About

Nicola Dell is an associate professor of information science at Cornell Tech, the Jacobs Technion-Cornell Institute, and the Cornell Ann S. Bowers College of Computing and Information Science. She advises Ph.D. and M.S. students in the fields of information science and computer science. Her research focuses on human interaction, information communications technology for development, and computer security and privacy. Dell has published over 80 peer-reviewed conference and journal papers, mostly at top-tier venues such as CHI, CSCW, ICTD, COMPASS, IEEE S&P Oakland, and USENIX Security. Her work has received numerous Best Paper and Honorable Mention recognitions, and she is the recipient of an NSF CAREER Award, a SIGCHI Societal Impact Award, and the MacArthur Foundation fellowship. At Cornell, she co-founded and co-directs the Clinic to End Tech Abuse, serves as the director of technology innovation for the Initiative on Home Care Work in the Center for Applied Research on Work, and was the inaugural Siegel Faculty Impact Fellow in the Public Interest Technology Initiative at Cornell Tech in 2023.

Research topics

• Political Science
• Computer Science
• Computer Security
• Sociology
• Medicine
• Psychology
• Internet privacy
• Public relations
• Criminology
• Medical emergency
• Nursing
• Social Science
• Law
• Environmental health
• Engineering
• Management
• Virology
• Gerontology
• Data science
• Knowledge management
• Economic growth
• World Wide Web
• Internal medicine
• Business

Selected publications

• AI-Facilitated Coercive Control: An Experimental Study

  2026-04-13 · 1 citations

  articleOpen accessSenior author

  We present an experimental study that investigates how LLM-driven conversational AI tools might be weaponized to facilitate, exacerbate, or commoditize coercive control. Inspired by speculative design, we construct four scenarios that combine well-known coercive control tactics with the current capabilities of conversational AI tools. Then, we explore these scenarios via interactions with popular AI agents (ChatGPT, Gemini). We find that although AI tools refuse straightforward requests for harmful content, their guardrails can be circumvented via strategies such as gradual persuasion, splitting conversations, pre-prompting, and manipulating the AI agent’s settings. Collectively, these strategies enable AI agents to be leveraged in ways that facilitate harassment, intimidation, gaslighting, monitoring, surveillance, and other coercive control tactics. To make these tools safer for everyone, we discuss opportunities for AI agents to resist being abused for coercive control via analysis of users’ conversational patterns, and ensuring that pre-programmed settings are clearly visible to prevent covert manipulation.

  PublisherDOI

• Home health aides’ perspectives towards achieving cardiovascular health and life’s essential 8: a qualitative study

  BMC Public Health · 2026-03-26

  articleOpen access

  Despite frequently providing care to adults with cardiovascular (CV) disease in the home, home health aides and attendants (HHAs) have poor CV health (CVH) themselves, which is problematic for their own health and potentially their patients. We elicited the perspectives of HHAs towards achieving optimal CVH, including the American Heart Association’s (AHA’s) Life’s Essential 8 (LE8). We conducted focus groups and interviews with HHAs from January 2023 to January 2024 in partnership with the 1199SEIU Training and Employment Fund, a benefit fund of the largest healthcare union in the US. We included English-and Spanish-speaking HHAs at risk for poor CVH, defined as having: 1) hypertension, 2) obesity/overweight, and 3) ≥ 1 other CV disease risk factors (hyperlipidemia, diabetes, smoking, and physical inactivity). Twenty-two HHAs employed by 12 home care agencies participated. They had a median age of 60 years (IQR 50, 64), 21 (95%) were female, 9 (41%) were Black, and 12 (55%) were Latinx. Consistent with the Social-Ecological Model, 5 themes emerged. At the individual level, many HHAs were motivated to carry out aspects of the LE8 (diet, physical activity), but faced challenges doing so, including varied perceptions of the severity of their CVH and constraints of their job (e.g. limited time). At the interpersonal level, HHAs perceived that their relationship with their patients influenced their own CVH, as well as that of their patients’. At the organizational level, shift-work and long commutes were barriers to certain LE8 (i.e. sleep). Notably, HHAs sought community among peers to learn about CVH. Policies and structural inequities (health insurance, citizenship) were barriers to achieving CVH. HHAs’ ability to achieve CVH is likely influenced by personal, interpersonal, organizational, and policy-level factors. Findings can inform future interventions better tailored to this workforce and the context in which they provide care. Such interventions can aim to improve not only HHAs’ CVH, but potentially that of their patients.

