Evidence map›Paper›PMID 36637885›Full record

ArticleJMIR formative research2023

"I Haven't Been Diagnosed, but I Should Be"-Insight Into Self-diagnoses of Common Mental Health Disorders: Cross-sectional Study.

Lauren A Rutter, Jacqueline Howard, Prabhvir Lakhan, Danny Valdez, Johan Bollen, Lorenzo Lorenzo-Luaces

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
8.3field-weighted citation impact, top 2% 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

23 citing papers in PubMed, 42 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Lauren A RutterDepartment of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States.ORCID https://orcid.org/0000-0002-8852-7602
Jacqueline HowardDepartment of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States.ORCID https://orcid.org/0000-0003-4153-3260
Prabhvir LakhanDepartment of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States.ORCID https://orcid.org/0000-0002-8126-2429
Danny ValdezDepartment of Applied Health Science, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States.ORCID https://orcid.org/0000-0002-2355-9881
Johan BollenLuddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, United States.ORCID https://orcid.org/0000-0001-7031-9293
Lorenzo Lorenzo-LuacesDepartment of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States.ORCID https://orcid.org/0000-0002-8882-0243
Indiana University Bloomington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn recent years, social media has become a rich source of mental health data. However, there is a lack of web-based research on the accuracy and validity of self-reported diagnostic information available on the web.

objectiveAn analysis of the degree of correspondence between self-reported diagnoses and clinical indicators will afford researchers and clinicians higher levels of trust in social media analyses. We hypothesized that self-reported diagnoses would correspond to validated disorder-specific severity questionnaires across 2 large web-based samples.

methodsThe participants of study 1 were 1123 adults from a national Qualtrics panel (mean age 34.65, SD 12.56 years; n=635, 56.65% female participants,). The participants of study 2 were 2237 college students from a large university in the Midwest (mean age 19.08, SD 2.75 years; n=1761, 75.35% female participants). All participants completed a web-based survey on their mental health, social media use, and demographic information. Additionally, the participants reported whether they had ever been diagnosed with a series of disorders, with the option of selecting "Yes"; "No, but I should be"; "I don't know"; or "No" for each condition. We conducted a series of ANOVA tests to determine whether there were differences among the 4 diagnostic groups and used post hoc Tukey tests to examine the nature of the differences.

resultsIn study 1, for self-reported mania (F

conclusionsIn general, if an individual believes that they should be diagnosed with an internalizing disorder, they are experiencing a degree of psychopathology similar to those who have already been diagnosed. Self-reported diagnoses correspond well with symptom severity on a continuum and can be trusted as clinical indicators, especially in common internalizing disorders such as depression and generalized anxiety disorder. Researchers can put more faith into patient self-reports, including those in web-based experiments such as social media posts, when individuals report diagnoses of depression and anxiety disorders. However, replication and further study are recommended.

Indexed as

anxietyassessmentdepressionself-reportsocial media

Identifiers

PMID36637885
PMCPMC9883736
OpenAlexW4313117795

What OpenQuestion holds

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LicenceCC BY
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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.