ArticleHeliyon2020
Digital images of pediatric mental disorders do not accurately represent the conditions.
Article in Heliyon, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Spanish media coverage of youth mental health issues during the COVID-19 pandemic.BMC psychiatry · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveDigital images might contribute to stigma associated with mental disorders. The aim of this study was to investigate whether these images accurately represent pediatric mental disorders, as well as to explore specific image-related factors that influence perception.
methodsFour hundred pictures were retrieved from three stock photograph websites ('Shutterstock', 'iStock' and 'Adobe') and 'Google Images' for mental disorders (ADHD, ASD, and depression) and somatic diseases (asthma, diabetes, and influenza) in childhood. Each picture was scored for gender, age, and emotional load. Data was compared against data from epidemiological studies. Ordinal regression was used to predict emotional load from image-related factors.
resultsThere was a significant difference in gender representation of ADHD, ASD, depression, diabetes, and influenza. With respect to age, models were significantly younger in pictures of depression but older in pictures of influenza. Pictures of ASD, asthma and diabetes were mostly positive; however, images for ADHD, depression and influenza carried more negative connotations. For mental disorders, a more positive emotional load was associated with images of young and/or male models. iStock gave more positive images.
conclusionsDigital images available in stock databases do not accurately represent pediatric mental and somatic disease. For mental disorders, image-related factors (including age, gender and emotional load) may influence societal perception.
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Registered trials
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.