Evidence map›Paper›PMID 37416490›Full record

ArticleMethodsX2023

Peer assessment as a method for measuring harmful internet use.

W W Koczkodaj, A Kowalczyk, M Mazurek, W Pedrycz, G Redlarski, E Rogalska, D Strzalka, A Szymanska, A Wilinski, O S Xue

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in MethodsX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

10 authors.

W W KoczkodajComputer Science, Laurentian University, Sudbury, ON P3E 2C6 Canada.
A KowalczykOphthalmology Eye and Ear Hospital, Melbourne University, Australia.
M MazurekDepartment of Complex Systems, Rzeszow University of Technology, Rzeszow, 35-959 Poland.
W PedryczDepartment of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2R3 Canada.
G RedlarskiBioTechMed Center, Faculty of Electronics & Control Engineering, Gdańsk University of Technology, Gdańsk, Poland.
E RogalskaInstitute of Pedagogy, University of Szczecin, Szczecin, 70-453 Poland.
D StrzalkaDepartment of Complex Systems, Rzeszów University of Technology, Rzeszów, 35-959 Poland.
A SzymanskaInstitute of Psychology, Cardinal Stefan Wyszynski University, Warsaw, 01-815 Poland.
A WilinskiComputer Science and New Technologies Department, WSB Merito University Gdańsk, Gdańsk, Poland.
O S XueComputer Science, Laurentian University, Sudbury, ON P3E 2C6 Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Harmful Internet use (HIU) describes unintended use of the Internet. It could be both self-harm and harming others. Our research goal is to develop a more accurate method for measuring HIU by this novel peer assessment. As such, it may become, with our call for more research, a paradigm shift supplementing every rating scale or other type of Internet use assessment. In addition to classic statistical analysis, structural equations have been employed. Results indicate that the true positive rate (TPR) is substantially higher than assessed in other studies.•Peer assessment improvement.•AUC for ROC was computed to establish cut-off points for the used scale.•Results obtained by the Structural Equation model indicate that parental care has a moderate influence on subjects' attempts to fight HIU.

Indexed as

Differential evolutionHarmful internet use (HIU)MeasurementPA4HIU measurePath analysisPeer assessmentRating scaleStructural equations model

Identifiers

PMID37416490
PMCPMC10320586

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.