The objective of this study was to compare health care resource utilization (HRU), health care costs, and glucagon-like peptide-1 (GLP-1) agonist use among working US adults who engaged in Noom Weight, a smartphone-based lifestyle intervention for weight management, to individuals offered Noom who did not enroll. Insurance claims data were used to conduct retrospective analyses of 723 Noom participants matched via propensity scores and compared to 723 non-Noom participants at 6 months post index. Compared to nonparticipants, Noom participants had significantly lower HRU, medical and pharmacy costs, and GLP-1 agonist use in the 6-month post-index period. On average, Noom participants had 3.2 fewer outpatient visits, 0.34 fewer emergency department visits, 0.25 fewer inpatient visits, and 0.012 fewer surgeries than non-Noom participants (all p values <0.001). Noom participants' health care costs were $831 lower than non-Noom participants. Relative to non-Noom users, Noom participants also had 42% fewer claims for GLP-1 agonists (p = 0.02). Compared to matched nonparticipants, Noom participation was associated with lower HRU, health care costs, and GLP-1 agonist use at 6 months post index. Results of this study support Noom as a cost-effective and HRU-lowering digital weight-management program for working adults in the United States.
The use of smartphone apps for dietary self-management among patients with high blood pressure is becoming increasingly common. Few commercially available DASH (Dietary Approaches to Stop Hypertension) diet apps have the potential to be effective, and only a few of these have adequate security and privacy measures. In previous studies, we identified 2 high-quality apps that are likely effective and safe. One of these, the Noom app, was selected as the most suitable app for use in the Saudi Arabian context based on health care professionals' and patients' preferences. This study aims to determine the feasibility and acceptability of using the Noom app to support DASH diet self-management among people with high blood pressure in Saudi Arabia. This mixed methods study evaluated the feasibility and acceptability of using the Noom app among people with high blood pressure in Riyadh, Saudi Arabia. Fourteen participants with high blood pressure were recruited and asked to use the app for 8 weeks. The quantitative outcome measures were DASH diet adherence and self-efficacy. Feasibility and acceptability were assessed during and after the intervention via the Noom diet-tracking engagement questionnaire, the System Usability Scale, and semistructured interviews. Most participants (8/13, 62%) logged their meals for 3 to 5 days a week; the frequency of logging increased over time. Snacks were the foods they most often forgot to log. The interviews revealed four main themes: (1) acceptance, (2) app usability, (3) technical issues, and (4) suggestions for improvement. Most participants found the Noom app acceptable, and most had no difficulties integrating it into their daily routines. The results of this feasibility study provided insights into the app's educational content, some of which was deemed unsuitable for Saudi Arabian users. App usability was identified as a critical theme: the app and its database were easy to use, convenient, and valuable to most of the participants. Despite this, some of the participants reported difficulties in identifying some foods because of a lack of local options on the app. Technical issues included the app freezing or responding slowly. Most participants also suggested developing an Arabic version of the app and simplifying the method of food logging. The participants showed some improvement in self-efficacy and adherence to the DASH diet, although these improvements were not statistically significant. The mean self-efficacy score increased from 18 (SD 4.7) to 20 (SD 6.3), and the mean DASH diet score increased from 3.4 (SD 1.4) to 4.3 (SD 1.1). The app was feasible and acceptable among the participants who completed the study. Further studies are needed to examine the potential of smartphone apps in promoting adherence to the DASH diet and their impact on blood pressure among individuals with hypertension in Saudi Arabia.
Mobile-based lifestyle intervention has been widely used to improve behavior for obesity and overweight. This study targeting adults with metabolic abnormalities aims to identify neural correlates related to weight loss due to mobile-based lifestyle intervention. We conducted 8 weeks of mobile-based lifestyle intervention for 37 adults with metabolic abnormalities, including overweight. Participants underwent physical measurements, blood tests, psychometric questionnaires, and resting-state functional magnetic resonance imaging (fMRI) scans before and after the mobile-based intervention. For the resting-state fMRI, brain regions that showed changes in functional connectivity (FC) before and after mobile-based intervention were explored. Seed-based FC analysis was performed focusing on the subregions of the insular cortex. Participants significantly reduced body mass index (BMI) after mobile-based intervention. The degree of BMI reduction was significantly correlated with compliance with the intervention. In resting fMRI, FC of the posterior insula with the bilateral inferior parietal lobule and the left ventrolateral prefrontal cortex were enhanced after mobile-based intervention. The increase in FC between the posterior insula and the inferior posterior lobule showed a significant correlation with the decrease in binge eating scale scores. The mobile-based lifestyle intervention significantly reduced weight and alleviated binge eating in adults with metabolic abnormalities. FC enhancement between the posterior insula and the frontoparietal regions was also observed after mobile-based lifestyle intervention. The relationship between these FC changes and strengthening weight control through mobile-based lifestyle intervention should be investigated through future research.
