Explore the vast range of titles available.

The 1997 Psychological Science paper “Writing About Emotional Experiences as a Therapeutic Process” summarized the results of several expressive writing studies. Since the publication of the first expressive writing study in 1986, a number of discoveries had emerged that had both theoretical and clinical implications. The scientific and personal backstories of the research are discussed. Finally, several possible reasons are advanced to explain why this particular paper has been cited as much as it has.

To date we know little about natural emotion word repertoires, and whether or how they are associated with emotional functioning. Principles from linguistics suggest that the richness or diversity of individuals’ actively used emotion vocabularies may correspond with their typical emotion experiences. The current investigation measures active emotion vocabularies in participant-generated natural speech and examined their relationships to individual differences in mood, personality, and physical and emotional well-being. Study 1 analyzes stream-of-consciousness essays by 1,567 college students. Study 2 analyzes public blogs written by over 35,000 individuals. The studies yield consistent findings that emotion vocabulary richness corresponds broadly with experience. Larger negative emotion vocabularies correlate with more psychological distress and poorer physical health. Larger positive emotion vocabularies correlate with higher well-being and better physical health. Findings support theories linking language use and development with lived experience and may have future clinical implications pending further research. Having a rich negative emotion vocabulary is assumed to help cope with adversity. Here, the authors show that emotion vocabularies simply mirror life experiences, with richer negative emotion vocabularies reflecting lower mental health, and richer positive emotion vocabularies reflecting higher mental health.

The smallest and most commonly used words in English are pronouns, articles, and other function words. Almost invisible to the reader or writer, function words can reveal ways people think and approach topics. A computerized text analysis of over 50,000 college admissions essays from more than 25,000 entering students found a coherent dimension of language use based on eight standard function word categories. The dimension, which reflected the degree students used categorical versus dynamic language, was analyzed to track college grades over students' four years of college. Higher grades were associated with greater article and preposition use, indicating categorical language (i.e., references to complexly organized objects and concepts). Lower grades were associated with greater use of auxiliary verbs, pronouns, adverbs, conjunctions, and negations, indicating more dynamic language (i.e., personal narratives). The links between the categorical-dynamic index (CDI) and academic performance hint at the cognitive styles rewarded by higher education institutions.

The mental health of college students is a growing concern, and gauging the mental health needs of college students is difficult to assess in real-time and in scale. To address this gap, researchers and practitioners have encouraged the use of passive technologies. Social media is one such \"passive sensor\" that has shown potential as a viable \"passive sensor\" of mental health. However, the construct validity and in-practice reliability of computational assessments of mental health constructs with social media data remain largely unexplored. Towards this goal, we study how assessing the mental health of college students using social media data correspond with ground-truth data of on-campus mental health consultations. For a large U.S. public university, we obtained ground-truth data of on-campus mental health consultations between 2011–2016, and collected 66,000 posts from the university’s Reddit community. We adopted machine learning and natural language methodologies to measure symptomatic mental health expressions of depression, anxiety, stress, suicidal ideation, and psychosis on the social media data. Seasonal auto-regressive integrated moving average (SARIMA) models of forecasting on-campus mental health consultations showed that incorporating social media data led to predictions with r = 0.86 and SMAPE = 13.30, outperforming models without social media data by 41%. Our language analyses revealed that social media discussions during high mental health consultations months consisted of discussions on academics and career, whereas months of low mental health consultations saliently show expressions of positive affect, collective identity, and socialization. This study reveals that social media data can improve our understanding of college students’ mental health, particularly their mental health treatment needs.

Previous relationship research has largely ignored the importance of similarity in how people talk with one another. Using natural language samples, we investigated whether similarity in dyads' use of function words, called language style matching (LSM), predicts outcomes for romantic relationships. In Study I, greater LSM in transcripts of 40 speed dates predicted increased likelihood of mutual romantic interest (odds ratio = 3.05). Overall, 33.3% of pairs with LSM above the median mutually desired future contact, compared with 9.1% of pairs with LSM at or below the median. In Study 2, LSM in 86 couples' instant messages positively predicted relationship stability at a 3-month follow-up (odds ratio = 1.95). Specifically, 76.7% of couples with LSM greater than the median were still dating at the follow-up, compared with 53.5% of couples with LSM at or below the median. LSM appears to reflect implicit interpersonal processes central to romantic relationships.

An in-class computer-based system, that included daily online testing, was introduced to two large university classes. We examined subsequent improvements in academic performance and reductions in the achievement gaps between lower- and upper-middle class students in academic performance. Students (N = 901) brought laptop computers to classes and took daily quizzes that provided immediate and personalized feedback. Student performance was compared with the same data for traditional classes taught previously by the same instructors (N = 935). Exam performance was approximately half a letter grade above previous semesters, based on comparisons of identical questions asked from earlier years. Students in the experimental classes performed better in other classes, both in the semester they took the course and in subsequent semester classes. The new system resulted in a 50% reduction in the achievement gap as measured by grades among students of different social classes. These findings suggest that frequent consequential quizzing should be used routinely in large lecture courses to improve performance in class and in other concurrent and subsequent courses.

