Days between sessions predict attrition in text-based internet intervention of Binge Eating Disorder.

Background: The number of days between treatment sessions is often overlooked as a predictor of attrition in psychotherapy. In text-based Internet interventions, days between sessions may be a simple yet powerful predictor of attrition. Objective: We hypothesized that a larger number of days between sessions increased the likelihood of attrition among participants with Binge Eating Disorder (BED) in a 12-session Internet-based cognitive behavioral therapy (iCBT) program. Participants could work on the sessions whenever convenient for them and received written support from a psychologist. Material and methods: We compared 201 adult participants with mild to moderate BED (85 non-completers and 116 completers) on the number of days between sessions to predict attrition rates. Results: Mixed model binomial logistic regression showed that non-completers spent significantly more days between sessions across the first four treatment sessions (1-4) when controlling for age, gender, and intake measures of BMI, BED, overall health status (EQ VAS), and depression symptoms (MDI) (OR = 1.042, p < .001). Age (OR = 0.976, p < .001) and EQ VAS (OR = 0.984, p < .001) were also significant. The risk of attrition increased by 4.2 % for each additional day participants spent completing a session.A receiver operating characteristic (ROC) curve analysis showed that classification accuracy increased across sessions from 61.1 % in session 1 and 65.7 % in session 2 to 68.8 % in session 3 and 73.2 % in session 4. The optimal cut-off point in session 4 was 17.5 days, which detected 60.4 % of non-completers (sensitivity) and 78.4 % of completers (specificity).An exploratory repeated measures of ANOVA of days between sessions showed a significant within-subjects effect, where both non-completers and completers spent more days between sessions as they progressed from sessions 1 through 4 (F = 20.54, df = 3, p < .001). There was no interaction effect, suggesting that the increase in slope did not differ between non-completers and completers. Conclusions: Participants spending more days between sessions are at increased risk of dropping out of treatment. This may have important implications for identifying measures to reduce attrition, e.g., intensifying interventions through automated reminders or therapist messages. Our findings may have important transdiagnostic implications for text-based Internet interventions. Further studies should investigate the predictive value of days between sessions in other diagnoses.

Behind the athletic body: a clinical interview study of identification of eating disorder symptoms and diagnoses in elite athletes.

Eating disorders are more prevalent in athletes than in the general population and may have severe consequences for sports performance and health. Identifying symptoms can be difficult in athletes because restrictive eating and slim body images are often idealised in a sports setting. The Eating Disorders Examination Questionnaire (EDE-Q) and the SCOFF (Sick, Control, One stone, Fat and Food) questionnaire (SCOFF) are widely used generic instruments to identify symptoms of eating disorders. This study aimed to investigate the instruments' validity and explore eating disorder symptoms in a sample of athletes. A sample of 28 athletes (25 females) competing at a national level was interviewed based on the diagnostic criteria for eating disorders. We interviewed 18 athletes with a high score on EDE-Q and 10 with a low score. All interviews were transcribed and analysed from a general inductive approach. We identified 20 athletes with an eating disorder diagnosis, while 8 had no diagnosis. EDE-Q found 90% of the cases, while SCOFF found 94%. EDE-Q found no false-positive cases, while SCOFF found one. The qualitative results showed that most athletes reported eating concerns, restrictive eating, eating control (counting calories), weight concerns, body dissatisfaction (feeling fat and non-athletic), excessive exercise and health problems (eg, pain, fatigue). In conclusion, EDE-Q and SCOFF seem valid instruments to screen athletes' samples but may fail to find 6%-10% cases with eating disorders. Despite athletic bodies and normal body mass index, many athletes report severe eating problems and dissatisfaction with weight and body appearance. Implementation of regular screening may identify these symptoms at an early stage.

Text based internet intervention of Binge Eating Disorder (BED): Words per message is associated with treatment adherence.

