Evidence map›Paper›PMID 34800240›Full record

ArticleJournal of gambling studies2022

Development and Validation of a Near Miss Scale for Assessing Gambling Tendency.

Mehmet Çakıcı, Nuriye Sancar, Ayşe Buran, Gökçe Çakır Şahan, Beniz Yılmaz

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Article in Journal of gambling studies, 2022. 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

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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

5 authors.

Mehmet ÇakıcıDepartment of Psychology, Faculty of Arts and Sciences, Near East University, Lefkoşa-Kibris 10, Mersin, Turkey. mehmet.cakici@neu.edu.tr.ORCID http://orcid.org/0000-0002-7043-183X
Nuriye SancarDepartment of Mathematics, Faculty of Arts and Sciences, Near East University, Nicosia, Cyprus.
Ayşe BuranDepartment of Psychology, Faculty of Arts and Sciences, Near East University, Lefkoşa-Kibris 10, Mersin, Turkey.
Gökçe Çakır ŞahanPembe Köşk Psychiatry Hospital, Karşıyaka, Cyprus.
Beniz YılmazPembe Köşk Psychiatry Hospital, Karşıyaka, Cyprus.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although near-miss is an important tendency indicator for gambling addiction, no scale has been developed to evaluate these feelings. In this study, the aim is to develop a Near Miss Scale (NMS) to assess the tendency of gambling. In the first step, a 38-item measurement tool was prepared by the first author, which was examined by 8 experts. According to their comments and opinions, a 32-item 5-point Likert-type pre-form was created. The study was conducted with 600 gamblers in Northern Cyprus between December 2018-March 2019 and data from 563 of them were included in the statistical analysis. In the questionnaire, Socio-demographic form, Gambling Craving Scale (GCS), South Oaks Gambling Screening Test (SOGST) and NMS were used. With the SPSS 23 and R Studio statistical programs, after calculating the item-total correlations of the items in the NMS form, items with low item total-correlation values were excluded from the scale and 30 items were analysed statistically. In the study, it was seen that the factor loads of the relevant items in NMS were between .715 and .896. Confirmatory factor analysis (CFA) showed that a single factor model in the scale was valid. NMS had a positive correlation with SOGST (r = 0.601) and GCS (r = 0.752). The 2-week test-retest results of NMS with a Cronbach alpha of 0.981 were determined as 0.972. The validity and reliability results suggest that NMS is a valid and reliable as 30-item, one-dimensional measurement tool for assessing gambling tendency among gamblers.

Indexed as

GamblingFactor Analysis, StatisticalHumansPsychometricsReproducibility of ResultsSurveys and QuestionnairesGambling addictionNear-missScale developmentTendency

Identifiers

What OpenQuestion holds

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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.