This study uses a randomized controlled trial (RCT) to test the health benefits of expressive writing that is culturally adapted for Chinese immigrant breast cancer survivors (BCSs) and to characterize how acculturation moderates the effects of expressive writing interventions. We will recruit Chinese immigrant BCSs (N = 240) diagnosed with stage 0-III breast cancer and within 5 years of completion of primary treatment. Recruitment will occur primarily through community-based organizations and cancer registries. Participants will be randomly assigned either to a control condition to write about neutral topics or to one of two intervention conditions, self-regulation or self-cultivation, both of which aim to promote adaptive cognitive processes but differ in how they achieve this goal. The self-regulation intervention culturally adapts a Western expressive writing paradigm and incorporates emotional disclosure, whereas the self-cultivation intervention originates from Asian cultural values without disclosing emotions. Participants in all three conditions will be asked to write in their preferred language for three 30-minute sessions. The primary outcome will be quality of life (QOL) at the 6- and 12-month follow-ups, and the secondary outcomes will be perceived stress, stress biomarkers, and medical appointments for cancer-related morbidities. This project will be the first large RCT to test culturally based brief interventions to improve QOL and reduce stress among Chinese immigrant BCSs. This project is expected to address two important needs of Chinese immigrant BCSs: their unmet psychological needs and the lack of culturally competent mental health care for Chinese immigrant BCSs. The immediate product of this line of research will be empirically evaluated, culturally responsive interventions ready for dissemination to Chinese immigrant BCSs across the United States. NCT04754412.

The huge power for social influence of digital media may come with the risk of intensifying common societal biases, such as gender and age stereotypes. Speaker’s gender and age also behaviorally manifest in language use, and language may be a powerful tool to shape impact. The present study took the example of TED, a highly successful knowledge dissemination platform, to study online influence. Our goal was to investigate how gender- and age-linked language styles–beyond chronological age and identified gender–link to talk impact and whether this reflects gender and age stereotypes. In a pre-registered study, we collected transcripts of TED Talks along with their impact measures, i.e., views and ratios of positive and negative talk ratings, from the TED website. We scored TED Speakers’ ( N = 1,095) language with gender- and age-morphed language metrics to obtain measures of female versus male, and younger versus more senior language styles. Contrary to our expectations and to the literature on gender stereotypes, more female language was linked to higher impact in terms of quantity, i.e., more talk views, and this was particularly the case among talks with a lot of views. Regarding quality of impact, language signatures of gender and age predicted different types of positive and negative ratings above and beyond main effects of speaker’s gender and age. The differences in ratings seem to reflect common stereotype contents of warmth (e.g., “beautiful” for female, “courageous” for female and senior language) versus competence (e.g., “ingenious”, “informative” for male language). The results shed light on how verbal behavior may contribute to stereotypical evaluations. They also illuminate how, within new digital social contexts, female language might be uniquely rewarded and, thereby, an underappreciated but highly effective tool for social influence. WC = 286 (max . 300 words) .

College students' study strategies were explored by tracking the ways they navigated the websites of two large (Ns of 1384 and 671) online introductory psychology courses. Students' study patterns were measured analyzing the ways they clicked outside of the regularly scheduled class on study materials within the online Learning Management System. Three main effects emerged: studying course content materials (as opposed to course logistics materials) outside of class and higher grades are consistently correlated; studying at any time except in the late night/early morning hours was strongly correlated with grades; students with higher Scholastic Aptitude Test (SAT) scores made higher grades but accessed course materials at lower rates that those with lower SATs. Multiple regressions predicting grades using just SATs and click rates accounted for almost 43 and 36 percent of the grade variance for the Fall and Spring classes respectively. Implications for using click patterns to understand and shape student learning are discussed.

Using social media data, the present study documents how three successive upheavals: the COVID pandemic, the Black Lives Matter (BLM) protests of 2020, and the US Supreme Court decision to overturn Roe v. Wade interacted to impact the cognitive, emotional, and social styles of people in the US. Text analyses were conducted on 45,225,895 Reddit comments from 2,451,289 users and 889,402 news headlines from four news sources. Results revealed significant shifts in language related to self-focus (e.g., first-person singular pronouns), collective-focus (e.g., first-person plural pronouns), negative emotion (anxiety and anger words), and engagement (e.g., discussion of upheaval-related topics) after each event. Language analyses captured how social justice-related upheavals (BLM, Roe v. Wade) may have affected people in different ways emotionally than those that affected them personally (COVID). The onset of COVID was related to people becoming increasingly anxious and people turned inward to focus on their personal situations. However, BLM and the overturning of Roe v. Wade aroused anger and action, as people may have looked beyond themselves to address these issues. Analysis of upheaval-related discussions captured the public’s sustained interest in BLM and COVID, whereas interest in Roe v. Wade declined relatively quickly. Shifts in discussions also showed how events interacted as people focused on only one national event at a time, with interest in other events dampening when a new event occurred. The findings underscore the dynamic nature of culturally shared events that are apparent in everyday online language use.