Psychometric properties of the Smartphone Addiction Inventory - Short Form (SPAI-SF) in Brazilian adolescents

Andrade, André Luiz Monezi; Spritzer, Daniel Tornaim; Scatena, Adriana; Pinheiro, Bruno de Oliveira; Silva, Gabriel Teixeira da; Kim, Hyoun S.; Breda, Vitor; Oliveira, Wanderlei Abadio de; Micheli, Denise De

doi:10.1016/j.psychres.2022.115001

Cited by 9 publications

(5 citation statements)

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“…Similar to the study of Al-Barashdi et al (20), we also found that the risk of smartphone addiction increases as the monthly income increases. JH Kim, in (8,26). Our study found that both the risk of smartphone addiction and poor sleep quality increase with increasing age in adolescents.…”

Section: Discussionmentioning

confidence: 51%

Smartphone Addiction and Sleep Quality in Adolescents

et al. 2023

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Objective: To determine the frequency of smartphone addiction and poor sleep in high school adolescents and to evaluate the relationship between phone addiction and sleep, together with demographic characteristics. Methods: A face-to-face survey was applied to 730 high school students in the Kahta district of Adıyaman, Turkey, between November 2021 and January 2022. The Smartphone Addiction Inventory-Short Form (SPAI-SF) was used to assess smartphone addiction, and the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. Results: The rate of smartphone addiction in adolescents was 41%, and poor sleep quality was 61%. When smartphone addiction increases, sleep quality decreases, and when sleep quality decreases smartphone addiction increases. Smartphone addiction and poor sleep quality were higher in girls compared to boys. As the parents’ education level and family income increase, the level of addiction increases, but sleep quality remain the same. We found that as age increases, the risk of smartphone addiction and the risk of deterioration in sleep quality increase. Conclusion: Smartphone addiction and poor sleep quality trigger each other in a vicious circle. The COVID-19 pandemic may have made smartphone addiction the most common addiction in the world. This addiction can increase the risk of substance addiction by impairing the quality of sleep in adolescents and lead to many physical, social, and mental problems. A multidisciplinary approach is vital for solving the problem.

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Section: Discussionmentioning

confidence: 51%

Smartphone Addiction and Sleep Quality in Adolescents

et al. 2023

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“…PSU is typically assessed with various scales, including the Mobile Phone Problem Use Scale (MPPUS; Bianchi & Phillips, 2005 ), the Problematic Mobile Phone Use Questionnaire (PMPUQ; Billieux, der Linden, & Rochat, 2008 ), the Smartphone Addiction Scale (SAS; Kwon, Lee, et al., 2013 ), the Short Version of Smartphone Addiction Scale (SAS-SV; Kwon, Kim, Cho, & Yang, 2013 ), the Smartphone Addiction Inventory (SPAI; Lin et al., 2014 ) and the Short-Form of Smartphone Addiction Inventory (SPAI-SF; Lin, Pan, Lin, & Chen, 2017 ), which measure factors like tolerance, withdrawal, overuse, loss of control and dangerous/prohibited use. While cross-cultural validation studies have shown satisfactory psychometric properties for these scales (e.g., Agus, Mascia, Bonfiglio, & Penna, 2022 ; Andrade et al., 2022 ; Khoury et al., 2017 ; Lopez-Fernandez, Honrubia-Serrano, Freixa-Blanxart, & Gibson, 2014 , 2018 ; Sfendla et al., 2018 ; Wang, Long, Liu, Liu, & Billieux, 2020 ; Zhao, Rafik-Galea, Fitriana, & Song, 2022 ), we would argue that there is room for improvement.…”

