Web-Based Cognitive Behavioral Therapy for Depression Among Homebound Older Adults: Development and Usability Study.

BACKGROUND: Homebound older adults are a high-risk group for depression. However, many of them face barriers to accessing evidence-supported mental health treatments. Digital mental health interventions can potentially improve treatment access, but few web-based interventions are explicitly tailored for depression in older adults. OBJECTIVE: This paper describes the development process of Empower@Home, a web-delivered intervention for depression in homebound older adults that is based on cognitive behavioral therapy, and reports on the outcomes of usability studies. METHODS: Empower@Home was developed in collaboration with community agencies, stakeholders, and older adults, guided by user-centered design principles. User needs were assessed through secondary data analysis, demographic and health profiles from administrative data, and interviews and surveys of community partners. A comparative usability evaluation was conducted with 10 older adults to assess the usability of Empower@Home compared to 2 similar programs. Field testing was conducted with 4 end users to detect additional usability issues. RESULTS: Feedback and recommendations from community partners heavily influenced the content and design of Empower@Home. The intervention consists of 9 sessions, including psychoeducation and an introduction to cognitive behavioral therapy skills and tools through short video clips, in-session exercises, an animated storyline, and weekly out-of-session home practice. A printed workbook accompanies the web-based lessons. In comparative usability testing (N=10), Empower@Home received a System Usability Scale score of 78 (SD 7.4), which was significantly higher than the 2 comparator programs (t9=3.28; P=.005 and t9=2.78; P=.011). Most participants, 80% (n=8), preferred Empower@Home over the comparators. In the longitudinal field test (n=4), all participants reported liking the program procedures and feeling confident in performing program-related tasks. The single-subject line graph showed an overall downward trend in their depression scores over time, offering an encouraging indication of the intervention's potential effects. CONCLUSIONS: Collaboration with community stakeholders and careful consideration of potential implementation issues during the design process can result in more usable, engaging, and effective digital mental health interventions.

Modern Senicide in the Face of a Pandemic: An Examination of Public Discourse and Sentiment About Older Adults and COVID-19 Using Machine Learning.

OBJECTIVES: This study examined public discourse and sentiment regarding older adults and COVID-19 on social media and assessed the extent of ageism in public discourse. METHODS: Twitter data (N = 82,893) related to both older adults and COVID-19 and dated from January 23 to May 20, 2020, were analyzed. We used a combination of data science methods (including supervised machine learning, topic modeling, and sentiment analysis), qualitative thematic analysis, and conventional statistics. RESULTS: The most common category in the coded tweets was "personal opinions" (66.2%), followed by "informative" (24.7%), "jokes/ridicule" (4.8%), and "personal experiences" (4.3%). The daily average of ageist content was 18%, with the highest of 52.8% on March 11, 2020. Specifically, more than 1 in 10 (11.5%) tweets implied that the life of older adults is less valuable or downplayed the pandemic because it mostly harms older adults. A small proportion (4.6%) explicitly supported the idea of just isolating older adults. Almost three-quarters (72.9%) within "jokes/ridicule" targeted older adults, half of which were "death jokes." Also, 14 themes were extracted, such as perceptions of lockdown and risk. A bivariate Granger causality test suggested that informative tweets regarding at-risk populations increased the prevalence of tweets that downplayed the pandemic. DISCUSSION: Ageist content in the context of COVID-19 was prevalent on Twitter. Information about COVID-19 on Twitter influenced public perceptions of risk and acceptable ways of controlling the pandemic. Public education on the risk of severe illness is needed to correct misperceptions.

Refractive Guide Switching a Regenerative Amplifier Free-Electron Laser for High Peak and Average Power Hard X Rays.

We present an x-ray regenerative amplifier free-electron laser design capable of producing fully coherent hard x-ray pulses across a broad tuning range at a high steady state repetition rate. The scheme leverages a strong undulator taper and an apertured diamond output-coupling cavity crystal to produce both high peak and average spectral brightness radiation that is 2 to 3 orders of magnitude greater than conventional single-pass self-amplified spontaneous emission free-electron laser amplifiers. Refractive guiding in the postsaturation regime is found to play a key role in passively controlling the stored cavity power. The scheme is explored both analytically and numerically in the context of the Linac Coherent Light Source II High Energy upgrade.