Evidence map›Paper›PMID 34457764›Full record

ArticleMedical science educator2020

Use of a Digital, Profession-Specific Dissection Guide Is Associated with Improved Examination Performance and Student Satisfaction.

Michael A Pascoe, Kourtney Betts

Open access · greenAbstract read
In one paragraph

Article in Medical science educator, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 54% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

2 authors at 1 institution in 1 country.

Michael A PascoePhysical Therapy Program, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA.ORCID https://orcid.org/0000-0003-0281-8167
Kourtney BettsPhysical Therapy Program, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA.
University of Colorado Anschutz Medical Campus · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anatomical knowledge is requisite for effective physical therapy (PT) practice. Cadaver dissection is a popular teaching method employed in PT anatomy courses. Limited time in the laboratory requires effective dissection instructions. Several limitations of a printed, non-discipline specific dissection guide have been identified by students and instructors in anatomy curricula. The objective of this project was to evaluate the effect of using a digital, PT specific dissection guide on examination performance and student satisfaction. A digital guide was developed that incorporated improvements based on observations of student experiences using a printed guide. The digital guide covered two lower extremity regional dissections and was distributed for use during the summer 2017 course. Enhancements included clarification of dissection procedures, formative quizzes, image galleries, embedded videos, and a glossary of terms. Students used a printed guide for all other dissections in the course. The percentage of correct answers from practical examinations was calculated and compared between summer of 2015 (print) and 2017 (digital) courses. A survey consisting of nineteen five-point Likert items was distributed. The percentage of correct answers was significantly higher for the digital guide (91.7 ± 7.11%) compared with the print guide (84.2 ± 9.51%,

Indexed as

Digital assetsDissection guideeBookGross anatomy laboratoryLearning outcomesTechnology-enhanced learning

Identifiers

PMID34457764
PMCPMC8368761
OpenAlexW3036661852

What OpenQuestion holds

Textmetadata
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.