Nilam Ram studies the dynamic interplay of psychological and media processes and how they change from moment-to-moment and across the life span.
Nilam’s research grows out of a history of studying change. After completing his undergraduate study of economics, he worked as a currency trader, frantically tracking and trying to predict the movement of world markets as they jerked up, down and sideways. Later, he moved on to the study of human movement, kinesiology, and eventually psychological processes - with a specialization in longitudinal research methodology. Generally, Nilam studies how short-term changes (e.g., processes such as learning, information processing, emotion regulation, etc.) develop across the life span, and how longitudinal study designs contribute to generation of new knowledge. Current projects include examinations of age-related change in children’s self- and emotion-regulation; patterns in minute-to-minute and day-to-day progression of adolescents’ and adults’ emotions; and change in contextual influences on well-being during old age. He is developing a variety of study paradigms that use recent developments in data science and the intensive data streams arriving from social media, mobile sensors, and smartphones to study change at multiple time scales.
- Journalism Thesis
COMM 289P (Win)
- Longitudinal Data Analysis in Social Science Research
COMM 365 (Win)
- Measurement and the Study of Change in Social Science Research
PSYCH 262 (Spr)
- Independent Studies (4)
Doctoral Dissertation Reader (AC)
The Idiosyncrasies of Everyday Digital Lives: Using the Human Screenome Project to Study User Behavior on Smartphones.
Computers in human behavior
Most methods used to make theory-relevant observations of technology use rely on self-report or application logging data where individuals' digital experiences are purposively summarized into aggregates meant to describe how the average individual engages with broadly defined segments of content. This aggregation and averaging masks heterogeneity in how and when individuals actually engage with their technology. In this study, we use screenshots (N > 6 million) collected every five seconds that were sequenced and processed using text and image extraction tools into content-, context-, and temporally-informative "screenomes" from 132 smartphone users over several weeks to examine individuals' digital experiences. Analyses of screenomes highlight extreme between-person and within-person heterogeneity in how individuals switch among and titrate their engagement with different content. Our simple quantifications of textual and graphical content and flow throughout the day illustrate the value screenomes have for the study of individuals' smartphone use and the cognitive and psychological processes that drive use. We demonstrate how temporal, textual, graphical, and topical features of people's smartphone screens can lay the foundation for expanding the Human Screenome Project with full-scale mining that will inform researchers' knowledge of digital life.
View details for DOI 10.1016/j.chb.2020.106570
View details for PubMedID 33041494
View details for PubMedCentralID PMC7543997
- Time for the Human Screenome Project NATURE 2020; 577 (7790): 314–17
Screenomics: A New Approach for Observing and Studying Individuals' Digital Lives.
Journal of adolescent research
2020; 35 (1): 16–50
This study describes when and how adolescents engage with their fast-moving and dynamic digital environment as they go about their daily lives. We illustrate a new approach - screenomics - for capturing, visualizing, and analyzing screenomes, the record of individuals' day-to-day digital experiences.Over 500,000 smartphone screenshots provided by four Latino/Hispanic youth, age 14-15 years, from low-income, racial/ethnic minority neighborhoods.Screenomes collected from smartphones for one to three months, as sequences of smartphone screenshots obtained every five seconds that the device is activated, are analyzed using computational machinery for processing images and text, machine learning algorithms, human-labeling, and qualitative inquiry.Adolescents' digital lives differ substantially across persons, days, hours, and minutes. Screenomes highlight the extent of switching among multiple applications, and how each adolescent is exposed to different content at different times for different durations - with apps, food-related content, and sentiment as illustrative examples.We propose that the screenome provides the fine granularity of data needed to study individuals' digital lives, for testing existing theories about media use, and for generation of new theory about the interplay between digital media and development.
