Protocol for a randomized controlled trial comparing phone-based prenatal mindfulness training to usual care for pregnant people at risk for hypertensive disorders of pregnancy.

Hypertensive disorders of pregnancy (HDP) are the most common medical conditions in pregnancy and a leading cause of maternal morbidity and mortality in the United States. There are few interventions available to prevent HDP, and those currently available do not target underlying mechanisms of disease. Mindfulness training (MT) is effective at reducing blood pressure in non-pregnant patients with pre-hypertension and hypertension and has proven more effective at blood pressure reduction than other stress management interventions.

Predicting psychosocial intervention response from baseline gene expression.

To address the challenge of predicting psychological response to a psychosocial intervention we tested the possibility that baseline gene expression profiles might provide information above and beyond baseline psychometric measures. The genomics strategy utilized individual level inferences of transcription factor activity to predict changes in loneliness and affect in response to two well-established meditation interventions. Initial algorithm development analyses focused on three a-priori defined stress-related gene regulation pathways (CREB, GR, and NF-ĸB) as inferred from TELiS promoter-based bioinformatic analysis of basal (pre-intervention) blood samples from a randomized-controlled trial comparing a compassion-based meditation (CM, n = 45) with mindfulness meditation (MM, n = 44).

How ready is speech-to-text for psychological language research? Evaluating the validity of AI-generated English transcripts for analyzing free-spoken responses in younger and older adults.

For the longest time, the gold standard in preparing spoken language corpora for text analysis in psychology was using human transcription. However, such standard comes at extensive cost, and creates barriers to quantitative spoken language analysis that recent advances in speech-to-text technology could address. The current study quantifies the accuracy of AI-generated transcripts compared to human-corrected transcripts across younger (n = 100) and older (n = 92) adults and two spoken language tasks.

When I am sixty-four… evaluating language markers of well-being in healthy aging narratives.

Natural language use is a promising candidate for the development of innovative measures of well-being to complement self-report measures. The type of words individuals use can reveal important psychological processes that underlie well-being across the lifespan. In this preregistered, cross-sectional study, we propose a conceptual model of language markers of well-being and use written narratives about healthy aging (N = 701) and computerized text analysis (LIWC) to empirically validate the model.

Comparing the language style of heads of state in the US, UK, Germany and Switzerland during COVID-19.

The COVID-19 pandemic posed a global threat to nearly every society around the world. Individuals turned to their political leaders to safely guide them through this crisis. The most direct way political leaders communicated with their citizens was through official speeches and press conferences.

Harnessing Speech-Derived Digital Biomarkers to Detect and Quantify Cognitive Decline Severity in Older Adults.

Introduction: Current cognitive assessments suffer from floor/ceiling and practice effects, poor psychometric performance in mild cases, and repeated assessment effects. This study explores the use of digital speech analysis as an alternative tool for determining cognitive impairment. The study specifically focuses on identifying the digital speech biomarkers associated with cognitive impairment and its severity.

Diversity, equity, and inclusivity in observational ambulatory assessment: Recommendations from two decades of Electronically Activated Recorder (EAR) research.

Ambient audio sampling methods such as the Electronically Activated Recorder (EAR) have become increasingly prominent in clinical and social sciences research. These methods record snippets of naturalistically assessed audio from participants' daily lives, enabling novel observational research about the daily social interactions, identities, environments, behaviors, and speech of populations of interest. In practice, these scientific opportunities are equaled by methodological challenges: researchers' own cultural backgrounds and identities can easily and unknowingly permeate the collection, coding, analysis, and interpretation of social data from daily life.

Loneliness and social isolation are not associated with executive functioning in a cross-sectional study of cognitively healthy older adults.

The literature on the relationship between social interaction and executive functions (EF) in older age is mixed, perhaps stemming from differences in EF measures and the conceptualization/measurement of social interaction. We investigated the relationship between social interaction and EF in 102 cognitively unimpaired older adults (ages 65-90). Participants received an EF battery to measure working memory, inhibition, shifting, and global EF.

SocialBit: protocol for a prospective observational study to validate a wearable social sensor for stroke survivors with diverse neurological abilities.

Introduction: Social isolation has been found to be a significant risk factor for health outcomes, on par with traditional risk factors. This isolation is characterised by reduced social interactions, which can be detected acoustically. To accomplish this, we created a machine learning algorithm called SocialBit.

Sleep Efficiency and Naturalistically-Observed Social Behavior Following Marital Separation: The Critical Role of Contact with an Ex-partner.

Marital disruption is associated with increased risk for a range of poor health outcomes, including disturbed sleep. This report examines trajectories of actigraphy-assessed sleep efficiency following marital separation as well as the extent to which daily social behaviors and individual differences in attachment explain variability in these trajectories over time. One hundred twenty-two recently-separated adults ( = 122) were followed longitudinally for three assessment periods over five months.

Emotional change in its "natural habitat": Measuring everyday emotion regulation with passive and active ambulatory assessment methods.

