Evidence map›Paper›PMID 34591021›Full record

ArticleJournal of medical Internet research2021

Finding Relevant Psychoeducation Content for Adolescents Experiencing Symptoms of Depression: Content Analysis of User-Generated Online Texts.

Kim K Dysthe, Ole R Haavet, Jan I Røssberg, Petter B Brandtzaeg, Asbjørn Følstad, Atle Klovning

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. The Depressed Teenage Brain: Chatbot Psychoeducation.Mayo Clinic proceedings. Digital health · 2023
    Article
  5. Article
  6. Article
  7. 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

6 authors at 2 institutions in 1 country.

Kim K DystheDepartment of General Practice/Family Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0001-9292-7986
Ole R HaavetDepartment of General Practice/Family Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0002-6847-8727
Jan I RøssbergDivision of Psychiatric Treatment Research, Department of Psychiatry, University of Oslo, Oslo, Norway.ORCID 0000-0003-4115-9133
Petter B BrandtzaegDepartment of Media and Communication, University of Oslo, Oslo, Norway.ORCID 0000-0002-9010-0800
Asbjørn FølstadSINTEF Digital, Software and Service Innovation, Oslo, Norway.ORCID 0000-0003-2763-0996
Atle KlovningDepartment of General Practice/Family Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0002-2917-1845
University of Oslo · NOSINTEF · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSymptoms of depression are frequent in youth and may develop into more severe mood disorders, suggesting interventions should take place during adolescence. However, young people tend not to share mental problems with friends, family, caregivers, or professionals. Many receive misleading information when searching the internet. Among several attempts to create mental health services for adolescents, technological information platforms based on psychoeducation show promising results. Such development rests on established theories and therapeutic models. To fulfill the therapeutic potential of psychoeducation in health technologies, we lack data-driven research on young peoples' demand for information about depression.

objectiveOur objective is to gain knowledge about what information is relevant to adolescents with symptoms of depression. From this knowledge, we can develop a population-specific psychoeducation for use in different technology platforms.

methodsWe conducted a qualitative, constructivist-oriented content analysis of questions submitted by adolescents aged 16-20 years to an online public information service. A sample of 100 posts containing questions on depression were randomly selected from a total of 870. For analysis, we developed an a priori codebook from the main information topics of existing psychoeducational programs on youth depression. The distribution of topic prevalence in the total volume of posts containing questions on depression was calculated.

resultsWith a 95% confidence level and a ±9.2% margin of error, the distribution analysis revealed the following categories to be the most prevalent among adolescents seeking advice about depression: self-management (33%, 61/180), etiology (20%, 36/180), and therapy (20%, 36/180). Self-management concerned subcategories on coping in general and how to open to friends, family, and caregivers. The therapy topic concerned therapy options, prognosis, where to seek help, and how to open up to a professional. We also found young people dichotomizing therapy and self-management as opposite entities. The etiology topic concerned stressors and risk factors. The diagnosis category was less frequently referred to (9%, 17/180).

conclusionsSelf-management, etiology, and therapy are the most prevalent categories among adolescents seeking advice about depression. Young people also dichotomize therapy and self-management as opposite entities. Future research should focus on measures to promote self-management, measures to stimulate expectations of self-efficacy, information about etiology, and information about diagnosis to improve self-monitoring skills, enhancing relapse prevention.

Indexed as

Mental Health ServicesSelf-ManagementAdaptation, PsychologicalAdolescentCaregiversDepressionHumansadolescentdepressiondigital healthearly medical interventioneducatione-healthinformation contentinternetonlinepreventive psychiatrypsychoeducationself-report

Identifiers

PMID34591021
PMCPMC8517813
OpenAlexW3196155135

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.