Weight loss journeys are often deeply personal and transformative experiences. This article explores the weight loss journey of Natalie Carter, a woman who lost 118 pounds, and examines the broader context of how social media-based interventions can aid in weight management, particularly for individuals struggling with obesity and overweight.
Natalie Carter's Inspiring Transformation
Natalie Carter, a 40-year-old woman from Birmingham, UK, embarked on a remarkable weight loss journey after a photograph taken last Christmas served as a wake-up call. Donning matching holiday-themed pajamas with her son Liam, then 10 years old, Natalie was "absolutely mortified" by her appearance in the picture. This moment became a catalyst for change, motivating her to prioritize her health and well-being.
"Last Christmas was the nail in the coffin for me," she confessed. "I tried desperately to enjoy my time with my family, but I was dying inside." Determined to avoid another holiday season feeling so low, Natalie resolved to make a change as she approached her 40th birthday.
In January, Natalie took decisive action. She replaced junk food grazing with a structured meal plan from The 1:1 Diet by Cambridge Weight Plan. This wasn't easy, as she had to "completely start again and rebuild my relationship with food." To combat cravings for her favorite foods like pizza and chocolate, she kept a list of reasons why she was unhappy with her weight and would read it whenever temptation struck.
Alongside dietary changes, Natalie incorporated daily walks into her routine, aiming for 10,000 steps each day. The combination of a healthy diet and regular exercise proved incredibly effective.
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Within the first month, Natalie shed approximately 28 pounds. Over the next eleven months, she continued to make progress, eventually losing 118 pounds and reaching a weight of 164 pounds.
"I felt on top of the world," she exclaimed. "For the first time in a long time, I was in control of food, and food was not in control of me. I was losing physical weight, but I was also losing mental fog."
Natalie's transformation extended beyond the physical realm. Inspired by her success, she left her full-time job to become a weight loss consultant for The 1:1 Diet. "It's become my passion," she explained. "I want to help others get themselves out of the dark place that I was in and give them the confidence to feel amazing."
This year, Natalie is looking forward to celebrating the holidays with newfound confidence and joy. "Looking back at last year, I can't believe how much has changed," she reflected. "I definitely won't be shying away from the camera this year, and I can't wait to have happy memories to look back on."
The Role of Social Media in Weight Management
Natalie's story highlights the power of personal determination and a supportive weight loss program. However, the broader landscape of weight management is increasingly influenced by the rise of social media. Social media-based interventions are emerging as a promising approach to address obesity and overweight, which are significant public health concerns affecting millions worldwide.
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Obesity and Overweight: A Global Health Crisis
Obesity and overweight are serious public health problems involving more than 1.9 billion and 650 million, respectively, of global population that attribute to four million global deaths and disability-adjusted life years. Overweight and obesity can increase the risk of coronavirus disease 2019. Both conditions have a considerable impact on the cardiometabolic comorbidities, medical and post-surgical complications, social costs and health-related quality of life. Weight discrimination is highly prevalent in adults with obesity and overweight. Weight stigma is likely to drive weight gain and poor metabolic health by triggering physiological and behavioral changes. Greater weight bias is associated with greater loneliness among adults with obesity and overweight. They are more likely to feel social exclusion owing to society’s body standard. They are also prone to lower emotional trust in close others, lower disclosure to close others and social withdrawal syndrome, all of which may lead to social isolation.
Social Support and the Potential of Social Media
Social support is effective for improving weight management. A supportive network contributing supportive messages and positive reinforcement can reduce weigh loss. Social media are a potential platform for weight management. Social media are web-based communication channels that facilitate community-based interaction and content sharing, with 3.484 billion users in 2019 worldwide. Majority (88%) of adults spend three hours daily on social media which is more heavily than older adults. Social media-based interventions can improve engagement by 82.9%, positively impact health behaviours and outcomes by 88.8% and provide wide accessibility across income levels, ages, education and ethnocultural groups.
