The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder
Background: Body dysmorphic disorder (BDD) is severe and undertreated. Digital mental health could be key to expanding access to evidence-based treatments, such as cognitive behavioral therapy for BDD (CBT-BDD). Coach guidance is posited to be essential for effective uptake of digital interventions....
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-06-01
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| Series: | Internet Interventions |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214782924000368 |
| _version_ | 1797198788868177920 |
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| author | Emily E. Bernstein Jennifer L. Greenberg Hilary Weingarden Ivar Snorrason Berta Summers Jasmine Williams Rachel Quist Joshua Curtiss Oliver Harrison Sabine Wilhelm |
| author_facet | Emily E. Bernstein Jennifer L. Greenberg Hilary Weingarden Ivar Snorrason Berta Summers Jasmine Williams Rachel Quist Joshua Curtiss Oliver Harrison Sabine Wilhelm |
| author_sort | Emily E. Bernstein |
| collection | DOAJ |
| description | Background: Body dysmorphic disorder (BDD) is severe and undertreated. Digital mental health could be key to expanding access to evidence-based treatments, such as cognitive behavioral therapy for BDD (CBT-BDD). Coach guidance is posited to be essential for effective uptake of digital interventions. However, little is known about how different patients may use coaching, what patterns correspond to meaningful outcomes, and how to match coaching to patient needs. Methods: Participants were 77 adults who received a 12-week guided smartphone CBT-BDD. Bachelor's-level coaches were available via asynchronous messaging. We analyzed the 400 messages sent by users to coaches during treatment. Message content was coded using the efficiency model of support (i.e., usability, engagement, fit, knowledge, and implementation). We aimed to clarify when and for what purposes patients with BDD used coaching, and if we can meaningfully classify patients by these patterns. We then assessed potential baseline predictors of coach usage, and whether distinct patterns relate to clinical outcomes. Results: Users on average sent 5.88 messages (SD = 4.51, range 1–20) and received 9.84 (SD = 5.74, range 2–30). Regarding frequency of sending messages, latent profile analysis revealed three profiles, characterized by: (1) peak mid-treatment (16.88 %), (2) bimodal/more communication early and late in treatment (10.39 %), and (3) consistent low/no communication (72.73 %). Regarding content, four profiles emerged, characterized by mostly (1) engagement (51.95 %), (2) fit (15.58 %), (3) knowledge (15.58 %), and (4) miscellaneous/no messages (16.88 %). There was a significant relationship between frequency profile and age, such that the early/late peak group was older than the low communication group, and frequency profile and adherence, driven by the mid-treatment peak group completing more modules than the low contact group. Regarding content, the engagement and knowledge groups began treatment with more severe baseline symptoms than the fit group. Content profile was associated with dropout, suggesting higher dropout rates in the miscellaneous/no contact group and reduced rates in the engagement group. There was no relationship between profile membership and other outcomes. Discussion: The majority of participants initiated little contact with their coach and the most common function of communications was to increase engagement. Results suggest that older individuals may prefer or require more support than younger counterparts early in treatment. Additionally, whereas individuals using coaching primarily for engagement may be at lower risk of dropping out, those who do not engage at all may be at elevated risk. Findings can support more personalized, data-driven coaching protocols and more efficient allocation of coaching resources. |
| first_indexed | 2024-04-24T07:05:26Z |
| format | Article |
| id | doaj.art-732498fe704a4b2da90020157551d32c |
| institution | Directory Open Access Journal |
| issn | 2214-7829 |
| language | English |
| last_indexed | 2024-04-24T07:05:26Z |
| publishDate | 2024-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Internet Interventions |
