■身体畸形障碍(BDD)严重且治疗不足。数字心理健康可能是扩大循证治疗的关键,如认知行为治疗BDD(CBT-BDD)。教练指导被认为是有效采用数字干预措施所必需的。然而,人们对不同的患者如何使用教练知之甚少,什么样的模式对应于有意义的结果,以及如何将指导与患者需求相匹配。
参与者是77名成年人,他们接受了为期12周的智能手机CBT-BDD。可以通过异步消息传递获得学士级别的教练。我们分析了用户在治疗期间发送给教练的400条消息。使用支持的效率模型对消息内容进行了编码(即,可用性,订婚,fit,知识,和实施)。我们的目的是澄清BDD患者何时以及出于何种目的使用教练,如果我们能根据这些模式对患者进行有意义的分类。然后,我们评估了教练使用的潜在基线预测因子,以及不同的模式是否与临床结果相关。
■用户平均发送5.88消息(SD=4.51,范围1-20),接收9.84(SD=5.74,范围2-30)。关于发送消息的频率,潜在剖面分析揭示了三个剖面,特点:(1)峰值中期治疗(16.88%),(2)治疗早期和晚期双峰/更多交流(10.39%),(3)持续低/无沟通(72.73%)。关于内容,出现了四个轮廓,特点主要是(1)参与度(51.95%),(2)拟合(15.58%),(3)知识(15.58%),和(4)杂项/无消息(16.88%)。频率分布和年龄之间有显著的关系,这样早/晚高峰组比低沟通组年龄大,以及频率分布和依从性,由中期治疗峰值组驱动,完成比低接触组更多的模块。关于内容,参与组和知识组开始治疗的基线症状比适合组更严重.内容简介与辍学有关,建议杂项/无接触组的辍学率较高,而参与组的辍学率较低。档案成员资格与其他结果之间没有关系。
■大多数参与者很少与教练联系,交流的最常见功能是增加参与度。结果表明,在早期治疗中,老年人可能比年轻人更喜欢或需要更多的支持。此外,而主要使用教练参与的个人可能会有较低的退学风险,那些根本不参与的人可能面临更高的风险。调查结果可以支持更个性化,数据驱动的教练协议和更有效的教练资源分配。
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.