  PublisherDOI

• Feasibility, Acceptability, and Perspectives Regarding the Use of Activity Tracking Wearable Devices Among Home Health Aides: Mixed Methods Study

  Journal of Medical Internet Research · 2026-01-26

  articleOpen access

  BACKGROUND: Home health aides and attendants (HHAs) provide in-home care to the growing population of older adults who want to age in place. Despite their vital role in patient care, HHAs are an underserved and vulnerable population of health care professionals who often experience poor health themselves. Activity tracking devices offer a promising way to improve HHAs' health-related awareness and promote health behavior change, particularly regarding physical activity and sleep quality, 2 areas in which the workforce struggles. OBJECTIVE: This study aimed to understand how feasible it is for HHAs to use activity tracking devices and assess their perceptions of such devices for improving their health. Specifically, we conducted (1) a field study to assess the use, feasibility, and acceptability of these devices among HHAs and (2) a qualitative study to understand HHAs' perspectives on and reactions to activity trackers on and off the job. METHODS: We partnered with the 1199 Service Employees International Union Training and Employment Fund to conduct a field study with home care agency-employed HHAs working in New York City, New York. Participants wore activity tracking devices for 4 weeks that collected data on physical activity and sleep. The HHAs were subsequently interviewed on their experiences with and attitudes toward the devices and asked to reflect on personalized visualizations of their data to prompt them to think aloud. Quantitative data were analyzed using descriptive statistics. Qualitative data were analyzed using grounded theory. RESULTS: A total of 17 HHAs participated; their mean age was 48.7 (SD 12.2) years, 15 (88%) were women, 11 (65%) identified as Black, 5 (29%) identified as Hispanic or Latinx, and they had worked as HHAs for a mean of 11.7 (SD 7.5) years. In total, 94% (n=16) of the HHAs wore their activity trackers for the full 28-day study period. Participants took a mean of 10,230 (SD 3586) daily steps during the study period and slept for a mean of 6.27 (SD 0.58) hours per night. Overall, 4 key themes emerged: (1) activity tracking devices enhanced participants' health awareness by providing empirical data for self-reflection; (2) this increased awareness led to positive behavior changes, including setting and achieving health-related goals; (3) HHAs believed that these devices could improve not only their own health but also that of their patients through positive behavior changes; and (4) despite this optimism, participants emphasized that their ability to modify sleep and activity patterns was constrained by social and occupational determinants, with sleep improvements being particularly challenging. CONCLUSIONS: Our findings suggest that appropriately designed personal tracking interventions could offer a promising approach to supporting positive health-related changes in this historically overlooked workforce, potentially improving their well-being and the quality of care they provide to their patients.

  PublisherDOI

• Sharing the Care: Investigating How Conversational AI Might Facilitate Coordination Among Home Care Workers and Family Caregivers

  2026-04-13 · 1 citations

  articleOpen accessSenior author

  This paper presents a qualitative study with 17 participants that uses video elicitations to investigate how conversational AI agents driven by large language models might support “shared care,” or coordination of home-based care among family caregivers (FCs) and home care workers (HCWs) who care for the same care recipient (CR). Participants saw conversational AI as a promising tool that might help streamline communication, coordinate shift handovers, bridge language gaps, and support onboarding of new or substitute caregivers. That said, caregivers assumed AI agents would inevitably make mistakes and should thus be designed to signal uncertainty and make it easy to report errors. More broadly, participants discussed how AI agents designed for sensitive home care contexts will need to explicitly preserve the human essence of care, minimize extra data work that might distract from caregiving, and always complement—not replace—human judgment.