Mobility disability is associated with functional decline in older adults. Resistance training (RT) improves mobility disability, but adherence to national RT guidelines is poor. We evaluated the effects of a 12-week brief, home-based functional RT program, FAST (Functional Activity Strength Training)-2, on adherence and functional impairment in older, inactive adults ≥ 65 years of age, with pre-existing walking difficulty. Eligible older adults were randomized using stratified assignment based on biological sex and age (65-72 and 73+) to either the FAST-2 intervention involving a 4-minute daily workout of four exercises lasting 30 seconds each or the delayed treatment control condition. Video coaching at baseline and at weeks 2, 4 and 8, provided feedback on exercise form, modifications and progression. Daily email reminders were sent for workout completion, and to report exercise performance and rate perceived exertion. Performance and adherence feedback were emailed biweekly. Functional performance was measured by video using the Five-Times Sit-to-Stand (FTSTS) test, One-Legged Stance Test (OLST) and the 30-second chair stand test at baseline and at weeks 6 and 12. Ninety-seven participants were randomized to either the FAST-2 treatment intervention (n = 44) or the delayed treatment control condition (n = 53). The linear mixed-effect model showed the intervention group decreased the FTSTS by 2.3 seconds (95% CI: 0.5-4.1, p = 0.01), increased OLST by 3.6 seconds (95% CI: 0.6-6.5, p = 0.02) and increased the number of chair stands by 4.2 repetitions (95% CI: 2.8-5.7, p < 0.001) more than the control group over 12 weeks. Intervention participants completed the workout 81% of the days. No significant adverse events were reported. The 12-week FAST-2 intervention, including only 60-seconds of lower extremity exercises in older individuals with pre-existing walking difficulty, yielded improvement in functional performance. ClinicalTrials.gov: ID NCT05697497 Study Details | NCT05697497 | Functional Activity Strength Training | ClinicalTrials.gov.
This narrative review synthesizes evidence identified through targeted searches of PubMed, Scopus, and Web of Science (2010-2025), with a focused selection of human and mechanistic studies examining GLP-1 receptor agonists (GLP-1s), food cue reactivity, prospective cognition, mindfulness-based interventions, and neural network dynamics relevant to 'food noise' and the default mode network (DMN). Food noise is conceptualized here as a form of maladaptive prospection: a faulty way of thinking about the future, characterized by repetitive, cue-driven mental simulation of short-term reward at the expense of long-term goals. Existing neuroimaging and behavioral data suggest that GLP-1s may influence neural systems underlying cue salience and reward anticipation, with several reports indicating reduced food-related intrusive thoughts. Although these findings are preliminary, some mechanistic models posit that GLP-1s could attenuate DMN activity associated with food-related rumination, potentially altering the cognitive context in which eating decisions occur. Patient reports of improved focus, reduced cravings, or greater ease in health-related planning are noted in the literature, but causal links to specific behavioral outcomes remain unestablished. This paper advances a testable hypothesis: reductions in food noise may shift the balance of activity among DMN, salience, and executive networks in ways that support more adaptive forms of prospection. However, current evidence is limited, and the proposed mechanisms and behavioral implications require empirical testing. Further research using direct measures of food noise, longitudinal neuroimaging, and controlled behavioral studies is needed to clarify mechanisms and determine their broader relevance for health and self-regulation.
