Evidence map›Paper›PMID 35620507›Full record

ArticlePlastic and reconstructive surgery. Global open2022

Creating a Spaced Repetition Model to Supplement Education in Plastic Surgery.

Zachary A Koenig, Joshua T Henderson, Sebastian M Brooke

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2022. 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.

  1. Trial
  2. Spaced learning versus traditional learning for pharmacists implementing β-lactam therapeutic drug monitoring.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Article
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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

3 authors.

Zachary A KoenigWest Virginia University School of Medicine, Morgantown, W.Va.
Joshua T HendersonDivision of Plastic Surgery, Department of Surgery, West Virginia University, Morgantown, W.Va.
Sebastian M BrookeDivision of Plastic Surgery, Department of Surgery, West Virginia University, Morgantown, W.Va.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plastic surgery encompasses a wide spectrum of material involving comprehensive anatomy, physiology, microbiology, biomaterials, complex surgical techniques, and many nonsurgical interventions. The core disciplines overlap extensively with the foundational knowledge of many other surgical specialties. With the ever-expanding knowledge base required to become a competent plastic surgeon, spaced repetition is a means to optimize learning in plastic surgery and help trainees master new concepts while retaining other facts that are easily forgotten. Platforms for spaced repetition are user-friendly and can be synchronized between devices to streamline progress and make efficient use of the limited free time that exists throughout the workday. Flashcard decks can be imported to these platforms to follow a spaced repetition algorithm. Currently, no publicly available comprehensive deck exists for education in plastic and reconstructive surgery. Creation of flashcard decks covering lectures, textbooks, or old examination questions can reinforce the foundational concepts of our field. Additionally, there is potential to improve resident performance on the Plastic Surgery In-service Training Examination. Once created, this comprehensive flashcard deck can be distributed to plastic surgery residency programs to pave the way for a uniform curriculum.

Identifiers

PMID35620507
PMCPMC9126508

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.