ArticleTechnological forecasting and social change2022
Developing a mental health index using a machine learning approach: Assessing the impact of mobility and lockdown during the COVID-19 pandemic.
Article in Technological forecasting and social change, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- An in-depth exploration of machine learning methods for mental health state detection: a systematic review and analysis.Frontiers in digital health · 2025Pooled it
- Is SARS-CoV-2 elimination or mitigation best? Regional and disease characteristics determine the recommended strategy.Royal Society open science · 2024Article
- Article
- Development and validation of the Environmental Confinement Stressors Scale (ECSS-20).Frontiers in psychology · 2024Article
- Unintended Consequences of COVID-19 Non-Pharmaceutical Interventions (NPIs) for Population Health and Health Inequalities.International journal of environmental research and public health · 2023Review
- Mental health issues assessment using tools during COVID-19 pandemic.Innovations in systems and software engineering · 2022Article
- Coping with pandemics using social network sites: A psychological detachment perspective to COVID-19 stressors.Technological forecasting and social change · 2022Article
- Aggressive measures, rising inequalities, and mass formation during the COVID-19 crisis: An overview and proposed way forward.Frontiers in public health · 2022Review
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Governments worldwide have implemented stringent restrictions to curtail the spread of the COVID-19 pandemic. Although beneficial to physical health, these preventive measures could have a profound detrimental effect on the mental health of the population. This study focuses on the impact of lockdowns and mobility restrictions on mental health during the COVID-19 pandemic. We first develop a novel mental health index based on the analysis of data from over three million global tweets using the Microsoft Azure machine learning approach. The computed mental health index scores are then regressed with the lockdown strictness index and Google mobility index using fixed-effects ordinary least squares (OLS) regression. The results reveal that the reduction in workplace mobility, reduction in retail and recreational mobility, and increase in residential mobility (confinement to the residence) have harmed mental health. However, restrictions on mobility to parks, grocery stores, and pharmacy outlets were found to have no significant impact. The proposed mental health index provides a path for theoretical and empirical mental health studies using social media.
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