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Published on 19.03.18 in Vol 7, No 3 (2018): March

Preprints (earlier versions) of this paper are available at http://preprints.jmir.org/preprint/8229, first published Jun 21, 2017.

This paper is in the following e-collection/theme issue:

    Original Paper

    Assessing the Feasibility of a Social Media to Promote Weight Management Engagement in Adolescents with Severe Obesity: Pilot Study

    1Division of Gastreoenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, United States

    2Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

    3Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States

    4Biostatistics Collaboration Core, Emory University, Atlanta, GA, United States

    5Department of Psychiatry, The Children's Hospital of Philadelphia, Philadelphia, PA, United States

    6College of Science and Technology, Temple University, Philadelphia, PA, United States

    7Pediatrics Advanced Care Team, The Children's Hospital of Philadelphia, Philadelphia, PA, United States

    8College of Public Health, Temple University, Philadelphia, PA, United States

    Corresponding Author:

    Elizabeth Prout Parks, MD, MSc

    Division of Gastreoenterology, Hepatology and Nutrition

    The Children's Hospital of Philadelphia

    2716 South St, Room 14361

    Philadelphia, PA, 19119

    United States

    Phone: 1 2167 426 9721

    Fax:1 267 425 1075

    Email:


    ABSTRACT

    Background: Severe obesity in adolescents has deleterious physical and psychological complications necessitating frequent multi-disciplinary clinic visits. Greater treatment engagement has been equated with weight-loss. However, traditional medical weight-loss programs for adolescents have high attrition rates. Social media is widely used by adolescents and may enhance medical weight management engagement and success.

    Objective: The first objective was to examine the acceptability and feasibility of using a private social media group as an adjunct to medical weight management in youth ages 14 to 20 years with severe obesity [body mass index (BMI) ≥ 35 kg/m2]. The second objective was to pilot test the use of social media to improve treatment engagement and decrease attrition rates.

    Methods: In this single arm, 12 week pre-post study, participants attended individual clinic visits and participated in a moderated private social media group that received nutrition, exercise, and behavior change social media communications or “posts” 3 to 4 times/week. Youth commented and/or liked posts from the moderator and each other. Social media engagement was measured with the number of likes and comments on social media. Clinic attrition was compared, measuring clinic visit attendance 12 weeks prior, during, and after the intervention with mixed linear regression models. Correlations of social media engagement with changes from baseline for BMI, BMI-z score, and psychosocial measures were fit.

    Results: All 13 enrolled youth completed the study and reported that the group was enjoyable, helpful, reinforced their weight management program, and would recommend using social media to support other youth. The pilot trial was acceptable and feasible. Youth mean weekly engagement (likes + comments) in social media was greater than once a day (8.6 ±3.6). Compared to 12 weeks prior to the intervention, there was no significant decrease in clinic visit attendance at the end of the intervention (M=.231, P=.69) or 12 weeks at the conclusion of the intervention (M=.589, P=.28). Increased social media comments correlated with weight change (r=–.633, P=.04).

    Conclusions: This pilot trial demonstrated that the use of social media as an adjunct to medical weight management was feasible and acceptable to adolescents with severe obesity. Based upon these preliminary findings, social media may be an effective way to mitigate attrition from obesity treatment programs, and improve health outcomes in this high-risk population.

    JMIR Res Protoc 2018;7(3):e52

    doi:10.2196/resprot.8229

    KEYWORDS

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    Introduction

    Over 3 million youth in the United States (9%) ages 10 to 19 have severe obesity, defined as a body mass index (BMI) ≥ 120% above the 95th percentile or BMI ≥ 35 kg/m2 [1,2]. Severe obesity and its associated physical impairments such as type 2 diabetes, obstructive sleep apnea and hypertension require treatment involving frequent follow-up with a multidisciplinary team (ie, dietitian, physical activity specialist, psychologist, physician and nurse) [3-5]. The United States Preventive Services Task Force recommends weekly contact with the weight management team over six months [5]. Challenges such as missing school or work, lack of social support, and frustration with weight-loss success contribute to observed attrition rates up to 82% in pediatric weight management programs [6-10]. Social media may provide an avenue to keep youth motivated and engaged in treatment.

