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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930145/ https://www.ncbi.nlm.nih.gov/pubmed/36819741 http://dx.doi.org/10.1016/j.invent.2023.100607 |
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author | Linnet, Jakob Hertz, Søren Peter Thygesen Jensen, Esben Skov Runge, Eik Tarp, Kristine Hæstrup Hindkjær Holmberg, Trine Theresa Mathiasen, Kim Lichtenstein, Mia Beck |
author_facet | Linnet, Jakob Hertz, Søren Peter Thygesen Jensen, Esben Skov Runge, Eik Tarp, Kristine Hæstrup Hindkjær Holmberg, Trine Theresa Mathiasen, Kim Lichtenstein, Mia Beck |
author_sort | Linnet, Jakob |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9930145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99301452023-02-16 Days between sessions predict attrition in text-based internet intervention of Binge Eating Disorder Linnet, Jakob Hertz, Søren Peter Thygesen Jensen, Esben Skov Runge, Eik Tarp, Kristine Hæstrup Hindkjær Holmberg, Trine Theresa Mathiasen, Kim Lichtenstein, Mia Beck Internet Interv Full length Article 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. Elsevier 2023-02-11 /pmc/articles/PMC9930145/ /pubmed/36819741 http://dx.doi.org/10.1016/j.invent.2023.100607 Text en © 2023 Published by Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Full length Article Linnet, Jakob Hertz, Søren Peter Thygesen Jensen, Esben Skov Runge, Eik Tarp, Kristine Hæstrup Hindkjær Holmberg, Trine Theresa Mathiasen, Kim Lichtenstein, Mia Beck Days between sessions predict attrition in text-based internet intervention of Binge Eating Disorder |
title | Days between sessions predict attrition in text-based internet intervention of Binge Eating Disorder |
title_full | Days between sessions predict attrition in text-based internet intervention of Binge Eating Disorder |
title_fullStr | Days between sessions predict attrition in text-based internet intervention of Binge Eating Disorder |
title_full_unstemmed | Days between sessions predict attrition in text-based internet intervention of Binge Eating Disorder |
title_short | Days between sessions predict attrition in text-based internet intervention of Binge Eating Disorder |
title_sort | days between sessions predict attrition in text-based internet intervention of binge eating disorder |
topic | Full length Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930145/ https://www.ncbi.nlm.nih.gov/pubmed/36819741 http://dx.doi.org/10.1016/j.invent.2023.100607 |
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