Evidence map›Paper›PMID 32814544›Full record

ArticleBMC musculoskeletal disorders2020

Epidemiological profile of pain and non-steroid anti-inflammatory drug use in collegiate athletes in the United States.

S Christopher, B A Tadlock, B J Veroneau, C Harnish, N K P Perera, A M Knab, S Vallabhajosula, G S Bullock

Open access · goldAbstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 16% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
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

8 authors at 5 institutions in 4 countries.

S ChristopherDepartment of Physical Therapy Education, Elon University, Elon, NC, USA.
B A TadlockDepartment of Physical Therapy Education, Elon University, Elon, NC, USA.
B J VeroneauDepartment of Physical Therapy Education, Elon University, Elon, NC, USA.
C HarnishDepartment of Exercise Science, Mary Baldwin College, Staunton, VA, USA.
N K P PereraCentre for Sport, Exercise and Osteoarthritis Research Versus Arthritis, University of Oxford, Oxford, UK.
A M KnabKinesiology Department, Queens University of Charlotte, Charlotte, NC, USA.
S VallabhajosulaDepartment of Physical Therapy Education, Elon University, Elon, NC, USA.
G S BullockCentre for Sport, Exercise and Osteoarthritis Research Versus Arthritis, University of Oxford, Oxford, UK. garrettbullock@gmail.com.ORCID http://orcid.org/0000-0003-0236-9015
Elon University · USLinköping University · SEMary Baldwin University · USNuffield Orthopaedic Centre · GBQueens University of Charlotte · US

Funding

Centre for Sport, Exercise and Osteoarthritis Research Versus Arthritis HFR02510
6 · The paper itself

Abstract

backgroundAlthough athletic endeavours are associated with a high amount of physical stress and injury, the prevalence of pain is underreported in the sports medicine literature with only a few studies reporting pain on collegiate athletes or exploring sex difference of pain. Impact of pain on athlete availability, training and performance can be mitigated when key epidemiological information is used to inform adequate pain management strategies. This study aims to 1) provide an epidemiological profile of self-reported pain experienced by the National Collegiate Athletic Association (NCAA) athletes by sex during the first half of the 2019 season, 2) describe their self-reported non-steroidal anti-inflammatory drug (NSAID) use.

methodsOnline survey was completed by athletes at three NCAA institutions from 1 August to 30 September 2019. Descriptive statistics were used to describe player demographic data, self-reported pain and self-reported NSAID use. Pain incidence proportion were calculated.

resultsTwo hundred thirty female athletes and 83 male athletes completed the survey. Self-reported pain incidence proportion for female athletes was 45.0 (95% CI 41.5-48.5) vs 34.9 (95% CI 29.4-40.4) for male athletes. Majority of the athletes did not report pain (55% female vs 62% male) during the first half of the 2019 season. Female athletes reported pain in their back (35%), knee (26%), and ankle/foot (23%) whilst male athletes reported pain in their knee (35%), back (28%), and shoulder (24%). Of all athletes, 28% female vs 20% male athletes reported currently taking NSAIDs. Of athletes that reported pain, 46% female vs 38% male athletes currently took NSAIDs. 70% female vs 61% male athletes self-purchased NSAIDs, and 40% female vs 55% male athletes consumed alcohol.

conclusionsHalf of female athletes and one in three male athletes reported pain. Most commonly back, knee and foot/ankle pain and knee, back and shoulder pain was reported in female and male athletes respectively. One in four female athletes and one in five male athletes use NSAIDs for pain or prophylactic purpose. Majority self-purchase these medications indicating need for health literacy interventions to mitigate potential adverse effects.

Indexed as

Athletic InjuriesPharmaceutical PreparationsAnti-Inflammatory Agents, Non-SteroidalAthletesFemaleHumansIncidenceMalePainUnited StatesUniversitiesAnti-Inflammatory Agents, Non-SteroidalPharmaceutical PreparationsAthlete healthElite sportFemale athletesHealth literacyInjury preventionSleepSports medicine

Identifiers

PMID32814544
PMCPMC7437034
OpenAlexW3068213337

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.