ArticleInternational journal of environmental research and public health2023
Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action.
Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Exploratory Spatial and Temporal Analysis of the Territorial Coexistence of Undernutrition and Excess Weight Among Children Under Five Years of Age in Peru, 2014-2024.International journal of environmental research and public health · 2026Article
- Digital epidemiology: Utilizing big data for public health surveillance and disease outbreak prediction.Journal of public health research · 2026Review
- Refining Established Practices for Research Question Definition to Foster Interdisciplinary Research Skills in a Digital Age: Consensus Study With Nominal Group Technique.JMIR medical education · 2025Article
- The impact of opioid analgesics with concomitant antipsychotic use on pain modulation and management in internal medicine: a cross-sequential study protocol.Frontiers in pain research (Lausanne, Switzerland) · 2025Article
- Unified framework for the ingestion of early epidemic data for downstream data analytics.Wellcome open research · 2025Article
- Digital epidemiology: harnessing big data for early detection and monitoring of viral outbreaks.Infection prevention in practice · 2024Review
- Spaceflight Induces Strength Decline inCells · 2023Article
- The Role of Social Media in Building Pandemic Resilience in an Urban Community: A Qualitative Case Study.International journal of environmental research and public health · 2023Article
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
The emergence of big data science presents a unique opportunity to improve public-health research practices. Because working with big data is inherently complex, big data research must be clear and transparent to avoid reproducibility issues and positively impact population health. Timely implementation of solution-focused approaches is critical as new data sources and methods take root in public-health research, including urban public health and digital epidemiology. This commentary highlights methodological and analytic approaches that can reduce research waste and improve the reproducibility and replicability of big data research in public health. The recommendations described in this commentary, including a focus on practices, publication norms, and education, are neither exhaustive nor unique to big data, but, nonetheless, implementing them can broadly improve public-health research. Clearly defined and openly shared guidelines will not only improve the quality of current research practices but also initiate change at multiple levels: the individual level, the institutional level, and the international level.
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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.