This randomized controlled study tested the effect of interoceptive exposure on anterior insula function and connectivity for the extinction of palatable and rotten food-cue associations in adolescent girls with low weight eating disorders (LWED). A food-related conditioning paradigm was performed by 39 adolescent girls with LWED and 19 matched controls during functional magnetic resonance imaging (fMRI). Adolescents with LWED were then randomized to 6 sessions of either interoceptive exposure (n = 18) or family-based (n = 21) treatment, followed by a second functional magnetic resonance imaging scan. Whole-brain activation and insula-driven connectivity for the extinction of palatable and rotten food-cue associations were compared between groups, and changes over treatment were compared between the 2 therapies. Adolescents with LWED exhibited diminished bilateral anterior insula activation for the extinction of palatable food-cue associations compared with controls (t1,55 = 3.9-4.1, p < .001; Hedges g = 0.47-0.55). Brief interoceptive exposure treatment increased left anterior insula activation for the extinction of palatable food-cue associations (t1,37 = 5.10, p < .001; Hedges g = 1.59) and nonsignificantly improved palatability ratings for these associations during extinction compared with family-based treatment (β = -1.492, p = .087). There were no effects of group or therapy on connectivity or activation for rotten food-cue associations. These results suggest that targeting food avoidance in adolescent girls with LWED using interoceptive exposure engages anterior insula regions that mediate the visceral sensation of disgust and may underlie the resistance to extinction. The findings present a window into possible pathophysiological mechanisms of anorexia nervosa and other LWED PLAIN LANGUAGE SUMMARY: This randomized controlled study tested the effect of interoceptive exposure, which aims to reduce conditioned disgust responses to food. This treatment was compared to family-based treatment and the focus was on changes in anterior insula function. 39 adolescent girls with low-weight eating disorders (LWED) and 19 matched controls underwent food-related conditioning during functional magnetic resonance imaging, followed by interoceptive exposure or family-based treatment and a post-intervention imaging session. Key results showed that brief interoceptive exposure treatment increased left anterior insula activation for the extinction of palatable food-cue associations. These results offer new insights into the role of disgust and possible triggers and pathways to anorexia nervosa and other LWED. Reward Systems and Food Avoidance in Eating Disorders; https://clinicaltrials.gov/study/NCT02795455.
Exposure-based cognitive behavioral therapy (CBT) is the frontline treatment for pediatric obsessive-compulsive disorder (OCD), but not all youth fully respond to this treatment. While multiple factors may influence CBT response, homework adherence in CBT is a modifiable target that can improve treatment outcomes. This report examines the relationship between homework adherence and clinical outcomes in a large sample of youth with OCD who received exposure-based CBT. Here, 137 youth with OCD between 7 and 17 years old (M = 12.42, SD = 2.88) participated in a randomized controlled trial of exposure-based CBT. Homework adherence was monitored weekly, and OCD severity was assessed by independent evaluators masked to treatment condition using gold-standard rating scales. Mixed-effects linear and logistic regression models examined the relationship between homework adherence, reductions in OCD severity, treatment response, and clinical remission at post-treatment. Follow-up investigations explored differences in patterns between early- and late-homework adherence. Finally, baseline clinical predictors of homework adherence were explored. There was a significant predictive relationship between greater homework adherence and reduced OCD severity, greater incidence of treatment response, and greater incidence of clinical remission at post-treatment. Greater homework adherence later in treatment-as opposed to earlier in treatment-was most impactful in predicting positive clinical outcomes in exposure-based CBT. Presence of co-occurring ADHD was a significant predictor of decreased homework adherence. Taken together, findings provide insight into a modifiable therapeutic target that can improve treatment outcomes in exposure-based CBT.
