ArticleJournal of the American Medical Informatics Association : JAMIA2016
Tweeting back: predicting new cases of back pain with mass social media data.
Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic literature review of machine learning in online personal health data.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Investigating Individuals' Perceptions Regarding the Context Around the Low Back Pain Experience: Topic Modeling Analysis of Twitter Data.Journal of medical Internet research · 2021Article
- A scoping review of the use of Twitter for public health research.Computers in biology and medicine · 2020Article
- Misinformation about spinal manipulation and boosting immunity: an analysis of Twitter activity during the COVID-19 crisis.Chiropractic & manual therapies · 2020Article
- Investigating Subjective Experience and the Influence of Weather Among Individuals With Fibromyalgia: A Content Analysis of Twitter.JMIR public health and surveillance · 2017Article
- Advancing psychological therapies for chronic pain.F1000Research · 2017Review
- Aspiring to Unintended Consequences of Natural Language Processing: A Review of Recent Developments in Clinical and Consumer-Generated Text Processing.Yearbook of medical informatics · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBack pain is a global health problem. Recent research has shown that risk factors that are proximal to the onset of back pain might be important targets for preventive interventions. Rapid communication through social media might be useful for delivering timely interventions that target proximal risk factors. Identifying individuals who are likely to discuss back pain on Twitter could provide useful information to guide online interventions.
methodsWe used a case-crossover study design for a sample of 742 028 tweets about back pain to quantify the risks associated with a new tweet about back pain.
resultsThe odds of tweeting about back pain just after tweeting about selected physical, psychological, and general health factors were 1.83 (95% confidence interval [CI], 1.80-1.85), 1.85 (95% CI: 1.83-1.88), and 1.29 (95% CI, 1.27-1.30), respectively.
conclusionThese findings give directions for future research that could use social media for innovative public health interventions.
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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.