Literature DB >> 17469896

Eating disorder diagnoses: empirical approaches to classification.

Stephen A Wonderlich1, Thomas E Joiner, Pamela K Keel, Donald A Williamson, Ross D Crosby.   

Abstract

Decisions about the classification of eating disorders have significant scientific and clinical implications. The eating disorder diagnoses in the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) reflect the collective wisdom of experts in the field but are frequently not supported in empirical studies and do not capture the disorders of eating experienced by most people with an eating disorder. Statistical approaches to classification such as latent class analysis and taxometrics can help to create a classification system with greater scientific validity and clinical utility. The field would benefit from direct empirical comparisons of different classification schemes with various clinical and scientific validators. Such studies would enable the creators of the next DSM eating disorder classification to increase understanding of the advantages and disadvantages associated with choosing various diagnostic criteria sets for the eating disorders. ((c) 2007 APA, all rights reserved).

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Year:  2007        PMID: 17469896     DOI: 10.1037/0003-066X.62.3.167

Source DB:  PubMed          Journal:  Am Psychol        ISSN: 0003-066X


  34 in total

1.  Stability and change in patterns of concerns related to eating, weight, and shape in young adult women: a latent transition analysis.

Authors:  Angela S Cain; Amee J Epler; Douglas Steinley; Kenneth J Sher
Journal:  J Abnorm Psychol       Date:  2010-05

2.  Binge eating in surgical weight-loss treatments. Long-term associations with weight loss, health related quality of life (HRQL), and psychopathology.

Authors:  J de Man Lapidoth; A Ghaderi; C Norring
Journal:  Eat Weight Disord       Date:  2011-12       Impact factor: 4.652

Review 3.  The diagnostic classification of eating disorders: current situation, possible alternatives and future perspectives.

Authors:  F Dazzi; F G Di Leone
Journal:  Eat Weight Disord       Date:  2013-10-09       Impact factor: 4.652

4.  Stability and change in patterns of eating disorder symptoms from adolescence to young adulthood.

Authors:  Carolyn M Pearson; Jonathan Miller; Diann M Ackard; Katie A Loth; Melanie M Wall; Ann F Haynos; Dianne Neumark-Sztainer
Journal:  Int J Eat Disord       Date:  2017-02-15       Impact factor: 4.861

5.  "I'm not White, I have to be pretty and skinny": A qualitative exploration of body image and eating disorders among Asian American women.

Authors:  Sarah J Javier; Faye Z Belgrave
Journal:  Asian Am J Psychol       Date:  2018-12-27

6.  Prospective association of common eating disorders and adverse outcomes.

Authors:  Alison E Field; Kendrin R Sonneville; Nadia Micali; Ross D Crosby; Sonja A Swanson; Nan M Laird; Janet Treasure; Francesca Solmi; Nicholas J Horton
Journal:  Pediatrics       Date:  2012-07-16       Impact factor: 7.124

7.  Are diagnostic criteria for eating disorders markers of medical severity?

Authors:  Rebecka Peebles; Kristina K Hardy; Jenny L Wilson; James D Lock
Journal:  Pediatrics       Date:  2010-04-12       Impact factor: 7.124

8.  Male clinical norms and sex differences on the Eating Disorder Inventory (EDI) and Eating Disorder Examination Questionnaire (EDE-Q).

Authors:  Kathryn E Smith; Tyler B Mason; Stuart B Murray; Scott Griffiths; Rachel C Leonard; Chad T Wetterneck; Brad E R Smith; Nicholas R Farrell; Bradley C Riemann; Jason M Lavender
Journal:  Int J Eat Disord       Date:  2017-04-24       Impact factor: 4.861

9.  An assessment of daily food intake in participants with anorexia nervosa in the natural environment.

Authors:  Carlye Burd; James E Mitchell; Ross D Crosby; Scott G Engel; Stephen A Wonderlich; Chad Lystad; Daniel Le Grange; Carol B Peterson; Scott Crow
Journal:  Int J Eat Disord       Date:  2009-05       Impact factor: 4.861

10.  Evaluating new severity dimensions in the DSM-5 for bulimic syndromes using mixture modeling.

Authors:  Pamela K Keel; Ross D Crosby; Thomas B Hildebrandt; Alissa A Haedt-Matt; Julie A Gravener
Journal:  Int J Eat Disord       Date:  2012-08-13       Impact factor: 4.861

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