ArticlePloS one2021
Predicting fear and perceived health during the COVID-19 pandemic using machine learning: A cross-national longitudinal study.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- The impact of health information seeking and social influence on functional food purchase intention.Scientific reports · 2025Article
- Sense of macro-level belonging supported university students' life satisfaction amid global threats: evidence from Latvia's first COVID-19 wave.Frontiers in psychology · 2025Article
- Corona phobia and mental health among nurses: identifying determinants in a cross-sectional survey.Frontiers in public health · 2025Article
- A cross-sectional survey on COVID-19 phobia and its influencing factors among undergraduate nursing students.BMC nursing · 2024Article
- A machine learning approach to predict self-protecting behaviors during the early wave of the COVID-19 pandemic.Scientific reports · 2023Article
- Trusting the Health System and COVID 19 Restriction Compliance.Economics and human biology · 2023Article
- Fear of contagion, emotional stress and coping strategies used by adults during the first wave of the COVID-19 pandemic in Nigeria.BMC psychiatry · 2022Article
- Effectiveness of Artificial Intelligence Methods in Personalized Aggression Risk Prediction within Inpatient Psychiatric Treatment Settings-A Systematic Review.Journal of personalized medicine · 2022Review
- First-onset major depression during the COVID-19 pandemic: A predictive machine learning model.Journal of affective disorders · 2022Article
- Fear of COVID-19 predicts vaccination willingness 14 months later.Journal of anxiety disorders · 2022Article
- Trust in Healthcare during COVID-19 in Europe: vulnerable groups trust the least.Zeitschrift fur Gesundheitswissenschaften = Journal of public health · 2022Article
- Pharmacological Adherence Behavior Changes during COVID-19 Outbreak in a Portugal Patient Cohort.International journal of environmental research and public health · 2022Article
- Measuring daily-life fear perception change: A computational study in the context of COVID-19.PloS one · 2022Article
- Article
- The impact of vaccination upon dental clinic avoidance and the cessation of individual protection measures.Frontiers in public health · 2022Article
- Poverty in old age in times of COVID-19-Empirical results from Austria.Frontiers in public health · 2022Article
- Does having various types of fear related to COVID-19 disrupt individuals' daily life?: Findings from a nationwide survey in Korea.Epidemiology and health · 2022Article
- Stress, coping, resilience, and sleep during the COVID-19 pandemic: A representative survey study of US adults.Brain and behavior · 2021Article
- Article
- Determinants of COVID-19 Vaccine Hesitancy in Portuguese-Speaking Countries: A Structural Equations Modeling Approach.Vaccines · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During medical pandemics, protective behaviors need to be motivated by effective communication, where finding predictors of fear and perceived health is of critical importance. The varying trajectories of the COVID-19 pandemic in different countries afford the opportunity to assess the unique influence of 'macro-level' environmental factors and 'micro-level' psychological variables on both fear and perceived health. Here, we investigate predictors of fear and perceived health using machine learning as lockdown restrictions in response to the COVID-19 pandemic were introduced in Austria, Spain, Poland and Czech Republic. Over a seven-week period, 533 participants completed weekly self-report surveys which measured the target variables subjective fear of the virus and perceived health, in addition to potential predictive variables related to psychological factors, social factors, perceived vulnerability to disease (PVD), and economic circumstances. Viral spread, mortality and governmental responses were further included in the analysis as potential environmental predictors. Results revealed that our models could accurately predict fear of the virus (accounting for approximately 23% of the variance) using predictive factors such as worrying about shortages in food supplies and perceived vulnerability to disease (PVD), where interestingly, environmental factors such as spread of the virus and governmental restrictions did not contribute to this prediction. Furthermore, our results revealed that perceived health could be predicted using PVD, physical exercise, attachment anxiety and age as input features, albeit with smaller effect sizes. Taken together, our results emphasize the importance of 'micro-level' psychological factors, as opposed to 'macro-level' environmental factors, when predicting fear and perceived health, and offer a starting point for more extensive research on the influences of pathogen threat and governmental restrictions on the psychology of fear and health.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.