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From Wikipedia, the free encyclopedia

The PICO process (or framework) is a mnemonic used in evidence-based practice (and specifically evidence-based medicine) to frame and answer a clinical or health care related question,[1] though it is also argued that PICO "can be used universally for every scientific endeavour in any discipline with all study designs".[2] The PICO framework is also used to develop literature search strategies, for instance in systematic reviews.[3]

The PICO acronym has come to stand for:[4][5]

  • P – Patient, problem or population
  • I – Intervention
  • C – Comparison, control or comparator[6]
  • O – Outcome(s) (e.g. pain, fatigue, nausea, infections, death)

An application that covers clinical questions about interventions, as well as exposures, risk/ prognostic factors, and test accuracy, is:[7][8]

  • P – Patient, problem or population
  • I – Investigated condition (e.g. intervention, exposure, risk/ prognostic factor, or test result)
  • C – Comparison condition (e.g. intervention, exposure, risk/ prognostic factor, or test result respectively)
  • O – Outcome(s) (e.g. symptom, syndrome, or disease of interest)

Alternatives such as SPICE and PECO (among many others) can also be used. Some authors suggest adding T and S, as follows:

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Transcription

PICO as a universal technique

It was argued that PICO may be useful for every scientific endeavor even beyond clinical settings.[2] This proposal is based on a more abstract view of the PICO mnemonic, equating them with four components that is inherent to every single research, namely (1) research object; (2) application of a theory or method; (3) alternative theories or methods (or the null hypothesis); and (4) the ultimate goal of knowledge generation.

Juxtaposing PICO with universal components of all research endeavors
PICO component Abstract component inherent to all research designs
Problem Research object
Intervention Application of a theory or method
Comparison Alternative theories or methods (or, in their absence, the null hypothesis)
Outcome Knowledge generation

This proposition would imply that the PICO technique could be used for teaching academic writing even beyond medical disciplines.

Examples

Clinical question: "In children with headache, is paracetamol more effective than placebo against pain?"

  • Population = Children with headaches; keywords = children + headache
  • Intervention = Paracetamol; keyword = paracetamol
  • Compared with = Placebo; keyword = placebo
  • Outcome of interest = Pain; keyword = pain

Pubmed (health research database) search strategy:children headache paracetamol placebo pain

Clinical question: "Is the risk of having breast cancer higher in symptom-free women with a positive mammography compared to symptom-free women with a negative mammography?"[8]

  • Population = Women without a history of breast cancer
  • Investigated test result = Positive result on mammography
  • Comparator test result = Negative result on mammography
  • Outcome of interest = Breast cancer according to biopsy (or not)

References

  1. ^ Huang X, Lin J, Demner-Fushman D (2006). "Evaluation of PICO as a knowledge representation for clinical questions" (PDF). AMIA Annu Symp Proc. 2006: 359–63. PMC 1839740. PMID 17238363.
  2. ^ a b Nishikawa-Pacher, Andreas (2022). "Research Questions with PICO: A Universal Mnemonic". Publications. 10 (3): 21. doi:10.3390/publications10030021. eISSN 2304-6775.
  3. ^ Schardt C, Adams MB, Owens T, Keitz S, Fontelo P (2007). "Utilization of the PICO framework to improve searching PubMed for clinical questions". BMC Med Inform Decis Mak. 7: 16. doi:10.1186/1472-6947-7-16. PMC 1904193. PMID 17573961.
  4. ^ "Asking a Good Question (PICO)". 17 November 2004. Archived from the original on 2011-02-26. Retrieved 2010-05-18.
  5. ^ Richardson, WS (1995). "The well-built clinical question: a key to evidence based-decisions". ACP Journal Club. 123, 3 (3): A12–A13. doi:10.7326/ACPJC-1995-123-3-A12.
  6. ^ "Chapter 2. Systematic Review Methods -- AHRQ Technical Reviews and Summaries -- NCBI Bookshelf". Agency for Healthcare Research and Quality (US). March 2009. Retrieved 2010-05-18.
  7. ^ Richardson, WS (1995). "The well-built clinical question: a key to evidence based-decisions". ACP Journal Club. 123, 3 (3): A12–A13. doi:10.7326/ACPJC-1995-123-3-A12.
  8. ^ a b Luijendijk HJ (2021). "How to PICO questions about medical tests". BMJ Evidence-Based Medicine. 26 (4): 155–157. doi:10.1136/bmjebm-2021-111676. PMC 8311106. PMID 33789913.
This page was last edited on 3 December 2023, at 08:25
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