To examine the effect of a brief behavioral intervention aimed at optimizing sleep duration in children on their overall health-related quality of life (HRQoL), and within physical and psychosocial health domains. Participants were 66 typically developing children (68.2% female), aged 8-11 years, identified as short sleepers (≤9.5 h/night), randomized to a sleep intervention (n = 33) or control (n = 33) group, and who reported on HRQoL. The intervention group was provided with behavioral strategies to increase their time in bed by approximately 1-1.5 h/night; those randomized to the control group were asked to sleep as usual. Pediatric Quality of Life Inventory was administered to both parents and children to assess HRQoL at baseline and 8 weeks post-randomization. Sleep duration was objectively measured using a wrist-worn actigraph. At baseline, participants had a mean actigraph-estimated sleep period of 8.56 ± .67 h/night, a parent proxy-report of overall HRQoL of 82.44 ± 12.70, and a child self-report of 78.96 ± 10.88. Repeated-measures ANOVAs revealed no significant differences in overall HRQoL, physical health, or psychosocial health over time between groups (ps > .05). However, in post-hoc analyses collapsing across groups, children who increased their sleep by ≥ 30 min/night reported higher overall HRQoL (t (57) = 2.82, p = .01), psychosocial health (t (57) = 2.82, p = .01), and physical health (t (57) = 2.28, p = .03) at 8 weeks. No significant differences were observed based on parent report (ps > .05). Improving sleep by ≥ 30 min/night for children who are short sleepers may enhance their HRQoL. However, further research is necessary.
Body dysmorphic disorder (BDD) is a severe psychiatric condition affecting approximately 2% of the population, yet access to evidence-based cognitive behavioral therapy (CBT) is limited due to insufficient clinician training. Web-based training offers a solution for disseminating specialized treatment skills, but real-world effectiveness data are lacking. This study evaluated a brief, online CBT training program for BDD delivered under naturalistic conditions. Between 2017 and 2023, 166 clinicians enrolled in a 4-week web-based training covering BDD assessment and CBT treatment techniques. The training included video lectures, case examples, discussion boards, and optional Q&A sessions. Participants completed surveys at baseline, post-training, and 6-month follow-up assessing self-reported confidence assessing and treating BDD, beliefs about CBT, self-reported implementation of evidence-based practices (EBPs), and perceived barriers. Mixed-effects models evaluated changes over time, and regression analyses examined predictors of dropout and outcomes. Clinicians demonstrated significant improvements from baseline to post-training in self-reported confidence assessing BDD (EMM difference = 31.1), confidence treating BDD (EMM difference = 37.7), positive beliefs about CBT (EMM difference = 7.9), and EBP implementation (EMM difference = 6.2%; all p < .001). Gains were maintained at 6-month follow-up. Several barriers showed descriptive decreases, though none reached statistical significance. Baseline EBP use was the only significant predictor of outcomes: clinicians with lower baseline EBP use showed greater improvement in assessment confidence but smaller gains in CBT-related beliefs. Brief web-based training can enhance clinician self-reported confidence and readiness to deliver CBT for BDD, supporting dissemination of specialized skills. However, high attrition and reliance on self-report highlight challenges inherent to naturalistic training evaluation.
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Depression is one of the leading causes of disability worldwide. Cognitive behavioral therapy (CBT) is an effective treatment, but it is difficult to access due to clinician shortages, waitlists, and logistical barriers. Smartphone-based CBT interventions offer a scalable alternative to traditional face-to-face care, but few provide transparency regarding how closely they adhere to evidence-based therapeutic principles. Understanding what therapeutic components are included in interventions helps clinicians and patients determine whether they follow CBT principles and how they might help reduce depressive symptoms. This study aimed to characterize the therapeutic content of Mindset (Koa Health), a therapist-guided smartphone intervention for depression, by identifying the core CBT techniques it delivers and the specific behavioral strategies the app uses to put those techniques into practice. A qualitative content analysis was conducted on all 393 unique intervention pages of Mindset. Using established CBT strategy definitions and the behavior change technique (BCT) Taxonomy version 1 (BCTTv1), coders independently evaluated each page using a collaborative consensus approach. Interrater agreement was 93.75% for CBT and 93.62% for BCT coding. Descriptive statistics (frequency, mean, and SD) and overlap between the two were calculated. All 16 core CBT techniques were identified. CBT techniques were used a total of 528 times (mean per module 66.0, SD 56.0). The most frequently used techniques included psychoeducation (164/325, 50.5% of pages), skill building (110/325, 33.8%), cognitive restructuring (46/325, 14.2%), activity scheduling (42/325, 12.9%), and self-monitoring (39/325, 12%). Across modules, 37 of 93 possible BCTs were coded 878 times (mean per module 109.8, SD 92.0) across 13 of 16 BCTTv1 categories. The most frequently applied BCT categories were shaping knowledge (205/325, 63.1% of pages), repetition and substitution (138/325, 42.5%), and feedback and monitoring (113/325, 34.8%). Overlap between the 2 frameworks was common, with the most frequent CBT-BCT pairings being psychoeducation (CBT technique)×Shaping knowledge (BCT category; appearing together on 119 pages), skill building×Shaping knowledge (80 pages), activity scheduling×Shaping knowledge (42 pages), and activity scheduling×Repetition and substitution (42 pages). Mindset demonstrates coverage of CBT techniques and alignment with evidence-based BCTs. This study is the first to introduce mechanism mapping, a dual-coding approach that describes the presence of therapeutic strategies and how they are behaviorally operationalized, addressing a gap in digital mental health transparency. Unlike existing content evaluations that use presence or absence checklists, our framework captures implementation depth through systematic documentation of behavioral scaffolding. This replicable methodology enables researchers to evaluate therapeutic fidelity, supports clinicians in making evidence-informed recommendations for digital mental health treatments, and provides a foundation for the development of adaptive interventions that can enhance real-world treatment outcomes for individuals with depression.