How Social Media Interventions Work: The Social Cognitive Theory
The possible mechanism of social media-based interventions is illustrated on the basis of Bandura’s social cognitive theory (SCT). SCT is a behavioural theory of motivation and action that contains essential concepts of social modelling, observational learning, verbal persuasion and vicarious reinforcement. Social modelling and verbal persuasion are the beliefs in capabilities to perform behaviour change. An individual can observe the performance of a given behaviour, learn and reproduce it subsequently through step-by-step instructional videos and models for behaviour demonstration. Verbal persuasion can develop self-efficacy through encouragement or videos that describe the behaviour.
Social media have five unique features, namely, data sharing, communication, activity data viewing, peer grouping and online social networks (OSNs). Many-to-many communication features include forums and chat rooms. Social media-based interventions incorporate social media features to facilitate behaviour change using behaviour change techniques. Self-efficacy is a major concept of SCT which can affect the person’s behaviour and cognition relating to their activity choice, goal-setting, effort, learning and achievement. High self-efficacy individuals can develop positive outcome expectations to believe in perceived benefits from behaviour change. Social support encompasses emotional, instrumental, informational or appraisal support that may be associated with increased physical activity, healthy eating and successful weight management. Blogs can be used as social-mediated support to help lonely morbidly obese participants with their weight loss goals, who found online social support more beneficial, consistent and reliable than the little support they received from family and in real-life. This showed how social media could provide online social support to individuals who felt alone in their weight loss journey and could not receive the help they needed.
Evidence of Effectiveness: A Systematic Review
A growing number of systematic reviews use social media-based interventions among adolescents, young adults, adults and individuals of any ages. Few of them focus on adults with obesity and overweight. A systematic review aimed to evaluate the effectiveness of social media-based interventions on weight, body mass index, waist circumference, fat, energy intake and physical activity among adults with obesity and overweight and explore potential covariates on treatment effect.
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Methodology of the Review
Eight databases, namely, PubMed, Cochrane Library, Embase, CINAHL, Web of Science, Scopus PsycINFO and ProQuest, were searched from inception until December 31, 2021. The Cochrane Collaboration Risk of Bias Tool and Grading of Recommendations, Assessment, Development and Evaluation criteria evaluated the evidence quality. The eligibility criteria included studies on adults with obesity (BMI ≥ 30) and overweight (BMI: 25-29) aged ≥18 years. Social media-based interventions involved at least one social media feature including OSNs, data sharing, activity data viewing, communication and peer grouping providing social support. Comparators included standard care, waitlist or placebo control. Outcomes included weight (kg), BMI (kg/m2), weight percentage (%), waist circumference (cm), body fat mass (kg), body fat percentage (%), energy intake (kcal/day), daily steps (steps/day) and moderate-to-vigorous physical activity change (MVPA, minutes/day). All types of randomised controlled trials (RCTs) were included.
A three-step comprehensive search strategy was created, with senior librarians following the Cochrane handbook for systematic review of interventions. Firstly, published and unpublished studies in databases from inception until December 31, 2021, using index terms and keywords documented (Table S3). Ongoing clinical trial registries, grey literature and targeted journals databases were also searched (Table S4). Study selection followed the identification, screening and inclusion of PRISMA flow diagram. Duplicates were removed using EndNote 20. Two reviewers (YLL and QPY) independently screened the articles’ titles and abstracts for assessment against the inclusion criteria. Cohen’s kappa (k) was used to measure inter-rater agreement between two independent reviewers for study selection, data extraction and quality assessment. Two reviewers independently performed data extraction following the Cochrane Handbook for Systematic Reviews of Interventions. Data extracted included RCT characteristics encompassing author, year, country, setting, design, population, BMI criteria, age, gender, intervention (name), comparator, sample size, outcome, measure, attrition rate, intention-to-treat (ITT), missing data management (MDM), protocol publication, registration in clinical registries and grant support. Description of intervention included social media features, content, regime (numbers of sessions, frequency, length and duration), provider or peer support, theory based and follow-up.
