Development and Pilot Evaluation of Smartphone-Delivered Cognitive Behavior Therapy Strategies for Mood- and Anxiety-Related Problems: MoodMission

Given the ubiquity and interactive power of smartphones, there are opportunities to develop smartphone applications (apps) that provide novel, highly accessible mental health supports. This paper details the development of a smartphone app, “MoodMission,” that aims to provide evidence-based Cognitive Behavior Therapy (CBT) strategies for mood- and anxiety-related problems, contributing to the prevention of clinically significant depression and anxiety disorders and serving as an adjunct to therapeutic interventions delivered by trained health professionals. MoodMission was designed to deliver strategies in the form of real-time, momentary responses to user-reported low moods and anxiety. The development process involved: (a) construction of a battery of strategies, (b) empirical evaluation, (c) a software and behavioral plan design and testing process, (d) user feedback, and (e) a public launch. A pilot study of 44 participants completed the Mobile Application Rating Scale (MARS; Hides et al., 2014) for usability testing and feedback. MoodMission was rated significantly higher than standardized health app norms on the majority of the domains, including Entertainment, Interest, Customization, Target Group, Graphics, Visual Appeal, Quality of Information, Quantity of Information, Visual Information, Credibility of Source, Recommendation to Use, Estimated Frequency of Use, and Overall Rating (Hedges’s g range 0.57–1.97, p < .006). Case examples illustrate the practical uses of the app. In addition to clinical applications, MoodMission holds promise as a research tool either as an augmentation to clinician-delivered therapy, or as a vehicle for standardizing client access to specific CBT strategies (e.g., in studies intending to study different change processes).     

Maternal distress in the context of their child’s type 1 diabetes: exploring the role of adaptive maternal emotion regulation on child outcomes

Parents of children with Type 1 diabetes (T1D) experience high levels of distress, which may negatively impact child functioning. However, little is known about mechanisms that may buffer the adverse impact of parental distress. The current study explored the possible buffering role of maternal adaptive cognitive emotion regulation (CER) for the relationship between maternal distress and child psychological functioning. Forty-three children with T1D (8–15 years) completed measures assessing trait anxiety and depressive symptoms. Their mothers reported on general distress, illness-related parenting stress, and adaptive CER. Maternal illness-related parenting stress (but not general distress) was significantly associated with child psychological functioning. No buffering role for maternal adaptive CER was observed. As the current study is rather preliminary, future research using other methods to examine maternal adaptive CER, and examining other parental variables that may buffer against the negative impact of parental distress is warranted.     

Striving Towards Empowerment and Medication Adherence (STEP-AD): A Tailored Cognitive Behavioral Treatment Approach for Black Women Living With HIV

In the U.S. Black women with HIV face numerous psychosocial challenges, particularly trauma, racism, HIV-related discrimination, and gender role expectations, that are associated with negative HIV health outcomes and low medical treatment adherence. Yet many of these factors are unaddressed in traditional cognitive behavioral approaches. This study presents a case series of a tailored cognitive behavioral treatment approach for Black women living with HIV. Striving Towards EmPowerment and Medication Adherence (STEP-AD) is a 10-session treatment aimed at improving medication adherence for Black women with HIV by combining established cognitive behavioral strategies for trauma symptom reduction, strategies for coping with race- and HIV-related discrimination, gender empowerment, problem-solving techniques for medication adherence, and resilient coping. A case series study of five Black women with HIV was conducted to evaluate the preliminary acceptability and feasibility of the treatment and illustrate the approach. Findings support the potential promise of this treatment in helping to improve HIV medication adherence and decrease trauma symptoms. Areas for refinement in the treatment as well as structural barriers (e.g., housing) in the lives of the women that impacted their ability to fully benefit from the treatment are also noted.     

Object representations are biased toward each other through statistical learning

The visual system is remarkably efficient at extracting regularities from the environment through statistical learning. While such extraction has extensive consequences on cognition, it is unclear how statistical learning shapes the representations of the individual objects that comprise the regularities. Here we examine how statistical learning alters object representations. In three experiments, participants were exposed to either random arrays containing objects in a random order, or structured arrays containing object pairs where two objects appeared next to each other in fixed spatial or temporal configurations. After exposure, one object in each pair was briefly presented and participants judged the location or the orientation of the object without seeing the other object in the pair. We found that when an object reliably appeared next to another object in space, it was judged as being closer to the other object in space even though the other object was never presented (Experiments 1 and 2). Likewise, when an object reliably preceded another object in time, its orientation was biased toward the orientation of the other object even though the other object was never presented (Experiment 3). These results demonstrated that statistical learning fundamentally shapes how individual objects are represented in visual memory, by biasing the representation of one object toward its co-occurring partner. Importantly, participants in all experiments were not explicitly aware of the regularities. Thus, the bias in object representations was implicit. The current study reveals a novel impact of statistical learning on object representation: spatially co-occurring objects are represented as being closer in space, and temporally co-occurring objects are represented as having more similar features.