Section: Introductionmentioning

confidence: 75%

“…In our study, we tested the SUPIQ's convergent validity with smartphone use statistics, mental health problems, and the SAS-SV. Future research could explore the overlap between the SUPIQ and other behavioral and substance-related addictions (e.g., Andrade et al., 2022 ; Kwon, Lee, et al., 2013 ) or the possible correlations between the SUPIQ and other variables like personality traits ( Giustiniani et al., 2022 ) and childhood trauma ( Fan et al., 2023 ). We have also tested the explanatory power of the SUPIQ in comparison to the SAS-SV ( Kwon, Kim, et al., 2013 ), while future studies would benefit from employing the full versions of the PMPUQ ( Billieux et al., 2008 ) and SAS ( Kwon, Lee, et al., 2013 ) to confirm the predictive power of the complete SUPIQ.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, we will compare the SUPIQ with the SAS-SV to assess its explanatory power in hierarchical multiple regression models ( Kwon, Kim, et al., 2013 ; Olson et al., 2022 ). While prior PSU scale studies have primarily focused on student and adolescent populations (e.g., Andrade et al., 2022 ; Cheung et al., 2019 ; Khoury et al., 2017 ; Leung, 2008 ; Lin et al., 2014 ; Lopez-Fernandez et al., 2014 ; Pavia, Cavani, Di Blasi, & Giordano, 2016 ; Walsh, White, & McDYoung, 2010 ; Wang et al., 2020 ; see Supplementary Table S1 ), leaving the applicability of these scales to the general population largely unexplored ( Busch, Hausvik, Ropstad, & Pettersen, 2021 ; Rosales & Fernández-Ardèvol, 2019 ). We will extend its applicability using two separate samples: one from the university community and a general population sample.…”

Section: Introductionmentioning

confidence: 99%

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From everyday life to measurable problematic smartphone use: The development and validation of the Smartphone Use Problems Identification Questionnaire (SUPIQ)

Su,

Cousijn,

Molenaar

et al. 2024

JBA

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Background and aimsProblematic smartphone use (PSU) has gained attention, but its definition remains debated. This study aimed to develop and validate a new scale measuring PSU-the Smartphone Use Problems Identification Questionnaire (SUPIQ).MethodsUsing two separate samples, a university community sample (N = 292) and a general population sample (N = 397), we investigated: (1) the construct validity of the SUPIQ through exploratory and confirmatory factor analyses; (2) the convergent validity of the SUPIQ with correlation analyses and the visualized partial correlation network analyses; (3) the psychometric equivalence of the SUPIQ across two samples through multigroup confirmatory factor analyses; (4) the explanatory power of the SUPIQ over the Short Version of Smartphone Addiction Scale (SAS-SV) with hierarchical multiple regressions.ResultsThe results showed that the SUPIQ included 26 items and 7 factors (i.e., Craving, Coping, Habitual Use, Social Conflicts, Risky Use, Withdrawal, and Tolerance), with good construct and convergent validity. The configural measurement invariance across samples was established. The SUPIQ also explained more variances in mental health problems than the SAS-SV.Discussion and conclusionsThe findings suggest that the SUPIQ shows promise as a tool for assessing PSU. Further research is needed to enhance and refine the SUPIQ as well as to investigate its clinical utility.

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“…These criteria were selected based on established guidelines (Cheung & Rensvold, 2002). To achieve the best-fit factor structure, all Modification Indices (MI) exceeding 10 (MI > 10.00) were analyzed, with consideration given solely to item covariances within the same dimension (Andrade et al, 2023a;Andrade et al, 2023b).…”

Section: Sociodemographic Datamentioning

confidence: 99%

Adaptation and validation of the Psychologist and Counsellor Self-Efficacy Scale (PCES) among Brazilian psychologists and psychology students

Preuhs,

Da Silva,

Da Silva

et al. 2023

CienciasPsi

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This study aimed to: (i) Translate, adapt, and evaluate the linguistic and semantic properties of the Psychologist and Counsellor Self-Efficacy Scale (PCES) for use among psychology students and psychologists in Brazil; (ii) Assess the psychometric attributes of the adapted PCES, including its construct validity and other related psychometric properties. A total of 2,139 participants, comprising psychologists and psychology students (Mage = 25.36 years; SD = 9.46), partook in this study. The PCES exhibited commendable fit indices (CFI = .990; TLI = .989; SMR = .043), and multigroup confirmatory factor analysis revealed a consistent level of invariance between students and practicing psychologists, as well as between male and female participants. Network analysis offered significant insights into the distribution of factors, while the convergent validity of PCES was corroborated by its correlations with the subscales of the General Perceived Self-Efficacy Scale (GPSS). These findings unequivocally affirm the reliability and suitability of PCES as an assessment instrument for both psychologists and psychology students in the Brazilian context.

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Psychometric properties of the Smartphone Addiction Inventory - Short Form (SPAI-SF) in Brazilian adolescents

Cited by 9 publications

References 44 publications

Smartphone Addiction and Sleep Quality in Adolescents

Smartphone Addiction and Sleep Quality in Adolescents

From everyday life to measurable problematic smartphone use: The development and validation of the Smartphone Use Problems Identification Questionnaire (SUPIQ)

Adaptation and validation of the Psychologist and Counsellor Self-Efficacy Scale (PCES) among Brazilian psychologists and psychology students

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