Preliminary Evaluation of a Conversational Agent to Support Self-management of Individuals Living With Posttraumatic Stress Disorder: Interview Study With Clinical Experts

BackgroundPosttraumatic stress disorder (PTSD) is a serious public health concern. However, individuals with PTSD often do not have access to adequate treatment. A conversational agent (CA) can help to bridge the treatment gap by providing interactive and timely interventions at scale. Toward this goal, we have developed PTSDialogue—a CA to support the self-management of individuals living with PTSD. PTSDialogue is designed to be highly interactive (eg, brief questions, ability to specify preferences, and quick turn-taking) and supports social presence to promote user engagement and sustain adherence. It includes a range of support features, including psychoeducation, assessment tools, and several symptom management tools. ObjectiveThis paper focuses on the preliminary evaluation of PTSDialogue from clinical experts. Given that PTSDialogue focuses on a vulnerable population, it is critical to establish its usability and acceptance with clinical experts before deployment. Expert feedback is also important to ensure user safety and effective risk management in CAs aiming to support individuals living with PTSD. MethodsWe conducted remote, one-on-one, semistructured interviews with clinical experts (N=10) to gather insight into the use of CAs. All participants have completed their doctoral degrees and have prior experience in PTSD care. The web-based PTSDialogue prototype was then shared with the participant so that they could interact with different functionalities and features. We encouraged them to “think aloud” as they interacted with the prototype. Participants also shared their screens throughout the interaction session. A semistructured interview script was also used to gather insights and feedback from the participants. The sample size is consistent with that of prior works. We analyzed interview data using a qualitative interpretivist approach resulting in a bottom-up thematic analysis. ResultsOur data establish the feasibility and acceptance of PTSDialogue, a supportive tool for individuals with PTSD. Most participants agreed that PTSDialogue could be useful for supporting self-management of individuals with PTSD. We have also assessed how features, functionalities, and interactions in PTSDialogue can support different self-management needs and strategies for this population. These data were then used to identify design requirements and guidelines for a CA aiming to support individuals with PTSD. Experts specifically noted the importance of empathetic and tailored CA interactions for effective PTSD self-management. They also suggested steps to ensure safe and engaging interactions with PTSDialogue. ConclusionsBased on interviews with experts, we have provided design recommendations for future CAs aiming to support vulnerable populations. The study suggests that well-designed CAs have the potential to reshape effective intervention delivery and help address the treatment gap in mental health

Color aesthetics: A transatlantic comparison of psychological and physiological impacts of warm and cool colors in garden landscapes

Evidence shows green space exposure has beneficial impacts on psychological and physiological wellbeing. However, aesthetic differences in color use in cultivated garden landscapes on wellbeing remains unexplored. This study investigates how warm and cool colored garden landscapes affect psychological and physiological wellbeing and how responses differ geographically.Our between subjects design used USA and UK participants exposed to videos of static garden landscapes consisting of (a) warm colors, (b) cool colors and (c) control images. Measures of subjective psychological wellbeing (UWIST Mood Adjective Checklist (MACL)) and biometrics of stress using the Empatica E4 watch (Heart rate; Heart Rate Variability (HRV); Skin Temperature; Galvanic Skin Response (GSR) and Photoplethysmography) were obtained to ascertain if warm and cool colored cultivated garden landscapes affected psychological and physiological responses.Results showed statistical differences between locations in psychological and physiological wellbeing. USA participants experienced increases in hedonic tone and decreases in perceived stress after viewing warm and cool colored garden landscapes, a result not found in UK participants. Physiological indicators show geographical differences with beneficial effects of warm colors in the USA, shown in HRV and GSR measures relative to control. The UK sample presented mixed evidence regarding positive effects of warm and cool colored garden landscapes on physiological measures.These findings show stronger psychological and physiological responses to color in the US sample compared to a UK sample, suggesting geographic disparities in these responses to plant color. This should be further explored to understand color choice for landscape design to optimize outdoor settings that maximize wellbeing

Uncertainty in Heart Rate Complexity Metrics Caused by R-Peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy