Evidence map›Paper›PMID 39534145›Full record

ArticleIndustrial psychiatry journal2024

Analysis of the quality of information provided by "Dr. YouTube™" on premature ejaculation.

Swarndeep Singh, Bastabika Neupane, Omkar Dhungel, Pawan Sharma

Abstract read
In one paragraph

Article in Industrial psychiatry journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Swarndeep SinghDepartment of Psychiatry, Vardhman Mahavir Medical College and Safdarjung Hospital, Delhi, India.
Bastabika NeupaneDepartment of Psychiatry, Patan Academy of Health Sciences, School of Medicine, Lalitpur, Nepal.
Omkar DhungelDepartment of Psychiatry, Patan Academy of Health Sciences, School of Medicine, Lalitpur, Nepal.
Pawan SharmaDepartment of Psychiatry, Patan Academy of Health Sciences, School of Medicine, Lalitpur, Nepal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: YouTube Aim: To assess the quality and reliability of information available on the treatment of premature ejaculation (PME) on YouTube Materials and Methods: A total of 151 (Hindi: 109, English: 42) YouTube videos were selected for assessment. The quality was evaluated using structured tools: Patient Education Materials Assessment Tool (PEMAT); and a 5-point modified DISCERN questionnaire (Range: 1-serious shortcomings; 5-minimal shortcomings). PEMAT assesses the understandability and actionability of video as separate percentages. Results: Three most common treatments suggested for PME were Kegel exercise (22.5%), start-stop technique (21.9%), and antidepressant medications (20.5%). Antidepressant medications, stop-squeeze techniques, and psychotherapy were more frequently suggested in English videos, whereas ayurvedic or herbal medicines were more frequently suggested in Hindi videos. About two-thirds of videos presented information in an easy-to-understand and actionable manner (PEMAT scores ≥70%). Only 6% of videos had a DISCERN score of ≥4, indicating good overall quality of information presented in them. Conclusion: People likely to encounter poor-quality information when seeking information for PME treatment on YouTube. A large number of videos suggested ineffective or unproven treatment strategies for PME. Healthcare professionals need to be mindful of this while counselling patients, and guide them regarding useful and reliable sources of health information available online.

Indexed as

DISCERNinternetmisinformation premature ejaculationPEMAT

Identifiers

PMID39534145
PMCPMC11553584

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Registered trials

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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.