Future Directions

To explore vulnerability models and scar theories, we intend to continue employing ecological momentary assessments, panel data, and other longitudinal designs. These tools might help clinical science comprehend the interplay among executive functioning (EF) deficits, common mental disorder (CMD) symptoms, coping skills (e.g., avoidance or tenacity), daily activities (e.g., frequency of engaging in CBT skills), and their effects over time. Building on prior work, our future studies aim to test how scalable positive emotions-focused digital mental health (MH) intervention might efficaciously alleviate not only MH symptoms but also improve EF, empathy, self-compassion, and social cognition. Further, our objective is to persist in optimizing psychological treatments and uncovering the factors that predict and moderate technology-enabled MH interventions, particularly cognitive-behavioral therapy (CBT)-focused ones that have garnered the most evidence of their efficacy in the existing suite of psychological therapies.

Simultaneously, we aim to optimize psychological interventions for common mental disorders (CMDs) by conducting a series of randomized controlled trials (RCTs). First, the convergence of diminished positive emotions in anxiety and depression and the insufficient efficacy of current treatments in addressing positive emotions underscores a substantial gap in therapeutic care. In response to this demand, our goal is to evaluate scalable adaptations of contemporary psychological interventions designed to enhance positive emotions. Utilizing a wealth of research associating anhedonia (deficits in joy and motivation) with reduced sensitivity to rewards in both anxiety (LaFreniere & Newman, 2023a, 2023b) and depression (Craske et al., 2016; Wang et al., 2021), our objective is to assess a self-guided digital treatment centered on enhancing positive emotions with a focus on boosting reward sensitivity. The latter concepts are under-measured yet essential functional outcomes to evaluate and monitor at baseline and follow-ups in MH trials. Harnessing the gold standard design for assessing the comparative efficacy of clinical outcomes, we plan to conduct another two-arm RCT of a 15-week self-guided positive emotions-focused cognitive behavioral therapy (CBT) (Craske et al., 2023) (vs. self-monitoring only) for participants with self-reported mild-to-moderate anxiety and depression. RCTs are considered the gold standard because randomization aims to impartially allocate individuals to different conditions, eliminating any potential bias. RCTs also aim to evenly distribute variables that could confound the outcomes and account for any disparities among the groups, prompting our decision to conduct a two-arm RCT in the near future. However, conducting RCTs can incur significant expenses related to infrastructure, continuous patient monitoring from baseline to final evaluation and follow-ups, maintaining treatment cases, and other related costs. Our goal is thus to evaluate the efficacy of a scalable, fully self-guided, positive emotions-focused CBT that does not incur costs related to hiring and training personnel to deliver this intensive psychological intervention.

Second, we believe testing digital MH interventions using a novel randomized controleld trial (RCT) approach, microrandomized trials (MRTs), is essential to advance clinical psychological science. In MRTs, interventions are administered during opportune moments and contexts when they could achieve maximum impact. The latest technological progress in mobile phones and wearable devices offers a novel, integrated platform for delivering real-time mental health (MH) interventions, such as push notifications, with minimal user demands (e.g., a few prompts daily) and optimal spatial and temporal adaptability (Grekin et al., 2019; Nahum-Shani et al., 2015). Mobile devices can gather real-time, objective data like physical activity and location coupled with user-provided self-assessments, such as self-report symptom surveys. Such efforts could inform the creation of personalized, just-in-time adaptive interventions (JITAIs) (Nahum-Shani et al., 2015; Nahum-Shani et al., 2018). Prior research has shown that JITAIs utilizing data from wearables and smartphones are linked to notable enhancements in health outcomes, including increased physical activity (Hardeman et al., 2019) and reduced alcohol/substance use (Perski et al., 2022). However, there remains a paucity of MRTs in clinical psychological science despite the recent proliferation of digital MH interventions (Teepe et al., 2021). Given this backdrop and how problems of anxiety, depression, and insomnia are prevalent yet largely remain untreated in Singapore (Chang et al., 2019; Chong et al., 2011; Seow et al., 2018; Subramaniam et al., 2020), we aim to conduct three MRTs, each testing an 8-week digitalized, fully self-guided, mobile, evidence-based treatment: (a) cognitive-behavioral therapy (CBT) for insomnia (Edinger & Carney, 2015), (b) transdiagnostic CBT for anxiety and depressive disorders (Unified Protocol) (Barlow et al., 2011), and (c) CBT for generalized anxiety disorder (GAD) (Newman et al., 2020). To this end, the hope is that this body of work would ameliorate suffering and optimize well-being.