Background: Digital behavioral weight loss programs are scalable and effective, and they provide an opportunity to personalize intervention components. However, more research is needed to test the acceptability and efficacy of personalized digital behavioral weight loss interventions.
Objective: In a 6-month single-arm trial, we examined weight loss, acceptability, and secondary outcomes of a digital commercial weight loss program (WeightWatchers). This digital program included a personalized weight loss program based on sex, age, height, weight, and personal food preferences, as well as synchronous (eg, virtual workshops and individual weekly check-ins) and asynchronous (eg, mobile app and virtual group) elements. In addition to a personalized daily and weekly PersonalPoints target, the program provided users with personalized lists of ≥300 ZeroPoint foods, which are foods that do not need to be weighed, measured, or tracked.
Methods: We conducted a pre-post evaluation of this 6-month, digitally delivered, and personalized WeightWatchers weight management program on weight loss at 3 and 6 months in adults with overweight and obesity. The secondary outcomes included participation, satisfaction, fruit and vegetable intake, physical activity, sleep quality, hunger, food cravings, quality of life, self-compassion, well-being, and behavioral automaticity.
Results: Of the 153 participants, 107 (69.9%) were female, and 65 (42.5%) identified as being from a minoritized racial or ethnic group. Participants' mean age was 41.09 (SD 13.78) years, and their mean BMI was 31.8 (SD 5.0) kg/m. Participants had an average weight change of -4.25% (SD 3.93%) from baseline to 3 months and -5.05% (SD 5.59%) from baseline to 6 months. At 6 months, the percentages of participants who experienced ≥3%, ≥5%, and ≥10% weight loss were 63.4% (97/153), 51% (78/153), and 14.4% (22/153), respectively. The mean percentage of weeks in which participants engaged in ≥1 aspects of the program was 87.53% (SD 23.40%) at 3 months and 77.67% (SD 28.69%) at 6 months. Retention was high (132/153, 86.3%), and more than two-thirds (94/140, 67.1%) of the participants reported that the program helped them lose weight. Significant improvements were observed in fruit and vegetable intake, physical activity, sleep quality, hunger, food cravings, quality of life, and well-being (all P values <.01).
Conclusions: This personalized, digital, and scalable behavioral weight management program resulted in clinically significant weight loss in half (78/153, 51%) of the participants as well as improvements in behavioral and psychosocial outcomes. Future research should compare personalized digital weight loss programs with generic programs on weight loss, participation, and acceptability.
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http://dx.doi.org/10.2196/44955 | DOI Listing |
Vaccines (Basel)
December 2024
The Vaccine Bio Research Institute, College of Medicine, The Catholic University of Korea, Annex to Seoul Saint Mary Hospital, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea.
Background: Influenza remains a significant public health challenge, with vaccination being a substantial way to prevent it. Cell-cultured influenza vaccines have emerged to improve on the drawbacks of egg-based vaccines, but there are few studies focusing on T cell immunity with both types of vaccines. Therefore, we studied the following 2022-2023 seasonal influenza vaccines with a standard dose and high dose: cell-based (C_sd and C_hd) and egg-based (E_sd and E_hd) vaccines.
View Article and Find Full Text PDFVaccines (Basel)
December 2024
Center for Vaccines and Immunology, University of Georgia, Athens, GA 30605, USA.
Standard-of-care influenza vaccines contain antigens that are typically derived from components of wild type (WT) influenza viruses. Often, these antigens elicit strain-specific immune responses and are susceptible to mismatch in seasons where antigenic drift is prevalent. Thanks to advances in viral surveillance and sequencing, influenza vaccine antigens can now be optimized using computationally derived methodologies and algorithms to enhance their immunogenicity.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
Electrocardiogram (ECG) signals contain complex and diverse features, serving as a crucial basis for arrhythmia diagnosis. The subtle differences in characteristics among various types of arrhythmias, coupled with class imbalance issues in datasets, often hinder existing models from effectively capturing key information within these complex signals, leading to a bias towards normal classes. To address these challenges, this paper proposes a method for arrhythmia classification based on a multi-branch, multi-head attention temporal convolutional network (MB-MHA-TCN).
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin 300132, China.
With the escalating threat posed by network intrusions, the development of efficient intrusion detection systems (IDSs) has become imperative. This study focuses on improving detection performance in programmable logic controller (PLC) network security while addressing challenges related to data imbalance and long-tail distributions. A dataset containing five types of attacks targeting programmable logic controllers (PLCs) in industrial control systems (ICS) was first constructed.
View Article and Find Full Text PDFPolymers (Basel)
December 2024
Catalysis Research Group (CRG), Department of Chemistry, College of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia.
This work focuses on the preparation and application of silver nanoparticles/organophilic clay/polyethylene glycol for the catalytic reduction of the contaminants methylene blue (MB) and 4-nitrophenol (4-NP) in a simple and binary system. Algerian clay was subjected to a series of treatments including acid treatment, ion exchange with the surfactant hexadecyltrimethylammonium bromide (HTABr), immobilization of polyethylene glycol polymer, and finally dispersion of AgNPs. The molecular weight of polyethylene glycol was varied (100, 200, and 4000) to study its effect on the stabilization of silver nanoparticles (AgNPs) and the catalytic activity of the resulting samples.
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