View details for DOI 10.1177/0743558419883362
View details for PubMedID 32161431
View details for PubMedCentralID PMC7065687
- Using Screenshots to Predict Task Switching on Smartphones ASSOC COMPUTING MACHINERY. 2019
- Text Extraction and Retrieval from Smartphone Screenshots: Building a Repository for Life in Media ASSOC COMPUTING MACHINERY. 2018: 948–55
Emotional Experience Improves With Age: Evidence Based on Over 10 Years of Experience Sampling
PSYCHOLOGY AND AGING
2011; 26 (1): 21-33
Recent evidence suggests that emotional well-being improves from early adulthood to old age. This study used experience-sampling to examine the developmental course of emotional experience in a representative sample of adults spanning early to very late adulthood. Participants (N = 184, Wave 1; N = 191, Wave 2; N = 178, Wave 3) reported their emotional states at five randomly selected times each day for a one week period. Using a measurement burst design, the one-week sampling procedure was repeated five and then ten years later. Cross-sectional and growth curve analyses indicate that aging is associated with more positive overall emotional well-being, with greater emotional stability and with more complexity (as evidenced by greater co-occurrence of positive and negative emotions). These findings remained robust after accounting for other variables that may be related to emotional experience (personality, verbal fluency, physical health, and demographic variables). Finally, emotional experience predicted mortality; controlling for age, sex, and ethnicity, individuals who experienced relatively more positive than negative emotions in everyday life were more likely to have survived over a 13 year period. Findings are discussed in the theoretical context of socioemotional selectivity theory.
View details for DOI 10.1037/a0021285
View details for Web of Science ID 000288590800003
View details for PubMedID 20973600
View details for PubMedCentralID PMC3332527
Sociohistorical Change in Urban Older Adults' Perceived Speed of Time and Time Pressure.
The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVES: Perceptions of time are shaped by sociohistorical factors. Specifically, economic growth and modernization often engender a sense of acceleration. Research has primarily focused on one time perception dimension (perceived time pressure) in one subpopulation (working-age adults), but it is not clear whether historical changes extend to other dimensions (e.g., perceived speed of time) and other subpopulations, such as older adults who are no longer in the workforce and experience age-related shifts in time perception. We therefore examined sociohistorical and age-related trends in two dimensions of time perception in two cohorts of urban older adults.METHOD: Using propensity score matching for age and education, samples were drawn from the Berlin Aging Study (1990-1993, n = 256, Mage = 77.49) and the Berlin Aging Study-II (2009-2014, n = 248, Mage = 77.49). Cohort differences in means, variances, covariance, and correlates of perceived speed of time and time pressure were examined using multigroup SEM.RESULTS: There were no cohort differences in the perceived speed of time, but later-born cohorts reported more time pressure than earlier-born cohorts. There were no significant age differences, but perceptions of speed of time were more heterogeneous in the 1990s than in the 2010s. Cohorts did not differ in how time perceptions were associated with sociodemographic, health, cognitive, and psychosocial correlates.DISCUSSION: These findings document sociohistorical trends toward greater perceived time pressure and reduced heterogeneity in perceived speed of time among later-born urban adults. Conceptualizations of social acceleration should thus consider the whole adult life span.
View details for DOI 10.1093/geronb/gbab094
View details for PubMedID 34180501
Describing and Controlling Multivariate Nonlinear Dynamics: A Boolean Network Approach.
Multivariate behavioral research
We introduce a discrete-time dynamical system method, the Boolean network method, that may be useful for modeling, studying, and controlling nonlinear dynamics in multivariate systems, particularly when binary time-series are available. We introduce the method in three steps: inference of the temporal relations as Boolean functions, extraction of attractors and assignment of desirability based on domain knowledge, and design of network control to direct a psychological system toward a desired attractor. To demonstrate how the Boolean network can describe and prescribe control for emotion regulation dynamics, we applied this method to data from a study of how children use bidding to an adult and/or distraction to regulate their anger during a frustrating task (N=120, T=480seconds). Network control strategies were designed to move the child into attractors where anger is OFF. The sample shows heterogeneous emotion regulation dynamics across children in 22 distinct Boolean networks, and heterogeneous control strategies regarding which behavior to perturb and how to perturb it. The Boolean network method provides a novel method to describe nonlinear dynamics in multivariate psychological systems and is a method with potential to eventually inform the design of interventions that can guide those systems toward desired goals.
View details for DOI 10.1080/00273171.2021.1911772
View details for PubMedID 33874843
Concordance of mother-child respiratory sinus arrythmia is continually moderated by dynamic changes in emotional content of film stimuli.