Ambulatory assessment methods have made it possible to study psychological phenomena in real-time, with translational potential for psychotherapy process research. This article uses case example data to demonstrate applications of ambulatory assessment to measuring emotion regulation, a process with relevance across diagnoses and treatment modalities that may be particularly important to measure . Two methods are reviewed: Ecological Momentary Assessment (EMA), which enables self-reported momentary assessments as people go about their days, and the Electronically Activated Recorder (EAR), an unobtrusive naturalistic observation methodology that collects short audio recordings from participants' moment-to-moment environments, capturing an acoustic diary of their social interactions, daily behaviors, and natural daily language use.

The paucity of morality in everyday talk.

Given its centrality in scholarly and popular discourse, morality should be expected to figure prominently in everyday talk. We test this expectation by examining the frequency of moral content in three contexts, using three methods: (a) Participants' subjective frequency estimates (N = 581); (b) Human content analysis of unobtrusively recorded in-person interactions (N = 542 participants; n = 50,961 observations); and (c) Computational content analysis of Facebook posts (N = 3822 participants; n = 111,886 observations). In their self-reports, participants estimated that 21.

Discovery of associative patterns between workplace sound level and physiological wellbeing using wearable devices and empirical Bayes modeling.

We conducted a field study using multiple wearable devices on 231 federal office workers to assess the impact of the indoor environment on individual wellbeing. Past research has established that the workplace environment is closely tied to an individual's wellbeing. Since sound is the most-reported environmental factor causing stress and discomfort, we focus on quantifying its association with physiological wellbeing.

Spinning Your Wheels: Psychological Overinvolvement and Actigraphy-Assessed Sleep Efficiency Following Marital Separation.

Background: This study investigated the ways in which adults reflect on their psychological experiences amid a recent marital separation and how these patterns of thought, manifest in language, are associated with self-reported negative affect and actigraphy-assessed sleep disturbance.

Methods: In a sample of 138 recently separated adults assessed three times over five months, we examined within- and between-person associations among psychological overinvolvement (operationalized using verbal immediacy derived as a function of the language participants used to discuss their relationship history and divorce experience), continued attachment to an ex-partner, negative affect, and sleep efficiency.

Results: The association between psychological overinvolvement and negative affect operated at the within-person level, whereas the associations between psychological overinvolvement and sleep disturbance, as well as negative affect and sleep disturbance, operated at the between-person level.

Leveraging Social Networks for the Assessment and Management of Neurological Patients.

Social networks are the persons surrounding a patient who provide support, circulate information, and influence health behaviors. For patients seen by neurologists, social networks are one of the most proximate social determinants of health that are actually accessible to clinicians, compared with wider social forces such as structural inequalities. We can measure social networks and related phenomena of social connection using a growing set of scalable and quantitative tools increasing familiarity with social network effects and mechanisms.

Beyond English: Considering Language and Culture in Psychological Text Analysis.

The paper discusses the role of language and culture in the context of quantitative text analysis in psychological research. It reviews current automatic text analysis methods and approaches from the perspective of the unique challenges that can arise when going beyond the default English language. Special attention is paid to closed-vocabulary approaches and related methods (and Linguistic Inquiry and Word Count in particular), both from the perspective of cross-cultural research where the analytic process inherently consists of comparing phenomena across cultures and languages and the perspective of generalizability beyond the language and the cultural focus of the original investigation.

Predicting Working Memory in Healthy Older Adults Using Real-Life Language and Social Context Information: A Machine Learning Approach.

Background: Language use and social interactions have demonstrated a close relationship with cognitive measures. It is important to improve the understanding of language use and behavioral indicators from social context to study the early prediction of cognitive decline among healthy populations of older adults.

Objective: This study aimed at predicting an important cognitive ability, working memory, of 98 healthy older adults participating in a 4-day-long naturalistic observation study.

Investigating the Relationship between Resident Physician Implicit Bias and Language Use during a Clinical Encounter with Hispanic Patients.

Prior research suggests that the implicit biases of physicians are negatively associated with quality of medical care and patient satisfaction among minority patients. However, relatively little is known about how physicians express these subtle forms of bias in patient interactions. This study examined the implicit and explicit anti-Hispanic biases of 53 resident physicians and the relationship between anti-Hispanic bias and language use during outpatient medical appointments with 291 Hispanic patients.

Effect of Workstation Type on the Relationship Between Fatigue, Physical Activity, Stress, and Sleep.

Objective: This study examined office workstation types' impact on the relationship between fatigue and three health metrics: physical activity, stress, and sleep quality.

Methods: Data from 225 office workers were collected for perceived fatigue, perceived sleep quality (Pittsburgh Sleep Quality Index [PSQI]), physiological stress response (standard deviation of heart rate variability [HRV]), and physical activity (total activity in minutes) during three consecutive workdays. Stress and physical activity were measured using chest-worn sensors.

Deep multiple instance learning for foreground speech localization in ambient audio from wearable devices.

Over the recent years, machine learning techniques have been employed to produce state-of-the-art results in several audio related tasks. The success of these approaches has been largely due to access to large amounts of open-source datasets and enhancement of computational resources. However, a shortcoming of these methods is that they often fail to generalize well to tasks from real life scenarios, due to domain mismatch.

Stereotyping in the digital age: Male language is "ingenious", female language is "beautiful" - and popular.

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.