Background: Some evidence suggests that in internet-based cognitive behavioral therapy (iCBT) the likelihood of adherence is increased when patients write longer messages to the therapist in the program. This association has not previously been investigated in iCBT for Binge Eating Disorder (BED). Objective: In this study, we hypothesized that the number of words written by patients with mild to moderate BED was associated with increased likelihood of treatment completion in a text-based iCBT program. Material and methods: We compared 143 BED patients (92 completers and 51 non-completers) on the number of messages and words written to their therapist during the treatment. Results: Completers wrote significantly more words per message (words/message) than non-completers. The results remained significant after controlling for gender, age, educational level, marital status, children, source of income and intake measures of BED, BMI and depression symptoms (Wald = 14.48, p < .001). The odds ratio of completion increased by 1.5% for each additional word patients wrote per message (OR = 1.015). The model showed a 72.4% classification accuracy, and an optimal cut-off point of 68.99 words/message for differentiating completers and non-completers. The model accurately identified 80.9% of completers (sensitivity) and 54.9% of non-completers (specificity). Conclusions: The number of words/message patients write may have important implications for ascertaining likelihood of adherence and improving adherence rates. From a clinical perspective, therapists should encourage patients to use the option of writing messages to the therapist. Words/message may prove to be a transdiagnostic predictor of treatment adherence in text based iCBT.

An analysis of patient motivation for seeking online treatment for binge eating disorder-A mixed methods study combining systematic text condensation with sentiment analysis.

Objective: Online treatment for binge eating disorder (BED) is an easily available option for treatment compared to most standard treatment procedures. However, little is known about how motivation types characterize this population and how these impact treatment adherence and effect in an online setting. Therefore, we aimed to investigate a sample of written motivation statements from BED patients, to learn more about how treatment and online treatment in particular, presents in this population. Methods: Using self-determination theory in a mixed methods context, we investigated which types of motivation were prevalent in our sample, how this was connected with patient sentiment, and how these constructs influence treatment and adherence. Results: Contrary to what most current literature suggests, we found that in our sample (n = 148), motivation type was not connected with treatment outcome. We did find a strong association between sentiment scores and motivation types, indicating the model is apt at detecting effects. We found that when comparing an adult and young adult population, they did not differ in motivation type and the treatment was equally effective in young adults and adults. In the sentiment scores there was a difference between sentiment score and adherence in the young adult group, as the more positive the young adults were, the less likely they were to complete the program. Discussion: Because motivation type does not influence online treatment to the same degree as it would in face-to-face treatment it indicates that the typical barriers to treatment may be less crucial in an online setting. This should be considered during intake; as less motivated patients may be able to adhere better to online treatment, because the latter imposes fewer barriers of the kind that only strong motivation can overcome. The fact that motivation type and sentiment score of the written texts are strongly associated, indicate a potential for automated models to detect motivation based on sentiment.

Early development of treatment motivation predicts adherence and symptom reduction in an internet-based guided self-help program for binge eating disorder.

Objective: Lack of motivation is widely acknowledged as a significant factor in treatment discontinuity and poor treatment outcomes in eating disorders. Treatment adherence is lower in internet-based treatment. The current study aimed to assess the relationship between treatment motivation and treatment outcomes in an internet-based therapist-guided intervention for Binge Eating Disorder (BED). Method: Adults (N = 153) with mild to moderate symptoms of BED participated in a 10-session internet-based treatment program. Baseline and between-session scores of "Readiness to change" and "Belief in change" were used to predict treatment completion and eating disorder symptom reduction (EDE-Q Global, BED-Q, and weekly number of binge eating episodes) at post-treatment. Results: Baseline treatment motivation could not predict treatment completion or symptom reduction. Early measures of treatment motivation (regression slope from sessions 1-5) significantly predicted both treatment completion and post-treatment symptom reduction. "Belief in change" was the strongest predictor for completing treatment (OR = 2.18, 95%-CI: 1.06, 4.46) and reducing symptoms (EDE-Q Global: B = -0.53, p = 0.001; number of weekly binge eating episodes: B = 0.81, p < 0.01). Discussion: The results indicated that patients entering online treatment for BED feel highly motivated. However, baseline treatment motivation could not significantly predict treatment completion, which contradicts previous research. The significant predictive ability of early measures of treatment motivation supports the clinical relevance of monitoring the development of early changes to tailor and optimize individual patient care. Further research is needed to examine treatment motivation in regard to internet-based treatment for BED with more validated measures.