Chang Sarah, Alon Noy, Torous John
Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Digit Health. 2023 Jul 7;9:20552076231187244. doi: 10.1177/20552076231187244. eCollection 2023 Jan-Dec.
Despite the proliferation of mobile mental health apps, evidence of their efficacy around anxiety or depression is inadequate as most studies lack appropriate control groups. Given that apps are designed to be scalable and reusable tools, insights concerning their efficacy can also be assessed uniquely through comparing different implementations of the same app. This exploratory analysis investigates the potential to report a preliminary effect size of an open-source smartphone mental health app, mindLAMP, on the reduction of anxiety and depression symptoms by comparing a control implementation of the app focused on self-assessment to an intervention implementation of the same app focused on CBT skills.
A total of 328 participants were eligible and completed the study under the control implementation and 156 completed the study under the intervention implementation of the mindLAMP app. Both use cases offered access to the same in-app self-assessments and therapeutic interventions. Multiple imputations were utilized to impute the missing Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9 survey scores of the control implementation.
Post hoc analysis revealed small effect sizes of Hedge's = 0.34 for Generalized Anxiety Disorder-7 and Hedge's = 0.21 for Patient Health Questionnaire-9 between the two groups.
mindLAMP shows promising results in improving anxiety and depression outcomes in participants. Though our results mirror the current literature in assessing mental health apps' efficacy, they remain preliminary and will be used to inform a larger, well-powered study to further elucidate the efficacy of mindLAMP.
尽管移动心理健康应用程序大量涌现,但由于大多数研究缺乏适当的对照组,关于其在焦虑或抑郁方面疗效的证据并不充分。鉴于应用程序被设计为可扩展和可重复使用的工具,关于其疗效的见解也可以通过比较同一应用程序的不同实现方式来独特地评估。这项探索性分析通过比较专注于自我评估的应用程序对照实现方式与专注于认知行为疗法(CBT)技能的同一应用程序干预实现方式,研究报告一款开源智能手机心理健康应用程序mindLAMP在减轻焦虑和抑郁症状方面初步效应大小的可能性。
共有328名参与者符合条件并在mindLAMP应用程序的对照实现方式下完成了研究,156名参与者在该应用程序的干预实现方式下完成了研究。两种用例都提供了相同的应用内自我评估和治疗干预。采用多重填补法对对照实现方式中缺失的广泛性焦虑障碍-7(Generalized Anxiety Disorder-7)和患者健康问卷-9(Patient Health Questionnaire-9)调查分数进行填补。
事后分析显示,两组之间广泛性焦虑障碍-7的赫奇斯效应大小(Hedge's)为0.34,患者健康问卷-9的赫奇斯效应大小为0.21。
mindLAMP在改善参与者的焦虑和抑郁结果方面显示出有希望的结果。尽管我们的结果与当前评估心理健康应用程序疗效的文献一致,但它们仍然是初步的,并将用于为一项更大规模、有充分效力的研究提供信息,以进一步阐明mindLAMP的疗效。