Evidence map›Paper›PMID 34255645›Full record

ArticleJournal of medical Internet research2021

Assessing Patient Perceptions and Experiences of Paracetamol in France: Infodemiology Study Using Social Media Data Mining.

Stéphane Schück, Avesta Roustamal, Anaïs Gedik, Paméla Voillot, Pierre Foulquié, Catherine Penfornis, Bernard Job

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Stéphane SchückKap Code, Paris, France.ORCID 0000-0003-2642-7726
Avesta RoustamalKap Code, Paris, France.ORCID 0000-0002-1446-0783
Anaïs GedikKap Code, Paris, France.ORCID 0000-0003-1284-5433
Paméla VoillotKap Code, Paris, France.ORCID 0000-0001-7156-9075
Pierre FoulquiéKap Code, Paris, France.ORCID 0000-0003-4485-0835
Catherine PenfornisSanofi, Paris, France.ORCID 0000-0001-7017-0919
Bernard JobSanofi, Paris, France.ORCID 0000-0002-9135-8563

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndividuals frequently turning to social media to discuss medical conditions and medication, sharing their experiences and information and asking questions among themselves. These online discussions can provide valuable insights into individual perceptions of medical treatment, and increasingly, studies are focusing on the potential use of this information to improve health care management.

objectiveThe objective of this infodemiology study was to identify social media posts mentioning paracetamol-containing products to develop a better understanding of patients' opinions and perceptions of the drug.

methodsPosts between January 2003 and March 2019 containing at least one mention of paracetamol were extracted from 18 French forums in May 2019 with the use of the Detec't (Kap Code) web crawler. Posts were then analyzed using the automated Detec't tool, which uses machine learning and text mining methods to inspect social media posts and extract relevant content. Posts were classified into groups: Paracetamol Only, Paracetamol and Opioids, Paracetamol and Others, and the Aggregate group.

resultsOverall, 44,283 posts were analyzed from 20,883 different users. Post volume over the study period showed a peak in activity between 2009 and 2012, as well as a spike in 2017 in the Aggregate group. The number of posts tended to be higher during winter each year. Posts were made predominantly by women (14,897/20,883, 71.34%), with 12.00% (2507/20,883) made by men and 16.67% (3479/20,883) by individuals of unknown gender. The mean age of web users was 39 (SD 19) years. In the Aggregate group, pain was the most common medical concept discussed (22,257/37,863, 58.78%), and paracetamol risk was the most common discussion topic, addressed in 20.36% (8902/43,725) of posts. Doliprane was the most common medication mentioned (14,058/44,283, 31.74%) within the Aggregate group, and tramadol was the most commonly mentioned drug in combination with paracetamol in the Aggregate group (1038/19,587, 5.30%). The most common unapproved indication mentioned within the Paracetamol Only group was fatigue (190/616, with 16.32% positive for an unapproved indication), with reference to dependence made by 1.61% (136/8470) of the web users, accounting for 1.33% (171/12,843) of the posts in the Paracetamol Only group. Dependence mentions in the Paracetamol and Opioids group were provided by 6.94% (248/3576) of web users, accounting for 5.44% (342/6281) of total posts. Reference to overdose was made by 245 web users across 291 posts within the Paracetamol Only group. The most common potential adverse event detected was nausea (306/12843, 2.38%) within the Paracetamol Only group.

conclusionsThe use of social media mining with the Detec't tool provided valuable information on the perceptions and understanding of the web users, highlighting areas where providing more information for the general public on paracetamol, as well as other medications, may be of benefit.

Indexed as

AcetaminophenSocial MediaAdultAnalgesics, OpioidData MiningFemaleHumansMalePerceptionAcetaminophenAnalgesics, Opioidanalgesic usedata mininginfodemiologyparacetamolpatient perceptionpharmacovigilancesocial media

Identifiers

PMID34255645
PMCPMC8314157

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Registered trials

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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.