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χ2 = 274.18; d.f. = 265; p = 0.34; RMSEA = 0.021, GFI = 0.97; AGFI = 0.97; CFI = 1; NFI = 1; and SRMR = 0.06.
Source publication
Mobile phone addiction has attracted much attention recently and is showing similarity to other substance use disorders. Because no studies on mobile phone addiction had yet been conducted in Spain, we developed and validated a questionnaire (Cuestionario de Abuso del Teléfono Móvil, ATeMo) to measure mobile phone abuse among young adults in Spanis...
Citations
... 3 Recognizing the complexities of translating and adapting psychological assessment tools across cultural boundaries and the potential for mistranslation, as highlighted by Mikulic and Muños, 38 some researchers have opted to develop assessment instruments directly within their cultural context. 9,14 This approach is illustrated by the creation of specific tools in Spanish, notably the Test of Mobile Phone Dependence (TMP) 10 for adolescents and the ATeMo scale 11 for young Spaniards. These instruments, which are based on the Diagnostic and Statistical Manual for Mental Disorders-Fourth Edition-Text Revision criteria for substance use disorders, offer a detailed exploration of mobile phone dependence. ...
... The PSSNUS revealed five distinct factors: 1) Psychological dependence (PD), which encompasses an individual's compelling need to have the smartphone close at hand and to frequently check it, experiencing discomfort when not using the device. This dimension is possibly the most commonly reported among other multidimensional scales, with instruments such as the SAS, 9 its Spanish abbreviated version, 37 the ATeMo, 11 the CPDQ, 34 and the Spanish version of the MMPUS 67 evaluating very similar aspects. 2) Online interaction preference (OIP), reflecting a tendency to resolve conflicts and express emotions via digital means rather than in-person, to avoid the discomfort of face-to-face interactions. ...
... However, in terms of the constitutive dimensions of these instruments, it has not been found that they exhibit a higher level of dependence or addiction. 10,11 Thus, it is noteworthy that the DRD dimension emphasizes the desire for social acceptance, illustrating the psychosocial component of our scale, which is almost absent in the rest of the instruments mentioned. The higher total PSSNUS scores among females might be attributed to the fact that three (OIP, DRD, and SNCS) out of the five dimensions are associated with an impact on social functioning. ...
Purpose
Addressing the complex pattern of digital behaviors and interactions among youth, this research introduces a novel comprehensive scale, the Problematic Smartphone and Social Network Use Scale (PSSNUS), meticulously developed and validated across five studies.
Methods
Using a mixed-methods approach across five stages, including focus groups (Study 1; n = 31), cognitive interviews (Study 2; n = 16), exploratory factor analysis (Study 3; n = 316), and expert panel (Study 4; n = 4), this procedure reduced 58 initial items to an 18-item scale. Subsequently, a confirmatory factor analysis and further analyses (Study 5; n = 355) examined the factorial structure’s replicability, reliability, and validity of the scale.
Results
The PSSNUS manifested as a reliable (ω ranging 0.70–0.89) instrument, comprising a structure with five key factors (x² = 173.994, df = 125, p = 0.002, CFI = 0.994, CFI = 0.993, SRMR = 0.039, and RMSEA = 0.027) that capture both individual and social aspects of this construct: Psychological dependence (PD), Online interaction preference (OIP), Digital recognition desire (DRD), Social networks control seeking (SNCS), and Productivity loss (PL). Minor gender differences in both the DRD factor and in the overall score were found, with females scoring higher. The PSSNUS showed convergent and divergent validity through significant but modest correlations with daily smartphone usage hours, procrastination, emotional intelligence and mental health symptomatology (anxiety, depression and stress). This measure further exhibited incremental validity, controlling for other possible predictors, regarding anxiety, depression, and stress (6.5, 11.5 and 7.5% of additional variance explained), highlighting the DRD dimension’s unique predictive power.
Conclusion
Emerging as a solid instrument, the PSSNUS broadens the concept of problematic smartphone use among young Spaniards to include social functioning aspects, serving as an interesting tool for those aiming to explore further the adverse influence of digital media on youth.
... 3. A significant association between socio-demographic differences (specifically: age, gender and occupation being students) and smartphone dependency [32,33,88,91,105,106,115]. 4. A significant relationship between social norms and increased smartphone dependency [25,44]. ...
