Objective: Review published findings on self-esteem and pediatric overweight, and changes in self-esteem subsequent to weight management programs.
Methods: We used PsycInfo and MedLine searches to identify peer-reviewed journal articles examining self-esteem changes following participation in weight management programs.
Results: Data regarding the relationship between self-esteem and obesity is mixed. Factors that place overweight children "at-risk" for low self-esteem include early adolescence, female gender, identification with majority cultural standards of body shape, exposure to teasing and peer victimization, a history of greater parental control over feeding, and internal attributions about weight status. Data from intervention studies suggest positive effects on self-esteem across settings. Components related to self-esteem improvements include weight change, parent involvement, and group intervention format.
Conclusions: Well-designed, longitudinal studies using multidimensional measures of self-esteem, and following CONSORT guidelines are needed to confirm and expand these findings. Emphasis should be placed on examining mediators and moderators of self-esteem change.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1093/jpepsy/jsm048 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Metabolic/bariatric surgery optimization: a position statement by Arabic association for the study of diabetes and metabolism (AASD).
Diabetol Metab Syndr
January 2025
Faculty of Medicine, Cairo University,Internal Medicine Diabetes and Endocrinology Department, Cairo, Egypt.
For patients considering bariatric surgery, it is essential to have clear answers to common questions to ensure the success of the procedure. Patients should understand that surgery is not a quick fix but a tool that must be complemented by lifestyle changes, including dietary adjustments and regular physical activity. The procedure carries potential risks that should be weighed against the potential benefits.
View Article and Find Full Text PDFscSMD: a deep learning method for accurate clustering of single cells based on auto-encoder.
BMC Bioinformatics
January 2025
Department of Surgery, Shanghai Key Laboratory of Gastric Neoplasms, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: Single-cell RNA sequencing (scRNA-seq) has transformed biological research by offering new insights into cellular heterogeneity, developmental processes, and disease mechanisms. As scRNA-seq technology advances, its role in modern biology has become increasingly vital. This study explores the application of deep learning to single-cell data clustering, with a particular focus on managing sparse, high-dimensional data.
View Article and Find Full Text PDFAI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios.
BMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah Health, 30 N. Mario Capecchi Dr., Level 5 South, Salt Lake City, UT, 84132, USA.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
Refined methodologies for probabilistic dietary exposure assessment for food contaminants based on the observed individual means methodology.
J Expo Sci Environ Epidemiol
January 2025
Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milano, Italy.
Background: The Observed Individual Means (OIM) methodology, based on the non-parametric bootstrap, is usually employed to perform basic probabilistic dietary chronic exposure assessment, and assumes independence and identical distribution of occurrence data within food category. However, this assumption may not be valid if several expected distributions of occurrence can be a priori identified within food category. Moreover, OIM assumes each analysed food sample to equally contribute to mean occurrence, as information about relevance of each food item cannot be incorporated into exposure assessment.
View Article and Find Full Text PDFExperimental and computational approach on the corrosion inhibition properties of two newly pyrazole derivatives on carbon steel in acid medium.
Sci Rep
January 2025
LCEA Laboratory, Faculty of Sciences, Mohammed Premier University, Oujda, Morocco.
In the current investigation, the efficiency inhibition of two newly synthesized bi-pyrazole derivatives, namely 2,3-bis[(bis((1 H-pyrazol-1-yl) methyl) amino)] pyridine (Tetra-Pz-Ortho) and 1,4-bis[(bis((1 H-pyrazol-1-yl) methyl) amino)] benzene (Tetra-Pz-Para) for corrosion of carbon steel (C&S) in 1 M HCl medium was evaluated. A Comparative study of inhibitor effect of Tetra-Pz-Ortho and Tetra-Pz-Para was conducted first using weight loss method and EIS (Electrochemical Impedance Spectroscopy) and PDP (Potentiodynamic Polarisation) techniques. Tetra-Pz-Ortho and Tetra-Pz-Para had a maximum inhibition efficacy of 97.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!