  PublisherDOI

• Home Health Aides Caring for Adults With Heart Failure

  JAMA Network Open · 2025-11-10 · 2 citations

  articleOpen access

  Importance: Home health aides (HHAs) frequently care for adults with heart failure (HF), but many lack HF training, confidence with HF caregiving, and cannot reach their nurse supervisors by telephone when they need guidance. This may have negative consequences for HHAs and patients. Objective: To examine the effectiveness of an education- and communication-based intervention among HHAs caring for patients with HF. Design, Setting, and Participants: This 2-group pilot randomized clinical trial was conducted in partnership with a large home care agency in New York, New York, from May 2022 to May 2024. HHAs caring for a patient with HF participated. Outcomes were ascertained on an intent-to-treat basis at baseline, mid-study (45 days after the training course), and 90 days. Interventions: The enhanced usual care (EUC) group received HF training, and the intervention group received HF training plus a mobile health application that allowed HHAs to message nurses. Main Outcomes and Measures: Co-primary outcomes were HF knowledge (assessed using the Dutch HF Knowledge Scale [DHFKS]; range 0-15; higher score indicates greater knowledge) and HF caregiver self-efficacy (assessed using the Caregiver Contribution to Self-Care in HF Index; range, 0-100; higher score indicates greater efficacy). The secondary outcome was self-reported preventable 911 calls. Exploratory outcomes included patient emergency department (ED) visits and hospitalizations. Mixed-effects models were used to compare trajectories of outcomes between and within study groups. Results: A total of 102 HHAs (mean [SD] age, 54 [10.5] years; 98 [96.1%] female) were assessed, including 50 in the EUC group and 52 in the intervention group. Overall, 62 HHAs (62.0%) were Black, 1 HHA (1.0%) was American Indian or Alaska Native, 7 HHAs (7.0%) were Asian, 9 HHAs (9.0%) were White, and 21 HHAs (21.0%) identified as other race; 27 HHAs (27.0%) were Hispanic. Within the intervention group, DHFKS scores improved at 90 days, from a median (IQR) score of 6.1 (5.5-6.7) points at baseline to 7.7 (7.0-8.4) points at 90 days (P = .02); however the change did not differ between groups. Across both groups, HHAs with the lowest baseline DHFKS and self-efficacy had the greatest increases at 90 days (median [IQR] change: DHFKS, 1.45 [0.84-2.04] points; self-efficacy, 8.06 [4.42-11.71] points). At 90 days, there were no statistically significant within-group differences in the proportion of HHAs reporting preventable 911 calls group (intervention: 0.51 [95% CI, 0.37-0.64] at baseline vs. 0.34 [95% CI, 0.2-0.49] at 90 days; P = .06; EUC: 0.42 [95% CI, 0.28-0.56] at baseline vs 0.54 [95% CI, 0.38-0.70] at 90 days; P = .21), but the difference between groups was statistically significant (P = .04). This pilot study was not powered for patient-level outcomes, so the risk of ED visits for patients of intervention HHAs (incidence rate ratio, 0.56 [95% CI, 0.25-1.28]; P = .17) should be considered exploratory. Conclusions and Relevance: In this randomized clinical trial of HHAs caring for patients with HF, HF training improved HHAs' knowledge and self-efficacy, with greatest gains among those with the lowest baseline scores. The ability to message nurses was associated with fewer preventable 911 calls among HHAs in the intervention group. These findings can inform the design of a large-scale trial to better support and integrate HHAs providing HF care. Trial Registration: ClinicalTrials.gov Identifier: NCT04239911.

  PublisherDOI

• Abstract 4360859: Feasibility, Acceptability, and Perspectives Towards Wearable Devices to Assess Life’s Essential 8 Among Home Health Aides

  Circulation · 2025-11-03

  article

  Background: Home health aides (HHAs) provide essential care to the growing population of older adults with cardiovascular (CV) disease who want to age in place. Despite their vital role in patient care, HHAs are a vulnerable population of healthcare professionals who often experience poor CV health. Activity tracking devices offer a promising way to improve HHAs’ CV health awareness and promote health behavior change, particularly with respect to physical activity (PA) and sleep quality, two areas of the AHA’s Life’s Essential 8. Objective: This study aimed to understand how feasible it is for HHAs to use activity tracking devices and assess their perceptions toward such devices with respect to improving their CV health. Methods: We partnered with the labor and management fund of the largest healthcare union in the US to conduct a field study with HHAs working in New York, NY. Participants wore activity tracking devices for four weeks. HHAs were subsequently interviewed on their experiences and attitudes towards the devices and asked to reflect on personalized visualizations of their data. Results: A total of 17 HHAs participated; they had a mean age of 48.7 (SD 12.2) years, 15 were female (88%), 11 identified as Black (65%), 5 identified as Hispanic or Latinx, and they worked as HHAs for a mean of 11.7 years (SD 7.5). Sixteen out of 17 HHAs (94%) wore their activity trackers for the full 28-day study period. Participants took a mean of 10,230 (SD 3,586) steps and slept for a mean of 6.27 (SD 0.58) hours per night. Overall, 4 key themes emerged: (1) Activity tracking devices enhanced participants' health awareness by providing empirical data for self-reflection; (2) This increased awareness led to positive behavioral changes, including setting and achieving health-related goals; (3) HHAs believed these devices could potentially improve not only their own health but also that of their patients ; and (4) Despite this optimism, participants emphasized that their ability to modify sleep and activity patterns was constrained by social and occupational determinants, with sleep improvements being particularly challenging. Conclusions: Our findings suggest that appropriately designed personal tracking interventions could offer a promising approach to supporting positive health-related changes in this historically overlooked workforce, potentially improving both their wellbeing and, by extension, the quality of care they provide to their patients.

  PublisherDOI

• "Who is running it?" Towards Equitable AI Deployment in Home Care Work

  2025-04-24 · 4 citations

  articleOpen accessSenior author

  We present a qualitative study that investigates the implications of current and near-future AI deployment for home care workers (HCWs), an overlooked group of frontline healthcare workers. Through interviews with 22 HCWs, care agency staff, and worker advocates, we find that HCWs do not understand how AI works, how their data can be used, or why AI systems might retain their information. HCWs are unaware that AI is already being utilized in their work, primarily via algorithmic shift-matching systems adopted by agencies. Participants detail the risks AI poses in sensitive care settings for HCWs, patients, and agencies, including threats to workers' autonomy and livelihoods, and express concerns that workers will be held accountable for AI mistakes, with the burden of proving AI's decisions incorrect falling on them. Considering these risks, participants advocate for new regulations and democratic governance structures that protect workers and control AI deployment in home care work.

