Remote Digital Measurement of Facial and Vocal Markers of Major Depressive Disorder Severity and Treatment Response: A Pilot Study.

Objectives: Multiple machine learning-based visual and auditory digital markers have demonstrated associations between major depressive disorder (MDD) status and severity. The current study examines if such measurements can quantify response to antidepressant treatment (ADT) with selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine uptake inhibitors (SNRIs). Methods: Visual and auditory markers were acquired through an automated smartphone task that measures facial, vocal, and head movement characteristics across 4 weeks of treatment (with time points at baseline, 2 weeks, and 4 weeks) on ADT (n = 18). MDD diagnosis was confirmed using the Mini-International Neuropsychiatric Interview (MINI), and the Montgomery-Åsberg Depression Rating Scale (MADRS) was collected concordantly to assess changes in MDD severity. Results: Patient responses to ADT demonstrated clinically and statistically significant changes in the MADRS [F (2, 34) = 51.62, p < 0.0001]. Additionally, patients demonstrated significant increases in multiple digital markers including facial expressivity, head movement, and amount of speech. Finally, patients demonstrated significantly decreased frequency of fear and anger facial expressions. Conclusion: Digital markers associated with MDD demonstrate validity as measures of treatment response.

Ecological momentary assessment as a measurement tool in depression trials.

We used ecological momentary assessment (EMA) to track symptoms during a clinical trial. Thirty-six participants with major depressive disorder (MDD) and MADRS scores ≥20 were enrolled in a nonrandomized 6-week open-label trial of commercially available antidepressants. Twice daily, a mobile device prompted participants to self-report the 6 items of the HamD6 sub-scale derived from the Hamilton rating scale for depression (HamD17). Morning EMA reports asked "how do you feel now" whereas evening reports gathered a full-day impression. Clinicians who were blinded to the EMA data rated the MADRS, HamD17 and HamD6 at screen, baseline and weeks 2,4, and 6. Hierarchical linear modeling (HLM) examined the course of the EMA assessments and convergence between EMA scores and clinician ratings. HLM analyses revealed strong correlations between AM and PM EMA derived HamD6 scores and revealed significant improvements over time. EMA improvements were significantly correlated with the clinician rated HamD6 scores at endpoint and predicted clinician rated HamD6 score changes from baseline to endpoint (p < .001). There was a large correlation between EMA and clinician derived HamD6 scores at each in-person assessment after baseline. Treatment response defined by EMA matched the clinician rated HamD6 treatment responses in 33 of 36 cases (91.7%). EMA derived symptom scores appear to be efficient and valid measures to track daily symptomatic change in clinical trials and may provide more accurate measures of symptom severity than the episodic "snapshots" that are currently used as clinical outcomes. These findings support further investigation of EMA for assessment in clinical trials.

From Deficit Remediation to Capacity Building: Learning to Enable Rather Than Disable Students With Dyslexia.

Purpose: In this article, we explore the deficit view of dyslexia and consider how it may narrow research so as to hamper the progress of scientific discovery and constrain best practices to the detriment of the overall well-being and growth of students with dyslexia. We consider the neurodiversity view of dyslexia as an alternative to the deficit view and explore how strengths-based approaches such as Universal Design for Learning can be used to support the overall well-being and development of students with dyslexia. Practical strategies are provided for applying a strengths-based approach in the speech-language pathologist setting to support students with dyslexia. Method: We completed a focused literature review of the history of the deficit view of dyslexia, the alternate neurodiversity view, exceptional abilities related to dyslexia, and strategies for Universal Design for Learning. Results: Although the research literature that deals with visual-spatial affordances associated with dyslexia is limited, there is significant evidence that a strengths-based approach to learning experience design can be leveraged by practitioners to improve student self-development, motivation, and academic outcomes. Conclusion: We find that further research is needed to explore strengths associated with dyslexia and argue that a shift in mindset from the deficit view toward the neurodiversity view is required to build the capacity of students with dyslexia to thrive in learning and life.

Use of a UDL Literacy Environment by Middle School Students With Intellectual and Developmental Disabilities.

Universal Design for Learning (UDL) has been shown to have benefits for students with disabilities. However, little is known about its potential to support literacy for students with intellectual and developmental disabilities (IDD). This qualitative study explored (a) to what extent students with IDD are able to use Udio, an online UDL literacy environment; and (b) how students with IDD experienced and perceived Udio. A grounded theory approach was used to analyze classroom observations, as well as teacher and student interviews. Electronic usage logs and student-produced discussions and projects were analyzed descriptively. Students independently navigated the environment and used embedded supports, including audio-assisted reading and sentence starters. In addition, findings indicate that age-relevant content, choice, and opportunities to socialize in online discussions were especially engaging for students. Further research is warranted to determine how UDL environments affect the literacy development of students with IDD.

Findings from the Community Health Intervention Program in South Carolina: implications for reducing cancer-related health disparities.

The South Carolina Cancer Prevention and Control Research Network (SC-CPCRN) implemented the Community Health Intervention Program (CHIP) mini-grants initiative to address cancer-related health disparities and reduce the cancer burden among high-risk populations across the state. The mini-grants project implemented evidence-based health interventions tailored to the specific needs of each community. This study aims to support the SC-CPCRN's goals of moving toward greater dissemination and implementation of evidence-based programs in the community to improve public health, prevent disease, and reduce the cancer burden. Three community-based organizations were awarded $10,000 each to implement one of the National Cancer Institute's evidence-based interventions. Each group had 12 months to complete their project. SC-CPCRN investigators and staff provided guidance, oversight, and technical assistance for each project. Grantees provided regular updates and reports to their SC-CPCRN liaisons to capture vital evaluation information. The intended CHIP mini-grant target population reach was projected to be up to 880 participants combined. Actual combined reach of the three projects reported upon completion totaled 1,072 individuals. The majority of CHIP participants were African-American females. Participants ranged in age from 19 to 81 years. Evaluation results showed an increase in physical activity, dietary improvements, and screening participation. The success of the initiative was the result of a strong community-university partnership built on trust. Active two-way communication and an honest open dialogue created an atmosphere for collaboration. Communities were highly motivated. All team members shared a common goal of reducing cancer-related health disparities and building greater public health capacity across the state.