Interest in a Twitter-delivered weight loss program among women of childbearing age

Translational Behavioral Medicine

Volumn 6, Issue 2, 2016, Pages 277-284

  Waring, Molly E ^a   Schneider, Kristin L ^b   Appelhans, Bradley M ^c   Simas, Tiffany A Moore ^a   Xiao, Rui S ^a   Whited, Matthew C ^d   Busch, Andrew M ^e,f   Evans, Martinus M ^a   Pagoto, Sherry L ^a  

^a UNIVERSITY OF MASSACHUSETTS MEDICAL SCHOOL   (United States)

^b ROSALIND FRANKLIN UNIVERSITY OF MEDICINE AND SCIENCE   (United States)

^c RUSH UNIVERSITY MEDICAL CENTER   (United States)

^d EAST CAROLINA UNIVERSITY   (United States)

^e BROWN UNIVERSITY   (United States)

^f MIRIAM HOSPITAL   (United States)

Author keywords

Childbearing; Obesity; Online social networks; Social media; Twitter; Weight loss; Women

Indexed keywords

ADULT; ARTICLE; FEMALE; HUMAN; LANGUAGE; MIDDLE AGED; MOBILE APPLICATION; ONLINE ANALYSIS; OPEN ENDED QUESTIONNAIRE; PREGNANCY; PRIORITY JOURNAL; PROGRAM EFFECTIVENESS; PROGRAM FEASIBILITY; SOCIAL NETWORK; TWITTER BASED WEIGHT LOSS INTERVENTION; WEIGHT LOSS PROGRAM; YOUNG ADULT; INTERNET; OBESITY; PROCEDURES; PROGRAM EVALUATION; SOCIAL MEDIA; SOCIAL SUPPORT;

ADULT; FEMALE; HUMANS; INTERNET; OBESITY; PROGRAM EVALUATION; SOCIAL MEDIA; SOCIAL SUPPORT; WEIGHT REDUCTION PROGRAMS; YOUNG ADULT;

EID: 84976573779     PISSN: 18696716     EISSN: 16139860     Source Type: Journal    
DOI: 10.1007/s13142-015-0382-4     Document Type: Article

References (49)