    The use of social media as an adjunct to traditional weight management allows for both peer-based and professional support. Social media can provide tailored and immediate feedback as well as practical, informational and peer support, which may be beneficial in childhood obesity treatment [11]. Traditional adolescent obesity treatment programs include parents and families, but generally do not include peers. Adolescent peers influence health-related behavior through modeling, imitation, and social learning [12,13]. Social media is readily accessible with 87% of youth ages 12 to 17 using social media and having internet access [14]. Further, 73% of all teens and 64% of teens with household incomes of ≤ $50,000, have smartphones [14]. Yet there is a paucity of studies examining the use of social media in weight management of children or adolescents with obesity [15]. This pilot study examined the feasibility of using private social media groups in conjunction with traditional weight management to promote obesity treatment engagement and to decrease attrition rates in adolescents with severe obesity. We hypothesized that the peer support social media intervention would improve clinic visit attendance.


    Methods

    Study Design

    This single-arm feasibility study employed a pre-post design. We piloted a social media intervention among youth ages 14 to 20 years enrolled in a multi-disciplinary weight management clinic. To assess change in clinic attrition with and without the social media intervention, adolescents were enrolled in social media after they had completed 12 weeks of weight management in a tertiary care center.

    Recruitment

    Participants were recruited from two urban tertiary care centers that treated adolescent obesity. Rosters were generated from the electronic health record of potentially eligible participants. Letters describing the study were sent to the home and participants were contacted and screened by telephone. Additionally, study flyers were placed in clinics. Eligible youth (n=13) were currently enrolled in an outpatient medical weight management program, had a BMI ≥ 35 kg/m2, spoke English and had access to either a computer, tablet or a smartphone with a data and text plan. Youth with syndromic or secondary obesity, developmental delay, active substance abuse, untreated depression, psychosis, or an eating disorder other than binge eating disorder were excluded. Secondary to issues of social maturity, youth were divided into two groups based upon age: Group 1 (14 to 16 years) and Group 2 (17 to 20 years). Informed consent was obtained for experimentation with human subjects. The study flow is outlined in Figure 1.

    Enrollment Visit

    Youth were encouraged to attend monthly clinic visits with 1 or 2 medical weight management team members (dietitian, exercise physiologist, physician and psychologist) for 45 minutes and to follow their recommendations. At the enrollment visit, youth met the members of their age-based group and the group moderator, played icebreaker games, were invited to the private social media Facebook group, as well as MyFitnessPal. Acceptance of the invitation to the group was confirmed at the visit. Youth were given an age appropriate treatment manual based upon national guidelines that has previously been tested in adolescents to complement the in-person clinic visits [16,17]. They were advised to consume 1300-1500 kcal/day, to increase daily physical activity to 60 minutes, and to self-monitor these goals daily. Participants completed surveys in person at the enrollment and 12-week follow-up visits.

    Figure 1. Study Flow diagram. SM=social media.
    View this figure

    Intervention

    This 12-week pilot intervention utilized the private social media group moderated by a clinical psychologist. The moderator posted challenges and requests for updates on progress of participants’ goal setting weekly, and posted videos three times each week. Videos featured both youth and “experts” (dieticians, exercise physiologist, physicians, and the psychologist from their weight management team). Video content complemented the treatment manual and included: nutrition, physical activity, behavioral modification topics, cooking, and exercise demonstrations, and youth describing successes and challenges with adopting healthier behaviors (Figures 2 and 3). Youth were encouraged to share their own videos of behaviors and to comment on the moderator and peer posts. The moderator logged in twice a day to check and respond to posts.