| spelling | doaj.art-732498fe704a4b2da90020157551d32c2024-04-22T04:11:43ZengElsevierInternet Interventions2214-78292024-06-0136100743The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorderEmily E. Bernstein0Jennifer L. Greenberg1Hilary Weingarden2Ivar Snorrason3Berta Summers4Jasmine Williams5Rachel Quist6Joshua Curtiss7Oliver Harrison8Sabine Wilhelm9Massachusetts General Hospital, United States of America; Harvard Medical School, United Kingdom; Corresponding author at: 185 Cambridge Street, Suite 2000, Boston, MA 02114, United States of America.Massachusetts General Hospital, United States of America; Harvard Medical School, United KingdomMassachusetts General Hospital, United States of America; Harvard Medical School, United KingdomMassachusetts General Hospital, United States of America; Harvard Medical School, United KingdomMassachusetts General Hospital, United States of AmericaMassachusetts General Hospital, United States of AmericaMassachusetts General Hospital, United States of AmericaMassachusetts General Hospital, United States of America; Northeastern University, United States of AmericaKoa Health, United States of AmericaMassachusetts General Hospital, United States of America; Harvard Medical School, United KingdomBackground: Body dysmorphic disorder (BDD) is severe and undertreated. Digital mental health could be key to expanding access to evidence-based treatments, such as cognitive behavioral therapy for BDD (CBT-BDD). Coach guidance is posited to be essential for effective uptake of digital interventions. However, little is known about how different patients may use coaching, what patterns correspond to meaningful outcomes, and how to match coaching to patient needs. Methods: Participants were 77 adults who received a 12-week guided smartphone CBT-BDD. Bachelor's-level coaches were available via asynchronous messaging. We analyzed the 400 messages sent by users to coaches during treatment. Message content was coded using the efficiency model of support (i.e., usability, engagement, fit, knowledge, and implementation). We aimed to clarify when and for what purposes patients with BDD used coaching, and if we can meaningfully classify patients by these patterns. We then assessed potential baseline predictors of coach usage, and whether distinct patterns relate to clinical outcomes. Results: Users on average sent 5.88 messages (SD = 4.51, range 1–20) and received 9.84 (SD = 5.74, range 2–30). Regarding frequency of sending messages, latent profile analysis revealed three profiles, characterized by: (1) peak mid-treatment (16.88 %), (2) bimodal/more communication early and late in treatment (10.39 %), and (3) consistent low/no communication (72.73 %). Regarding content, four profiles emerged, characterized by mostly (1) engagement (51.95 %), (2) fit (15.58 %), (3) knowledge (15.58 %), and (4) miscellaneous/no messages (16.88 %). There was a significant relationship between frequency profile and age, such that the early/late peak group was older than the low communication group, and frequency profile and adherence, driven by the mid-treatment peak group completing more modules than the low contact group. Regarding content, the engagement and knowledge groups began treatment with more severe baseline symptoms than the fit group. Content profile was associated with dropout, suggesting higher dropout rates in the miscellaneous/no contact group and reduced rates in the engagement group. There was no relationship between profile membership and other outcomes. Discussion: The majority of participants initiated little contact with their coach and the most common function of communications was to increase engagement. Results suggest that older individuals may prefer or require more support than younger counterparts early in treatment. Additionally, whereas individuals using coaching primarily for engagement may be at lower risk of dropping out, those who do not engage at all may be at elevated risk. Findings can support more personalized, data-driven coaching protocols and more efficient allocation of coaching resources.http://www.sciencedirect.com/science/article/pii/S2214782924000368Body dysmorphic disorderCognitive behavioral therapySmartphoneDigital healthClinical trialCoach |
| spellingShingle | Emily E. Bernstein Jennifer L. Greenberg Hilary Weingarden Ivar Snorrason Berta Summers Jasmine Williams Rachel Quist Joshua Curtiss Oliver Harrison Sabine Wilhelm The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder Internet Interventions Body dysmorphic disorder Cognitive behavioral therapy Smartphone Digital health Clinical trial Coach |
| title | The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder |
| title_full | The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder |
| title_fullStr | The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder |
| title_full_unstemmed | The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder |
| title_short | The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder |
| title_sort | use of coaching in smartphone app based cognitive behavioral therapy for body dysmorphic disorder |
| topic | Body dysmorphic disorder Cognitive behavioral therapy Smartphone Digital health Clinical trial Coach |
| url | http://www.sciencedirect.com/science/article/pii/S2214782924000368 |
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