Evidence suggests that concordance between parent and child physiological states is an important marker of interpersonal interaction. However, studies have focused on individual differences in concordance, and we have limited understanding of how physiological concordance may vary dynamically based on the situational context. We examined whether mother-child physiological concordance is moderated by dynamic changes in emotional content of a film clip they viewed together. Second-by-second estimates of respiratory sinus arrythmia were obtained from mothers and children (N=158, Mchild age = 45.16 months) as they viewed a chase scene from a children's film. In addition, the film clip's negative emotional content was rated second-by-second. Results showed that mother-child dyads displayed positive physiological concordance only in seconds when there was an increase in the clip's negative emotional content. Thus, dynamic changes in mother-child physiological concordance may indicate dyadic responses to challenge.
View details for DOI 10.1016/j.biopsycho.2021.108053
View details for PubMedID 33617928
Dyadic analysis and the reciprocal one-with-many model: Extending the study of interpersonal processes with intensive longitudinal data.
Newly available data streams from experience sampling studies and social media are providing new opportunities to study individuals' dyadic relations. The "one-with-many" (OWM) model (Kenny et al., 2006; Kenny & Winquist, 2001) was specifically constructed for and is used to examine features of multiple dyadic relationships that one set of focal persons (e.g., therapists, physicians) has with others (e.g., multiple clients, multiple patients). Originally, the OWM model was constructed for and applied to cross-sectional data. However, the model can be extended to accommodate and may be particularly useful for the analysis of intensive repeated measures data now being obtained through experience sampling and social media. This article (a) provides a practical tutorial on fitting the OWM model, (b) describes how the OWM model is extended for analysis of repeated measures data, and (c) illustrates application of the OWM model using reports about interpersonal behavior and benefits individuals experienced in 64,111 social interactions during 9 weeks of study (N = 150). Our presentation highlights the utility of the OWM model for examining interpersonal processes in everyday life. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
View details for DOI 10.1037/met0000380
View details for PubMedID 33475420
Screenomics: A Framework to Capture and Analyze Personal Life Experiences and the Ways that Technology Shapes Them.
2021; 36 (2): 150–201
Digital experiences capture an increasingly large part of life, making them a preferred, if not required, method to describe and theorize about human behavior. Digital media also shape behavior by enabling people to switch between different content easily, and create unique threads of experiences that pass quickly through numerous information categories. Current methods of recording digital experiences provide only partial reconstructions of digital lives that weave - often within seconds - among multiple applications, locations, functions and media. We describe an end-to-end system for capturing and analyzing the "screenome" of life in media, i.e., the record of individual experiences represented as a sequence of screens that people view and interact with over time. The system includes software that collects screenshots, extracts text and images, and allows searching of a screenshot database. We discuss how the system can be used to elaborate current theories about psychological processing of technology, and suggest new theoretical questions that are enabled by multiple time scale analyses. Capabilities of the system are highlighted with eight research examples that analyze screens from adults who have generated data within the system. We end with a discussion of future uses, limitations, theory and privacy.
View details for DOI 10.1080/07370024.2019.1578652
View details for PubMedID 33867652
View details for PubMedCentralID PMC8045984
Political context is associated with everyday cortisol synchrony in older couples.
2020; 124: 105082
Prior research with predominantly younger to middle-aged samples has demonstrated that couples' cortisol levels covary throughout the day (cortisol synchrony). Not much is known about cortisol synchrony in old age, and its potential broader societal correlates. The current study investigates associations between the socio-political context and cortisol synchrony as observed in older couples' daily lives. 160 older German couples (Mage =72 years, range: 56-89) provided salivary cortisol samples 7 times daily for a 7-day period. Socio-political context was quantified using state-specific voting data from the 2017 German federal election along the left-right political spectrum. Multilevel models controlling for diurnal cortisol rhythm, food intake, sex, age, body mass index, education, and individual-level political orientation revealed evidence for synchrony in partners' cortisol fluctuations (b=0.03, p<.001). The extent of cortisol synchrony was moderated by left-right political context, such that older couples living in a federal state placed further right exhibited greater cortisol synchrony than couples living in a federal state placed further left (b=0.01, p=.015). Findings point to the importance of considering the socio-political context of health-relevant biopsychosocial dynamics in old age. Future research needs to investigate mechanisms underlying such associations, including how politics shape opportunities and motivation for interdependencies that promote better or worse health.