    As the study involved participants using their personal mobile phones to access the group, each received a US $25 monthly stipend for 3 months to offset the cost of their phone data plan. Youth were informed that in order to be eligible for the stipend, they needed to post, like, or comment in Facebook at least 3 times per week. Beyond those basic guidelines, they were told that they could participate in the group as much or as little as desired. Participants who did not access the group for over 1 week received a private Facebook message with a reminder from the group moderator. Youth were also compensated for two in-person study visits to collect questionnaires and measure height and weight ($25/each). Facebook was chosen as the social media platform because of prior work, and because it was the most popular with youth in our age demographic at the time [14]. A generic name was given to the group “FACE” (Figure 2) that was not health or obesity related. Youth were counselled about the privacy settings. The Children’s Hospital of Philadelphia Internal Review Board was an active participant in insuring participant privacy and protection. Only participants who were invited by the study team could view or post to the group. Participants were able to receive individualized tailored feedback weekly in their social media inbox from the moderator and during their regular clinic appointments. Participants were encouraged to set individual goals, and to post them to the group based upon the weekly challenges and video posts. Participants were encouraged to share feedback on the progress of their goals with the group and to also provide feedback to their peers. They also had the option to inbox the moderator with the progress of their goals, to receive feedback.

    Measures

    Acceptability and Clinic Attrition

    Acceptability of the social media group was assessed using a 28-item questionnaire which consisted of 14 Likert-scale questions and 14 open-response questions adapted from a previously used questionnaire [15]. Families were advised (by their medical team) to come to clinic once a month. Clinic attendances 12 weeks prior, during, and after the intervention were compared. The total clinic visits attended over a 12-week period were calculated to determine attrition. [8].

    Social Media Engagement

    Social media engagement was assessed by compiling the total number of “likes” plus comments [18]. “Likes” and comments were each also examined separately. Participants were incentivized to engage a minimum of 3 times per week in order to watch the 3 video postings. Participants were not considered to be engaged in social media if total engagement was less than or equal to 3 times per week. In exploratory analysis, the effect of social media engagement on BMI, BMI-z-score, depression, quality of life and perceived social support was examined.

    Figure 2. This is the Facebook support page video introduction.
    View this figure
    Figure 3. This is a FACE page with prompt and participant response leading to the video.
    View this figure
    Anthropometrics

    BMI (kg/m2) and BMI-z-score were calculated from mean weight (to 0.1 kg) and height (0.1cm), which were measured on a digital electronic scale and wall-mounted stadiometer in triplicate at the enrollment visit and at the end of 12 weeks. Youth changed into scrubs at each measurement visit.

    Psychosocial measures

    Psychosocial outcomes included depression, quality of life and perceived social support, which were measured by self-report measures. Depression was measured by using the Beck Depression Inventory II (BDI-II), a 21-item inventory that measures mood with a higher score indicating greater depression [19]. Quality of life was measured with the Impact of Weight on Quality of Life Kids (IWQOL-kids), a 27-item inventory designed to assess the impact of weight status on quality of life, with a higher score indicating a better quality of life [20]. Perceived social support was assessed with the Multidimensional Scale of Perceived Social Support (MSPSS), a 12-item inventory assessing the social support of family, friends, and significant others, with a higher score indicating increased perceived social support [21]. The BDI-II, the IWQOL-kids and the MSPSS items report a test retest reliability of ≥ .78 and a validity score of ≥ .80 in obese adolescents [19,21,22].

    Statistical Analysis

    Descriptive analyses were described using calculated means and standard deviations. For the exploratory analysis of secondary outcomes, Wilcoxon rank sum was used to test changes at 12 weeks. Models were fit correlating mean total engagement (likes + comments), total likes and total comments, and total weekly engagement as a binary variable ≤ or > three times per week and total engagement ≤ or > 36 times total with BMI, BMI-z, depression, quality of life and perceived social support. To test our hypothesis and to assess changes in clinic visit, attendance over time mixed effects analysis were used. Mixed-model analyses allow for the incorporation of proper time trends (eg, nonlinear) and a variance-covariance structure that accounts for the correlation between repeated measures. The mixed-model included the group variable and time. Results are summarized with mean and by time. Analyses were conducted utilizing SAS statistical software (version 9.4; SAS Institute, Cary, NC). For all analyses, an α level of 0.05 was considered statistically significant.


