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A bunch of APS talks on related topics :)

This is a pre-registered analysis plan for our randomized controlled trial (RCT) "An Online Wellness Intervention: Investigating the Efficacy of the Common Elements Toolbox" (NCT05379881). The RCT is registered in clinicaltrials.gov: https://clinicaltrials.gov/ct2/show/NCT05379881. This is a two-arm (1:1 allocation) RCT comparing short (i.e., 2-week) and longer-term (i.e., 8 weeks) depression and anxiety changes in online workers randomized to received the Common Elements Toolbox (COMET) or a waiting list control (WLC). The trial aims to (1) assess the efficacy of COMET on primary (1a) and secondary outcomes (1b; see below). Additionally, we (2) aimed to build a prediction algorithm to identify individuals who most strongly respond to COMET. We determined the choice of control condition by using the Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials. This framework specifies that no one control group is optimal. Instead, it recommends that the primary aim of the trial and limitations and barriers must be considered when choosing a control condition. While some control groups like sham controls and active placebos are traditionally thought to provide a lot of rigor, they may not be the best control group in any specific study. One consideration in designing our trial is that the efficacy of SSIs in general has been well-established in youth. The efficacy of SSIs in adults and of COMET specifically is not as well-established (see Wasil et al., 2021). Thus, the early state of research on COMET's efficacy would be one factor supporting the use of a WLC. Another important consideration in choosing a comparator is that the aim of single-session interventions like COMET is to make treatment more scalable. Because the intervention is freely available, the consideration of whether it is more effective than a well-controlled sham or placebo is not relevant. If COMET was no more effective than, for example psychoeducation on dream interpretation or tapping, but all interventions were more effective than a WLC, *all other factors being equal,* COMET would be preferable because it is meant to be a bona-fide intervention that uses evidence-based psychological principles.

Study aiming to explore the relative attitudes of individuals toward using self-help in a book print media (i.e., bibliotherapy) vs. internet-based format (i.e., DMHIs).

We are conducting a randomized controlled trial of an online single-session intervention to improve mental health and wellness among college students.

Depression and anxiety are now the 1st and 10th leading causes of disability worldwide. However, their variegated presentation and symptoms complicate efforts to develop a better understanding of the complex factors that shape the dynamics of their development within individuals. The development of personalized detection, diagnostics, and treatment options has been hindered by the lack of within-subject longitudinal observations at high temporal resolution and for large samples of individuals across the spectrum of internalizing disorders. Here, we discuss our efforts in the burgeoning field of precision mental health which leverages large-scale data of the behavioral, cognitive, emotional and social traces that billions of individuals leave behind when they interact with social media platforms. Our results point towards the possibility of modeling individualized mental health trajectories at population scale to identify high-precision targets for the detection, intervention, and mitigation of internalizing disorders.

Depression is a leading cause of disability worldwide, but is often under-diagnosed and under-treated. One of the tenets of cognitive-behavioral therapy (CBT) is that individuals who are depressed exhibit distorted modes of thinking, so-called cognitive distortions, which can negatively affect their emotions and motivation. Here, we show that individuals with a self-reported diagnosis of depression on social media express higher levels of distorted thinking than a random sample. Some types of distorted thinking were found to be more than twice as prevalent in our depressed cohort, in particular Personalizing and Emotional Reasoning. This effect is specific to the distorted content of the expression and can not be explained by the presence of specific topics, sentiment, or first-person pronouns. Our results point towards the detection, and possibly mitigation, of patterns of online language that are generally deemed depressogenic. They may also provide insight into recent observations that social media usage can have a negative impact on mental health.