Summary Adolescent obesity is increasing and a range of treatment approaches are needed. Provision of tailored treatment options accounting for individual and family needs, preferences, and capacity may encourage adolescents with obesity to seek treatment, and/or improve treatment outcomes. Delivered by trained health care professionals, novel dietary interventions may have utility for adolescents not responding to conventional diets, adolescents with comorbidities or severe obesity, and/or when rapid or substantial weight loss is required. This review describes current evidence and clinical considerations relating to the use of very low energy diets, low carbohydrate diets, and intermittent energy restriction in the treatment of adolescent obesity. Emerging evidence on the use of these novel dietary interventions demonstrates short‐term weight‐related and cardiometabolic improvements. While the evidence is encouraging, and no serious adverse effects have been reported, monitoring of intervention safety is essential. Considerations for health care professionals providing care to adolescents include nutritional adequacy, psychosocial health and social relationships during the intervention. Furthermore, long‐term weight‐related, cardiometabolic and psychological health outcomes of these dietary interventions are not well understood. Large randomised controlled trials are warranted to inform clinical practice and future guidelines for the use of novel dietary interventions in adolescents with obesity.

Non-dieting approaches, including mindful/intuitive eating, to health improvement are of increasing interest, yet little is known about young adults’ social media exposure to them. Therefore, this study aimed to describe the imagery related to mindful/intuitive eating which is visible to young adult Instagram users. Images categorized under the hashtags ‘mindfuleating’ and ‘intuitiveeating’ were searched in September 2021 using the ‘top posts’ view. Screen captures of 1200 grid-view images per hashtag were used to construct coding frameworks and to determine saturation. Sample sizes for #mindfuleating and #intuitiveeating were 405 and 495 images, respectively. Individual images were coded collaboratively. Almost half of each sample depicted food or drink, of which 50–60% were healthy foods. Approximately 17% were single-person images, of which the majority were young, female adults with healthy weight. Approximately one-third of text suggested credibility through credentials, profession, or evidence. Messaging was similar for both hashtags, encompassing mindful/intuitive eating (~40%), nutrition/eating behaviours (~15%), physical/mental health (~20%), disordered eating (~12%), and body-/self-acceptance (~12%). Differences were observed between hashtags for weight-related concepts (20%/1%) and anti-diet/weight-neutral approaches (10%/35%). The representation on Instagram of mindful and intuitive eating portrays healthy lifestyles without a focus on weight but lacks demographical and body-type diversity. Instagram holds the potential for health professionals to disseminate culturally/demographically inclusive, evidence-based health/nutrition information to youth.

Objectives Most Instagram users are young people, and social media is often used to search nutrition information. Health interventions aimed at young people should consider such information sources. Content analyses of Instagram images offer insights into types of content that may influence nutrition-related decision making and health behaviors. However, the number of analyzed images in existing studies has varied, and methods to determine data-specific sample sizes to reach saturation have not been explored. We aimed to develop a method to determine sample sizes for image-based content analyses on Instagram. We piloted the method and determined the reliability by identifying the saturation point for content categorized under two separate nutrition-related hashtags. Methods Instagram ‘top posts’ for a 21-year-old user were searched using hashtags ‘mindfuleating’ and ‘intuitiveeating’. 1200 images from each were extracted. Hashtag-specific coding frameworks were constructed inductively by two authors, initially coding the image- and text-based elements of the first 90 images collaboratively. Next, increments of 45 images were coded independently, then compared, solving disagreements by discussion. The process was repeated until saturation occurred when no new codes emerged. This was repeated seven weeks later to determine reliability. Results The coding frameworks constructed for #mindfuleating at first and second capture comprised 63 and 74 distinct codes, with saturation occurring at 360 and 405 images, respectively. The #intuitiveeating frameworks comprised 83 and 86 codes, with saturation at 450 and 495 images, respectively. The codes captured detailed pictorial content (e.g., ‘female’, ‘White’, ‘young adult’) and text (e.g., ‘nutrition information’, ‘relationship with food’). For both hashtags, the number of image-based codes decreased while text-based codes increased between coding. Conclusions Variations in coding frameworks and sample sizes over a short timeframe reflect the dynamic nature of Instagram content. Assessment of diet trends on social media requires accurate sampling to ensure nuances of a specific topic are captured, while research efficiency benefits from reduced data redundancy. Funding Sources NHMRC Peter Doherty Early Career Fellowship; Sydney Medical School Foundation, The University of Sydney.