171 research outputs found

    Comparison of two models of family-based treatment for childhood obesity: A pilot study

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    BackgroundFamily-based weight loss treatment (FBT) for childhood obesity, the current "gold standard," is typically provided in weekly groups for 6 months. Although this program is considered effective, it poses limitations to treatment engagement, due to time commitment and lack of widespread availability. A guided self-help version of FBT (gshFBT; eleven 20-minute sessions and one 1-hour over 5 months) was developed to circumvent such limitations. The current study examined the comparative efficacy of a 5-month FBT and gshFBT program.MethodsParticipants included 50 parent-child dyads enrolled in FBT between 2011 and 2013 and 50 parent-child dyads enrolled in gshFBT between 2009 and 2010. Data were collected at baseline, posttreatment, and 6-month follow-up. Noninferiority analyses were conducted to assess comparative efficacy of changes in parent and child weight status, child nutrition, child physical activity, and drop-out.ResultsResults indicated that gshFBT was noninferior to FBT in changes in child BMI z-score, overweight parent BMI, child nutritional intake, child vigorous physical activity, and drop-out. Results did not support noninferiority for changes in moderate to vigorous physical activity.ConclusionsgshFBT is less intensive, more flexible, and may be similarly effective to FBT and could reach a greater proportion of the pediatric overweight population. Further research, including a randomized clinical trial, is needed to confirm these results

    A framework for applying natural language processing in digital health interventions

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    BACKGROUND: Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources: (1) open correspondence between users and the trained practitioners supporting them through a messaging system and (2) text data recorded during the intervention by users, such as diary entries. Natural language processing (NLP) offers methods for analyzing text, augmenting the understanding of intervention effects, and informing therapeutic decision making. OBJECTIVE: This study aimed to present a technical framework that supports the automated analysis of both types of text data often present in DHIs. This framework generates text features and helps to build statistical models to predict target variables, including user engagement, symptom change, and therapeutic outcomes. METHODS: We first discussed various NLP techniques and demonstrated how they are implemented in the presented framework. We then applied the framework in a case study of the Healthy Body Image Program, a Web-based intervention trial for eating disorders (EDs). A total of 372 participants who screened positive for an ED received a DHI aimed at reducing ED psychopathology (including binge eating and purging behaviors) and improving body image. These users generated 37,228 intervention text snippets and exchanged 4285 user-coach messages, which were analyzed using the proposed model. RESULTS: We applied the framework to predict binge eating behavior, resulting in an area under the curve between 0.57 (when applied to new users) and 0.72 (when applied to new symptom reports of known users). In addition, initial evidence indicated that specific text features predicted the therapeutic outcome of reducing ED symptoms. CONCLUSIONS: The case study demonstrates the usefulness of a structured approach to text data analytics. NLP techniques improve the prediction of symptom changes in DHIs. We present a technical framework that can be easily applied in other clinical trials and clinical presentations and encourage other groups to apply the framework in similar contexts

    A Unified Model of Exclusive ρ0\rho^0, ϕ\phi and \jpsi Electroproduction

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    A two-component model is developed for diffractive electroproduction of ρ0\rho^0, ϕ\phi and \jpsi, based on non-perturbative and perturbative two-gluon exchange. This provides a common kinematical structure for non-perturbative and perturbative effects, and allows the role of the vector-meson vertex functions to be explored independently of the production dynamics. A good global description of the vector-meson data is obtained.Comment: 30 pages, 35 figure

    Организация электроснабжения электрохимической защиты магистральных трубопроводов

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    В процессе эксплуатации магистральные газопроводы (МГ), как и большинство других металлических подземных коммуникаций, подвергаются воздействию процессов коррозии. Интенсивность этих процессов, а, следовательно, и состояние МГ зависит от целого ряда факторов, к числу которых следует отнести: коррозионную активность и характеристики грунтов в местах прокладки газопровода, глубину залегания участков газопровода, пересечениями с ЛЭП высокого напряжения или с электрифицированной железной дорогой – источниками блуждающих токов, качеством изоляционного покрытия, наличием и эффективностью настройки средств электрохимической защитыIn the process of exploitation of magistral gas pipelines (MG), like most other metal pose of communication, are exposed to corrosion processes. The intensity of these processes, and, consequently, the condition of the person MG depends on a number of factors, among which include: corrosiveness and the characteristics of the grunts in the field strip, the gazebo, the depth of the selenium sites gazebo leading from Lap high voltage electrician or from the sale of honey for the presence of wandering well, the quality of the insulation coating, lithium and effective tuning of electrochemical protectio

    Effectiveness of a digital cognitive behavior therapy-guided self-help intervention for eating disorders in college women: A cluster randomized clinical trial

