilled interventionists [4, 5]. Furthermore, the efficacy studies testing such interventions have selected highly motivated participants, and provided an abundance of resources and incentives to participants to optimize interest in participation. Thus, translation of these efficacious interventions to resource-limited settings and high-risk populations has been challenging [5]. Numerous attempts have been made to translate the core intervention components in a manner that increases their dissemination and sustainability potential in “real-world” settings to improve the health of populations who are at an increased risk for obesity, such as low-income postpartum women [6–8]. In contrast to the highly motivated individuals who participated in efficacy studies, low-income postpartum women have life priorities and other challenges that may reduce interest in weight loss and chronic disease prevention programs, including work schedules, transportation challenges, and limited childcare [9–11]. As a result, previous behavioral interventions in this population have had limited impact on weight loss [9, 10, 12]. Social media usage has increased exponentially in recent years; more than three-quarters (76%) of Internet-using U.S. adults currently use at least one social media account compared to 60% in 2010 [13]. Adults use social media for many purposes, including for seeking and sharing health-related information [14–16]. Leveraging this trend, recent studies have utilized social media as an intervention delivery mode to translate efficacious interventions to promote weight loss in real-world settings [15–18]. Delivering a behavioral weight loss intervention via social media may be more cost-effective [18] and alleviate some key barriers associated with in-person delivery as participants would not have to worry about the cost and inconvenience associated with weekly sessions attendance (e.g., transportation, childcare) [19, 20]. Finally, social media-delivered interventions are unique in that participants can access the intervention content during their preexisting daily social media routine, and participants and interventionists are able to easily connect and interact with one another in real time [16, 19]. Reducing the burdens and barriers associated with in-person interventions may draw greater interest in social media-delivered interventions among underserved populations, such as low-income postpartum women. Studies of weight loss intervention preferences among minority and low-income women have endorsed programs that are low cost, alleviate transportation and childcare barriers, and address social support, emotional concerns, and cultural influences [21–24]. Although the research exploring specific interest in social media-delivered interventions is limited, one cross-sectional survey study found that a majority (81%) of women of childbearing age (N = 63) were interested in a weight loss program delivered via Twitter, and cited convenience and support/accountability as program advantages [25]. Another qualitative study among adolescents (n = 11) and parents (n = 21) demonstrated enthusiasm for delivering weight loss interventions via Facebook, and endorsed several benefits of this type of delivery, including receiving support, maintaining motivation, and connecting with other children [26]. However, these studies were conducted among primarily White participants, and research is needed to understand the interest in participating in social media-delivered weight loss interventions among low-income postpartum women who are at higher risk for obesity. One potential way to explore interest in social media-delivered interventions is by examining recruitment rates, which can serve as a proxy for interest, and potentially allow for a deeper understanding of the extent to which this interest translates to actual enrollment into a social media-delivered intervention. Therefore, the purpose of this article was to compare the recruitment rates of overweight and obese low-income postpartum women into two weight loss interventions adapted from the DPP lifestyle intervention: one delivered via in-person sessions [27] and the other delivered via Facebook. We hypothesized that given the convenience and low cost of the Facebook-delivered program, the recruitment rate for this program would be higher than that of the in-person program. METHODS Study design and participants This study is an analysis of two separate (asynchronous) pilot studies of the Fresh Start intervention that targeted overweight and obese low-income postpartum women in Worcester, MA [27, 28]. Although the time difference between the two studies may result in suboptimal evaluations, we targeted the same population of low-income postpartum women. Participants in both studies were postpartum women served by Women, Infants, and Children (WIC) clinics in the Worcester area. Both studies used a pre-post design. The first pilot program (“in-person intervention”) took place in 2010 [27], and the second one (“Facebook intervention”) took place in 2016–2017. Recruitment targets differed in the two studies. The in-person intervention sought to recruit 60 women in two recruitment waves over 8 months. The Facebook intervention sought to recruit 90 women in three recruitment waves over 8 months. Study design, eligibility criteria, and recruitment methods were the same in both pilots, except where otherwise noted. Eligibility criteria included being 6 weeks to 6 months postpartum, aged 18 and older, body mass index (BMI) > 27 kg/m2, English speaking, and having approval from their health care provider to participate in a weight loss program. Additional inclusion criteria for the Facebook intervention included the requirement of being a regular Facebook user, defined as currently using Facebook at least once per week. Participants were excluded if they were unable or unwilling to give informed consent, were pregnant or planning to become pregnant within the following 24 months, had a psychiatric illness that limited their ability to participate, were taking medication that causes weight changes, had no telephone, and/or were planning to move out of the area within the study period. During routine WIC visits, nutritionists screened clients for pre-eligibility by completing a checklist that included child and parent age, English proficiency, whether