Prevalence of Problematic Mobile Phone Use in British Adolescents
By Olatz Lopez-Fernandez, Maria Luisa Honrubia-Serrano, Montserrat Freixa-Blanxart, William Gibson. Cyberpsychology, Behavior, and Social Networking, 2014
348 citations recorded by the source corpus.
Abstract The problematic use of mobile phones among adolescents has not been widely studied. There are very few instruments for assessing potential technological addiction to mobile phones, or for categorizing different types of users or uses. The most widely used scale is the Mobile Phone Problem Use Scale (MPPUS), which is used to study adult populations, and has been applied in various forms in international contexts. The aims of this study were to adapt the Spanish version of this scale (MPPUSA) to British adolescents, and then to estimate the prevalence of possible problematic users. A questionnaire was administered to a sample of 1,529 secondary school pupils aged between 11 and 18 years, with 1,026 completed questionnaires being collected. The analysis showed that the factor and construct validity and reliability were comparable to those obtained in previous studies. The prevalence of problematic users among the students was 10%, and the typical problematic user tended to be an adolescent between 11 and 14 years old, studying in a public school, who considered themselves to be an expert user of this technology, who made extensive use of his/her mobile phone, and who attributed the same problem of use among their peers. These users presented notable scores in all the symptoms covered by the scale used to assess problematic use. In conclusion, the adaptation of the MPPUSA as a screening scale for British adolescents presents good sensitivity and specificity for detecting the main addictive symptoms proposed in this validated version.
Subfields: Communication, Education, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/28e022ab33ef2ff929fe008bd32e1cd652e1327a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Communication
- Jason C. Levine
- Brian J. Hall
- Jon D. Elhai
- Robert D. Dvorak
- Sabrina M. Hegner
- A. V. van Deursen
- J. V. van Dijk
In Education
- Jon D. Elhai
- Jason C. Levine
- Brian J. Hall
- Robert D. Dvorak
- Fuyin Yang
- Xiaodan Xie
- Wenjie Tang
- Li Chen
In Sociology and Political Science
- Jon D. Elhai
- Jason C. Levine
- Brian J. Hall
- Robert D. Dvorak
- Fuyin Yang
- José De-Sola Gutiérrez
- G. Rubio
- Xiaodan Xie
Citations in the corpus
- Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use (2016, background): “Because smartphone use is important in need fulfillment for emotional (Clayton et al., 2015; Hoffner & Lee, 2015), social (Clayton et al., 2015; Lopez-Fernandez et al., 2014) and tactile needs (Lee et al., 2014), we expected to find support for this hypothesis.”
- Mobile phone addiction levels and negative emotions among Chinese young adults: The mediating role of interpersonal problems (2016, background): “It is estimated that prevalence of mobile phone addicts ranges from 0% to 38% of mobile phone users across cultures and societies (Lopez-Fernandez et al., 2014), suggesting at least 62% of mobile phone users are with possible addiction or even without addition.”
- Non-social features of smartphone use are most related to depression, anxiety and problematic smartphone use (2017, background): “However, with a sample of schoolaged adolescents, another study discovered that social smartphone use was more prevalent than process use among problematic smartphone users (Lopez-Fernandez et al., 2014), a finding typical in the internet addiction literature (Chou & Hsiao, 2000; Yang & Tung, 2007).”
- Cell-Phone Addiction: A Review (2016, background): “In general, the data show that the total time spent on cell phones decreases with age, with the highest times reported for people less than 20 years old, principally adolescents, approximately 14 years old (50, 61, 75, 78, 82, 83, 121).”
- Modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender (2015, background): “, 2014), while tending to isolate themselves offline (Lopez-Fernandez et al., 2014).”