... Mehrere Studien berichteten, dass auf exzessive Smart-phonenutzer_innen typische Suchtkriterien zutreffen können, wie z. B. Kontrollverlust, Craving, Entzugserscheinungen, Toleranzaufbau, die weitere Fortdauer der Nutzung trotz des Auftretens negativer Konsequenzen, Nutzung in gefährlichen Situationen, Stimmungsmodifikation, negative Effekte auf das soziale, private und berufliche Leben, physische Probleme, sowie Vernachlässigung anderer Bereiche (Csibi, Griffiths, Cook, Demetrovics & Szabo, 2018;Kwon, Lee et al., 2013;Lee, Kim et al., 2017;Lin et al., 2014;Lin et al., 2016;Merlo, Stone & Bibbey, 2013;Olivencia-Carrión, Ramírez-Uclés, Holgado-Tello & López-Torrecillas, 2018;Pamuk & Atli, 2016;Rozgonjuk, Rosenvald, Janno & Täht, 2016). Besonders im Vordergrund stünde die Beeinträchtigung täglicher Erledigungen und Aufgaben (Kwon, Kim, Cho & Yang, 2013;Parasuraman, Sam, Yee, Chuon & Ren, 2017), sowie der negative Einfluss auf die akademische Leistung und weitere kognitive Einbußen, wie z. ...
Zusammenfassung: Ziel: In der Fachwelt besteht noch große Uneinigkeit im Hinblick auf eine mögliche Klassifikation exzessiver Smartphone-Nutzung (ESN) als Störung aufgrund einer Verhaltenssucht. In diesem Positionspapier werden relevante inhaltliche und methodische Aspekte bisheriger Forschungsarbeiten zum Thema ESN dargestellt. Daraus werden Empfehlungen abgeleitet, welche Vorgehensweisen bei zukünftigen Forschungsarbeiten verstärkt Berücksichtigung finden sollten. Schlussfolgerungen: Unsere Empfehlungen umfassen folgende Punkte: 1. Entwicklung und konsistente Nutzung von Smartphone-basierten Messinstrumenten, die die Erhebung von Echtzeitnutzungsdaten und das Vorlegen von zeitgesteuerten Fragebögen erlauben, 2. Validierung dieser Instrumente an großen, repräsentativen Stichproben in Deutschland, 3. Untersuchungen mittels Echtzeit-Messinstrumenten zur Beantwortung der Frage, inwiefern ESN Suchtcharakter annehmen kann, sprich inwieweit zentrale Suchtkriterien erfüllt werden, 4. Klärung der zentralen Frage, inwiefern ESN spezifisch (d. h. die Nutzung von spezifischen Smartphone-Funktionen wie z. B. soziale Netzwerke) oder generalisiert (d. h. im Sinne eines Verhaltensmusters der allgemeinen Smartphone-Überbeanspruchung) erfolgt. Langfristig sollten weitere Studien zur Neurobiologie, sowie zur Langzeitstabilität von ESN durchgeführt werden, bevor die Klassifikation der ESN als Störung aufgrund einer Verhaltenssucht empfohlen werden kann.
... Para estos autores lo que define a una adicción no es únicamente la frecuencia de ocurrencia de una conducta, sino la presencia de síntomas de tolerancia y abstinencia porque estos dos criterios diagnósticos podrían darse con y sin sustancias. En esta misma dirección otros investigadores han definido las conductas adictivas como toda conducta que representa una pérdida de control por parte del sujeto ya sea de tipo comportamental o de consumo de drogas, que en el transcurrir generan dependencia, tolerancia y síndrome de abstinencia, con el consiguiente desequilibrio general en la vida de la persona (Becoña & Cortés, 2010;Olivencia-Carrión et al., 2018;Rodríguez-Monje et al., 2019). Las adicciones no solo se limitan al uso y abuso de sustancias como: cannabis, anfetaminas, cocaína, opiáceos, cafeína, nicotina, ingesta de bebidas alcohólicas, sino también a aquellas prácticas de conductas inofensivas que en determinadas circunstancias pueden convertirse en adictivos e interferir gravemente en la vida cotidiana de las personas afectando su salud integral (Chóliz et al., 2016). ...
Impacto del distrés y la intolerancia a la incertidumbre sobre las conductas adictivas en universitarios en tiempos de pandemia.