the mother was able to make her own decision about taking part in a research study (i.e., not cognitively impaired; able to provide informed consent), and BMI, based on chart reviews. WIC providers then gave these pre-eligible women a study fact sheet and inquired about their interest in learning more about the study. Interested women provided their contact information. This information was then passed to the study recruiter who contacted pre-eligible and interested women to explain the study further, ask additional eligibility questions, and ascertain interest. For the Facebook-delivered intervention, women also provided verbal consent during this phone call for the study to contact their health care provider for approval to participate in the study. For the in-person intervention, we contacted the health care provider after women had been seen in-person to provide written consent and baseline data collection Intervention procedures The in-person and Facebook interventions included the same content, which was adapted from the DPP [2, 29]. Briefly, Fresh Start was a manualized curriculum based on the DPP and adapted to increase the saliency of the intervention for diverse low-income postpartum women [27]. In-person intervention The in-person intervention methods have been published elsewhere [27]. Briefly, women attended eight, 90-min weekly group sessions followed by two telephone contacts. The intervention was delivered by a WIC nutritionist and a nutrition assistant. Facebook intervention The Facebook intervention consisted of a library of intervention posts adapted from the Fresh Start intervention manual, and delivered in the same order and over the same period of time as the original Fresh Start curriculum, via a secret, private Facebook group, accessible to participants only. The Facebook group format included two automated Facebook posts per day for 8 weeks with additional feedback from a lifestyle coach to answer questions, provide support, and facilitate interaction among participants. Analysis Descriptive statistics were calculated for the following demographic variables: age, BMI, number of children, race/ethnicity, marital status, and education. In order to test for differences in demographic characteristics between groups, we performed chi-square tests for categorical variables and t-test for continuous variables. Recruitment rates were calculated by determining the proportion of women who were eligible, agreed to be contacted, and enrolled in each of the interventions. The final percentage of women enrolled was calculated by dividing the total number of participants enrolled by the total number of women who were eligible. We also performed a chi-square test of independence to compare the proportion of women who enrolled in each of the two interventions. RESULTS Demographic characteristics of the in-person and Facebook interventions are presented in Table 1. Twenty-seven and 71 women participated in the in-person and Facebook interventions, respectively. Women in the in-person intervention were, on average, 27.8 years old (SD = 5.1), had a mean BMI of 32 (SD = 3.6), had an average 2.2 (SD = 1.2) children. Women were also predominantly Hispanic/Latina (29.6%) or non-Hispanic Black (22.2%), married or living with a partner (77.8%), and had a high school degree or less (55.6%). Women in the Facebook intervention had a mean age of 30.4 years (SD = 5.5), a mean BMI of 36.1 (SD = 6.2), and an average 2.4 (SD = 1.3) children. A majority was Hispanic/Latina (32.4%) or non-Hispanic Black (22.5%) and married or living with a partner (57.7%), and over one-third had a high school degree or less (35.2%). Women in the Facebook intervention were significantly older (p = .003) and had a significantly higher BMI (p = .002) compared to women in the in-person intervention. There were no differences in number of children, race/ethnicity, education, and marital status. Table 1 | Participant characteristics of the in-person and Facebook interventions Variable In-person intervention (N = 27) Facebook intervention (N = 71) p Age, mean (SD)a 27.8 (5.1) 30.4 (5.5) .003 BMI, mean (SD)a 32 (3.6) 36.1 (6.2) .002 Number of children, mean (SD) 2.2 (1.2) 2.4 (1.3) .36 Race/ethnicity, n (%) .78  Hispanic/Latina 8 (29.6) 23 (32.4)  Non-Hispanic Black 6 (22.2) 16 (22.5)  Non-Hispanic White 12 (44.4) 25 (35.2)  Asian 0 (0.0) 3 (4.2)  Other 1 (3.7) 4 (5.6) Education, n (%) .13  High school degree or less 15 (55.6) 25 (35.2)  Some college/2-year degree 6 (22.2) 30 (42.2)  4-year college degree or higher 6 (22.2) 16 (22.5) Marital status, n (%)a  Single (never married) 5 (18.5) 25 (35.2) .21  Married or living with partner 21 (77.8) 41 (57.7)  Separated, divorced, widowed 1 (3.7) 4 (5.6) Variable In-person intervention (N = 27) Facebook intervention (N = 71) p Age, mean (SD)a 27.8 (5.1) 30.4 (5.5) .003 BMI, mean (SD)a 32 (3.6) 36.1 (6.2) .002 Number of children, mean (SD) 2.2 (1.2) 2.4 (1.3) .36 Race/ethnicity, n (%) .78  Hispanic/Latina 8 (29.6) 23 (32.4)  Non-Hispanic Black 6 (22.2) 16 (22.5)  Non-Hispanic White 12 (44.4) 25 (35.2)  Asian 0 (0.0) 3 (4.2)  Other 1 (3.7) 4 (5.6) Education, n (%) .13  High school degree or less 15 (55.6) 25 (35.2)  Some college/2-year degree 6 (22.2) 30 (42.2)  4-year college degree or higher 6 (22.2) 16 (22.5) Marital status, n (%)a  Single (never married) 5 (18.5) 25 (35.2) .21  Married or living with partner 21 (77.8) 41 (57.7)  Separated, divorced, widowed 1 (3.7) 4 (5.6) BMI body mass index. aMissing one value. View Large Table 1 | Participant characteristics of the in-person and Facebook interventions Variable In-person intervention (N = 27) Facebook intervention (N = 71) p Age, mean (SD)a 27.8 (5.1) 30.4 (5.5) .003 BMI, mean (SD)a 32 (3.6) 36.1 (6.2) .002 Number of children, mean (SD) 2.2 (1.2) 2.4 (1.3) .36 Race/ethnicity, n (%) .78  Hispanic/Latina 8 (29.6) 23 (32.4)  Non-Hispanic Black 6 (22.2) 16 (22.5)  Non-Hispanic White 12 (44.4) 25 (35.2)  Asian 0 (0.0) 3 (4.2)  Other 1 (3.7) 4 (5.6) Education, n (%) .13  High school degree or less 15 (55.6) 25 (35.2)  Some college/2-year degree 6 (22.2) 30 (42.2)  4-year college degree or higher 6 (22.2) 16 (22.5) Marital status, n (%)a  Single (never married) 5 (18.5) 25 (35.2) .21  Married or living with partner 21 (77.8) 41 (57.7)  Separated, divorced, widowed 1 (3.7) 4 (5.6) Variable In-person intervention (N = 27) Facebook