A Systematic Review of Taste Differences Among People With Eating Disorders.
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ABSTRACT: Background
Eating disorders are a significant cause of morbidity and mortality. The etiology and maintenance of eating-disorder symptoms are not well understood. Evidence suggests that there may be gustatory alterations in patients with eating disorders.Objective
This article systematically reviews research assessing gustatory differences in patients with anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED).Method
A systematic review was performed, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, examining taste and eating disorders. We reviewed electronic databases and identified 1,490 peer-reviewed English-language studies. Of these, 49 met inclusion criteria.Results
Studies employed psychophysical measures (n = 27), self-reported questionnaires (n = 5), and neuroimaging techniques (i.e., electroencephalography, functional magnetic resonance imaging; n = 17). Psychophysical studies showed that individuals with BN, in general, had greater preference for sweetness than healthy controls, and those with AN had a greater aversion for fat than controls. In neuroimaging studies, findings suggested that predictable administration of sweet-taste stimuli was associated with reduced activation in taste-reward regions of the brain among individuals with AN (e.g., insula, ventral, and dorsal striatum) but increased activation in BN and BED.Discussion
To our knowledge, this systematic review is the first to synthesize literature on taste differences in AN, BN, and BED. The inconsistency and variability in methods used across studies increased difficulties in comparing studies and disease processes. Further studies with well-defined population parameters are warranted to better understand how taste varies in patients with eating disorders.
SUBMITTER: Chao AM
PROVIDER: S-EPMC6912928 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Patients with eating disorders are characterized by pathological eating habits and a tendency to overestimate their weight and body shape. Virtual reality shows promise for the evaluation and management of patients with eating disorders. This technology, when accepted by this population, allows immersion in virtual environments, assessment, and therapeutic approaches, by exposing users to high-calorie foods or changes in body shape. OBJECTIVE:To better understand the value of virtual reality, we conducted a review of the literature, including clinical studies proposing the use of virtual reality for the evaluation and management of patients with eating disorders. METHODS:We searched PubMed, PsycINFO, ScienceDirect, the Cochrane Library, Scopus, and Web of Science up to April 2017. We created the list of keywords based on two domains: virtual reality and eating disorders. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify, select, and critically appraise relevant research while minimizing bias. RESULTS:The initial database searches identified 311 articles, 149 of which we removed as duplicates. We analyzed the resulting set of 26 unique studies that met the inclusion criteria. Of these, 8 studies were randomized controlled trials, 13 were nonrandomized studies, and 5 were clinical trials with only 1 participant. Most articles focused on clinical populations (19/26, 73%), with the remainder reporting case-control studies (7/26, 27%). Most of the studies used visual immersive equipment (16/26, 62%) with a head-mounted display (15/16, 94%). Two main areas of interest emerged from these studies: virtual work on patients’ body image (7/26, 27%) and exposure to virtual food stimuli (10/26, 38%). CONCLUSIONS:We conducted a broad analysis of studies on the use of virtual reality in patients with eating disorders. This review of the literature showed that virtual reality is an acceptable and promising therapeutic tool for patients with eating disorders.
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Project description:BackgroundNetwork science represents a powerful and increasingly promising method for studying complex real-world problems. In the last decade, it has been applied to psychometric data in the attempt to explain psychopathologies as complex systems of causally interconnected symptoms. One category of mental disorders, relevant for their severity, incidence and multifaceted structure, is that of eating disorders (EDs), serious disturbances that negatively affect a person's eating behavior.AimsWe aimed to review the corpus of psychometric network analysis methods by scrutinizing a large sample of network-based studies that exploit psychometric data related to EDs. A particular focus is given to the description of the methodologies for network estimation, network description and network stability analysis providing also a review of the statistical software packages currently used to carry out each phase of the network estimation and analysis workflow. Moreover, we try to highlight aspects with potential clinical impact such as core symptoms, influences of external factors, comorbidities, and related changes in network structure and connectivity across both time and subpopulations.MethodsA systematic search was conducted (February 2022) on three different literature databases to identify 57 relevant research articles. The exclusion criteria comprehended studies not based on psychometric data, studies not using network analysis, studies with different aims or not focused on ED, and review articles.ResultsAlmost all the selected 57 papers employed the same analytical procedures implemented in a collection of R packages specifically designed for psychometric network analysis and are mostly based on cross-sectional data retrieved from structured psychometric questionnaires, with just few exemptions of panel data. Most of them used the same techniques for all phases of their analysis. In particular, a pervasive use of the Gaussian Graphical Model with LASSO regularization was registered for in network estimation step. Among the clinically relevant results, we can include the fact that all papers found strong symptom interconnections between specific and nonspecific ED symptoms, suggesting that both types should therefore be addressed by clinical treatment.ConclusionsWe here presented the largest and most comprehensive review to date about psychometric network analysis methods. Although these methods still need solid validation in the clinical setting, they have already been able to show many strengths and important results, as well as great potentials and perspectives, which have been analyzed here to provide suggestions on their use and their possible improvement.
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