    Results

    Participant Characteristics

    Secondary to the limited sample size, results for the combined groups are presented. The majority of youth were female, with private insurance, and had an average BMI of 45 kg/m2, which is adult class III extreme obesity, or pediatric severe obesity. There was an almost even racial distribution. The mean age of participants was 16 years of age (Table 1).

    Social Media Usage

    Overall, youth remained engaged in social media weekly (likes/comments > 4 times per week), mean 8.6 (SD 3.6). Youth “liked” more than they “commented” (Table 2). The number of times that posts were viewed by participants was unknown.

    Intervention Acceptability

    Overall, youth found the social media support group to be enjoyable (100% [13/13]), helpful (100% [13/13]), a source of motivation (100% [13/13]), and would recommend the social media group to other youth with severe obesity (100 [13/13]). Participants felt the group was helpful for peer support (85% [11/13]), advice on nutrition (100% [13/13]), exercise (85% [11/13]), and helpful to reinforce the goals for their weight management program (100% [13/13]). From the open responses, youth identified the group as helping them to be “accountable and feel that they were not alone” and “to receive positive reinforcement.” Youth reported that it was important to have an in-person weight management program along with the social media support group (92% [12/13]). Although adolescents could participate in social media at whatever time was convenient to them, they listed “time constraints of schoolwork and extracurricular activities” as preventing more frequent logins.

    Intervention Feasibility

    There were a total of 105 social media contacts from the moderator. Posts from the moderator included videos (63), challenges (6), requests for updates from participants (12), polls (2), pictures and links (9) and other information relevant to the intervention (13). Youth also uploaded videos and pictures (12). The moderator spent approximately 5 hours per week posting material and moderating comments for a total of 60 hours over the course of the 12-week intervention. All participants (n=13) completed the intervention and based upon insurance information included socioeconomically diverse background with 38% (5/13) using Medicaid.

    Table 1. Participant baseline characteristics (N=13). BMI: body mass index.
    View this table
    Table 2. Descriptive results of social media engagement over the course of 12 weeks (total) and weekly (N=13). Engagement = likes + comments.
    View this table
    Table 3. Spearman Correlation of social media engagement with change in secondary outcomes in all subjects (N=13). BMI: body mass index.
    View this table

    Clinic Attrition

    In mixed effects analysis, we included all subjects controlling for group to evaluate change in clinic attendance with time. The number of visits prior to the start of the intervention (baseline) were compared at 12 weeks (the end of the intervention) mean (M) =.231, P=.69, and 6 months (3 months at the conclusion of the intervention) (M=.589, P=.28). There was no significant change in clinic visit attendance across time points. This indicates there was not an increase in clinic attrition. Given high attrition rates from adolescent obesity treatment programs, this preliminary finding of continued engagement in treatment is encouraging [9].

    Social Media Engagement

    All analyses were exploratory and conducted in the combined sample controlling for group effect, secondary to the sample size. Mean changes were observed at 12 weeks for all participants for weight in kilograms (odds ratio [OR] –1.01 [95% CI –6.1, 4.08]), BMI (OR –1.25 [CI –2.99, 0.49]), BMI-z-score (OR –0.03 [CI –0.1, 0.03]), depression ( OR –1.69 [CI –4.96, 1.57]), quality of life (OR 3.84 [CI –2.63, 10.31]) and perceived social support (OR 3.46 [CI –1.06, 7.99]). Greater numbers of comments correlated with weight-loss at 12 weeks (r=–.633, P=.04) (Table 3).


