Cue Integration in Categorical Tasks: Insights from Audio-Visual Speech Perception

Previous cue integration studies have examined continuous perceptual dimensions (e.g., size) and have shown that human cue integration is well described by a normative model in which cues are weighted in proportion to their sensory reliability, as estimated from single-cue performance. However, this normative model may not be applicable to categorical perceptual dimensions (e.g., phonemes). In tasks defined over categorical perceptual dimensions, optimal cue weights should depend not only on the sensory variance affecting the perception of each cue but also on the environmental variance inherent in each task-relevant category. Here, we present a computational and experimental investigation of cue integration in a categorical audio-visual (articulatory) speech perception task. Our results show that human performance during audio-visual phonemic labeling is qualitatively consistent with the behavior of a Bayes-optimal observer. Specifically, we show that the participants in our task are sensitive, on a trial-by-trial basis, to the sensory uncertainty associated with the auditory and visual cues, during phonemic categorization. In addition, we show that while sensory uncertainty is a significant factor in determining cue weights, it is not the only one and participants' performance is consistent with an optimal model in which environmental, within category variability also plays a role in determining cue weights. Furthermore, we show that in our task, the sensory variability affecting the visual modality during cue-combination is not well estimated from single-cue performance, but can be estimated from multi-cue performance. The findings and computational principles described here represent a principled first step towards characterizing the mechanisms underlying human cue integration in categorical tasks

Increasing Access to Places for Physical Activity Through a Joint Use Agreement: A Case Study in Urban Honolulu

BackgroundTo increase levels of physical activity (PA), interventions that create or enhance access to places for PA are recommended. Establishing a joint use agreement is one way to increase access to existing PA and recreational facilities. The purpose of this article is to present a case study of In-Motion, a pilot joint use agreement project at one urban high school in Honolulu, Hawaii.ContextResidents of urban Honolulu are underserved by the amount of parkland and recreational facilities available for their use. The Honolulu County Department of Parks and Recreation sought to implement a joint use agreement to use the facilities of one urban high school for a recreational program. The high school selected for the pilot project has a student population primarily from low-income and ethnic minority backgrounds.MethodsAn assessment of the potential of 7 urban high schools to implement a joint use agreement was conducted to select the pilot site. In-Motion developed and implemented a joint use agreement. PA preferences of students, staff, and community members were assessed to guide recreational program offerings. Various recreational classes were offered free to the school community.ConsequencesSeveral barriers to implementing the joint use agreement and recreational program were encountered. However, participants were satisfied with the recreational classes they attended and said that the In-Motion program helped them to engage in more PA. Program awareness by high school students and staff was high.InterpretationIn-Motion has successfully modeled a pilot joint use agreement and provided new opportunities for PA to the high school’s students, teachers, and staff, and to community residents

Real‐World Evaluation of an Automated Algorithm to Detect Patients With Potentially Undiagnosed Hypertension Among Patients With Routine Care in Hawaiʻi

Background This real‐world evaluation considers an algorithm designed to detect patients with potentially undiagnosed hypertension, receiving routine care, in a large health system in Hawaiʻi. It quantifies patients identified as potentially undiagnosed with hypertension; summarizes the individual, clinical, and health system factors associated with undiagnosed hypertension; and examines if the COVID‐19 pandemic affected detection. Methods and Results We analyzed the electronic health records of patients treated across 6 clinics from 2018 to 2021. We calculated total patients with potentially undiagnosed hypertension and compared patients flagged for undiagnosed hypertension to those with diagnosed hypertension and to the full patient panel across individual characteristics, clinical and health system factors (eg, clinic of care), and timing. Modified Poisson regression was used to calculate crude and adjusted risk ratios. Among the eligible patients (N=13 364), 52.6% had been diagnosed with hypertension, 2.7% were flagged as potentially undiagnosed, and 44.6% had no evidence of hypertension. Factors associated with a higher risk of potentially undiagnosed hypertension included individual characteristics (ages 40–84 compared with 18–39 years), clinical (lack of diabetes diagnosis) and health system factors (clinic site and being a Medicaid versus a Medicare beneficiary), and timing (readings obtained after the COVID‐19 Stay‐At‐Home Order in Hawaiʻi). Conclusions This evaluation provided evidence that a clinical algorithm implemented within a large health system's electronic health records could detect patients in need of follow‐up to determine hypertension status, and it identified key individual characteristics, clinical and health system factors, and timing considerations that may contribute to undiagnosed hypertension among patients receiving routine care

A Mixed-Methods Implementation Evaluation of Virtual Reality Job Interview Training in IPS Supported Employment

Objective: Employment rates among individuals with serious mental illness may be improved by engagement in the individual placement and support (IPS) model of supported employment. Results from a recent randomized controlled trial (RCT) indicate that virtual reality job interview training (VR-JIT) improves employment rates among individuals with serious mental illness who have been actively engaged in IPS for at least 90 days. This study reports on an initial implementation evaluation of VR-JIT during the RCT in a community mental health agency. Methods: A sequential, complementary mixed-methods design included use of qualitative data to improve understanding of quantitative findings. Thirteen IPS staff trained to lead VR-JIT implementation completed VR-JIT acceptability, appropriateness, and feasibility surveys. Participants randomly assigned to IPS with VR-JIT completed acceptability (N=42) and usability (N=28) surveys after implementation. The authors also conducted five focus groups with IPS staff (N=11) and VR-JIT recipients (N=13) and semistructured interviews with IPS staff (N=9) and VR-JIT recipients (N=4), followed by an integrated analysis process. Results: Quantitative results suggest that IPS staff found VR-JIT to be highly acceptable, appropriate for integration with IPS, and feasible for delivery. VR-JIT was highly acceptable to recipients. Qualitative results add important context to the quantitative findings, including benefits of VR-JIT for IPS staff as well as adaptations for delivering technology-based interventions to individuals with serious mental illness. Conclusions: These qualitative and quantitative findings are consistent with each other and were influenced by VR-JIT’s adaptability and perceived benefits. Tailoring VR-JIT instruction and delivery to individuals with serious mental illness may help optimize VR-JIT implementation within IPS