Health: Academic Discipline — Prolific Citations Library

Explore 18 peer-reviewed papers in Health (2020–2025). Academic research using Prolific for high-quality human data collection.

This page lists 18 peer-reviewed papers in the discipline of Health in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (18 of 18)

Laypeople's use of and attitudes toward large language models and search engines for health queries: survey study

Authors: T Mendel, N Singh, DM Mann, B Wiesenfeld

Year: 2025

Published in: Journal of medical ..., 2025 - jmir.org

Institution: The City University of New York, George Washington University, New York University

Research Area: LLMs in Digital Health, Health Queries, User Attitudes

Discipline: Digital Health

Laypeople primarily use search engines over large language models (LLMs) for health queries, perceiving LLMs as less useful but less biased and more human-like while exhibiting no significant difference in trust or ease of use.

Methods: A screening survey followed by logistic regression analysis and a follow-up survey; comparisons were performed using ANOVA, Tukey post hoc tests, and paired-sample Wilcoxon tests.

Key Findings: Demographics and behaviors of LLM and search engine users for health queries, perceived usefulness, ease of use, trustworthiness, bias, and anthropomorphism.

Citations: 21

Sample Size: 2002
Impact of AI-Assisted Diagnosis on American Patients' Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey ...

Authors: C Chen, Z Cui

Year: 2025

Published in: Journal of Medical Internet Research, 2025 - jmir.org

Institution: Medical College of Wisconsin

Research Area: Trust in AI, AI-assisted diagnosis, Health communication, Healthcare human-AI interaction

Discipline: Digital Health, Human-Computer Interaction (HCI), Behavioral Science

Patients trust and are more likely to seek help from doctors explicitly avoiding AI-assisted diagnosis rather than those using extensive or moderate AI, highlighting a strong aversion to AI in healthcare settings.

Methods: A randomized, web-based 4-group survey experiment was conducted with controls for sociodemographic factors and analysis using regression, mediation, and moderation techniques.

Key Findings: Trust in and intention to seek medical help from health care professionals using AI-assisted diagnosis versus those avoiding AI, and the influence of demographic, social, and experiential factors.

DOI: https://doi.org/10.2196/66083

Citations: 4

Sample Size: 1762
Leveraging Social Media and Crowdsourcing to Recruit and Retain Military Veterans With Posttraumatic Stress Disorder or Experience of Harmful Gambling ...

Authors: C Heath, JM Williams, D Leightley

Year: 2025

Published in: JMIR mHealth and ..., 2025 - mhealth.jmir.org

Institution: Swansea University, King's College London, Reykjavík University

Research Area: mHealth Interventions, Crowdsourcing, Social Media Recruitment, Mental Health Research (PTSD, Harmful Gambling)

Discipline: Digital Health, Mental Health Research

Social media and online platforms like Facebook and Prolific were effective but faced challenges in recruiting and retaining military veterans with PTSD or harmful gambling for a digital mHealth intervention pilot study.

Methods: Multiple recruitment strategies were used, including paid and unpaid advertisements on Facebook, Prolific, direct mailing, event hosting with veterans' charities, snowball sampling, and incentives.

Key Findings: The effectiveness of different recruitment strategies for enrolling military veterans with PTSD or harmful gambling into a digital intervention study.

Sample Size: 79
Multimodal machine learning for video based single question mental health assessment

Authors: B Grimm, P Yilmam, B Talbot, L Larsen

Year: 2025

Published in: npj Digital Medicine, 2025 - nature.com

Institution: Videra Health

Research Area: Computational Mental Health Assessment, Multimodal Machine Learning

Discipline: Computational Health, Digital Medicine

A multimodal machine learning model using text (MPNet) and voice (HuBERT) analysis predicts depression, anxiety, and trauma from a single video-based question with strong performance and demographic consistency while significantly reducing assessment time.

Methods: Multimodal analysis combining MPNet for textual data and HuBERT for prosodic voice features trained on video-based responses.

Key Findings: Efficient prediction of self-reported scores for depression (PHQ-9), anxiety (GAD-7), and trauma (PCL-5) from brief video responses.

Sample Size: 2420
Influence of believed AI involvement on the perception of digital medical advice

Authors: M Reis, F Reis, W Kunde

Year: 2024

Published in: Nature Medicine, 2024 - nature.com

Institution: University of Cambridge, Julius Maximilians Universität

Research Area: AI in Healthcare, Medical Ethics, Cognitive Psychology, Human-Computer Interaction (HCI) in Medicine

Discipline: AI in Healthcare, Medical Ethics, Cognitive Psychology

The study found that medical advice labeled as being sourced from AI (or AI supervised by humans) is perceived as less reliable and empathetic compared to advice labeled as originating solely from a human physician, resulting in reduced willingness to follow such advice.

Methods: Two preregistered studies were conducted where participants were presented with identical medical advice scenarios but with manipulated labels for the advice source ('AI', 'human physician', 'human+AI').

Key Findings: Participants' perceptions of reliability, empathy, and willingness to follow medical advice based on the perceived source.

Citations: 78

Sample Size: 2280
The impact of the cost of living crisis and food insecurity on food purchasing behaviours and food preparation practices in people living with obesity

Authors: RA Stone, A Brown, F Douglas, M Green, E Hunter, M Lonnie, AM Johnstone, CA Hardman, FIO-Food Team

Year: 2024

Published in: Science Direct

Institution: Robert Gordon University, University College London, University of Aberdeen, University of Liverpool

Research Area: Food Insecurity, Public Health, Behavioral Economics (focusing on food purchasing behaviors and preparation practices related to obesity, cost of living)

Discipline: Public Health

The study examines how the UK cost of living crisis affects food purchasing and preparation behaviors in people with obesity, highlighting food insecurity and associated coping strategies, and calls for policy interventions to improve access to healthy foods.

Methods: An online survey was conducted with self-reported data on food insecurity, diet quality, cost of living impact, and food purchasing/preparation behaviors among adults with BMI ≥30 kg/m2 in England or Scotland.

Key Findings: Food insecurity, diet quality, impacts of the cost of living crisis, food purchasing behaviors, and food preparation practices among participants.

Citations: 46

Sample Size: 583
Planning for New Threats to Online Research Data Validity: The Issue of Computer-Using Agents

Authors: J Agley

Year: 2024

Published in: Evaluation & the Health Professions, 2025 - journals.sagepub.com

Institution: Indiana University, Prevention Insights

Research Area: Health Research and Evaluation, Data Validity, Computational Social Science

Discipline: Public Health, Computational Social Science

Citations: 2
Researching childhood vaccine hesitancy in the wake of COVID-19

Authors: Alistair Anderson, Tom Douglass, Pru Hobson-West

Year: 2024

Published in: Science Direct

Institution: University of Birmingham, University of Nottingham

Research Area: Vaccine Hesitancy, Public Health, Sociology of Health

Discipline: Sociology of Health, Public Health

Citations: 2
Clinicians diagnosing virtual patients with the classification algorithm for chronic pain in the ICD-11 (CAL-CP) achieve better diagnoses and prefer the algorithm to standard tools: An experimental validation study

Authors: G Hay, Beatrice Korwisi, Norman Lahme-Hütig, Winfried Rief, Antonia Barke

Year: 2024

Published in: Wiley

Institution: Marburg University, Münster School of Business, University of Duisburg-Essen

Research Area: ICD-11 Chronic Pain Classification, Clinical Diagnosis, Algorithmic Decision-Making

Discipline: Health, Medicine, Artificial Intelligence
Fear of COVID-19: Data of a large longitudinal survey conducted between March 2020 and June 2021

