An Unguided, Computerized Cognitive Behavioral Therapy Intervention (TreadWill) in a Lower Middle-Income Country: Pragmatic Randomized Controlled Trial.

BACKGROUND: Globally, most individuals who are susceptible to depression do not receive adequate or timely treatment. Unguided computerized cognitive behavioral therapy (cCBT) has the potential to bridge this treatment gap. However, the real-world effectiveness of unguided cCBT interventions, particularly in low- and middle-income countries (LMICs), remains inconclusive. OBJECTIVE: In this study, we aimed to report the design and development of a new unguided cCBT-based multicomponent intervention, TreadWill, and its pragmatic evaluation. TreadWill was designed to be fully automated, engaging, easy to use, and accessible to LMICs. METHODS: To evaluate the effectiveness of TreadWill and the engagement level, we performed a double-blind, fully remote, and randomized controlled trial with 598 participants in India and analyzed the data using a completer's analysis. RESULTS: The users who completed at least half of the modules in TreadWill showed significant reduction in depression-related (P=.04) and anxiety-related (P=.02) symptoms compared with the waitlist control. Compared with a plain-text version with the same therapeutic content, the full-featured version of TreadWill showed significantly higher engagement (P=.01). CONCLUSIONS: Our study provides a new resource and evidence for the use of unguided cCBT as a scalable intervention in LMICs. TRIAL REGISTRATION: ClinicalTrials.gov NCT03445598; https://clinicaltrials.gov/ct2/show/NCT03445598.

Mosquito Olfactory Response Ensemble enables pattern discovery by curating a behavioral and electrophysiological response database.

Many experimental studies have examined behavioral and electrophysiological responses of mosquitoes to odors. However, the differences across studies in data collection, processing, and reporting make it difficult to perform large-scale analyses combining data from multiple studies. Here we extract and standardize data for 12 mosquito species, along with Drosophila melanogaster for comparison, from over 170 studies and curate the Mosquito Olfactory Response Ensemble (MORE), publicly available at https://neuralsystems.github.io/MORE. We demonstrate the ability of MORE in generating biological insights by finding patterns across studies. Our analyses reveal that ORs are tuned to specific ranges of several physicochemical properties of odorants; the empty-neuron recording technique for measuring OR responses is more sensitive than the Xenopus oocyte technique; there are systematic differences in the behavioral preferences reported by different types of assays; and odorants tend to become less attractive or more aversive at higher concentrations.