Background: A plethora of weight management apps are available, but many individuals, especially those living with overweight and obesity, still struggle to achieve adequate weight loss. An emerging area in weight management is the support for one’s self-regulation over momentary eating impulses. Objective: This study aims to examine the feasibility and effectiveness of a novel artificial intelligence–assisted weight management app in improving eating behaviors in a Southeast Asian cohort. Methods: A single-group pretest-posttest study was conducted. Participants completed the 1-week run-in period of a 12-week app-based weight management program called the Eating Trigger-Response Inhibition Program (eTRIP). This self-monitoring system was built upon 3 main components, namely, (1) chatbot-based check-ins on eating lapse triggers, (2) food-based computer vision image recognition (system built based on local food items), and (3) automated time-based nudges and meal stopwatch. At every mealtime, participants were prompted to take a picture of their food items, which were identified by a computer vision image recognition technology, thereby triggering a set of chatbot-initiated questions on eating triggers such as who the users were eating with. Paired 2-sided t tests were used to compare the differences in the psychobehavioral constructs before and after the 7-day program, including overeating habits, snacking habits, consideration of future consequences, self-regulation of eating behaviors, anxiety, depression, and physical activity. Qualitative feedback were analyzed by content analysis according to 4 steps, namely, decontextualization, recontextualization, categorization, and compilation. Results: The mean age, self-reported BMI, and waist circumference of the participants were 31.25 (SD 9.98) years, 28.86 (SD 7.02) kg/m2, and 92.60 (SD 18.24) cm, respectively. There were significant improvements in all the 7 psychobehavioral constructs, except for anxiety. After adjusting for multiple comparisons, statistically significant improvements were found for overeating habits (mean –0.32, SD 1.16; P<.001), snacking habits (mean –0.22, SD 1.12; P<.002), self-regulation of eating behavior (mean 0.08, SD 0.49; P=.007), depression (mean –0.12, SD 0.74; P=.007), and physical activity (mean 1288.60, SD 3055.20 metabolic equivalent task-min/day; P<.001). Forty-one participants reported skipping at least 1 meal (ie, breakfast, lunch, or dinner), summing to 578 (67.1%) of the 862 meals skipped. Of the 230 participants, 80 (34.8%) provided textual feedback that indicated satisfactory user experience with eTRIP. Four themes emerged, namely, (1) becoming more mindful of self-monitoring, (2) personalized reminders with prompts and chatbot, (3) food logging with image recognition, and (4) engaging with a simple, easy, and appealing user interface. The attrition rate was 8.4% (21/251). Conclusions: eTRIP is a feasible and effective weight management program to be tested in a larger population for its effectiveness and sustainability as a personalized weight management program for people with overweight and obesity. Trial Registration: ClinicalTrials.gov NCT04833803; https://classic.clinicaltrials.gov/ct2/show/NCT04833803

Objective: To explore motivations, self-regulation barriers and strategies in a multi-ethnic Southeast Asian population with overweight and obesity.Design: Qualitative design using semi-structured face-to-face and videoconferencing interviews. Data were analysed using thematic framework analysis and constant comparison method.Setting: Specialist weight management clinic.Participants: Twenty-two participants were purposively sampled from 13 April to 30 April 2021. Median age and BMI of the participants were 37·5 (interquartile range (IQR) = 13·3) and 39·2 kg/m² (IQR = 6·1), respectively. And 31·8 % were men, majority had a high intention to adopt healthy eating behaviours (median = 6·5; IQR = 4·8–6·3) and 59 % of the participants had a medium level of self-regulation.Results: Six themes and fifteen subthemes were derived. Participants were motivated to lose weight by the sense of responsibility as the family’s pillar of support and to feel ‘normal’ again. We coupled self-regulation barriers with corresponding strategies to come up with four broad themes: habitual overconsumption – mindful self-discipline; proximity and convenience of food available – mental tenacity; momentary lack of motivation and sense of control – motivational boosters; and overeating triggers – removing triggers. We highlighted six unique overeating triggers namely: trigger activities (e.g. using social media); eating with family, friends and colleagues; provision of food by someone; emotions (e.g. feeling bored at home, sad and stressed); physiological condition (e.g. premenstrual syndrome); and the time of the day.Conclusions: Future weight management interventions should consider encompassing participant-led weight loss planning, motivation boosters and self-regulation skills to cope with momentary overeating triggers.

(1) Background: Intra-operative neuronavigation is currently an essential component to most neurosurgical operations. Recent progress in mixed reality (MR) technology has attempted to overcome the disadvantages of the neuronavigation systems. We present our experience using the HoloLens 2 in neuro-oncology for both intra- and extra-axial tumours. (2) Results: We describe our experience with three patients who underwent tumour resection. We evaluated surgeon experience, accuracy of superimposed 3D image in tumour localisation with standard neuronavigation both pre- and intra-operatively. Surgeon training and usage for HoloLens 2 was short and easy. The process of image overlay was relatively straightforward for the three cases. Registration in prone position with a conventional neuronavigation system is often difficult, which was easily overcome during use of HoloLens 2. (3) Conclusion: Although certain limitations were identified, the authors feel that this system is a feasible alternative device for intra-operative visualization of neurosurgical pathology. Further studies are being planned to assess its accuracy and suitability across various surgical disciplines.

While various influencing factors of overweight and obesity have been identified, the underlying mechanism remains unclear. We examined the relationships among sociodemographic, behavioral, and psychological factors on anthropometry in a multi-ethnic population with overweight and obesity. Participants (N = 251) were recruited from January to October 2022. Mean age and self-reported BMI were 31.7 ± 10.1 years and 29.2 ± 7.2 kg/m². Participants were mostly female (52.4%) and overweight (58.2%). Multivariate multiple regression was performed using maximum likelihood estimation. Body mass index was associated with waist circumference, age, sex, race, marital status, education level, residential region, overeating habit, immediate thinking, self-regulation, and physical activity, but not anxiety, depression, or the intention to change eating habits. Final model indicated good fit: χ² (30, N = 250) = 33.5, p = 0.32, CFI = 0.993, TLI = 0.988, RMSEA = 0.022, and SRMR = 0.041. Direct effects were found between BMI and overeating (β = 0.10, p = 0.004), race (β = −0.82, p < 0.001), marital status (β = −0.42, p = 0.001), and education level (β = −0.28, p = 0.019). Crisps (68.8%), cake (66.8%) and chocolate (65.6%) were identified as the most tempting foods. Immediate thinking indirectly increased overeating habits through poor self-regulation, although sociodemographic characteristics better predicted anthropometry than psycho-behavioral constructs.