Internet-based relapse prevention for anorexia nervosa: Nine- month follow-up

被引:25
作者
Fichter M.M. [1 ,2 ]
Quadflieg N. [1 ]
Lindner S. [1 ]
机构
[1] Department of Psychiatry and Psychotherapy, University of Munich (LMU), Nussbaumstraße 7
[2] Schön Klinik Roseneck affiliated with the Medical Faculty of the Univ. of Munich (LMU)
关键词
Adherence; Anorexia nervosa; Eating disorder; Follow-up; Internet; Internet-based prevention; Maintenance; Online psychotherapy; Relapse prevention; Risk of relapse;
D O I
10.1186/2050-2974-1-23
中图分类号
学科分类号
摘要
Background: To study the longer term effects of an internet-based CBT intervention for relapse prevention (RP) in anorexia nervosa.Methods: 210 women randomized to the RP intervention group (full and partial completers) or the control group were assessed for eating and general psychopathology. Multiple regression analysis identified predictors of favorable course concerning Body Mass Index (BMI). Logistic regression analysis identified predictors of adherence to the RP program.Results: Most variables assessed showed more improvement for the RP than for the control group. However, only some scales reached statistical significance (bulimic behavior and menstrual function, assessed by expert interviewers blind to treatment condition). Very good results (BMI) were seen for the subgroup of " full completers" who participated in all nine monthly RP internet-based intervention sessions. " Partial completers" and controls (the latter non-significantly) underwent more weeks of inpatient treatment during the study period than " full completers" , indicating better health and less need for additional treatment among the " full completers" Main long-term predictors for favorable course were adherence to RP, more spontaneity, and more ineffectiveness. Main predictors of good adherence to RP were remission from lifetime mood and lifetime anxiety disorder, a shorter duration of eating disorder, and additional inpatient treatment during RP.Conclusions: Considering the high chronicity of AN, internet-based relapse prevention following intensive treatment appears to be promising. © 2013 Fichter et al.; licensee BioMed Central Ltd.
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