    Discussion

    Principal Findings

    All enrolled adolescents (n=13) completed this social media intervention and found the use as an adjunct to medical weight management feasible and acceptable. Adolescents enjoyed the social media group, found it that it kept them motivated, encouraged, accountable, and informed. More than half of the group wanted to have more in-person groups as part of an intervention. Participants remained engaged in the social media group and within the in-person clinic. Clinic attrition decreased during the intervention. Youth remained engaged in the social media group overall with more likes than comments. Increased engagement with comments was correlated with weight-loss and increased perceived social support. We developed a privacy and safety plan that met the requirements of the institutional review board, which included the use of a private/secret group and monitoring/screening of posts.

    Comparison with Prior Work

    Compared with prior studies, our pilot demonstrated lower clinic visit attrition rates (27%) vs 42-82% [6-8]. The addition of a social media support group addressed key factors identified by adolescents for attrition from obesity treatment: a lack of peer support, logistical challenges, poor expectations, and a lack of tailoring of treatment for adolescents [7,23]. Participants confirmed the role of social media on clinic attendance in our acceptability survey in which they indicated that the social media group influenced their clinic participation, motivation and compliance with behavior changes.

    Despite the small size of our pilot group, the overall engagement in social media was high at 71% compared with studies using social media alone in older adolescents (41%) [11,18]. In order to achieve higher rates of engagement, we incorporated successful strategies from prior studies such as having an in-person group session for participants to meet one another at the beginning of the intervention, the use of a facilitator who provided constant reinforcement of participation according to Social Learning Theory, and utilized a “secret” group for privacy [15,24]. While polls were the most popular type of post in a study examining types of posts in adults, videos were the most popular post in this study [18]. Videos also included other adolescents, which may have encouraged participation. [25] Also similar to prior work we provided a US $25 monthly incentive to assist with the cost of mobile data for active participants [15]. Participants were incentivized for 3 posts and did not receive any additional incentives. Participant engagement was more than twice the incentivized amount (weekly mean=8.6 compared with requested 3 times per week). Additionally, youth were not incentivized to attend clinic visits.

    To our knowledge, this is the first study to examine the influence of a social media support group on medical weight management engagement/attrition. Attrition from in-person clinic visits did not increase in our study compared to rates of 50% or more normally seen in this population. Our use of age-based adolescent peer groups may address attrition by providing adolescent tailored interventions and increasing perceived peer support [26]. On the acceptability survey, participants indicated that the social media group influenced their clinic participation and reinforced what they learned in their medical weight management (100% [13/13]).

    Inclusion of Parents/Family Members

    Finding ways to incorporate parents/caregivers into the social media component will be important in next steps. Parents purchase the food for the home, provide transportation and financial support for physical activity, serve as role models of behavior and provide encouragement and support for behavioral modification [27-29]. In this study, parents attended clinic sessions with adolescents where goal setting was made at both the family and individual levels. During baseline and 12-week follow-up visits, parents of participants remained in a separate room to get to know one another. Parents expressed interest in a parent social media group. As parents are key agents of change, providing peer support on the parent level may also increase adolescent clinic attendance and should be explored in next steps.

    Limitations and Strengths

    Our study has both strengths and limitations. This single arm pilot study had a small sample size to determine feasibility. All enrolled participants completed this pre-post study. Although our sample size was small, it was racially and socioeconomically diverse. Heights and weights were objectively measured. Both quantitative and qualitative assessments of acceptability were used. Despite the small sample size, some significant associations were detected.