  PublisherOA PDFDOI

• Digital Technologies and Human Trafficking: Combating Coercive Control and Navigating Digital Autonomy

  2025-04-25 · 4 citations

  articleOpen accessSenior author

  This paper describes a qualitative study that interrogates the types of technology-facilitated coercive control faced by survivors of human trafcking and uncovers potential interventions to aid survivors' recovery.Via semi-structured interviews with 21 participants, including trafcking survivors and professional advocates, we show how trafckers use technology as a lever for control, engaging in surveillance, blackmail, impersonation, and harassment as they compel survivors to stay in the trafcking situation.In recovery, digital footprints keep survivors tethered to their traffcking experience, impacting their digital autonomy, economic mobility, and feelings of safety.Nevertheless, technology can also be a valuable tool for survivors' recovery, connecting them to essential resources and support systems.We discuss the need for interventions and services that account for the specifcity of the trafcking context to help survivors attain digital safety and autonomy, including the potential to adapt existing tech safety services designed for other contexts to human trafcking. CCS Concepts Human-centered computing Empirical studies in HCI ; Security and privacy Human and societal aspects of security and privacy.

  PublisherOA PDFDOI

• Faster Information for Effective Long-Term Discharge: A Field Study in Adult Foster Care

  Proceedings of the ACM on Human-Computer Interaction · 2025-05-02 · 2 citations

  article

  As the US population ages, a growing challenge is placing hospital patients who require long-term post-acute care into adult foster care facilities: small long-term nursing facilities that care for those unable to age in place because their care requirements exceed what can be delivered at home. A key challenge in patient placement is the dynamic matching process between hospital discharge coordinators looking to place patients and facilities looking for residents. We designed, built, deployed, and maintain a system to support decision making among a team of six discharge coordinators assisting in the discharge of 127 patients across 1,047 facilities in Hawai'i. Our system collects vacancy and capability data from facilities via conversational SMS and processes it to recommend facilities that discharge coordinators might contact. Findings from a 14-month deployment provide evidence for how timely, accurate information positively impacts matching efficacy. We close with lessons learned for information collection systems and provisioning platforms in similar contexts.

  PublisherDOI

• 'This is eye opening:' Raising Awareness of Home Care Workers' Health and Wellbeing via Activity Tracking

  Proceedings of the ACM on Human-Computer Interaction · 2025-10-16 · 1 citations

  articleOpen accessSenior author

  Home care workers (HCWs) are an important group of frontline workers that deliver essential at-home care services to enable older adults to age in place. Despite their importance in patient care, research has shown that HCWs are an overlooked and undervalued workforce: HCWs work in isolated conditions, are paid low wages, experience high levels of stress and burnout, and more. As a result, despite being motivated to try and be healthy, this essential workforce suffers from poor physical and mental health outcomes. This paper combines data from focus groups, interviews, and a month-long field study with HCWs to investigate the feasibility and utility of using activity tracking devices to provide HCWs with fine-grained awareness and insights into daily activities that affect their health and wellbeing. We explore HCWs' reactions to both their individual and collective data, discussing their efforts towards positive behavior change, but also highlighting systemic and occupational factors that may limit HCWs' agency and control over their own activities. Finally, we discuss the potential for HCWs' collective data to raise awareness about their working conditions and provide data-driven evidence to aid advocacy efforts towards improved policies, better wages, or greater protections for this vital workforce.

  PublisherDOI

Recent grants

• FW-HTF-RM: The Future of Home Care Work: Designing Technologies for Trust, Privacy, and Empowerment

  NSF · $1.5M · 2020–2024

• SaTC: CORE: Medium: Collaborative: Safety and Security for Targets of Digital Violence

  NSF · $850k · 2019–2024

• CAREER: Global Digital Privacy Innovation

  NSF · $548k · 2018–2024

Frequent coauthors

• Madeline R. Sterling

  Cornell University

  53 shared

• Thomas Ristenpart

  Cornell University

  32 shared

• Emily Tseng

  Cornell University

  27 shared

• Aditya Vashistha

  19 shared

• Jacklyn Cho

  Weill Cornell Medicine

  17 shared

• Deborah Estrin

  Cornell University

  16 shared

• Elizabeth Kuo

  Weill Cornell Medicine

  14 shared

• Rosanna Bellini

  12 shared

Awards & honors

• NSF CAREER Award
• SIGCHI Societal Impact Award
• MacArthur Foundation fellowship