... In particular, we sought to compare males and females in order to understand how this socio-demographic variable may influence smartphone overuse in terms of addiction and in relation to the factors that may lead to such overuse. Some studies emphasise that females are more at risk of PSU [37,116,117,118,119,120]; fewer studies highlight the opposite [41]. Some studies [42] show no differences between females and males in mobile phone use. ...
The Mobile Phone Problematic Use Scale (MPPUS) is a self-report measure developed to identify the problematic use of mobile phones (PSU) among adults. The purpose of this study was to create an Italian version. A sample of 568 Italian adults completed the MPPUS, presented in association with another validated scale for the assessment of smartphone addiction.
We carried out exploratory factor analyses on the MPPUS. Findings emphasised that the Italian version of the MPPUS fits a bi-factor model, in which the general factor ‘PSU’ was found, including two additional specific factors (i.e., ‘Withdrawal and social aspects’ and ‘Craving and escape from other problems’).
The MPPUS was correlated with the Smartphone Addiction Scale short version. With respect to criterion-oriented validity, the MMPUS was also evaluated in relation to socio-demographic variables (i.e., age and gender). The internal consistency and temporal stability of the scales (test–retest assessment after three months) were confirmed.
... En los años pre pandemia por COVID-19 ya existían grandes preocupaciones en la comunidad académica por el uso indiscriminado y ocioso del celular en los espacios de aprendizaje dado el impacto negativo en el rendimiento académico de los universitarios (Askew et al., 2019;Olivencia-Carrión et al., 2018;Senel et al., 2019). Con las medidas de confinamiento adoptadas como estrategia de bioseguridad durante la pandemia en todo el mundo, y en el Perú, declarada con carácter obligatorio (Decreto Supremo N° 044-2020-PCM) desde 15 de marzo del 2020, llevó a la suspensión de clases en las universidades, hecho que a su vez obligó a los estudiantes a pasar gran parte del tiempo en sus hogares y dedicar el tiempo libre o de ocio al uso del internet, smartphones y los videojuegos (Gao et al., 2020), que con el paso de tiempo conllevó a un uso descontrolado y problemático (Sixto-Costoya et al., 2021) y en algunos casos sobrellevó a desarrollar adicciones tecnológicas (Jalal et al., 2020). ...
... Nuestros resultados se aproximan a lo reportado por Carbonell et al. (2010) quienes aplicaron un programa para el uso saludable de las tecnologías informáticas (internet, móvil y videojuegos) para adolescentes, reportando que su programa de intervención generó cambios significativos reduciendo el uso de las tecnologías en el grupo experimental en comparación al grupo control. Cabe señalar que los objetivos preventivos son diferentes entre las adicciones químicas y las conductuales (Olivencia-Carrión et al., 2018), en este sentido en lo referente a la intervención temprana o tratamiento de las adicciones a internet o las tecnologías, con los años se ha logrado determinar que no se puede llegar a la abstinencia total del uso de internet, sino plantear una opción más realista que consiste en entrenar a los estudiantes en hacer uso adecuado y consciente de las tecnologías (Echeburúa et al., 2005;Greenfield, 2018;Young, 2011). La preocupación por reducir la adicción a internet ya se ha dado en otros países, por ejemplo en Hong Kong el gobierno ha movilizado recursos logísticos, humanos y tecnológicos para reducir el uso problemático o adicción al internet, con el objetivo de fortalecer la conciencia pública y optimizar la alfabetización digital a través del desarrollo de temas como las consecuencias adversas del uso Propósitos y Representaciones Mayo-Agosto 2022, 10(2), e1517 https://doi.org/10.20511/pyr2022.v10n2.1517 ...