    However, as this is a cross-sectional study, the associations found do not necessarily reflect causality. Furthermore, it is possible that participants in this sample had a higher level of intrinsic motivation which kept them engaged. The data from this pilot trial will inform the conduct of a larger randomized controlled clinical trial. Adolescents were incentivized to like or comment which could have increased social media engagement. Incentives did not increase for liking vs commenting, or for engagement above the required 3 times per week. Engagement was above the minimum requirement for incentivization. While the majority of peer support came from social media, we acknowledge that the two in-person visits (for measurements and to meet other group members) could have also influenced perceived social support. That being said, adolescents were not incentivized to attend clinic visits. Our findings cannot be extrapolated to other forms of social media. Facebook was the most popular form of social media in youth at the time of our study [13]. Although, not as popular with youth today, Facebook is still one of the most popular social media platforms used by adolescents [14]. That being said, other platforms should also be tested.

    Other studies have found that social media engagement decreases over time [18,30]. It will be important to test the effects of a social media group longer term on attrition. Similar to prior studies, we measured engagement as a combination of likes and comments [18]. We acknowledge that commenting most likely reflects a higher level of engagement than liking as it requires reflection. This is also reflective of increased commenting as opposed to liking being associated with weight-loss. Finding ways to assist youth with interacting through comments is important for future interventions.


    Conclusions

    In summary, youth with severe obesity found social media support acceptable and useful as an adjunct to clinical care, and perceived it as helpful to remain motivated to attend medical weight management. Pilot results suggest social media groups may assist with decreasing clinic attrition rates and potentially contribute to successful weight management in this high-risk population.

    Acknowledgments

    We would like to thank the patients and staff of the Healthy Weight Program of The Children’s Hospital of Philadelphia and the Medical Weight Management program of the Hospital of University of Pennsylvania, the Pediatric Research Consortium for facilitating recruitment and data collection. We thank Peter Palumbo, with CHOP Information Services Department, for providing filming and video editing services for the intervention curriculum. Special thanks to Amber Nauman, BS, and Brittany Clark, MPH, for their assistance in this project.

    This research was funded by the Joint Penn-CHOP Center for Digestive, Liver and Pancreatic Medicine Pilot Project program of The Children’s Hospital of Philadelphia and the University of Pennsylvania. Dr. Prout Parks is funded by National Cancer Institute Mentored Research Scientist Development Award to Promote Diversity (K01): PAR-012-050: U.S. Department of Health and Human Services/National Institute of Health (K01 CA 160818-01).

    Authors' Contributions

    EPP and CTB conceptualized and designed the study. DLH assisted with developing videos, other intervention materials, and moderating the group. EPP, CTB, and AG implemented the pilot group intervention. EPP, and ARG acquired the data. EPP, RHM, ZL analyzed data. EPP, CTB, ZL, and DBS interpreted the data. EPP drafted the initial manuscript. All authors critically reviewed the final manuscript for submission. The contents of this manuscript were presented in 2015 at the ObesityWeek annual meeting in Boston, MA.

