About

Mark C. Pachucki is a sociologist affiliated with the Department of Sociology at the University of Massachusetts Amherst. His research investigates phenomena at the intersection of social determinants of health, social network dynamics, and culture. He employs perspectives from computational social science to better understand how the structure and meanings of relationships influence individuals' health behaviors, social status, and disparities at both interpersonal and population levels. Pachucki was trained under an interdisciplinary social science model that emphasizes a 'right to health' and considers many of the cumulative disadvantages arising from intersecting group-based differences as unjust and avoidable.

Research topics

• Psychology
• Medicine
• Demography
• Sociology
• Gerontology

Selected publications

• Network threats to causal inference: Variations in network position by participation in randomized controlled trials

  Social Networks · 2026-03-28

  articleOpen access

  Researchers and practitioners rely on randomized controlled trials (RCTs) to make causal inferences. However, most people who participate in RCTs are part of multiple, overlapping social networks that shape their behaviors and attitudes. As a result, variations in trial participants’ and non-participants’ network positions may impede the generalizability of a RCT’s conclusions. The current project evaluates the extent and impact of these variations by comparing the network positions of RCT participants to RCT non-participants. As an informative case study, we considered a workplace-based RCT at a large hospital where a subset of employees was randomized to a healthy eating intervention or control group from 2016 to 2019. We constructed longitudinal social networks from data about employees’ cafeteria purchases and applied stochastic actor-oriented models (SAOMs) to determine whether RCT participants and non-participants occupied significantly different structural positions. Then, we performed a series of computational knockout experiments to assess whether the elimination of specific network-related phenomena impacted estimates of the intervention’s effect. Results suggest that RCT participants made cafeteria co-purchases with more of their colleagues than non-participants did. These differences downwardly biased estimates of the intervention’s impact, both with respect to the trial’s efficacy among participants and its expected effectiveness in the larger population of employees. • Limited research considers how variations in network position impact RCT findings • Focus on a healthy eating workplace-based intervention as a case study • Construct co-purchasing networks from employees’ cafeteria transactions • RCT participants are highly connected and there is homophily by RCT enrollment • Differences in network position impacted estimates of the intervention’s effect

  PublisherDOI

• Network threats to causal inference: Variations in network position by participation in randomized controlled trials

  CrimRxiv · 2026-04-07

  articleOpen access

  Researchers and practitioners rely on randomized controlled trials (RCTs) to make causal inferences. However, most people who participate in RCTs are part of multiple, overlapping social networks that shape their behaviors and attitudes. As a result, variations in trial participants’ and non-participants’ network positions may impede the generalizability of a RCT’s conclusions. The current project evaluates the extent and impact of these variations by comparing the network positions of RCT participants to RCT non-participants. As an informative case study, we considered a workplace-based RCT at a large hospital where a subset of employees was randomized to a healthy eating intervention or control group from 2016 to 2019. We constructed longitudinal social networks from data about employees’ cafeteria purchases and applied stochastic actor-oriented models (SAOMs) to determine whether RCT participants and non-participants occupied significantly different structural positions. Then, we performed a series of computational knockout experiments to assess whether the elimination of specific network-related phenomena impacted estimates of the intervention’s effect. Results suggest that RCT participants made cafeteria co-purchases with more of their colleagues than non-participants did. These differences downwardly biased estimates of the intervention’s impact, both with respect to the trial’s efficacy among participants and its expected effectiveness in the larger population of employees.

  PublisherOA PDFDOI

• Equitable Evaluation & Impact Statements

  ScholarWorks@UMassAmherst (University of Massachusetts Amherst) · 2025-01-01

  article

  As successive waves of disruption ripple through higher education, they generate disparate impacts on faculty work and careers. Equitable faculty evaluation requires attention to how unexpected disruptions affect the teaching, research, and service load and outcomes for differently situated faculty. This tool supports those involved in reading and reviewing faculty dossiers to use Impact Statements to support equitable faculty evaluation, to account for this information in a way that recognizes how each faculty member’s workload (how much they were doing in different areas) and work context (where and how they did their work) have differed. This allows the university to equitably evaluate faculty activity and achievements, deliver appropriate support, and plan for possible long-term effects.