Objetivo: Se evaluó los efectos de un programa de prevención en línea sobre las adicciones tecnológicas y disposiciones cognitiva-afectivas en universitarios durante la pandemia COVID-19. Método: Participaron en la muestra 42 estudiantes, de los cuales 21 conformaron el grupo experimental (GE) y los otros 21 estudiantes el control (GC). Se utilizaron las escalas de eficacia académica y engagement académico, así como los test de adicción al teléfono móvil, al internet y a los videojuegos. Resultados: La aplicación del programa redujo significativamente la adicción al internet, teléfono móvil y videojuegos y a la vez aumentó significativamente la valoración positiva del compromiso académico y la eficacia académica; las comparaciones entre los grupos de estudio (GE versus GC) de acuerdo con los tamaños de efecto (.30 < d >.50) evidenciaron diferencias prácticas importantes en cuanto al uso adictivo de internet, del teléfono móvil y los videojuegos, para las tres variables el GE mostró menores promedios que el GC; de otra parte las comparaciones entre GE y GC resultaron con diferencias de magnitudes de efecto entre mediano (d >.50) y grande (d >.80) en eficacia académica y compromiso académico respectivamente, en estas dos variables el GE mostró mayores promedios. Conclusión: el programa de prevención ha reducido las adicciones tecnológicas, así como incrementó las disposiciones cognitiva-afectivas en el estudiantado.
... The SFE scale was adopted from Ghani and Deshpande (1994). The items forming the smartphone addiction and MRS scales were derived from Caplan (2010) and Olivencia-Carrión et al. (2018) and adapted to the case of smartphone addiction. Since the data collection was carried out in Italy, the items were translated from English into Italian with a double translation method. ...
Recent studies found that smartphone usage has become an addiction nowadays, especially among young consumers. The abuse of these digital devices affects individuals' social life and well-being. Of particular interest in this regard is the study of compulsive buying, as it has been noted a possible co-occurrence of this disorder with smartphone abusive tendencies. With a model theoretically anchored in the stimulus-organism-response framework, the current study investigates the novel connection between smartphone addiction and online compulsive buying in a sample of 275 Generation Z consumers. The proposed model integrates mood regulatory behaviours and flow experiences associated with smartphone addiction to affect online compulsive buying behaviours. Employing a multi-method approach, the current research contributes to the literature on compulsive buying behaviours and smartphone addiction by offering empirical evidence that (1) smartphone addiction and online compulsive buying are related; and (2) mood regulatory behaviours and flow experience act as strengthening factors in this relationship. This article advances knowledge in terms of theory and practice on Generation Z consumers’ smartphone addiction and online compulsive buying.
... The sample was composed of n r = 856 respondents, recruited in faceto-face interviews under a three-stage cluster sampling design, which produced an estimated sampling error of ±3.3% in the case of p = q = 0.5 with a confidence level of 95%. The survey questionnaire included screening instruments for abuse and dependence, namely the Spanish Mobile Phone Abuse Questionnaire (ATeMo) (Olivencia-Carrión et al. 2018), which provides a score between 0 and 100 points that reflects the level of mobile phone abuse of the participant. The ATeMo Table 4 Estimated mean and median of Relative Bias and Effect of estimates using PSA for each algorithm, and number of times its estimates have been among the best (Relative Bias less than 1% greater than the minimum) or have been more efficient than using all variables (Effect under 1 and under 0.9) in the real (bootstrapped) data simulation considering inclusion probabilities proportional to age in the nonprobability sample (Legleye et al. 2007) and the Severity of Dependence Scale (SDS) (Gossop et al. 1995), together with subscales regarding internet and videogames addiction from the MULTICAGE-CAD4 instrument (Pedrero-Pérez et al. 2007). ...
The development of new survey data collection methods such as online surveys has been particularly advantageous for social studies in terms of reduced costs, immediacy and enhanced questionnaire possibilities. However, many such methods are strongly affected by selection bias, leading to unreliable estimates. Calibration and Propensity Score Adjustment (PSA) have been proposed as methods to remove selection bias in online nonprobability surveys. Calibration requires population totals to be known for the auxiliary variables used in the procedure, while PSA estimates the volunteering propensity of an individual using predictive modelling. The variables included in these models must be carefully selected in order to maximise the accuracy of the final estimates. This study presents an application, using synthetic and real data, of variable selection techniques developed for knowledge discovery in data to choose the best subset of variables for propensity estimation. We also compare the performance of PSA using different classification algorithms, after which calibration is applied. We also present an application of this methodology in a real-world situation, using it to obtain estimates of population parameters. The results obtained show that variable selection using appropriate methods can provide less biased and more efficient estimates than using all available covariates.
... Furthermore, they found little research to support the theoretical foundation of many of the scales (Harris et al., 2020). For the present research, we chose the ATeMo Questionnaire by Olivencia-Carrión et al. (2018) because the sample to be used in the analyses was collected in Spain. ATeMo was specifically developed in Spain to measure mobile phone abuse among young Spanish adults. ...