    Conflicts of Interest

    None declared

    References

    1. Kelly AS, Barlow SE, Rao G, Inge TH, Hayman LL, Steinberger J, et al. American Heart Association Atherosclerosis, Hypertension, and Obesity in the Young Committee of the Council on Cardiovascular Disease in the Young, Council on Nutrition, Physical Activity and Metabolism, and Council on Clinical Cardiology. Severe obesity in children and adolescents: identification, associated health risks, and treatment approaches: a scientific statement from the American Heart Association. Circulation 2013 Oct 08;128(15):1689-1712 [FREE Full text] [CrossRef] [Medline]
    2. Ogden CL, Carroll MD, Lawman HG, Fryar CD, Kruszon-Moran D, Kit BK, et al. Trends in Obesity Prevalence Among Children and Adolescents in the United States, 1988-1994 Through 2013-2014. JAMA 2016 Jun 07;315(21):2292-2299. [CrossRef] [Medline]
    3. Deitel M. The Surgeon-General's call to action to prevent an increase in overweight and obesity. Released Dec. 13, 2001. Obes Surg 2002 Feb;12(1):3-4. [Medline]
    4. Rappaport EB, Daskalakis C, Andrel J. Obesity and other predictors of absenteeism in Philadelphia school children. J Sch Health 2011 Jun;81(6):341-344. [CrossRef] [Medline]
    5. Whitlock EP, O'Connor EA, Williams SB, Beil TL, Lutz KW. Effectiveness of weight management interventions in children: a targeted systematic review for the USPSTF. Pediatrics 2010 Feb;125(2):e396-e418. [CrossRef] [Medline]
    6. Dolinsky DH, Armstrong SC, Østbye T. Predictors of attrition from a clinical pediatric obesity treatment program. Clin Pediatr (Phila) 2012 Dec;51(12):1168-1174. [CrossRef] [Medline]
    7. Rhodes ET, Boles RE, Chin K, Christison A, Testa EG, Guion K, et al. Expectations for Treatment in Pediatric Weight Management and Relationship to Attrition. Child Obes 2017 Apr;13(2):120-127. [CrossRef] [Medline]
    8. Dhaliwal J, Nosworthy NMI, Holt NL, Zwaigenbaum L, Avis JLS, Rasquinha A, et al. Attrition and the management of pediatric obesity: an integrative review. Child Obes 2014 Dec;10(6):461-473. [CrossRef] [Medline]
    9. Nogueira TFD, Zambon MP. Reasons for non-adherence to obesity treatment in children and adolescents. Rev Paul Pediatr 2013 Sep;31(3):338-343 [FREE Full text] [CrossRef] [Medline]
    10. Skelton JA, Beech BM. Attrition in paediatric weight management: a review of the literature and new directions. Obes Rev 2011 May;12(5):e273-e281 [FREE Full text] [CrossRef] [Medline]
    11. Napolitano MA, Hayes S, Bennett GG, Ives AK, Foster GD. Using Facebook and text messaging to deliver a weight loss program to college students. Obesity (Silver Spring) 2013 Jan;21(1):25-31 [FREE Full text] [CrossRef] [Medline]
    12. Bandura A. Self-efficacy: Toward a unifying theory of behavioral change, New York, NY, US. New Your, NY: Psychology Press; 1999:265-298.
    13. McNeeley C, Crosnoe R. Social status, peer influence, and weight gain in adolescence: promising directions for addressing the obesity epidemic. Arch Pediatr Adolesc Med 2008 Jan;162(1):91-92. [CrossRef] [Medline]
    14. Lenhart A. Teen, Social Media and Technology Overview. 2015.   URL: http://www.pewinternet.org/files/2015/04/PI_TeensandTech_Update2015_0409151.pdf [accessed 2018-02-05] [WebCite Cache]
    15. Gruver RS, Bishop-Gilyard CT, Lieberman A, Gerdes M, Virudachalam S, Suh AW, et al. A Social Media Peer Group Intervention for Mothers to Prevent Obesity and Promote Healthy Growth from Infancy: Development and Pilot Trial. JMIR Res Protoc 2016 Aug 02;5(3):e159 [FREE Full text] [CrossRef] [Medline]
    16. Barlow SE, Expert C. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics 2007 Dec;120 Suppl 4:S164-S192. [CrossRef] [Medline]
    17. Berkowitz RI, Rukstalis MR, Bishop-Gilyard CT, Moore RH, Gehrman CA, Xanthopoulos MS, et al. Treatment of adolescent obesity comparing self-guided and group lifestyle modification programs: a potential model for primary care. J Pediatr Psychol 2013 Oct;38(9):978-986 [FREE Full text] [CrossRef] [Medline]
