ArticleFrontiers in public health2024
Public perceptions of digital mental health awareness campaign in the Arab Gulf states: a qualitative thematic analysis.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
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
4 citing papers in PubMed.
- Neurodiversity-affirming SEA for ADHD: evaluation of an online program for parents and children in the ultra-orthodox Jewish community.European child & adolescent psychiatry · 2026Article
- Mental-Health Help-Seeking Among Muslims in the Liverpool City Region: A System-Informed Qualitative Study of Knowledge, Attitudes, Practices.Health expectations : an international journal of public participation in health care and health policy · 2026Article
- Artificial Intelligence in Mental Health Care: Task-Specific Perspectives of Professionals in Saudi Arabia.Healthcare (Basel, Switzerland) · 2026Article
- Public Attention to Mpox in China During the Pandemic: Qualitative Analysis of TikTok Data Using Latent Dirichlet Allocation Topic Modeling.Journal of medical Internet research · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mental illness is a significant public health concern and a leading cause of disability worldwide. Research shows a lack of mental health knowledge and inappropriate practices in the Gulf Cooperation Council (GCC) states. Our study aimed to evaluate individuals' perspectives on mental health by analyzing their responses to a digital campaign directed at GCC adolescents. We conducted a qualitative thematic analysis of comments in response to the Gulf Health Council's mental health campaign. The campaign content was shared on four social media platforms: TikTok, YouTube, Instagram, and X. A total of 2,146 comments were included in the analysis. There was a widespread denial of the existence of mental illness. The comments revealed a lack of understanding and insufficient support for individuals dealing with mental health issues. Stigma and discrimination against people with mental illness were evident in the comments. The general perception was that individuals have control over their mental health, often associating mental illness with weakness and lack of willpower. Mental illness was believed to be caused by religious and moral shortcomings, and religion was viewed as the solution. Some comments highlighted the need to acknowledge mental illness and urged the development of strategies to promote mental health. Our research shows a lack of awareness, stigma, and inadequate resources for individuals dealing with mental health issues. It highlights the importance of addressing barriers to mental healthcare and increasing access to support. Interventions focusing on stigma reduction and promoting acceptance of mental health disorders are crucial and require collaborative efforts from various stakeholders.
Indexed as
Identifiers
What OpenQuestion holds
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.