intervention (N = 71) p Age, mean (SD)a 27.8 (5.1) 30.4 (5.5) .003 BMI, mean (SD)a 32 (3.6) 36.1 (6.2) .002 Number of children, mean (SD) 2.2 (1.2) 2.4 (1.3) .36 Race/ethnicity, n (%) .78  Hispanic/Latina 8 (29.6) 23 (32.4)  Non-Hispanic Black 6 (22.2) 16 (22.5)  Non-Hispanic White 12 (44.4) 25 (35.2)  Asian 0 (0.0) 3 (4.2)  Other 1 (3.7) 4 (5.6) Education, n (%) .13  High school degree or less 15 (55.6) 25 (35.2)  Some college/2-year degree 6 (22.2) 30 (42.2)  4-year college degree or higher 6 (22.2) 16 (22.5) Marital status, n (%)a  Single (never married) 5 (18.5) 25 (35.2) .21  Married or living with partner 21 (77.8) 41 (57.7)  Separated, divorced, widowed 1 (3.7) 4 (5.6) BMI body mass index. aMissing one value. View Large The flow of recruitment for the in-person and Facebook interventions is presented in Fig. 1. Given the higher recruitment target, more women were assessed for eligibility in Facebook intervention (n = 494) compared to the in-person intervention (n = 169). Among women screened for initial eligibility by WIC nutritionists, 31.4% were ineligible and 26% refused permission to be contacted for the in-person intervention; 45.5% were ineligible and 22.7% refused permission to be contacted for the Facebook intervention. Among women screened for pre-eligibility, 42.6% were eligible and contacted for the in-person intervention and 31.8% were eligible and contacted for the Facebook intervention. Among women contacted for the interventions, 5.6% were ineligible and 56.9% refused or were unable to be contacted for the in-person intervention; 12.7% were ineligible and 42% refused or were unable to be contacted for the Facebook intervention. Subtracting women who were ineligible during the initial screening for eligibility at WIC and women who were ineligible after being contacted by study staff, a total number of 112 and 249 women were eligible for the in-person and Facebook interventions, respectively. Among eligible women, 24.1% enrolled in the in-person intervention and 28.5% enrolled in the Facebook intervention. There was no significant difference between the proportion of eligible women who enrolled in the in-person intervention versus the Facebook intervention (χ2 = 0.76, p = .38). Fig 1 View largeDownload slide | Consort diagram of the flow of recruitment for the in-person and Facebook interventions. *Percent enrolled was determined by calculating the total number of enrolled divided by the total number eligible. Fig 1 View largeDownload slide | Consort diagram of the flow of recruitment for the in-person and Facebook interventions. *Percent enrolled was determined by calculating the total number of enrolled divided by the total number eligible. DISCUSSION There is emerging evidence that demonstrates the potential utility of engaging individuals in social media-delivered behavioral weight loss interventions [15, 16], but there is still a need to better understand the extent to which social media-delivered programs generate interest among socioeconomically disadvantaged groups, such as low-income postpartum women, many of whom are at high risk for obesity and obesity-related cardiometabolic conditions [30, 31]. The present study described the recruitment rates of low-income postpartum women into two weight loss interventions adapted from the DPP, one delivered in-person and the other delivered via Facebook. About a quarter of eligible women enrolled in each of the interventions, and women were similarly as likely to enroll in an intervention delivered via in-person groups or private Facebook groups. Our findings are lower compared to two other in-person weight loss studies conducted among women enrolled in WIC programs, each with a recruitment rate of approximately 30% [9, 11]. However, a similar study using text messaging and Facebook support among postpartum women enrolled only 18 out of 152 eligible women (11.8%), potentially suggesting a slight increase in the interesting in engaging in a social media-delivered intervention in the past few years [12]. Our results suggest that the interest and enrollment of low-income and racial/ethnic minority women in behavioral weight loss interventions may not be influenced by the intervention modality types included in this study, namely in-person groups versus Facebook groups. A 2017 review by Rosenbaum et al. [19] concluded that behavioral weight loss studies that included both technological components (i.e., smartphone) and in-person components had the highest minority enrollment (~58%) compared to studies without in-person visits (~30%). Furthermore, while e-mail and websites were the most common types of technology included in behavioral weight loss trials, studies that incorporated both modes of intervention delivery showed no difference in terms of enrollment of minority individuals [19]. These similarities in recruitment suggest that multiple modality types may do little to influence whether or not low-income or racial/ethnic minority groups enroll in a given behavioral intervention. However, reporting enrollment by race and ethnicity is historically uncommon [32, 33], and more research is needed to evaluate the extent to which racial/ethnic minority enrollment in behavioral interventions is driven by the format of the intervention delivery. Another possible explanation for similar recruitment rates between the two studies is that, while social media-delivered interventions seemingly attenuate barriers associated with in-person trials (e.g., transportation and scheduling) [16], additional barriers may persist and influence the recruitment and receptivity of an intervention in low-income and racial/ethnic minority groups. For example, previous research has suggested that minority and low-income adults often face barriers to research participation that include linguistic differences, limited health literacy, distrust of the medical and scientific community, and limited understanding of research studies and informed consent [32, 34–39]. These important challenges would persist regardless of intervention delivery modality, and may have contributed to similar recruitment rates between the two interventions presented in this study. It is important to note that social media access was not a major barrier to recruitment into the Facebook-delivered intervention, as only 2 out of 157 women contacted for the Facebook intervention (1.3%) were ineligible due to not being a regular Facebook user. This study has several limitations. First, the recruitment processes occurred at different points in time, rather than concurrently. Thus, temporal changes over time may insert bias into comparing asynchronous interventions. However, we targeted the same population of low-income postpartum women; finding no significant differences in race/ethnicity, education level, or marital status, and the increase in BMI from the in-person to the Facebook intervention is consistent with population trends over time [40, 41]. Further, although social media usage increased from 2010 to 2016, a majority of U.S. adult Internet users had at least one social media account as of 2010 [42]. While these comparisons are less than optimal, our analysis still provided an opportunity for addressing an important research question and obtaining information that has not been previously examined in the literature. Second, women were not choosing one intervention over the other. Future research is needed to directly compared recruitment with synchronous timing in order to better understand whether participants prefer Facebook or in-person delivery. Qualitative work can also assess participants’ reasons and interest in participating in social media-delivered programs. Furthermore, we did not assess motivations for enrollment into each of the separate studies and more research is needed to determine what factors contribute to enrollment in weight loss interventions among low-income and racial/ethnic minority women. Third, this study focused on low-income postpartum women, and the results may not be generalizable to other socioeconomically disadvantaged groups with similarly high risk for obesity and other cardiometabolic conditions. Finally, recruitment does not necessarily predict participation and long-term engagement in weight loss interventions. Our future research will determine the extent to which low-income and minority women engage and participate in the Facebook-delivered weight loss intervention. CONCLUSIONS Recruiting high-risk populations, such as diverse low-income postpartum women, into lifestyle interventions has historically been challenging [19, 43]. This study compared the recruitment rates for two behavioral weight loss interventions targeting low-income postpartum women, one delivered in-person and the other delivered via Facebook. Findings showed that recruitment rates were similar between the two interventions, suggesting that while a Facebook-delivered intervention may alleviate some barriers to participation in a weight loss intervention, this format of intervention delivery may not increase the likelihood of enrollment. Thus, although Facebook-delivered weight loss interventions hold promise for reaching wider segments of the population, future research comparing synchronous recruitment may improve the interest, uptake, and reach of evidence-based weight loss interventions in real-world settings. Authors’ Contributions: V.J.S., S.C.L., and M.C.R. conceived the study and participated in the design and coordination. V.J.S., B.E., and A.L.-C. collected the data and performed the analysis. V.J.S. drafted the manuscript. All authors reviewed the manuscript and approved the final version. Compliance with Ethical Standards Conflict of Interest: The authors have no conflicts of interest: The findings presented in this manuscript have not been previously published and this manuscript is not being simultaneously submitted elsewhere. Ethical Approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed Consent: Informed consent was obtained from all individual participants included in the study. Acknowledgments: We acknowledge the contributions of our community partners and organizations that made this research possible: the Worcester Women, Infants, and Children (WIC) Program and our University of Massachusetts Medical School colleagues and staff (Karen Ronayne and Linda Olsen). This research was generously supported through grants from the National Institute of Minority Health and Health Disparities (1 P60 MD006912-02), the National Heart, Lung and Blood Institute Training Grant 1T32HL120823-01, and the Centers for Disease Control and Prevention (U48 DP005031-01). References 1. Kriska AM , Delahanty LM , Pettee KK . Lifestyle intervention for the prevention of type 2 diabetes: translation and future recommendations . Curr Diab Rep . 2004 ; 4 ( 2 ): 113 – 118 . Google Scholar CrossRef Search ADS PubMed 2. The Diabetes Prevention Program Research Group . The Diabetes Prevention Program: design and methods for a clinical trial in the prevention of type 2 diabetes . 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Obes Rev . 2014 ; 15 ( suppl 4 ): 146 – 158 . Google Scholar CrossRef Search ADS PubMed © Society of Behavioral Medicine 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Translational Behavioral Medicine Oxford University Press

Recruiting low-income postpartum women into two weight loss interventions: in-person versus Facebook delivery

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Abstract

Abstract Several studies, such as the Diabetes Prevention Program (DPP), have provided foundational evidence for the efficacy of lifestyle interventions on weight loss and cardiometabolic prevention. However, translating these interventions to real-world settings and engaging at-risk populations has proven difficult. Social media-delivered interventions have high potential for reaching high-risk populations, but there remains a need to understand the extent to which these groups are interested in social media as a delivery mode. One potential way to this is by examining recruitment rates as a proxy for interest in the intervention delivery format. The aim of this study was to describe the recruitment rates of overweight and obese low-income postpartum women into two asynchronous behavioral weight loss interventions: one delivered in-person and the other delivered via Facebook. Both interventions used the same recruitment methods: participants were overweight low-income postpartum women who were clients of Women, Infants, and Children (WIC) clinics in Worcester, MA, screened for the study by nutritionists during routine WIC visits. Similarly, eligibility criteria were the same for both interventions except for a requirement