Evidence map›Paper›PMID 35095659›Full record

ArticleFrontiers in psychology2021

Social Networks Addiction (SNA-6) - Short: Validity of Measurement in Mexican Youths.

Edwin Salas-Blas, César Merino-Soto, Berenice Pérez-Amezcua, Filiberto Toledano-Toledano

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Edwin Salas-BlasInstituto de Investigación de Psicología, Universidad de San Martín de Porres, Lima, Peru.
César Merino-SotoInstituto de Investigación de Psicología, Universidad de San Martín de Porres, Lima, Peru.
Berenice Pérez-AmezcuaCentro de Investigación Transdisciplinar en Psicología, Universidad Autónoma del Estado de Morelos, Cuernavaca, Mexico.
Filiberto Toledano-ToledanoUnida de Investigación en Medicina Basada en Evidencias, Hospital Infantil de México Federico Gómez, Mexico City, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The excessive use of social networks needs to be addressed, and this phenomenon needs to be measured for the purpose of evaluation, prevention, and intervention among adolescents and young people. The objective of the study was to adapt and psychometrically validate the Brief Scale of Addiction to Social Networks (SNA-6) among Mexican adolescents and young adults. The participating sample consisted of 2,789 students from 6 public educational campuses in Cuernavaca (Morelos, Mexico). Data collection was carried out through a web platform to strictly maintain anonymity, voluntary participation, and confidentiality. Data analysis first focused on the detection of possible response biases (random intercept model and careless/insufficient effort), the quality of the response structure partial credit model (PCM), dimensionality (CFA and invariance), and the relationship with external variables. It was found that when the range of efficient response options was limited to less than five, reliability was high (0.91), and unidimensionality was maintained. Response biases slightly affected the dimensional structure of the instrument. Measurement invariance reached scalar invariance in the sex, age, and campus groups. The association with sensation seeking and depression, controlling for sex and age covariates, was statistically significant, small, and theoretically consistent. Implications of the results are discussed.

Indexed as

addictionadolescentsMexicanrandom intercept modelsocial networksvalidity

Identifiers

PMID35095659
PMCPMC8790061

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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.