1. Ogden CL et al. Prevalence of childhood and adult obesity in the United States, 2011–2012. JAMA. 2014; 311(8): 806-814.
2. Burke GL et al. Differences in weight gain in relation to race, gender, age and education in young adults: the CARDIA Study. Coronary Artery Risk Development in Young Adults. Ethn Health. 1996; 1(4): 327-335.
3. Gunderson EP et al. Excess gains in weight and waist circumference associated with childbearing: the Coronary Artery Risk Development in Young Adults Study (CARDIA). Int J Obes Relat Metab Disord. 2004; 28(4): 525-535.
4. Abrams B et al. Parity and body mass index in US women: a prospective 25-year study. Obesity (Silver Spring). 2013; 21(8): 1514-1518.
5. Pi-Sunyer FX. Medical hazards of obesity. Ann Intern Med. 1993; 119(7 Pt 2): 655-660.
6. Institute of Medicine (IOM) and National Research Council (NRC). Weight gain during pregnancy: reexamining the guidelines, K.M. Rasmussen and A.L. Yaktine, Eds. The National Academies Press; 2009.
7. Arendas K, Qiu Q, Gruslin A. Obesity in pregnancy: pre-conceptional to postpartum consequences. J Obstet Gynaecol Can. 2008; 30(6): 477-488.
8. Herring SJ, Oken E. Obesity and diabetes in mothers and their children: can we stop the intergenerational cycle? Curr Diab Rep. 2011; 11(1): 20-27.
9. Johnson DB et al. Preventing obesity: a life cycle perspective. J Am Diet Assoc. 2006; 106(1): 97-102.
10. American College of Obstetricians and Gynecologists. ACOG committee opinion no. 549: obesity in pregnancy. Obstet Gynecol. 2013; 121(1): 213-217.
11. NIH Obestiy Research Task Force. Strategic plan for NIH obesity research. Washington DC; 2011.
12. Healthy People 2010 Topics & Objectives. Accessed 3 October 2014; Available from: http://www.healthypeople.gov/2020/topicsobjectives2020/default.
13. Pagoto S. The current state of lifestyle intervention implementation research: where do we go next? Transl Behav Med. 2011; 1(3): 401-405.
14. Montgomery KS et al. Women’s challenges with postpartum weight loss. Matern Child Health J. 2011; 15(8): 1176-1184.
15. Ciao AC, Latner JD, Durso LE. Treatment seeking and barriers to weight loss treatments of different intensity levels among obese and overweight individuals. Eat Weight Disord. 2012; 17(1): e9-e16.
16. Womble LG et al. A randomized controlled trial of a commercial internet weight loss program. Obes Res. 2004; 12(6): 1011-1018.
17. Harvey-Berino J et al. Internet delivered behavioral obesity treatment. Prev Med. 2010; 51: 123-128.
18. Chang T et al. The role of social media in online weight management: systematic review. J Med Internet Res. 2013; 15(11), e262.
19. Ashrafian H et al. Social networking strategies that aim to reduce obesity have achieved significant although modest results. Health Aff (Millwood). 2014; 33(9): 1641-1647.
20. Gold B et al. Weight loss on the web: a pilot study comparing a structured behavioral intervention to a commercial program. Obesity. 2007; 15(1): 155-164.
21. Webber KH, Tate DF, Bowling JM. A randomized comparison of two motivationally enhanced Internet behavioral weight loss programs. Behav Res Ther. 2008; 46(9): 1090-1095.
22. Turner-McGrievy G, Tate D. Weight loss social support in 140 characters or less: use of an online social network in a remotely delivered weight loss intervention. Transl Behav Med: Pract, Policy Res. 2013; 3(3): 287-294.
23. Turner-McGrievy GM et al. Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program. J Am Med Inform Assoc. 2013; 20(3): 513-518.
24. Number of monthly active Twitter users worldwide from 1st quarter 2010 to 3rd quarter 2015 (in millions) 2015; Available from: http://www.statista.com/statistics/282087/number-of-monthly-active-twitter-users/.
25. Social Networking Fact Sheet. 2014; Available from: http://www.pewinternet.org/fact-sheets/social-networking-fact-sheet/.
26. Brenner J, Smith A. 72% of Online adults are social networking site users. 2013; Available from: http://www.pewinternet.org/2013/08/05/72-of-online-adults-are-social-networking-site-users/.
27. Harris PA et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009; 42(2): 377-381.
28. Jensen MD et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association task force on practice guidelines and the Obesity Society. Circulation. 2014; 129(25 Suppl 2): S102-S138.
29. Pagoto S et al. The adoption and spread of a physical activity challenge through an online social network. J Phys Act Health. 2014; 11(3): 648-653.
30. Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005; 15(9): 1277-1288.
31. Hallgren KA. Computing inter-rater reliability for observational data: an overview and tutorial. Tutor Quant Methods Psychol. 2012; 8(1): 23-34.
32. Mailey E et al. Physical activity barriers and facilitators among working mothers and fathers. BMC Public Health. 2014; 14(1): 657.
33. Hutchesson MJ, Hulst J, Collins CE. Weight management interventions targeting young women: a systematic review. J Acad Nutr Diet. 2013; 113(6): 795-802.
34. Pagoto SL et al. Twitter-delivered behavioral weight loss interventions: a pilot series. JMIR Res Proc. 2015; 4(4), e123.
35. Tate DF, Jackvony EH, Wing RR. Effects of Internet behavioral counseling on weight loss in adults at risk for type 2 diabetes: a randomized trial. JAMA. 2003; 289(14): 1833-1836.
36. Tate DF, Wing RR, Winett RA. Using Internet technology to deliver a behavioral weight loss program. JAMA. 2001; 285(9): 1172-1177.
37. Krukowski RA et al. Internet-based weight control: the relationship between web features and weight loss. Telemed J E Health. 2008; 14(8): 775-782.
38. Krukowski RA et al. Patterns of success: online self-monitoring in a web-based behavioral weight control program. Health Psychol. 2013; 32(2): 164-170.
39. Bennett GG et al. Web-based weight loss in primary care: a randomized controlled trial. Obesity (Silver Spring). 2010; 18(2): 308-313.
40. Funk KL et al. Associations of internet website use with weight change in a long-term weight loss maintenance program. J Med Internet Res. 2010; 12(3), e29.
41. Eysenbach G. The law of attrition. J Med Internet Res. 2005; 7(1), e11.
42. Rafaeli S, Ravid G., Soroka V. De-lurking in virtual communities: a social communication network approach to measuring the effects of social and cultural capital. in System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on. 2004.
43. Hwang KO et al. Social support in an Internet weight loss community. Int J Med Inform. 2010; 79(1): 5-13.
44. Duggan ME, Nicole B, Lampe C, Lenhart A, Madden M. Social Media Update 2014. Accessed 22 January 2015; Available from: http://www.pewinternet.org/2015/01/09/social-media-update-2014/.
45. Pagoto S et al. Tweeting it off: characteristics of adults who tweet about a weight loss attempt. J Am Med Inform Assoc. 2014; 21(6): 1032-1037.
46. Lampe C, Ellison N, Steinfield C. A Face(book) in the crowd: social searching vs. social browsing, in Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work. Banff: ACM; 2006: 167-170.
47. Leonard A et al. Recruitment and retention of young women into nutrition research studies: practical considerations. Trials. 2014; 15: 23.
48. Quach S et al. The good, bad, and ugly of online recruitment of parents for health-related focus groups: lessons learned. J Med Internet Res. 2013; 15(11), e250.
49. O’Connor A et al. Can I get a retweet please? Health research recruitment and the Twittersphere. J Adv Nurs. 2014; 70(3): 599-609.