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      Smartphone Addiction Inventory (SPAI): Translation, adaptation and validation of the tool in Spanish adult population

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          Abstract

          The wide functionality and the vast range of attributes offered by smartphones has led to a substantial increase in the average amount of time these devices are used per day. An excessive use of these tools has been shown to result in symptomatology similar to psychological disorders caused by substance addiction. In Spain, smartphone use has risen exponentially but the effects of this increase remain unclear. Therefore, an instrument is required to help determine the extent of smartphone addiction in the Spanish population. The Smartphone Addiction Inventory (SPAI) is a valid and reliable mean to identify and measure smartphone addiction and so, the aim of this research is the translation and adaptation of SPAI to Spanish, as well as the analysis of its psychometric properties in a Spanish adult population of 2,958 adults, at the University of Valencia. A multiphase-interactive model has been used, based on classical translation–back-translation methods to translate and adapt the SPAI. Moreover, a confirmatory factor analysis to verify that the inventory showed acceptable goodness of fit indices (χ 2 293 = 4795.909, Comparative Fit Index = 0.927, Tucker–Lewis Index = 0.919, Root Mean Square Error of approximation = 0.072, and Standardised Root Mean square Residual = 0.051) has been carried out. Also good reliability has been found for the global inventory (Cronbach’s alpha = 0.949), and each of its corresponding factors: compulsive behaviour, functional impairment, abstinence, and tolerance (Cronbach’s alpha = 0.856, 0.888, 0.855, and 0.712, respectively). Hence, the SPAI has been adequately translated and adapted for its use in Spain and therefore it is a useful tool for evaluating the degree of smartphone addiction in the Spanish adult population.

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          Most cited references40

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          The Smartphone Addiction Scale: Development and Validation of a Short Version for Adolescents

          Objective This study was designed to investigate the revised and short version of the smartphone addiction scale and the proof of its validity in adolescents. In addition, it suggested cutting off the values by gender in order to determine smartphone addiction and elaborate the characteristics of smartphone usage in adolescents. Method A set of questionnaires were provided to a total of 540 selected participants from April to May of 2013. The participants consisted of 343 boys and 197 girls, and their average age was 14.5 years old. The content validity was performed on a selection of shortened items, while an internal-consistency test was conducted for the verification of its reliability. The concurrent validity was confirmed using SAS, SAPS and KS-scale. Receiver operating characteristics analysis was conducted to suggest cut-off. Results The 10 final questions were selected using content validity. The internal consistency and concurrent validity of SAS were verified with a Cronbach's alpha of 0.911. The SAS-SV was significantly correlated with the SAS, SAPS and KS-scale. The SAS-SV scores of gender (p<.001) and self-evaluation of smartphone addiction (p<.001) showed significant difference. The ROC analysis results showed an area under a curve (AUC) value of 0.963(0.888–1.000), a cut-off value of 31, sensitivity value of 0.867 and specificity value of 0.893 in boys while an AUC value of 0.947(0.887–1.000), a cut-off value of 33, sensitivity value of 0.875, and a specificity value of 0.886 in girls. Conclusions The SAS-SV showed good reliability and validity for the assessment of smartphone addiction. The smartphone addiction scale short version, which was developed and validated in this study, could be used efficiently for the evaluation of smartphone addiction in community and research areas.
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            Psychological predictors of problem mobile phone use.

            Mobile phone use is banned or illegal under certain circumstances and in some jurisdictions. Nevertheless, some people still use their mobile phones despite recognized safety concerns, legislation, and informal bans. Drawing potential predictors from the addiction literature, this study sought to predict usage and, specifically, problematic mobile phone use from extraversion, self-esteem, neuroticism, gender, and age. To measure problem use, the Mobile Phone Problem Use Scale was devised and validated as a reliable self-report instrument, against the Addiction Potential Scale and overall mobile phone usage levels. Problem use was a function of age, extraversion, and low self-esteem, but not neuroticism. As extraverts are more likely to take risks, and young drivers feature prominently in automobile accidents, this study supports community concerns about mobile phone use, and identifies groups that should be targeted in any intervention campaigns.
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              Development and Validation of a Smartphone Addiction Scale (SAS)

              Objective The aim of this study was to develop a self-diagnostic scale that could distinguish smartphone addicts based on the Korean self-diagnostic program for Internet addiction (K-scale) and the smartphone's own features. In addition, the reliability and validity of the smartphone addiction scale (SAS) was demonstrated. Methods A total of 197 participants were selected from Nov. 2011 to Jan. 2012 to accomplish a set of questionnaires, including SAS, K-scale, modified Kimberly Young Internet addiction test (Y-scale), visual analogue scale (VAS), and substance dependence and abuse diagnosis of DSM-IV. There were 64 males and 133 females, with ages ranging from 18 to 53 years (M = 26.06; SD = 5.96). Factor analysis, internal-consistency test, t-test, ANOVA, and correlation analysis were conducted to verify the reliability and validity of SAS. Results Based on the factor analysis results, the subscale “disturbance of reality testing” was removed, and six factors were left. The internal consistency and concurrent validity of SAS were verified (Cronbach's alpha = 0.967). SAS and its subscales were significantly correlated with K-scale and Y-scale. The VAS of each factor also showed a significant correlation with each subscale. In addition, differences were found in the job (p<0.05), education (p<0.05), and self-reported smartphone addiction scores (p<0.001) in SAS. Conclusions This study developed the first scale of the smartphone addiction aspect of the diagnostic manual. This scale was proven to be relatively reliable and valid.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                17 October 2018
                2018
                : 13
                : 10
                : e0205389
                Affiliations
                [1 ] Hospital General Universitario de Valencia, Valencia, Spain
                [2 ] Nursing Department, University of Valencia, Valencia, Spain
                North Carolina Neuropsychiatry Clinics, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-5170-891X
                Article
                PONE-D-17-38139
                10.1371/journal.pone.0205389
                6192628
                30332481
                737fea59-6812-4345-b465-50833705ae69
                © 2018 Simó-Sanz et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 December 2017
                : 16 September 2018
                Page count
                Figures: 1, Tables: 3, Pages: 12
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Engineering and Technology
                Equipment
                Communication Equipment
                Cell Phones
                Biology and Life Sciences
                Psychology
                Addiction
                Social Sciences
                Psychology
                Addiction
                Biology and Life Sciences
                Psychology
                Addiction
                Behavioral Addiction
                Social Sciences
                Psychology
                Addiction
                Behavioral Addiction
                Social Sciences
                Sociology
                Culture
                Cross-Cultural Studies
                People and Places
                Population Groupings
                Age Groups
                Biology and Life Sciences
                Psychology
                Addiction
                Substance Addiction
                Social Sciences
                Psychology
                Addiction
                Substance Addiction
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Substance-Related Disorders
                Substance Addiction
                Medicine and Health Sciences
                Public and Occupational Health
                Substance-Related Disorders
                Substance Addiction
                People and places
                Geographical locations
                Europe
                European Union
                Spain
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Factor Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Factor Analysis
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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