Authors: G Mertens, P Lodder, T Smeets, S Duijndam

Year: 2023

Published in: Data in Brief, 2023 - Elsevier

Institution: Tilburg University

Research Area: COVID-19 Fear, Longitudinal Survey Data, Psychology, Public Health

Discipline: Public Health, Psychology

Citations: 8
How is online self-reported weight compared with image-captured weight? A comparative study using data from an online longitudinal study of young adults

Authors: MC Whatnall, KZ Kolokotroni, TE Fozard

Year: 2023

Published in: The American Journal of ..., 2023 - Elsevier

Institution: The University of Sheffield, The University of Edinburgh

Research Area: Public Health, Behavioral Science, Digital Health

Discipline: Clinical Nutrition, Public Health, Behavioral Science

Citations: 4
Further psychometric validation and test–retest reproducibility of the WOUND-Q

Authors: Nina Vestergaard Simonsen, Anne F. Klassen, Charlene Rae, Farima Dalaei, Stefan Cano, Lotte Poulsen, Andrea L. Pusic, Jens Ahm Sørensen

Year: 2023

Published in: Wiley

Institution: Harvard Medical School, McMaster University, Modus Outcomes, Odense University Hospital, University of Southern Denmark

Research Area: Patient-reported outcomes (PROMs), Psychometrics, Chronic Wound Care

Discipline: Health Sciences, Psychometrics
Impact of social reference cues on misinformation sharing on social media: Series of experimental studies

Authors: CM Jones, D Diethei, J Schöning, R Shrestha

Year: 2022

Published in: Journal of Medical ..., 2023 - jmir.org

Research Area: Social Media, Misinformation, Social Influence

Discipline: Social Science, Digital Health

DOI: https://doi.org/10.2196/45583

Citations: 19
Recruitment and retention in remote research: learnings from a large, decentralized real-world study

Authors: SX Li, R Halabi, R Selvarajan, M Woerner

Year: 2022

Published in: JMIR Formative ..., 2022 - formative.jmir.org

Institution: Massachusetts General Hospital, Harvard Medical School, Boston University, University of Waterloo

Research Area: Digital Health, Remote Research Methods, Recruitment and Retention Studies

Discipline: Digital Health, Research Methodology

Citations: 19
Understanding eating behaviours, mental health and weight change in young adults: protocol paper for an international longitudinal study

Authors: M Whatnall, T Fozard, K Kolokotroni, J Marwood, T Evans, L Jane Ells, T Burrows

Year: 2022

Published in: British Medical Journal

Institution: Leeds Beckett University, The University of Newcastle Australia

Research Area: Eating behaviors, Mental Health, Weight Change in Young Adults, Public Health

Discipline: Public Health
The impact of explanations on layperson trust in artificial intelligence-driven symptom checker apps: experimental study

Authors: C Woodcock, B Mittelstadt, D Busbridge

Year: 2021

Published in: Journal of medical Internet ..., 2021 - jmir.org

Institution: Oxford University, Alan Turing Institute, University of Edinburgh

Research Area: Health Informatics, Explainable AI (XAI), Trust in AI, Digital Health

Discipline: Digital Health

DOI: https://doi.org/10.2196/29386

Citations: 52
Rather than inducing psychological reactance, requiring vaccination strengthens intentions to vaccinate in US populations

Authors: Dolores Albarracin, Haesung Jung, Wen Song, Andy Tan & Jessica Fishman

Year: 2021

Published in: Nature

Institution: University of Pennsylvania

Research Area: Vaccine Uptake, Psychological Reactance, Health Behavior

Discipline: Behavioral Science, Public Health
Use of rapid online surveys to assess people's perceptions during infectious disease outbreaks: a cross-sectional survey on COVID-19

Authors: P Geldsetzer

Year: 2020

Published in: Journal of medical Internet research, 2020 - jmir.org

Institution: Stanford University

Research Area: Public Health Surveillance, Survey Methodology, Infectious Disease Outbreaks, COVID-19

Discipline: Public Health, Digital Health Research

Citations: 596