The Effect of Moderation on Online Mental Health Conversations

Many people struggling with mental health issues are unable to access adequate care due to high costs and a shortage of mental health professionals, leading to a global mental health crisis. Online mental health communities can help mitigate this crisis by offering a scalable, easily accessible alternative to in-person sessions with therapists or support groups. However, people seeking emotional or psychological support online may be especially vulnerable to the kinds of antisocial behavior that sometimes occur in online discussions. Moderation can improve online discourse quality, but we lack an understanding of its effects on online mental health conversations. In this work, we leveraged a natural experiment, occurring across 200,000 messages from 7,000 conversations hosted on a mental health mobile application, to evaluate the effects of moderation on online mental health discussions. We found that participation in group mental health discussions led to improvements in psychological perspective, and that these improvements were larger in moderated conversations. The presence of a moderator increased user engagement, encouraged users to discuss negative emotions more candidly, and dramatically reduced bad behavior among chat participants. Moderation also encouraged stronger linguistic coordination, which is indicative of trust building. In addition, moderators who remained active in conversations were especially successful in keeping conversations on topic. Our findings suggest that moderation can serve as a valuable tool to improve the efficacy and safety of online mental health conversations. Based on these findings, we discuss implications and trade-offs involved in designing effective online spaces for mental health support.Comment: Accepted as a full paper at ICWSM 2021. 13 pages, 12 figures, 3 table

Beyond Summarization: Designing AI Support for Real-World Expository Writing Tasks

Large language models have introduced exciting new opportunities and challenges in designing and developing new AI-assisted writing support tools. Recent work has shown that leveraging this new technology can transform writing in many scenarios such as ideation during creative writing, editing support, and summarization. However, AI-supported expository writing--including real-world tasks like scholars writing literature reviews or doctors writing progress notes--is relatively understudied. In this position paper, we argue that developing AI supports for expository writing has unique and exciting research challenges and can lead to high real-world impacts. We characterize expository writing as evidence-based and knowledge-generating: it contains summaries of external documents as well as new information or knowledge. It can be seen as the product of authors' sensemaking process over a set of source documents, and the interplay between reading, reflection, and writing opens up new opportunities for designing AI support. We sketch three components for AI support design and discuss considerations for future research.Comment: 3 pages, 1 figure, accepted by The Second Workshop on Intelligent and Interactive Writing Assistant

The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces

Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the need for new technology to support the reading process grows. In contrast to the process of finding papers, which has been transformed by Internet technology, the experience of reading research papers has changed little in decades. The PDF format for sharing research papers is widely used due to its portability, but it has significant downsides including: static content, poor accessibility for low-vision readers, and difficulty reading on mobile devices. This paper explores the question "Can recent advances in AI and HCI power intelligent, interactive, and accessible reading interfaces -- even for legacy PDFs?" We describe the Semantic Reader Project, a collaborative effort across multiple institutions to explore automatic creation of dynamic reading interfaces for research papers. Through this project, we've developed ten research prototype interfaces and conducted usability studies with more than 300 participants and real-world users showing improved reading experiences for scholars. We've also released a production reading interface for research papers that will incorporate the best features as they mature. We structure this paper around challenges scholars and the public face when reading research papers -- Discovery, Efficiency, Comprehension, Synthesis, and Accessibility -- and present an overview of our progress and remaining open challenges

Language as Design: Adapting Language to Different Online Audiences

Thesis (Ph.D.)--University of Washington, 2022One of our most powerful language capabilities is our ability to adapt written and spoken language use to different audiences (sometimes referred to as audience design or linguistic accommodation). How we explain a topic to a fifth grader differs from how we explain it to a college student, or how we write about it in a paper. Targeting language messages to different receivers enriches and empowers our communication. However, as online audiences expand in size and demographics, it becomes increasingly difficult to adapt to all potential receivers. Though research papers, news articles, legal documents and social media posts proliferate on the internet, much of their language appeals to an ever-narrowing audience segment. New techniques in natural language processing (NLP) have the potential to make such language adaptation automatic. However, developing systems that effectively rewrite language require an understanding of what language is important to change. In this thesis, we show that language style changes, similar to other interface design changes, influence user behavior and introduce automated systems that design language for different people. We begin by focusing the study of language style changes to the subreddit r/science and show how language in it is associated with changes in people's behavior, potentially restricting access to scientific information. To understand what language is important to change when adapting to different people, we investigate how experts design scientific language for a general audience. We take inspiration from these expert strategies to build Paper Plain – a reading interface for making medical research papers approachable to a general audience. To adjust language to finer-grained audiences, we investigate how people respond to levels of language complexity based on their background knowledge and develop a novel controllable generation method to adjust the complexity of generated summaries. In two user studies we observed that generated summaries using our method leads to similar reader responses as with expert summaries, establishing the feasibility of generating summaries with varying complexities. Our work provides guidance on designing language for specific audiences and adaptable communication at scale. We conclude with a summary of the contributions and a discussion of future research on designing language to encourage better communication online

Children's Oncology Group Trial AALL1231: A Phase III Clinical Trial Testing Bortezomib in Newly Diagnosed T-Cell Acute Lymphoblastic Leukemia and Lymphoma

PurposeTo improve the outcomes of patients with T-cell acute lymphoblastic leukemia (T-ALL) and lymphoblastic lymphoma (T-LL), the proteasome inhibitor bortezomib was examined in the Children's Oncology Group phase III clinical trial AALL1231, which also attempted to reduce the use of prophylactic cranial radiation (CRT) in newly diagnosed T-ALL.Patients and methodsChildren and young adults with T-ALL/T-LL were randomly assigned to a modified augmented Berlin-Frankfurt-Münster chemotherapy regimen with/without bortezomib during induction and delayed intensification. Multiple modifications were made to the augmented Berlin-Frankfurt-Münster backbone used in the predecessor trial, AALL0434, including using dexamethasone instead of prednisone and adding two extra doses of pegaspargase in an attempt to eliminate CRT in most patients.ResultsAALL1231 accrued 824 eligible and evaluable patients from 2014 to 2017. The 4-year event-free survival (EFS) and overall survival (OS) for arm A (no bortezomib) versus arm B (bortezomib) were 80.1% ± 2.3% versus 83.8% ± 2.1% (EFS, P = .131) and 85.7% ± 2.0% versus 88.3% ± 1.8% (OS, P = .085). Patients with T-LL had improved EFS and OS with bortezomib: 4-year EFS (76.5% ± 5.1% v 86.4% ± 4.0%; P = .041); and 4-year OS (78.3% ± 4.9% v 89.5% ± 3.6%; P = .009). No excess toxicity was seen with bortezomib. In AALL0434, 90.8% of patients with T-ALL received CRT. In AALL1231, 9.5% of patients were scheduled to receive CRT. Evaluation of comparable AALL0434 patients who received CRT and AALL1231 patients who did not receive CRT demonstrated no statistical differences in EFS (P = .412) and OS (P = .600).ConclusionPatients with T-LL had significantly improved EFS and OS with bortezomib on the AALL1231 backbone. Systemic therapy intensification allowed elimination of CRT in more than 90% of patients with T-ALL without excess relapse