for the Facebook-delivered intervention to currently use Facebook at least once per week. Among women pre-eligible for the in-person intervention, 42.6% gave permission to be contacted to determine full eligibility and 24.1% of eligible women enrolled. Among women pre-eligible for the Facebook intervention, 31.8% gave permission to be contacted and 28.5% of eligible women enrolled. Recruitment rates for a Facebook-based weight loss intervention were similar to recruitment rates for an in-person intervention, suggesting similar interest in the two program delivery modes among low-income postpartum women. Implications Practice: Social media delivery may be used to increase the interest and enrollment of socioeconomically disadvantaged groups in behavioral weight loss interventions. Policy: Policymakers who want to decrease the cost of real-world behavioral interventions should explore the extent to which weight loss intervention can be delivered via social media. Research: Future research should aim at understanding the intervention delivery modalities that increase interest and uptake of behavioral weight loss interventions among postpartum women. INTRODUCTION Several milestone studies, such as the Finnish Diabetes Prevention Study and the Diabetes Prevention Program (DPP), have demonstrated the efficacy of behavioral lifestyle interventions for weight loss and cardiometabolic risk reduction [1–3]. However, these interventions have been highly intensive and costly, and employed highly skilled interventionists [4, 5]. Furthermore, the efficacy studies testing such interventions have selected highly motivated participants, and provided an abundance of resources and incentives to participants to optimize interest in participation. Thus, translation of these efficacious interventions to resource-limited settings and high-risk populations has been challenging [5]. Numerous attempts have been made to translate the core intervention components in a manner that increases their dissemination and sustainability potential in “real-world” settings to improve the health of populations who are at an increased risk for obesity, such as low-income postpartum women [6–8]. In contrast to the highly motivated individuals who participated in efficacy studies, low-income postpartum women have life priorities and other challenges that may reduce interest in weight loss and chronic disease prevention programs, including work schedules, transportation challenges, and limited childcare [9–11]. As a result, previous behavioral interventions in this population have had limited impact on weight loss [9, 10, 12]. Social media usage has increased exponentially in recent years; more than three-quarters (76%) of Internet-using U.S. adults currently use at least one social media account compared to 60% in 2010 [13]. Adults use social media for many purposes, including for seeking and sharing health-related information [14–16]. Leveraging this trend, recent studies have utilized social media as an intervention delivery mode to translate efficacious interventions to promote weight loss in real-world settings [15–18]. Delivering a behavioral weight loss intervention via social media may be more cost-effective [18] and alleviate some key barriers associated with in-person delivery as participants would not have to worry about the cost and inconvenience associated with weekly sessions attendance (e.g., transportation, childcare) [19, 20]. Finally, social media-delivered interventions are unique in that participants can access the intervention content during their preexisting daily social media routine, and participants and interventionists are able to easily connect and interact with one another in real time [16, 19]. Reducing the burdens and barriers associated with in-person interventions may draw greater interest in social media-delivered interventions among underserved populations, such as low-income postpartum women. Studies of weight loss intervention preferences among minority and low-income women have endorsed programs that are low cost, alleviate transportation and childcare barriers, and address social support, emotional concerns, and cultural influences [21–24]. Although the research exploring specific interest in social media-delivered interventions is limited, one cross-sectional survey study found that a majority (81%) of women of childbearing age (N = 63) were interested in a weight loss program delivered via Twitter, and cited convenience and support/accountability as program advantages [25]. Another qualitative study among adolescents (n = 11) and parents (n = 21) demonstrated enthusiasm for delivering weight loss interventions via Facebook, and endorsed several benefits of this type of delivery, including receiving support, maintaining motivation, and connecting with other children [26]. However, these studies were conducted among primarily White participants, and research is needed to understand the interest in participating in social media-delivered weight loss interventions among low-income postpartum women who are at higher risk for obesity. One potential way to explore interest in social media-delivered interventions is by examining recruitment rates, which can serve as a proxy for interest, and potentially allow for a deeper understanding of the extent to which this interest translates to actual enrollment into a social media-delivered intervention. Therefore, the purpose of this article was to compare the recruitment rates of overweight and obese low-income postpartum women into two weight loss interventions adapted from the DPP lifestyle intervention: one delivered via in-person sessions [27] and the other delivered via Facebook. We hypothesized that given the convenience and low cost of the Facebook-delivered program, the recruitment rate for this program would be higher than that of the in-person program. METHODS Study design and participants This study is an analysis of two separate (asynchronous) pilot studies of the Fresh Start intervention that targeted overweight and obese low-income postpartum women in Worcester, MA [27, 28]. Although the time difference between the two studies may result in suboptimal evaluations, we targeted the same population of low-income postpartum women. Participants in both studies were postpartum women served by Women, Infants, and Children (WIC) clinics in