Evidence map›Paper›PMID 38373925›Full record

ArticleBMC public health2024

Analysis of the hikikomori phenomenon - an international infodemiology study of Twitter data in Portuguese.

Francisca Correia Lopes, Mariana Pinto da Costa, Cesar I Fernandez-Lazaro, Francisco J Lara-Abelenda, Victor Pereira-Sanchez, Alan R Teo, Miguel Angel Alvarez-Mon

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
16.8field-weighted citation impact, top 1% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
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

7 authors at 6 institutions in 4 countries.

Francisca Correia LopesInstitute of Biomedical Sciences Abel Salazar, University of Porto, Porto, Portugal.
Mariana Pinto da CostaInstitute of Biomedical Sciences Abel Salazar, University of Porto, Porto, Portugal. mariana.pintodacosta@kcl.ac.uk.ORCID 0000-0002-5966-5723
Cesar I Fernandez-LazaroDepartment of Preventive Medicine and Public Health, School of Medicine, University of Navarra, IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.
Francisco J Lara-AbelendaDepartment of Signal Theory and Communications and Telematic Systems and Computing, School of Telecommunications Engineering, Rey Juan Carlos University, 28942, Madrid, Spain.
Victor Pereira-SanchezChild Mind Institute, New York, NY, USA.
Alan R TeoHealth Services Research & Development Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland, OR, USA.ORCID 0000-0002-2393-088X
Miguel Angel Alvarez-MonDepartment of Medicine and Medical Specialties, Faculty of Medicine and Health Sciences, University of Alcala, Alcala de Henares, Spain.
Universidade do Porto · PTChild Mind Institute · USOregon Health & Science University · USUniversidad de Alcalá · ESUniversidad de Navarra · ESUniversidad Rey Juan Carlos · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHikikomori refers to the extreme isolation of individuals in their own homes, lasting at least six months. In recent years social isolation has become an important clinical, social, and public health problem, with increased awareness of hikikomori around the globe. Portuguese is one of the six most spoken languages in the world, but no studies have analysed the content regarding this phenomenon expressed in Portuguese.

objectiveTo explore the hikikomori phenomenon on Twitter in Portuguese, utilising a mixed-methods approach encompassing content analysis, emotional analysis, and correlation analysis.

methodsA mixed methods analysis of all publicly available tweets in the Portuguese language using a specific keyword (hikikomori) between 1st January 2008 and 19th October 2022. The content analysis involved categorising tweets based on tone, content, and user types, while correlation analysis was used to investigate user engagement and geographical distribution. Statistical analysis and artificial intelligence were employed to classify and interpret the tweet data.

resultsAmong the total of 13,915 tweets generated, in terms of tone 10,731 were classified as "negative", and 3184 as "positive". Regarding content, "curiosities" was the most posted, as well as the most retweeted and liked topic. Worldwide, most of the hikikomori related tweets in Portuguese were posted in Europe, while "individuals with hikikomori" were the users most active posting. Regarding emotion analysis, the majority of tweets were "neutral".

conclusionsThese findings show the global prevalence of the discourse on hikikomori phenomenon among Portuguese speakers. It also indicates an increase in the number of tweets on this topic in certain continents over the years. These findings can contribute to developing specific interventions, support networks, and awareness-raising campaigns for affected individuals.

Indexed as

Artificial IntelligencePhobia, SocialSocial MediaHumansInfodemiologyLanguagePortugalShameHikikomoriInternetInternet addictionLonelinessMental healthSocial isolationSocial mediaSocial withdrawal

Identifiers

PMID38373925
PMCPMC10875796
OpenAlexW4391932514

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.