Body dysmorphic disorder (BDD) is characterized by distressing preoccupations with perceived appearance flaws, leading to functional impairment and suicidal ideation (SI). Traditional approaches for monitoring clinical deterioration in BDD include self-reports and clinician assessments, which can miss acute changes in risk due to infrequent administration and recall biases. Alternatively, real-time monitoring via smartphones and wearable devices can enable low-burden early detection of deterioration, identifying intervention opportunities before someone's condition critically worsens. This study tests the feasibility of using smartphone sensor and demographic data to predict daily clinical acuity. Eighty-two participants with BDD completed ecological momentary assessments (EMA) over 28 days, reporting levels of SI, BDD-related avoidance, and time spent on BDD-related concerns. Smartphone sensor data were collected for 3 months that overlapped with EMA. Machine learning models were trained to predict same-day levels of SI, avoidance, and time spent on BDD using the Global Positioning System (GPS), accelerometer, and demographic data. We evaluated model performance using mean absolute error, Pearson and Spearman correlations, and permutation tests. Random forest (RF) models using time and random split validation outperformed dummy regressor models across outcomes (maximum SI, mean SI, maximum avoidance, mean avoidance, time spent on BDD-related behaviors). Pearson correlations for RF models showed strong predictive performance for BDD-related time (r = .74-.75) and mean and max SI (r = .70-.73). Mean and max avoidance was moderately well predicted (r = .56-.62). Step count and demographic factors (e.g., education, living situation) were the most consistent and important features. This study provides initial evidence that smartphone sensor and demographic data can be used to monitor real-time clinical worsening in BDD, without burdening the patient. This work has potential for building just-in-time interventions that are delivered as deterioration onsets, to prevent its escalation. Future research should test these models in real-world datasets collected over longer periods and subsequently explore integration into interventions and clinical decision making. Trial Registration: ClinicalTrials.gov Identifier: NCT04254575.
Obsessive-compulsive spectrum disorders are rarely included in hierarchical dimensional models of psychopathology due to limited available data. The current study examined the higher order structure of the obsessive-compulsive and related disorders (OCRDs) in the DSM/ICD. Measures of OCRD severity were administered in community (N = 1110) and clinical (N = 690) samples. Confirmatory factor analyses were used to determine the optimal structure of OCRD symptoms, and structural regression models to explore association with indicators from the internalizing, externalizing and thought disorder spectra. In both samples, the data fit best with a correlated two-factor model comprised of a grooming dimension (with loadings from hair pulling, skin picking and nail biting/picking disorders) and a compulsivity dimension (with loadings from obsessive-compulsive, hoarding, body dysmorphic, olfactory reference, and illness anxiety disorders). A three-factor model which included body preoccupation factor (body dysmorphic, olfactory reference, and illness anxiety disorders) was not viable due to out of bounds correlations with compulsivity (obsessive-compulsive and hoarding disorders). The broad compulsivity factor, but not the grooming factor, had robust associations with indicators of internalizing and thought disorder spectrum. Both factors had small and inconsistent associations with alcohol and substance use. The findings suggest that the higher order structure of OCRDs may be best represented by separable compulsivity and grooming dimensions. Future research is needed to examine the scope of these dimensions, and their placement within the meta structure of psychopathology.
