Ulster University, Coleraine, UK.
Br J Clin Psychol. 2020 Jun;59(2):169-185. doi: 10.1111/bjc.12237. Epub 2019 Nov 7.
Research largely supports the clinical effectiveness of low-intensity cognitive behavioural therapy (LICBT) for mild-to-moderate anxiety and depression, delivered by psychological well-being practitioners (PWPs). Knowledge regarding the predictors of treatment response, however, is relatively limited. The primary aim of this study was to model the heterogeneity in longitudinal changes in anxiety and depression throughout LICBT provided by PWPs in Northern Ireland (NI), and to explore associations between pre-treatment variables and differences in treatment response.
Growth mixture modelling (GMM) techniques were employed to examine changes in psychological status in clients (N = 253) over the first six sessions of treatment, to identify divergent early response trajectories. A series of pre-treatment variables were used to predict class membership using chi-square tests and binary logistic regression models.
There was one class representing improvement and one representing no improvement for both anxiety and depression. Class membership was predictive of treatment outcome. Pre-treatment variables associated with less improvement included unemployment, risk of suicide, neglect of self or others, using medication, receiving previous or concurrent treatments, a longer duration of difficulties, and comorbidities.
Findings indicate most of the sample populated an 'improvers' class for both depression and anxiety. Pre-treatment variables identified as predictive of poor treatment response may need to be considered by practitioners in potential triage referral decision policies, supporting cost-effective and efficient services. Further research around predictors of clinical outcome is recommended.
Most of the sample belonged to an 'improvers' class. Several pre-treatment variables predicted poor treatment response (unemployment, suicide risk, neglect, medication, previous or concurrent treatments, longer duration of difficulties, and comorbidities). Few studies have utilized GMM to determine predictors of outcome following LICBT Regarding pre-treatment variables, the possibility of self-report bias cannot be excluded. The time period was relatively short, although represented the optimum number of sessions recommended for LICBT. The lack of a control group and random allocation were the main limitations.
研究在很大程度上支持了由心理健康从业者（PWPs）提供的低强度认知行为疗法（LICBT）治疗轻度至中度焦虑和抑郁的临床疗效。然而，关于治疗反应的预测因素的知识相对有限。本研究的主要目的是通过 PWPs 在北爱尔兰（NI）提供的 LICBT ，对焦虑和抑郁的纵向变化进行建模，并探讨治疗前变量与治疗反应差异之间的关系。
采用增长混合模型（GMM）技术，考察了 253 名患者在治疗的前六次疗程中心理状态的变化，以确定不同的早期反应轨迹。使用卡方检验和二项逻辑回归模型，采用一系列治疗前变量预测类别的成员资格。
焦虑和抑郁都有一个代表改善的类和一个代表没有改善的类。类别的成员资格是治疗结果的预测因素。与改善程度较低相关的治疗前变量包括失业、自杀风险、忽视自己或他人、使用药物、接受过以前或同时的治疗、困难持续时间较长，以及合并症。
研究结果表明，样本中大多数患者属于抑郁和焦虑的“改善”类。确定为治疗反应不良预测因素的治疗前变量可能需要从业者在潜在的分诊转介决策政策中考虑，以支持成本效益高和高效的服务。建议进一步研究临床结果的预测因素。
大多数患者属于“改善”类。几个治疗前变量预测了不良的治疗反应（失业、自杀风险、忽视、药物、以前或同时的治疗、困难持续时间较长，以及合并症）。很少有研究利用 GMM 来确定 LICBT 治疗后的结果预测因素。关于治疗前变量，不能排除自我报告偏差的可能性。时间相对较短，尽管代表了推荐的 LICBT 最佳疗程数。主要的局限性是缺乏对照组和随机分配。