Two reviewers (YLL and QPY) independently used the Cochrane risk of bias tool version 1 to assess the following six domains: allocation concealment, random sequence generation, outcome data completeness, selective outcome reporting, blinding of participant and personnel and blinding of outcome assessment to detect selection, performance, detection, attrition and reporting biases. Attrition rate, MDM, ITT, protocol publication and registration in clinical registries were used to assess the evidence quality. The Comprehensive Meta-analysis software version 3 was used to performed meta-analyses and meta-regression. Inverse-variance (IV) method was used to calculate the mean difference with 95% confidence interval (CI) of continuous data. Z-statistics at a significant level of P < 0.05 was used to evaluate the overall effect following the Cochrane Handbook for Systematic Review. Given the small sample size in selected RCTs, Hedges’s g was adopted because it provides an accurate estimation of the corrected effect size. Heterogeneity was determined by I² and Cochran’s Q (Chi-square, χ² test) statistics. Subgroup and meta-regression analyses were conducted to explore the observed heterogeneity. GRADEpro GDT software was used to assess certainty of evidence through the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria. Publications bias was assessed for an outcome with ≥10 RCTs via visual inspection of funnel plot and Egger’s regression test.
Key Findings of the Review
Twenty-eight randomised controlled trials were identified. Meta-analyses found that social media-based interventions had small-to-medium significant effects on weight, BMI, waist circumference, body fat mass and daily steps. Subgroup analysis found greater effect in interventions without published protocol or not registered in trial registries than their counterparts. Meta-regression analysis showed that duration of intervention was a significant covariate. The certainty of evidence quality of all outcomes was very low or low.
Study selection is illustrated in Fig. 2, with 29,191 articles from eight databases and 1210 trials from seven registries. From the articles, 14,385 duplicates were removed via EndNote software. Two reviewers independently screened 15,894 articles’ titles and abstracts, excluded 15,814, selected 80 for full-text retrieval, selected 51 for full-text eligibility and excluded 23 with reasons (Table S5). From the trials, 122 unpublished trials were excluded with reasons (Table S6). Twenty-eight RCTs were selected, that is, 25 published studies and 3 trial reports.
Table 1 summarises the characteristics of the 28 RCTs in 29 articles among 13,195 individuals across Australia (N = 5), the United States of America (N = 21), Malaysia (N = 1) and the United Kingdom (N = 1). The RCTs were published between 2011 and 2021. BMI criteria ranged between 25 kg/m2 and 55 kg/m2. The mean age ranged between 20 years and 50.3 years. Sample sizes ranged between 18 and 8112 participants. Attrition rates ranged between 0% and 94.2%. Less than half (N = 13) conducted ITT, and 17 RCTs adopted MDM.
The risk of bias summary is illustrated in Fig. 3. The majority (91.07%) had low risks across six domains. All trials used random sequence generation. Allocation concealment was unclear in seven studies. Given that outcomes were measured objectively, all trials had low risk of performance and detection biases. Seventeen RCTs published protocols, and 20 RCTs registered in various clinical trial registries.
The social media-based interventions are detailed in Table S7. Main RCTs (N = 26) used OSNs, 13 RCTs were theory based and 26 RCTs used multi-component interventions encompassing PA (100%), healthy diet (78.6%), weight management (75%) and SS (82.1%). Frequencies of social media features ranged between twice daily and bimonthly. Intervention duration ranged between ei…
Implications and Future Directions
The systematic review suggests that social media-based interventions can be a valuable adjunct to traditional weight management strategies. The ability of these interventions to provide social support, facilitate communication, and promote engagement makes them a promising tool for individuals seeking to improve their health and well-being.
However, it is important to note that the certainty of evidence quality for all outcomes was very low or low. Further research is needed to strengthen the evidence base and to identify the most effective components of social media-based interventions.