Overweight or obesity is a prognostic factor for breast cancer recurrence and breast cancer-related deaths. However, weight control is difficult for breast cancer survivors because of menopause, chemotherapy, antihormonal therapy, and psychological issues. This study aimed to develop a 24-week mobile app-based human coaching program using Noom and evaluate its efficacy in breast cancer survivors who are excessively overweight or with obesity, including those who successfully used the program. In this single-arm prospective cohort study, 130 breast cancer survivors with BMI ≥25 were enrolled and received a 24-week program, including diet-, exercise-, and psychology-based content with the trained human coach in Noom between 2019 and 2021. For a hyperactive group who joined for more than 16 weeks, we evaluated weight, BMI, lipid level, bioimpedance, and quality of life at baseline, 6-month, and 12-month follow-up. Among 130 breast cancer survivors, 101 (77.7%) and 93 (71.5%) completed the 6-month and 12-month follow-ups, respectively. The mean age of all participants was 54.90 (SD 7.42) years. At baseline, the median BMI was 27.14 (IQR 25.20-35.36) for the hyperactive group and 27.50 (IQR 25.20-35.50) for the active and inactive group. In the hyperactive group (68/101, 67%), body weight and BMI significantly reduced (mean difference -1.97, 95% CI -2.65 to -1.26 kg; P<.01 and mean difference -0.86, 95% CI -1.15 to -0.56; P<.01, respectively) at 6 months and were maintained at 12 months without the yo-yo effect. Among the lipid panel, triglyceride levels decreased significantly (-34.13, 95% CI -58.09 to-10.17; P<.01) and were maintained at 12 months. With respect to bioimpedance components, skeletal muscle mass (kg), body fat mass (kg), percent body fat (%), waist-to-hip ratio, and visceral fat area (cm2) improved in the first 6 months. However, waist-to-hip ratio and visceral fat area increased during the next 6 months. Based on the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ C30) and Breast Cancer Module (23 items), nausea or vomiting, constipation, body image, and arm and breast symptoms significantly improved during the first 6 months. This study demonstrated that a 24-week mobile app-based human coaching program is beneficial for controlling body weight, BMI, triglyceride, and body composition in terms of bioimpedance for breast cancer survivors who are excessively overweight or have obesity.
The number of living donors in the US has stagnated for over two decades, in part because a substantial number of intended donors are disqualified due to potentially modifiable health conditions like obesity and smoking. Although these conditions can be improved with lifestyle changes, many candidates lack the support to achieve these changes on their own. Project Donor is a national program to help living donor candidates achieve donation eligibility. Project Donor provides individualized virtual case management and free access to commercially available programs, including Noom, Weight Watchers, and OnPoint Nutrition, as well as nicotine replacement products and talk therapy. Between May 2022 and January 2025, Project Donor enrolled 680 participants. Among these, 142 continue working toward their goals, 435 dropped out, and 95 reached their goal after achieving a mean 8.1 kg weight loss over 9.5 months. Participants who reached their weight loss goal had a lower starting weight (93.4 vs. 101.7 kg, p < 0.001) and BMI (34.1 vs. 36.7 kg/m2, p < 0.001) than those who dropped out. Among those who reached their goal, 72 went on to become living donors. These results indicate that with sufficient resources and support, some potential donors can achieve eligibility for donation through lifestyle interventions. While a high dropout rate and lack of a control group limit the generalizability of this study, we demonstrate how lifestyle interventions for living donors can be implemented at scale. Additional studies are warranted to determine whether programs like Project Donor could increase the number of living donations.