  Publisher

• Systems science methods reveal and address links between discrimination and health disparities in US food systems

  Nature Food · 2025-09-15

  articleOpen access
  PublisherOA PDFDOI

• A participatory systems approach for visualizing and testing implementation strategies and mechanisms: evidence adoption in community coalitions

  Implementation Science Communications · 2025-10-01 · 9 citations

  articleOpen access

  BACKGROUND: The strengths of Implementation Science can be further enhanced by embracing methods that account for the complexity of real-world systems, complementing its existing focus on translating evidence into practice. Systems science offers an approach to understanding the interactions, feedback loops, and non-linear relationships that drive implementation processes. Despite its potential, practical examples of systems methods for designing and linking implementation strategies to mechanisms remain scarce. This case study demonstrates how systems methods can help operationalize implementation strategies and mechanisms within the context of a project called the Feasibility of Network Interventions for Coalition Adoption of Evidence-Informed Strategies initiative, which focuses on community coalitions advancing child health equity. METHODS: Using the Participatory Implementation Systems Mapping approach, the research team and a five-member Community Advisory Council engaged in a structured, four-stage process to identify system determinants, co-specify implementation strategies and mechanisms, and simulate dynamic behavior. Causal loop diagrams and stock-and-flow diagrams were developed to visualize relationships, inform strategy design, and test expected effects on knowledge, adoption, and coalition decision-making. RESULTS: The approach generated over 50 implementation determinants, organized into a coalition-focused conceptual systems framework (Stage 1); causal loop diagrams highlighting key feedback dynamics like knowledge diffusion and positive attitude toward evidence (Stage 2); and stock-and-flow diagrams translating five prioritized strategies into core system variables (Stage 3). Strategies, which included network weaving, informing local leaders, facilitating knowledge exchange, structured evidence review, and decision support tools, were operationalized with specific mechanisms (e.g., communication frequency, network density, perceived appropriateness). Simulations (Stage 4) showed that doubling review frequency increased knowledge by 17% but raised adoption by only 4% without complementary strategies. Adding decision support tools reduced time to reach adoption by 3 weeks, while introducing perceived relative advantage mid-simulation boosted adoption by 22%. Diffusion rates ranged from 0.02 to 0.08/week, moderated by social network quality. DISCUSSION: The study illustrates how systems science methods bridge qualitative insights with quantitative modeling to design and preliminarily test adaptive, contextually relevant implementation strategies. Visualizing feedback loops and representing relationships as stocks and flows provides a framework to assess how implementation strategies influence coalition processes and outcomes. The findings emphasize the importance of participatory processes to ensure strategies are practical and aligned with coalition priorities. Future work should focus on implementation, testing and scaling systems-based approaches to address implementation challenges.

  PublisherOA PDFDOI

• Disentangling associations between pubertal development, healthy activity behaviors, and sex in adolescent social networks

  PLoS ONE · 2024-05-16

  articleOpen access1st authorCorresponding

  With the onset of puberty, youth begin to choose their social environments and develop health-promoting habits, making it a vital period to study social and biological factors contextually. An important question is how pubertal development and behaviors such as physical activity and sleep may be differentially linked with youths' friendships. Cross-sectional statistical network models that account for interpersonal dependence were used to estimate associations between three measures of pubertal development and youth friendships at two large US schools drawn from the National Longitudinal Study of Adolescent to Adult Health. Whole-network models suggest that friendships are more likely between youth with similar levels of pubertal development, physical activity, and sleep. Sex-stratified models suggest that girls' friendships are more likely given a similar age at menarche. Attention to similar pubertal timing within friendship groups may offer inclusive opportunities for tailored developmental puberty education in ways that reduce stigma and improve health behaviors.

  PublisherOA PDFDOI

• Social isolation and depression as risk factors for weight loss of 5kg or more among older Korean adults