the Worcester area. Both studies used a pre-post design. The first pilot program (“in-person intervention”) took place in 2010 [27], and the second one (“Facebook intervention”) took place in 2016–2017. Recruitment targets differed in the two studies. The in-person intervention sought to recruit 60 women in two recruitment waves over 8 months. The Facebook intervention sought to recruit 90 women in three recruitment waves over 8 months. Study design, eligibility criteria, and recruitment methods were the same in both pilots, except where otherwise noted. Eligibility criteria included being 6 weeks to 6 months postpartum, aged 18 and older, body mass index (BMI) > 27 kg/m2, English speaking, and having approval from their health care provider to participate in a weight loss program. Additional inclusion criteria for the Facebook intervention included the requirement of being a regular Facebook user, defined as currently using Facebook at least once per week. Participants were excluded if they were unable or unwilling to give informed consent, were pregnant or planning to become pregnant within the following 24 months, had a psychiatric illness that limited their ability to participate, were taking medication that causes weight changes, had no telephone, and/or were planning to move out of the area within the study period. During routine WIC visits, nutritionists screened clients for pre-eligibility by completing a checklist that included child and parent age, English proficiency, whether the mother was able to make her own decision about taking part in a research study (i.e., not cognitively impaired; able to provide informed consent), and BMI, based on chart reviews. WIC providers then gave these pre-eligible women a study fact sheet and inquired about their interest in learning more about the study. Interested women provided their contact information. This information was then passed to the study recruiter who contacted pre-eligible and interested women to explain the study further, ask additional eligibility questions, and ascertain interest. For the Facebook-delivered intervention, women also provided verbal consent during this phone call for the study to contact their health care provider for approval to participate in the study. For the in-person intervention, we contacted the health care provider after women had been seen in-person to provide written consent and baseline data collection Intervention procedures The in-person and Facebook interventions included the same content, which was adapted from the DPP [2, 29]. Briefly, Fresh Start was a manualized curriculum based on the DPP and adapted to increase the saliency of the intervention for diverse low-income postpartum women [27]. In-person intervention The in-person intervention methods have been published elsewhere [27]. Briefly, women attended eight, 90-min weekly group sessions followed by two telephone contacts. The intervention was delivered by a WIC nutritionist and a nutrition assistant. Facebook intervention The Facebook intervention consisted of a library of intervention posts adapted from the Fresh Start intervention manual, and delivered in the same order and over the same period of time as the original Fresh Start curriculum, via a secret, private Facebook group, accessible to participants only. The Facebook group format included two automated Facebook posts per day for 8 weeks with additional feedback from a lifestyle coach to answer questions, provide support, and facilitate interaction among participants. Analysis Descriptive statistics were calculated for the following demographic variables: age, BMI, number of children, race/ethnicity, marital status, and education. In order to test for differences in demographic characteristics between groups, we performed chi-square tests for categorical variables and t-test for continuous variables. Recruitment rates were calculated by determining the proportion of women who were eligible, agreed to be contacted, and enrolled in each of the interventions. The final percentage of women enrolled was calculated by dividing the total number of participants enrolled by the total number of women who were eligible. We also performed a chi-square test of independence to compare the proportion of women who enrolled in each of the two interventions. RESULTS Demographic characteristics of the in-person and Facebook interventions are presented in Table 1. Twenty-seven and 71 women participated in the in-person and Facebook interventions, respectively. Women in the in-person intervention were, on average, 27.8 years old (SD = 5.1), had a mean BMI of 32 (SD = 3.6), had an average 2.2 (SD = 1.2) children. Women were also predominantly Hispanic/Latina (29.6%) or non-Hispanic Black (22.2%), married or living with a partner (77.8%), and had a high school degree or less (55.6%). Women in the Facebook intervention had a mean age of 30.4 years (SD = 5.5), a mean BMI of 36.1 (SD = 6.2), and an average 2.4 (SD = 1.3) children. A majority was Hispanic/Latina (32.4%) or non-Hispanic Black (22.5%) and married or living with a partner (57.7%), and over one-third had a high school degree or less (35.2%). Women in the Facebook intervention were significantly older (p = .003) and had a significantly higher BMI (p = .002) compared to women in the in-person intervention. There were no differences in number of children, race/ethnicity, education, and marital status. Table 1 | Participant characteristics of the in-person and Facebook interventions Variable In-person intervention (N = 27) Facebook intervention (N = 71) p Age, mean (SD)a 27.8 (5.1) 30.4 (5.5) .003 BMI, mean (SD)a 32 (3.6) 36.1 (6.2) .002 Number of children, mean (SD) 2.2 (1.2) 2.4 (1.3) .36 Race/ethnicity, n (%) .78  Hispanic/Latina 8 (29.6) 23 (32.4)  Non-Hispanic Black 6 (22.2) 16 (22.5)  Non-Hispanic White 12 (44.4) 25 (35.2)  Asian 0 (0.0) 3 (4.2)  Other 1 (3.7) 4 (5.6) Education, n (%) .13  High school degree or less 15 (55.6) 25 (35.2)  Some college/2-year degree 6 (22.2) 30 (42.2)  4-year college degree or higher 6 (22.2) 16 (22.5) Marital status, n (%)a  Single (never married) 5 (18.5) 25 (35.2) .21  Married or living with partner 21 (77.8) 41 (57.7)  Separated, divorced, widowed 1 (3.7) 4 (5.6) Variable In-person intervention (N = 27) Facebook intervention (N = 71) p Age, mean (SD)a 27.8 (5.1) 30.4 (5.5) .003 BMI, mean (SD)a 32 (3.6) 