Evidence map›Paper›PMID 38268608›Full record

ArticleHeliyon2024

Development and Validation of the Compensatory Belief Scale for the Internet Instant Gratification Behavior.

Bin Yin, Yong Shen

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. 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
6.8field-weighted citation impact, top 4% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  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

2 authors at 1 institution in 1 country.

Bin YinLaboratory for Learning and Behavioral Sciences, School of Psychology, Fujian Normal University, Fuzhou, 350117, Fujian, China.
Yong ShenLaboratory for Learning and Behavioral Sciences, School of Psychology, Fujian Normal University, Fuzhou, 350117, Fujian, China.
Fujian Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The concept of "compensatory belief" pertains to an individual's conviction that the negative consequences of a specific behavior can be counteracted by engaging in a subsequent positive behavior. This study sought to devise a scale tailored to gauge compensatory beliefs concerning internet instant gratification behaviors. Methods: Utilizing the Credamo online questionnaire platform, data were amassed from two distinctive cohorts: organizational employees and college students. A collective 1064 responses were amassed. Results: The newly created Compensatory Belief Scale for Internet Instant Gratification Behavior was bifurcated into two versions: one tailored for employees (CBS-IIGB-E) and the other for college students (CBS-IIGB-S). Through an exploratory factor analysis, two factors were discerned, namely "Compensatory Beliefs for Working/Studying " and "Compensatory Beliefs for Resting". A confirmatory factor analysis validated this two-factor model with the following metrics for the employee version: SBχ2 = 54.88, Conclusion: The Compensatory Belief Scale for Internet Instant Gratification Behavior (CBS-IIGB) is a reliable and valid tool for measuring compensatory belief in situations where the allure of immediate internet gratification comes into conflict with long-term objectives, among both organizational employees (CBS-IIGB-E) and college students (CBS-IIGB-S).

Indexed as

Compensatory beliefCompensatory Belief Scale for the Internet Instant Gratification Behavior (CBS-IIGB)Delayed gratificationInternet Instant Gratification BehaviorInternet temptation

Identifiers

PMID38268608
PMCPMC10805770
OpenAlexW4390511865

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.