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    Importance: Eating disorders (EDs) are common, serious psychiatric disorders on college campuses, yet most affected individuals do not receive treatment. Digital interventions have the potential to bridge this gap. Objective: To determine whether a coached, digital, cognitive behavior therapy (CBT) intervention improves outcomes for college women with EDs compared with referral to usual care. Design, Setting, and Participants: This cluster randomized trial was conducted from 2014 to 2018 at 27 US universities. Women with binge-purge EDs (with both threshold and subthreshold presentations) were recruited from enrolled universities. The 690 participants were followed up for up to 2 years after the intervention. Data analysis was performed from February to September 2019. Interventions: Universities were randomized to the intervention, Student Bodies-Eating Disorders, a digital CBT-guided self-help program, or to referral to usual care. Main Outcomes and Measures: The main outcome was change in overall ED psychopathology. Secondary outcomes were abstinence from binge eating and compensatory behaviors, as well as ED behavior frequencies, depression, anxiety, clinical impairment, academic impairment, and realized treatment access. Results: A total of 690 women with EDs (mean [SD] age, 22.12 [4.85] years; 414 [60.0%] White; 120 [17.4%] Hispanic; 512 [74.2%] undergraduates) were included in the analyses. For ED psychopathology, there was a significantly greater reduction in the intervention group compared with the control group at the postintervention assessment (β [SE], -0.44 [0.10]; d = -0.40; t1387 = -4.23; P \u3c .001), as well as over the follow-up period (β [SE], -0.39 [0.12]; d = -0.35; t1387 = -3.30; P \u3c .001). There was not a significant difference in abstinence from any ED behaviors at the postintervention assessment (odds ratio, 1.48; 95% CI, 0.48-4.62; P = .50) or at follow-up (odds ratio, 1.51; 95% CI, 0.63-3.58; P = .36). Compared with the control group, the intervention group had significantly greater reductions in binge eating (rate ratio, 0.82; 95% CI, 0.70-0.96; P = .02), compensatory behaviors (rate ratio, 0.68; 95% CI, 0.54-0.86; P \u3c .001), depression (β [SE], -1.34 [0.53]; d = -0.22; t1387 = -2.52; P = .01), and clinical impairment (β [SE], -2.33 [0.94]; d = -0.21; t1387 = -2.49; P = .01) at the postintervention assessment, with these gains sustained through follow-up for all outcomes except binge eating. Groups did not differ in terms of academic impairment. The majority of intervention participants (318 of 385 participants [83%]) began the intervention, whereas only 28% of control participants (76 of 271 participants with follow-up data available) sought treatment for their ED (odds ratio, 12.36; 95% CI, 8.73-17.51; P \u3c .001). Conclusions and Relevance: In this cluster randomized clinical trial comparing a coached, digital CBT intervention with referral to usual care, the intervention was effective in reducing ED psychopathology, compensatory behaviors, depression, and clinical impairment through long-term follow-up, as well as realizing treatment access. No difference was found between the intervention and control groups for abstinence for all ED behaviors or academic impairment. Given its scalability, a coached, digital, CBT intervention for college women with EDs has the potential to address the wide treatment gap for these disorders. Trial Registration: ClinicalTrials.gov Identifier: NCT02076464

    Evaluating psychometric properties of the Emotional Eating Scale Adapted for Children and Adolescents (EES-C) in a clinical sample of children seeking treatment for obesity: a case for the unidimensional model.

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    BackgroundThe Emotional Eating Scale - Adapted for Children and Adolescents (EES-C) assesses children's urge to eat in response to experiences of negative affect. Prior psychometric studies have demonstrated the high reliability, concurrent validity, and test-retest reliability of theoretically defined subconstructs among non-clinical samples of children and adolescents who were primarily healthy weight; however, no psychometric studies exist investigating the EES-C among clinical samples of children with overweight/obesity (OW/OB). Furthermore, studies conducted in different contexts have suggested a discordant number of subconstructs of emotions related to eating. The purpose of this study was to evaluate the validity of the EES-C in a clinical sample of children seeking weight-loss treatment.MethodUsing a hierarchical bi-factor approach, we evaluated the validity of the EES-C to measure a single general construct, a set of two separate correlated subconstructs, or a hierarchical arrangement of two constructs, and determined reliability in a clinical sample of treatment-seeking children with OW/OB aged 8-12 years (N = 147, mean age = 10.4 years.; mean BMI z = 2.0; female = 66%; Hispanic = 32%, White and other = 68%).ResultsComparison of factor-extraction methods suggested a single primary construct underlying EES-C in this clinical sample. The bi-factor indices provided clear evidence that most of the reliable variance in the total score (90.8 for bi-factor model with three grouping factors and 95.2 for bi-factor model with five grouping factors) was attributed to the general construct. After adjusting for relationships with the primary construct, remaining correlations among sets of items did not suggest additional reliable constructs.ConclusionResults suggest that the primary interpretive emphasis of the EES-C among treatment-seeking children with overweight or obesity should be placed on a single general construct, not on the 3- or 5- subconstructs as was previously suggested

    Nanorings and rods interconnected by self-assembly mimicking an artificial network of neurons

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    [EN] Molecular electronics based on structures ordered as neural networks emerges as the next evolutionary milestone in the construction of nanodevices with unprecedented applications. However, the straightforward formation of geometrically defined and interconnected nanostructures is crucial for the production of electronic circuitry nanoequivalents. Here we report on the molecularly fine-tuned self-assembly of tetrakis-Schiff base compounds into nanosized rings interconnected by unusually large nanorods providing a set of connections that mimic a biological network of neurons. The networks are produced through self-assembly resulting from the molecular conformation and noncovalent intermolecular interactions. These features can be easily generated on flat surfaces and in a polymeric matrix by casting from solution under ambient conditions. 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