36.1 (6.2) .002 Number of children, mean (SD) 2.2 (1.2) 2.4 (1.3) .36 Race/ethnicity, n (%) .78  Hispanic/Latina 8 (29.6) 23 (32.4)  Non-Hispanic Black 6 (22.2) 16 (22.5)  Non-Hispanic White 12 (44.4) 25 (35.2)  Asian 0 (0.0) 3 (4.2)  Other 1 (3.7) 4 (5.6) Education, n (%) .13  High school degree or less 15 (55.6) 25 (35.2)  Some college/2-year degree 6 (22.2) 30 (42.2)  4-year college degree or higher 6 (22.2) 16 (22.5) Marital status, n (%)a  Single (never married) 5 (18.5) 25 (35.2) .21  Married or living with partner 21 (77.8) 41 (57.7)  Separated, divorced, widowed 1 (3.7) 4 (5.6) BMI body mass index. aMissing one value. View Large Table 1 | Participant characteristics of the in-person and Facebook interventions Variable In-person intervention (N = 27) Facebook intervention (N = 71) p Age, mean (SD)a 27.8 (5.1) 30.4 (5.5) .003 BMI, mean (SD)a 32 (3.6) 36.1 (6.2) .002 Number of children, mean (SD) 2.2 (1.2) 2.4 (1.3) .36 Race/ethnicity, n (%) .78  Hispanic/Latina 8 (29.6) 23 (32.4)  Non-Hispanic Black 6 (22.2) 16 (22.5)  Non-Hispanic White 12 (44.4) 25 (35.2)  Asian 0 (0.0) 3 (4.2)  Other 1 (3.7) 4 (5.6) Education, n (%) .13  High school degree or less 15 (55.6) 25 (35.2)  Some college/2-year degree 6 (22.2) 30 (42.2)  4-year college degree or higher 6 (22.2) 16 (22.5) Marital status, n (%)a  Single (never married) 5 (18.5) 25 (35.2) .21  Married or living with partner 21 (77.8) 41 (57.7)  Separated, divorced, widowed 1 (3.7) 4 (5.6) Variable In-person intervention (N = 27) Facebook intervention (N = 71) p Age, mean (SD)a 27.8 (5.1) 30.4 (5.5) .003 BMI, mean (SD)a 32 (3.6) 36.1 (6.2) .002 Number of children, mean (SD) 2.2 (1.2) 2.4 (1.3) .36 Race/ethnicity, n (%) .78  Hispanic/Latina 8 (29.6) 23 (32.4)  Non-Hispanic Black 6 (22.2) 16 (22.5)  Non-Hispanic White 12 (44.4) 25 (35.2)  Asian 0 (0.0) 3 (4.2)  Other 1 (3.7) 4 (5.6) Education, n (%) .13  High school degree or less 15 (55.6) 25 (35.2)  Some college/2-year degree 6 (22.2) 30 (42.2)  4-year college degree or higher 6 (22.2) 16 (22.5) Marital status, n (%)a  Single (never married) 5 (18.5) 25 (35.2) .21  Married or living with partner 21 (77.8) 41 (57.7)  Separated, divorced, widowed 1 (3.7) 4 (5.6) BMI body mass index. aMissing one value. View Large The flow of recruitment for the in-person and Facebook interventions is presented in Fig. 1. Given the higher recruitment target, more women were assessed for eligibility in Facebook intervention (n = 494) compared to the in-person intervention (n = 169). Among women screened for initial eligibility by WIC nutritionists, 31.4% were ineligible and 26% refused permission to be contacted for the in-person intervention; 45.5% were ineligible and 22.7% refused permission to be contacted for the Facebook intervention. Among women screened for pre-eligibility, 42.6% were eligible and contacted for the in-person intervention and 31.8% were eligible and contacted for the Facebook intervention. Among women contacted for the interventions, 5.6% were ineligible and 56.9% refused or were unable to be contacted for the in-person intervention; 12.7% were ineligible and 42% refused or were unable to be contacted for the Facebook intervention. Subtracting women who were ineligible during the initial screening for eligibility at WIC and women who were ineligible after being contacted by study staff, a total number of 112 and 249 women were eligible for the in-person and Facebook interventions, respectively. Among eligible women, 24.1% enrolled in the in-person intervention and 28.5% enrolled in the Facebook intervention. There was no significant difference between the proportion of eligible women who enrolled in the in-person intervention versus the Facebook intervention (χ2 = 0.76, p = .38). Fig 1 View largeDownload slide | Consort diagram of the flow of recruitment for the in-person and Facebook interventions. *Percent enrolled was determined by calculating the total number of enrolled divided by the total number eligible. Fig 1 View largeDownload slide | Consort diagram of the flow of recruitment for the in-person and Facebook interventions. *Percent enrolled was determined by calculating the total number of enrolled divided by the total number eligible. DISCUSSION There is emerging evidence that demonstrates the potential utility of engaging individuals in social media-delivered behavioral weight loss interventions [15, 16], but there is still a need to better understand the extent to which social media-delivered programs generate interest among socioeconomically disadvantaged groups, such as low-income postpartum women, many of whom are at high risk for obesity and obesity-related cardiometabolic conditions [30, 31]. The present study described the recruitment rates of low-income postpartum women into two weight loss interventions adapted from the DPP, one delivered in-person and the other delivered via Facebook. About a quarter of eligible women enrolled in each of the interventions, and women were similarly as likely to enroll in an intervention delivered via in-person groups or private Facebook groups. Our findings are lower compared to two other in-person weight loss studies conducted among women enrolled in WIC programs, each with a recruitment rate of approximately 30% [9, 11]. However, a similar study using text messaging and Facebook support among postpartum women enrolled only 18 out of 152 eligible women (11.8%), potentially suggesting a slight increase in the interesting in engaging in a social media-delivered intervention in the past few years [12]. Our results suggest that the interest and enrollment of low-income and racial/ethnic minority women in behavioral weight loss interventions may not be influenced by the intervention modality types included in this study, namely in-person groups versus Facebook groups. A 2017 review by Rosenbaum et al. [19] concluded that behavioral weight loss studies that included both technological components (i.e., smartphone) and in-person components had the highest minority enrollment (~58%) compared to studies without in-person visits (~30%). Furthermore, while e-mail and websites were the most common types of technology included in behavioral weight loss trials, studies that incorporated both modes of intervention delivery showed no difference in terms of enrollment of minority individuals [19]. These similarities in recruitment suggest