Although the growing prevalence of obesity has led to an increased reliance on health-tracking apps for weight management, their effectiveness remains limited owing to missing data and irregular sampling of user-reported records. These issues highlight the need for more sophisticated predictive models to address real-world data limitations and offer personalized interventions. This study developed a gated recurrent unit-ordinary differential equation (GRU-ODE)-Bayes-based deep learning framework to predict successful weight loss using real-world lifelog data. We analyzed a retrospective cohort of Noom Coach users, who logged data at least twice a month for six months between 2012 and 2014. We included demographic and self-monitoring variables, with weight loss ≥5% in three months as the primary outcome. We evaluated the model performance using the area under the receiver operating characteristic curve (ROC AUC) and precision-recall curve (PRC AUC). This study utilized a large-scale dataset (N = 34,322) that was subdivided into training (N = 24,292), validation (N = 6074), and test sets (N = 3375). Participants who frequently logged their weight, exercise, meals, and snacks were more likely to achieve weight loss. The model achieved an ROC AUC of 0.830 [95% confidence interval 0.819-0.840] and PRC AUC of 0.727 [0.707-0.746] in the validation set, and an ROC AUC of 0.821 [0.806-0.835] and PRC AUC of 0.717 [0.689-0.744] in the test set, using only the first four weeks of lifelog data. Early weight change and initial weight were the most important features as determined by the integrated gradients. The proposed model predicted early outcomes in weight management and might contribute to developing effective intervention methods for participants at risk of failure and reducing the burden of frequent self-reporting.
Hospital-acquired otitis media (OM) is a common complication in children with bacterial pneumonia, associated with prolonged morbidity. Systemic inflammation indices (SII and AISI) may serve as biomarkers for OM risk. This study aimed to evaluate the association of SII and AISI with hospital-acquired OM risk in children (≤12 years) with bacterial pneumonia. A total of 388 children (aged ≤12 years) diagnosed with bacterial pneumonia were enrolled in this study from January 2024 to June 2025.. Data included demographic characteristics, birth history, feeding history, and laboratory tests. Logistic regression analysis was used to analyze the relationship between SII, AISI, and the risk of OM. This study constructed a nomogram prediction model, and the performance of the model was assessed by the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA). The majority of patients were male (54.90%) and aged ≤3 years (55.93%). Based on OM status, children were divided into No-OM group (n = 289) and OM group (n = 99). The OM group showed significantly elevated levels of inflammatory markers (WBC, NEU, MON, PLT, CRP, SII and AISI), alongside lower levels of RBC, HGB, and TP, compared to the No-OM group (all p<0.05). Multivariate analysis found log2-SII (OR = 1.38, 95% CI: 1.05-1.82, p = 0.021) and log2-AISI (OR = 1.37, 95% CI: 1.07-1.78, p < 0.001) were risk factors of hospital acquired OM. Compared to log2-SII model (0.827, 95% CI: 0.780-0.875), log2-AISI model (0.834, 95% CI: 0.788-0.881) demonstrated superior discriminatory ability. Both models exhibited a favorable clinical benefit rate. Additionally, restricted cubic spline (RCS) analysis showed a significant linear relationship between log2-SII, log2-AISI and OM risk (all P for nonlinear >0.05), with inflection points at 9.71 (log2-SII) and 8.16 (log2-AISI). This study established the predictive value of SII and AISI for hospital acquired OM in children aged ≤12 years with bacterial pneumonia. Integrating them into clinical practice can guide targeted prevention and thereby improve prognosis.
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease but remains widely under-recognized in primary care. The 2023 shift from "nonalcoholic fatty liver disease" to MASLD emphasized metabolic dysfunction as a driver of disease but introduced new communication and educational challenges for primary care providers (PCPs). We aimed to assess PCPs' awareness, risk assessment, and management practices related to MASLD in the four most populous U.S. cities. A cross-sectional online survey was conducted from 5 to 13 September 2024 among 800 primary care providers (PCPs; n = 200 per city) in New York City, Los Angeles, Chicago, and Houston. Participants included physicians, physician assistants, nurse practitioners, and other primary care professionals. The survey assessed awareness of "MASLD" and "fatty liver disease", risk assessment practices for high-risk groups, patient discussions, management strategies, and the use of patient-reported outcomes (PROs). Descriptive statistics characterized sample responses, and logistic regression models identified correlates of awareness. Overall, 54.7% of PCPs reported awareness of MASLD and 86.6% were aware of fatty liver disease. Awareness of MASLD was highest among physicians (81.3%) and hospital-based practitioners (odds ratio [OR] = 2.02, 95% confidence interval [CI] 1.02-4.02) and lowest among nurse practitioners (OR = 0.21, 95% CI 0.09-0.49). Awareness of fatty liver disease increased with provider age (OR = 1.04, 95% CI 1.00-1.08). Lifestyle modification was the most recommended management approach (41.3-65.5%), while referral rates to specialists and PRO use varied substantially across cities, and 48.5% were aware of the FIB-4 Index. Only half of PCPs recognized the term MASLD, highlighting gaps in awareness and clinical practice following the mid-2023 terminology change. Targeted educational initiatives and standardized implementation of MASLD guidelines in primary care are needed to improve timely detection and management of this highly prevalent condition.