  PLoS ONE · 2024-03-13 · 11 citations

  articleOpen accessSenior authorCorresponding

  Given a well-known overlapping prevalence of social isolation with loneliness and depression among older adults, this study aimed to contextually investigate the relationship of these constructs with weight loss of more than 5kg in a year, with a special focus on the intersection of living alone and marital dissolution as key dimensions of isolation. The data were obtained from the Korean Longitudinal Study of Aging (KLoSA) from 2006, 2008, 2010, 2012, 2014, 2016, and 2018, with an adult sample of those aged 65 and older (n = 5,481). The study evaluated several critical dimensions of social isolation: living alone, transition to living alone, infrequent social contact with children or friends, and infrequent social participation. These dimensions were examined individually and as a composite scale, along with loneliness and depressive symptoms, to determine their association with weight loss of 5kg or greater among older men and women. Generalized Estimating Equation (GEE) regression models enabled investigation of whether socially isolated men and women tended to lose 5kg or more in weight, given other confounding factors. Surprisingly, the results showed no evidence of such a trend. However, significant associations were found between weight loss and changes in living alone and marital status. For older men, transitioning to living alone without a change in marital status was linked to significant weight loss. For older women, transitioning to living alone following widowhood or divorce was the risk factor. These relationships remained significant even after adjusting for depression and a wide range of covariates. Additional analysis testing a cumulative effect revealed that only depression was a risk factor for being underweight at the last observation. Therefore, to prevent a clinically risky extent of weight loss, health policies for older Koreans should focus on those who transition to living alone, especially due to spousal bereavement or divorce (among women) and separation from living with children (among men).

  PublisherOA PDFDOI

• Network spillover effects associated with the ChooseWell 365 workplace randomized controlled trial to promote healthy food choices

  Social Science & Medicine · 2024-06-27 · 2 citations

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• The Food, Activity, Screens, and Teens (FAST) Study; Design and protocol

  medRxiv · 2024-10-08

  preprintOpen access

  ABSTRACT The Food, Activity, Screens, and Teens (FAST) Study was a school-based prospective cohort study, aiming to identify mechanisms of peer influence on weight-related behaviors (WRBs) among early adolescents. In 2017-18, FAST investigators conducted focus group interviews and field observations of sixth grade students at four ethnoracially diverse urban middle schools, then administered pilot surveys in two of the schools. In Fall 2018, investigators recruited a cohort of sixth graders in the same four schools for a three-year panel study, with four waves per year. Each wave measured height and weight, demographic characteristics, WRBs (physical activity, screen time, and dietary patterns), classes and activities, and social networks among peers. Peer network measures included friendship, social sentiments (liking/disliking), online and face to face interaction, kinship, cohabiting, and shared WRBs. The pandemic school closure in March 2020 interrupted fieldwork after wave 6, and the next five waves employed online and mail surveys while schools operated remotely. In Spring 2022, after schools reopened, investigators followed a subset of students into high school to collect a twelfth wave of data.

  PublisherOA PDFDOI

• Determinants and facilitators of community coalition diffusion of prevention efforts

  PLOS complex systems. · 2024-09-03 · 5 citations

  articleOpen accessCorresponding

  This study examines how individual characteristics and network features of coalition participation in an intervention predict coalition members’ diffusion of Knowledge and Engagement in childhood obesity prevention. The study involved six communities in the U.S. measured across two to five time points from 2018 to 2021. Each community participated in the Stakeholder-driven Community Diffusion theory-informed intervention, a three-phase intervention that employs group model building and technical assistance with convened stakeholders to build Knowledge, Engagement, and utilize research evidence in community-led, childhood obesity prevention actions. Findings indicate that key individual-level characteristics (e.g., years of experience, gender, eigenvector centrality) and network-level features (e.g., hierarchy, clustering) are associated with higher increases in intervention outcomes of Knowledge and Engagement in childhood obesity prevention. We attend to issues of perceived influence and power in community coalitions, finding that younger, less experienced women who are not well connected to other well-connected coalition members experience smaller increases in intervention outcomes. Our discussion focuses on how individual- and network-level characteristics are associated with coalition support for evidence-based practice adoption and implementation.

  PublisherDOI

Recent grants

• Social Network Analysis of Puberty, Activity Behaviors, and Health Disparities

  NIH · $453k · 2018–2022

• A taste for tastes?The spread of food choices & health behaviors in networks

  NIH · $30k · 2009–2010

Frequent coauthors

• Matthew Harding

  University of California, Irvine

  16 shared

• Michał Stokłosa

  University of Illinois Chicago

  13 shared

• Christina D. Economos

  Tufts University

  13 shared

• Amy L. Yaroch

  13 shared

• Kerem Shuval

  Cooper Institute

  13 shared

• Jeffrey Drope

  Johns Hopkins University

  13 shared

• Erin Hennessy

  Tufts University

  11 shared

• Nicholas A. Christakis

  Yale University

  9 shared