View details for DOI 10.1016/j.psyneuen.2020.105082
View details for PubMedID 33316693
In-Person Contacts and Their Relationship With Alcohol Consumption Among Young Adults With Hazardous Drinking During a Pandemic.
The Journal of adolescent health : official publication of the Society for Adolescent Medicine
PURPOSE: Social distancing strategies such as "stay-at-home" (SAH) orders can slow the transmission of contagious viruses like the SARS-CoV-2 virus, but require population adherence to be effective. This study explored adherence to SAH orders by young adults with hazardous drinking, and the role of alcohol consumption with in-person contacts on adherence.METHODS: Analyses included young adults with hazardous drinking (i.e., AUDIT-C score ≥3/4 for women/men; n= 50; ages 18-25) participating in a randomized trial in Pittsburgh, PA. Participants provided experience sampling reports on drinking twice per week from the week before SAH orders started on April 1, 2020 through 6weeks during the SAH period. We examined how in-person contact with non-household friends changed over time and event-level relationships between alcohol consumption and in-person contacts.RESULTS: The percentage of participants with any in-person contact in the week before SAH was 44% (95% confidence interval [CI] 30%-59%), which decreased to 29% (95% CI 15%-43%) in the first SAH week and increased to 65% (95% CI 46%-85%) by SAH week 6. Controlling for average levels of alcohol consumption, on days when young adults drank, participants reported more in-person contacts compared to nondrinking days.CONCLUSIONS: Preliminary data indicate that, among young adults with hazardous drinking, adherence to public policies like SAH orders is suboptimal, declines over time, and is associated with drinking events. Interventions aimed at enhancing young adults' adherence to social distancing policies are urgently needed.
View details for DOI 10.1016/j.jadohealth.2020.08.007
View details for PubMedID 32943290
- Discovering the Fabric of Supportive Conversations: A Typology of Speaking Turns and Their Contingencies JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY 2020
- Rollman and Brent: Phonotype. Journal of general internal medicine 2020
#Science: The potential and the challenges of utilizing social media and other electronic communication platforms in health care.
Clinical and translational science
Electronic communication is becoming increasingly popular worldwide, as evidenced by its widespread and rapidly growing use. In medicine however, it remains a novel approach to reach out to patients. Yet, they have the potential for further improving current health care. Electronic platforms could support therapy adherence and communication between physicians and patients. The power of social media as well as other electronic devices can improve adherence as evidenced by the development of the app bant. Additionally, systemic analysis of social media content by Screenome can identify health events not always captured by regular health care. By better identifying these health care events we can improve our current health care system as we will be able to better tailor to the patients' needs. All these techniques are a valuable component of modern health care and will help us into the future of increasingly digital health care. This article is protected by copyright. All rights reserved.
View details for DOI 10.1111/cts.12687
View details for PubMedID 31392837
Screenomics: a framework to capture and analyze personal life experiences and the ways that technology shapes them
View details for DOI 10.1080/07370024.2019.1578652
Daily Actigraphy Profiles Distinguish Depressive and Interepisode States in Bipolar Disorder
Clinical Psychological Science
2016; 4 (4): 641– 650
Disruptions in activity are core features of mood states in bipolar disorder (BD). This study sought to identify activity patterns that discriminate between mood states in BD. Locomotor activity was collected using actigraphy for six weeks in participants with inter-episode BD type I (n=37) or participants with no lifetime mood disorders (n=39). The 24-hour activity pattern of each participant-day was characterized and within-person differences in activity patterns were examined across mood states. Results show that among participants with BD, depressive days are distinguished from other mood states by an overall lower activity level, and a pattern of later activity onset, a midday elevation of activity, and low evening activity. No distinct within-person activity patterns were found for hypomanic/manic days. Since activity can be monitored non-invasively for extended time periods, activity pattern identification may be leveraged to detect mood states in BD, thereby providing more immediate delivery of care.
View details for DOI 10.1177/2167702615604613
View details for PubMedCentralID PMC5022043