    18. Merchant G, Weibel N, Patrick K, Fowler JH, Norman GJ, Gupta A, et al. Click “like” to change your behavior: a mixed methods study of college students' exposure to and engagement with Facebook content designed for weight loss. J Med Internet Res 2014;16(6):e158 [FREE Full text] [CrossRef] [Medline]
    19. Barrera M, Garrison-Jones CV. Properties of the Beck Depression Inventory as a screening instrument for adolescent depression. J Abnorm Child Psychol 1988 Jun;16(3):263-273. [Medline]
    20. Kolotkin RL, Zeller M, Modi AC, Samsa GP, Quinlan NP, Yanovski JA, et al. Assessing weight-related quality of life in adolescents. Obesity (Silver Spring) 2006 Mar;14(3):448-457 [FREE Full text] [CrossRef] [Medline]
    21. Zimet GD, Powell SS, Farley GK, Werkman S, Berkoff KA. Psychometric characteristics of the Multidimensional Scale of Perceived Social Support. J Pers Assess 1990;55(3-4):610-617. [CrossRef] [Medline]
    22. Kolotkin RL, Crosby RD, Kosloski KD, Williams GR. Development of a brief measure to assess quality of life in obesity. Obes Res 2001 Feb;9(2):102-111 [FREE Full text] [CrossRef] [Medline]
    23. Hampl S, Demeule M, Eneli I, Frank M, Hawkins MJ, Kirk S, et al. Parent perspectives on attrition from tertiary care pediatric weight management programs. Clin Pediatr (Phila) 2013 Jun;52(6):513-519. [CrossRef] [Medline]
    24. Cavallo DN, Sisneros JA, Ronay AA, Robbins CL, Jilcott PSB, Keyserling TC, et al. Assessing the Feasibility of a Web-Based Weight Loss Intervention for Low-Income Women of Reproductive Age: A Pilot Study. JMIR Res Protoc 2016;5(1):e30 [FREE Full text] [CrossRef] [Medline]
    25. Kim H, Ray CD, Veluscek AM. Complementary Support from Facilitators and Peers for Promoting mHealth Engagement and Weight Loss. J Health Commun 2017 Nov;22(11):905-912. [CrossRef] [Medline]
    26. Woolford SJ, Sallinen BJ, Schaffer S, Clark SJ. Eat, play, love: adolescent and parent perceptions of the components of a multidisciplinary weight management program. Clin Pediatr (Phila) 2012 Jul;51(7):678-684 [FREE Full text] [CrossRef] [Medline]
    27. Coulton C, Irwin M. Parental and community level correlates of participation in out-of-school activities among children living in low income neighborhoods. Children and Youth Services Review 2009 Mar;31(3):300-308. [CrossRef]
    28. Lohman BJ, Stewart S, Gundersen C, Garasky S, Eisenmann JC. Adolescent overweight and obesity: links to food insecurity and individual, maternal, and family stressors. J Adolesc Health 2009 Sep;45(3):230-237. [CrossRef] [Medline]
    29. Madsen KA, McCulloch CE, Crawford PB. Parent modeling: perceptions of parents' physical activity predict girls' activity throughout adolescence. J Pediatr 2009 Feb;154(2):278-283 [FREE Full text] [CrossRef] [Medline]
    30. Hales SB, Davidson C, Turner-McGrievy GM. Varying social media post types differentially impacts engagement in a behavioral weight loss intervention. Transl Behav Med 2014 Dec;4(4):355-362 [FREE Full text] [CrossRef] [Medline]


    Abbreviations

    BDI-II: Beck Depression Inventory II
    BMI: body mass index
    IWQOL-kids: Impact of Weight on Quality of Life Kids
    MSPSS: Multidimensional Scale of Perceived Social Support
    OR: odds ratio
    CHOP: The Children’s Hospital of Philadelphia


    Edited by G Eysenbach; submitted 21.06.17; peer-reviewed by D Cavallo, A Ronay; comments to author 03.08.17; revised version received 28.09.17; accepted 07.12.17; published 19.03.18

    ©Elizabeth Prout Parks, Renee' H Moore, Ziyi Li, Chanelle T Bishop-Gilyard, Andrew R Garrett, Douglas L Hill, Yasmeen P. Bruton, David B Sarwer. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 19.03.2018.

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