... The four ATeMo factors were associated with alcoholism, compulsive Internet use, and buying. The authors concluded that ATeMo is a valid and reliable instrument that can be used in future research on mobile phone abuse in the Spanish socio-cultural context (Olivencia-Carrión et al., 2018). ...
... The value for the total score was .90. Additional details can be found at Olivencia-Carrión et al. (2018). The ATeMo items can be found at Olivencia-Carrión et al. (2018). ...
Available data indicate that the frequency of Problematic Smartphone Use (PSU) has been increasing over the years. Although there is some debate as to whether or not this behavior corresponds to true addiction, comorbidity has been found with problematic outcomes typically related to traditional addictions. Thus, there is interest in better understanding which individual variables interact with this behavior. The present study uses a large sex-balanced sample covering a wide age range to shed light on this question. The main purpose of this study is to examine the relationship between personality, assessed by Zuckerman's alternative five-factor model, and PSU. The possible mediating role of individual decision-making styles as well as the effect of sociodemographic variables such as age, sex, and social position are also investigated. The results indicated a strong association between Aggressiveness, Neuroticism, and, to a lesser extent, Sensation Seeking with PSU. The decision-making styles that were most related to the problematic use of smartphones were Avoidant and Spontaneous. Neuroticism, Sensation Seeking, and Aggression explained 24% of the variance of the PSU measure. Only Avoidant showed some incremental validity for this model. However, a mediation analysis by structural equation modeling revealed generally significant indirect effects for Avoidant and Spontaneous, explaining part of the effect of personality on the factor assessed by the PSU measure. The percentage of variance explained for latent scores ranged from 20-32%. The practical implications of the study and future research directions are discussed.
... To sum up, the use of cell phones has also increased at global level (11) and mobile addiction is prevalent in the adolescents, especially in students, which may cause many problems in occupational and educational performances and family relationships; thus, it seems necessary to survey cell phone addiction in this population (13,14). The benefit of MPA to perform this study is mainly due to its factor analysis (compulsive behavior, functional impairment, withdrawal and tolerance) (15). The four aspects of the MPA constitute some of the DSM substance abuse diagnosis criteria . ...
... The four aspects of the MPA constitute some of the DSM substance abuse diagnosis criteria . This condition makes Mobile Phone Abuse questionnaire especially interesting for the establishment of a parallelism between the addictive use of the cell phone and the addictive disorder by substances (15). We hypothesize that the Persian version of MPA will be a reliable and valid tool to measure the abuse for the smart mobile phone in the student population. ...
... These reliability coefficients were higher than those gained in some previous studies (25), which confirmed the reliability of this questionnaire. Olivencia et al (2018) reported that the reliability of MPA was calculated using Cronbach's alpha and the findings were as follow: total score of reliability was 0.91; the reliability of factors was 0.74, 0.70, 0.77, and 0.77 respectively (15). Therefore, the reliability gained in the Persian language and original version may be advantageous. ...
Objective: Smartphone is an important technology device in our lifestyle. It has an important part of our daily lives, but it also has a negative effect, such as cell phone dependency. This research aimed to evaluate the psychometric properties of mobile phone abuse (MPA) in the Iranian population.
Method: In this study, data were chosen from 1100 participants who were studying in Tehran universities. The principal version of the scale was translated into Persian using the back translation method. All attendees completed Demographic Questionnaire, MPA Questionnaire, and Mobile Phone Problematic Use Scale (MPPUS). Eventually, a clinical interview (based on the fifth version of DSM) was done for all the participants. For data analysis, internal and external consistency, factor analysis, construct validity and confirmatory factor analysis (CFA) were used. Statistically, less than 0.05 were considered to be significant.
Results: According to expert judgments, content validity index was satisfactory. Furthermore, the reliability of the questionnaire was confirmed with Cronbach’s α of 0.90 and test-retest reliability of 0.56 after 3 weeks. The best cutoff point for this questionnaire (MPA) was 46. Also, 4 factors were extracted by principal components method and varimax rotation: “excessive use of cell phone,” “addictive use of social networks,” “mood modification,” and “preoccupation” for both male and female students.
Conclusion: MPA could be used in studies on the evaluation of mobile phone addiction. This can be a stepping stone towards the identification of problems and improvement of students’ mobile phone abuse.