General anesthesia (GA) is frequently used for pediatric dental treatment in cases of extensive decay, behavioral challenges, or medical conditions that prevent conventional care. This study presents a 24-year retrospective analysis of dental treatments performed under GA at the Children's Hospital. A retrospective review was conducted on dental treatments performed under GA between January 1, 2001, and December 31, 2024. Data collection included patient age, sex, details on dental procedures, medical status, and postoperative follow-up. Statistical analyses included linear regression, Pearson's correlation, Mann-Kendall trend test, Student's t-tests, Chi-square tests, and descriptive statistics. Between 2001 and 2024, 4,062 patients underwent dental treatment under GA, representing 1.59% of all admissions. The proportion of treatments under GA increased significantly (p = 0.008). The mean age was 6.29 years for girls and 5.98 years for boys, with a statistically significant difference (p < 0.0001) but a small effect size. Boys (53.77%) were treated under GA more often than girls (p = 1.55 × 10-6). In total, 39,818 teeth were treated, mainly restorations (65.84%) and extractions (22.68%), with no gender difference. Among patients, 12.08% had a disability, 6.96% had systemic conditions, and 80.96% were healthy. Healthy children had significantly more treated teeth than others (p < 0.0001). Follow-up attendance dropped from 56.57% at 1 month to 3.80% at 9 months, with 43.43% missing all follow-ups. Only 1.87% of patients failed NOOM (nitrous oxide/oxygen mixture) and required GA. Twelve children, mostly with autism or cerebral palsy, underwent multiple GA procedures. The demand for dental treatment under GA has significantly increased over the past 24 years. While GA remains a crucial option for pediatric patients with extensive dental needs or special conditions, the low postoperative follow-up rates highlight the need for improved follow-up strategies. Shayegan A, Makanz VM, Abergel C. Dental Treatment in Children under General Anesthesia: A 24-year Retrospective Study. Int J Clin Pediatr Dent 2025;18(9):1134-1139.
The increasing prevalence of metabolic syndrome and type 2 diabetes places a burden on healthcare systems, necessitating cost-effective, engaging and accessible interventions to address the underlying behavioral and lifestyle drivers. Our study evaluated combining Bluetooth connected OneTouch blood glucose meters (BGM) and the OneTouch Reveal mobile app with one of four digital therapeutic apps. Each group was independent, with people with type 2 diabetes (PwT2D) themselves choosing their therapeutic intervention, to better reflect real-world use. Our 3-month decentralized study screened 912 subjects, with 612 returning mail-in A1cs, providing 191 subjects (Noom = 68, Fitbit = 31, Cecelia Health = 47, Welldoc = 45) who met all inclusion criteria, including entry A1c 7.5 to 12.0%. The primary endpoint of A1c change showed improvement in the overall group by - 0.77% (95% CI - 0.98 to - 0.56, n = 141) after 3-months, Noom - 1.03% (CI - 1.4 to - 0.61, n = 49), Fitbit - 0.56% (CI - 1.0 to - 0.11, n = 24), Cecelia Health - 0.76% (CI - 1.2 to - 0.36, n = 36), Welldoc - 0.55% (CI - 0.94 to - 0.17, n = 32). In terms of secondary endpoints, more than half (56%) of these PwT2D lowered A1c by ≥ 0.5% and more than a third (36%) lowered A1c by ≥ 1.0%, with similar improvements across each of the four independent groups. Our real-world approach shows the potential for connected BGMs and widely accessible digital therapeutics to contribute to improvements in glycemic outcomes.