Publications by authors named "A S Juarascio"

Article Synopsis
  • * Interviews with 12 participants revealed a strong desire for features like goal-setting for skill use, self-monitoring of eating disorder behaviors, and tracking mood and food intake.
  • * Participants also expressed the need for knowledge-based content, such as skill practice instructions, mental health strategies, mindfulness exercises, and nutrition advice within the app.
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Global sleep disturbance is robustly linked with a subjective sense of loss-of-control over eating (LOC). Depressed mood has been proposed as a mechanism to explain the bi-directional relationship between sleep disturbance and LOC eating. The current study evaluated whether sleep disturbance indirectly affects LOC eating via depressed mood.

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Bulimia nervosa (BN) is characterized by recurrent loss of control over eating (LOC) and inappropriate compensatory behaviors. Although cognitive-behavioral therapy (CBT) is efficacious for BN, many patients continue to experience symptoms at posttreatment. One potential driver of this low treatment response may be low mood, which maintains BN symptoms through negative reinforcement.

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Prior research on ultra-processed food addiction (FA) has utilized the self-report Yale Food Addiction Scale (YFAS) measures to identify individuals who experience indicators of substance-use disorders with respect to their consumption of ultra-processed foods. Studies using the YFAS have provided insight into the clinical utility of FA as both a distinct construct and an indicator of more severe psychopathology among individuals with eating disorders. However, the absence of clinician-administered assessment tools for FA has been identified as a barrier to the evaluation of FA as a novel clinical syndrome.

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Article Synopsis
  • Binge eating and self-induced vomiting are prevalent symptoms of eating disorders that are often analyzed through self-reports, which can be unreliable.
  • This study explored the use of continuous glucose monitors (CGMs) to identify these eating behaviors by analyzing blood glucose responses in 22 adults over two weeks.
  • The study found that CGM data could accurately classify binge eating (88% accuracy) and vomiting (79% accuracy), indicating its potential for improving research and treatment methods for eating disorders.
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