Evidence map›Paper›PMID 38798095›Full record

ReviewJournal of genetic counseling2025

Small programs, big challenges: Reimagining the evaluation of clinical teaching in genetic counseling.

Susan Randall Armel

Abstract readReview
In one paragraph

Review in Journal of genetic counseling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

1 author.

Susan Randall ArmelBhalwani Familial Cancer Clinic, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.ORCID 0000-0001-5016-3148

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Within the health professions education system, a significant proportion of teaching and learning occurs in the clinical setting. As such, the need to measure effective teaching for accreditation standards, faculty development, merit pay, academic promotion, and for monitoring the safety of the learning environment has led to numerous universities developing instruments to evaluate teaching effectiveness in this context. To date; however, these instruments typically focus on the student perspective, despite evidence demonstrating that student evaluations of teaching (SETs) lack correlation with learning outcomes and are not a true measure of teaching effectiveness. This issue is further exacerbated in small health professional training programs, such as genetic counseling, where clinical teachers may only supervise 1-3 students per year. As a result, not only are SETs more confounded due to small sample sizes, but a direct conflict exists between respecting learner anonymity and providing timely and relevant feedback to faculty. In such contexts, even using SETs to evaluate the nature of the learning environment may be unreliable due to student concerns about identifiability and fear of retaliation for unfavorable evaluation. This paper will review the literature regarding SETs, barriers to this process within the clinical setting, and the unintended downstream consequences. Options for addressing issues related to the use of SETs will be considered, with particular focus on the process of reflection and the use of teaching consultations or peer support groups as a means to improve teaching effectiveness in this learning environment.

Indexed as

Genetic CounselingTeachingHumansclinical supervisionpeer support groupreflective practiceself‐assessmentstudent evaluation of teachingteaching consultationteaching effectiveness

Identifiers

PMID38798095
PMCPMC11735188

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.