that multiple modality types may do little to influence whether or not low-income or racial/ethnic minority groups enroll in a given behavioral intervention. However, reporting enrollment by race and ethnicity is historically uncommon [32, 33], and more research is needed to evaluate the extent to which racial/ethnic minority enrollment in behavioral interventions is driven by the format of the intervention delivery. Another possible explanation for similar recruitment rates between the two studies is that, while social media-delivered interventions seemingly attenuate barriers associated with in-person trials (e.g., transportation and scheduling) [16], additional barriers may persist and influence the recruitment and receptivity of an intervention in low-income and racial/ethnic minority groups. For example, previous research has suggested that minority and low-income adults often face barriers to research participation that include linguistic differences, limited health literacy, distrust of the medical and scientific community, and limited understanding of research studies and informed consent [32, 34–39]. These important challenges would persist regardless of intervention delivery modality, and may have contributed to similar recruitment rates between the two interventions presented in this study. It is important to note that social media access was not a major barrier to recruitment into the Facebook-delivered intervention, as only 2 out of 157 women contacted for the Facebook intervention (1.3%) were ineligible due to not being a regular Facebook user. This study has several limitations. First, the recruitment processes occurred at different points in time, rather than concurrently. Thus, temporal changes over time may insert bias into comparing asynchronous interventions. However, we targeted the same population of low-income postpartum women; finding no significant differences in race/ethnicity, education level, or marital status, and the increase in BMI from the in-person to the Facebook intervention is consistent with population trends over time [40, 41]. Further, although social media usage increased from 2010 to 2016, a majority of U.S. adult Internet users had at least one social media account as of 2010 [42]. While these comparisons are less than optimal, our analysis still provided an opportunity for addressing an important research question and obtaining information that has not been previously examined in the literature. Second, women were not choosing one intervention over the other. Future research is needed to directly compared recruitment with synchronous timing in order to better understand whether participants prefer Facebook or in-person delivery. Qualitative work can also assess participants’ reasons and interest in participating in social media-delivered programs. Furthermore, we did not assess motivations for enrollment into each of the separate studies and more research is needed to determine what factors contribute to enrollment in weight loss interventions among low-income and racial/ethnic minority women. Third, this study focused on low-income postpartum women, and the results may not be generalizable to other socioeconomically disadvantaged groups with similarly high risk for obesity and other cardiometabolic conditions. Finally, recruitment does not necessarily predict participation and long-term engagement in weight loss interventions. Our future research will determine the extent to which low-income and minority women engage and participate in the Facebook-delivered weight loss intervention. CONCLUSIONS Recruiting high-risk populations, such as diverse low-income postpartum women, into lifestyle interventions has historically been challenging [19, 43]. This study compared the recruitment rates for two behavioral weight loss interventions targeting low-income postpartum women, one delivered in-person and the other delivered via Facebook. Findings showed that recruitment rates were similar between the two interventions, suggesting that while a Facebook-delivered intervention may alleviate some barriers to participation in a weight loss intervention, this format of intervention delivery may not increase the likelihood of enrollment. Thus, although Facebook-delivered weight loss interventions hold promise for reaching wider segments of the population, future research comparing synchronous recruitment may improve the interest, uptake, and reach of evidence-based weight loss interventions in real-world settings. Authors’ Contributions: V.J.S., S.C.L., and M.C.R. conceived the study and participated in the design and coordination. V.J.S., B.E., and A.L.-C. collected the data and performed the analysis. V.J.S. drafted the manuscript. All authors reviewed the manuscript and approved the final version. Compliance with Ethical Standards Conflict of Interest: The authors have no conflicts of interest: The findings presented in this manuscript have not been previously published and this manuscript is not being simultaneously submitted elsewhere. Ethical Approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed Consent: Informed consent was obtained from all individual participants included in the study. Acknowledgments: We acknowledge the contributions of our community partners and organizations that made this research possible: the Worcester Women, Infants, and Children (WIC) Program and our University of Massachusetts Medical School colleagues and staff (Karen Ronayne and Linda Olsen). This research was generously supported through grants from the National Institute of Minority Health and Health Disparities (1 P60 MD006912-02), the National Heart, Lung and Blood Institute Training Grant 1T32HL120823-01, and the Centers for Disease Control and Prevention (U48 DP005031-01). References 1. Kriska AM , Delahanty LM , Pettee KK . Lifestyle intervention for the prevention of type 2 diabetes: translation and future recommendations . Curr Diab Rep . 2004 ; 4 ( 2 ): 113 – 118 . Google Scholar CrossRef Search ADS PubMed 2. The Diabetes Prevention Program Research Group . The Diabetes Prevention Program: design and methods for a clinical trial in the prevention of type 2 diabetes . 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Translational Behavioral MedicineOxford University Press

Published: Feb 21, 2018

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