Evidence map›Paper›PMID 32754401›Full record

ArticleCureus2020

Dermatology Resident Training on Depression Screening: A Cross-Sectional Survey.

Kaitlyn L Streight, Harry Dao, Soo Jung Kim

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2020. 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, top 90% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 2 institutions in 1 country.

Kaitlyn L StreightDermatology, Baylor College of Medicine, Houston, USA.
Harry DaoDermatology, Loma Linda University Health, Loma Linda, USA.
Soo Jung KimDermatology, Baylor College of Medicine, Houston, USA.
Baylor College of Medicine · USLoma Linda University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Many dermatologic diseases are implicated in the development of depression. Currently, there is no literature addressing the extent of dermatology residency training on depression screening. Objective Our study aimed to determine the extent of dermatology residency training on depression screening to potentially improve education in this area. Methods We designed a 12-question survey to assess the level of resident training and comfort in depression screening for patients with acne vulgaris, atopic dermatitis, psoriasis, hidradenitis suppurativa, and skin cancer. Fifty-six residents completed the survey, and data for each question was analysed in aggregate. Results Participants found depression screening most important for patients with acne vulgaris, psoriasis, and hidradenitis suppurativa (p<0.0001, 95% CI). Ratings of confidence in screening were similar across all conditions. Most residents reported only occasional screening in the setting of these diseases. Sixty-four percent of participants stated that education on depression screening is not included as part of their curriculum or clinical practice, while 23% were uncertain. Conclusions Our results suggest a lack in relevant training during residency, warranting the inclusion of education on depression screening into the dermatology residency curriculum to facilitate better recognition of the mental health comorbidities of dermatologic diseases.

Indexed as

depression screening in dermatologydermatology educationdermatology residency curriculummental health comorbiditiesquality improvement researchresident educationsurvey research

Identifiers

PMID32754401
PMCPMC7386085
OpenAlexW3037793866

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.