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3 Apr 2019

Hsieh YP et al. Int J Environ Res Public Health 2019; 16: pii: E1423

Compared with adults, adolescents are more likely to develop a smartphone addiction (Chóliz 2012). Internet addiction can have a negative impact on social, psychological and behavioural well-being, and therefore prevention and intervention are warranted. Through the use of smartphones, adolescents can also gain access to the internet, and ADHD has been associated with internet addiction (Yen et al. 2007). Parents should be able to talk to their children about online behaviour and safety, and execute a plan to manage their adolescents’ internet and smartphone use. The Parental Smartphone Use Management Scale (PSUMS) was developed as a metric to assess the self-perceived parents’ self-efficacy regarding the management of smartphone use by their adolescents with ADHD. The validity and reliability of the PSUMS was evaluated in this study.

Parents of adolescents (aged 11–18 years) with a diagnosis of ADHD according to the Diagnostic and Statistical Manual of Mental Disorders – Fifth Edition (DSM-5TM) from two child and adolescent psychiatric outpatient clinics in Taiwan were invited to participate in this study between August 2014 and July 2015.* Parents were interviewed by research assistants using the PSUMS, the Problematic Cellular Phone Use Questionnaire (PCPU-Q) and the short version of the Swanson, Nolan, and Pelham, Version IV (SNAP-IV, Chinese version).§ Construct validity of the PSUMS was determined using factor analysis.

In total, 211 parents of adolescents with ADHD participated in the study. Most parents were female (82.9%; mean age [standard deviation, SD] 43.5 [5.9] years) and most adolescents were male (86.7%; mean age [SD] 13.7 [1.8] years). The mean (SD) score on the SNAP-IV (Chinese version) for inattention, hyperactivity and impulsivity, and oppositional behaviour was 12.8 (6.1), 8.9 (6.0) and 9.9 (5.7), respectively. The majority of adolescents were identified as not having smartphone addiction (81.0% vs 19.0% for smartphone addiction) based on the PCPU-Q. From the 20-item pool, 17 items on the PSUMS accounted for 78.58% of the total variance, and contained three theoretically and statistically appropriate subscales: reactive management, proactive management and monitoring.

  • Reactive management (α = 0.93) included the seven items with factor loadings of 0.52–73 and reflected parents’ management of adolescents’ smartphone use through rule-setting practices, and responding to and controlling this use to avoid negative impacts on adolescents’ daily-life functioning.
  • Proactive management (α = 0.95) included six items with factor loadings of 0.55–93 and reflected parents’ perceived efficacy of their proactive management and active mediation of adolescent’s smartphone use through positive communication and reasoning.
  • Monitoring (α = 0.93) included four items with factor loading 0.63–91 and reflected parents’ behaviour in monitoring what their adolescents do on their smartphones, including who they talk to, what applications they use and the websites they visit.

The results of the PSUMS were compared between parents of adolescents with ADHD with smartphone addiction and those without based on the PCPU-Q. Lower mean (SD) scores on all three subscales of the PSUMS were associated with parents of adolescents with smartphone addiction compared with those without smartphone addiction (reactive management: 3.30 [1.46] vs 4.52 [1.14], p < 0.001; proactive management: 2.90 [1.39] vs 4.11 [1.27], p < 0.001; management: 2.94 [1.56] vs 4.05 [1.47], p < 0.001). The results of the Pearson’s correlation provided strong evidence for concurrent validity and the PSUMS was found to significantly correlate with the PCPU-Q (all p < 0.001). Moreover, the factorial validity of the PSUMS was good and showed high reliabilities, with Cronbach’s α ranging between 0.93 and 0.95.

This study has some limitations which need to be addressed. The sample size of 211 participants was relatively small and future studies with a larger sample size are needed to corroborate these findings. All subscales of the PSUMS were significantly correlated with all subscales of the PCPU-Q which indicates that the subscales of PSUMS may not be distinguishable.

The authors conclude that, despite these limitations, the overall results show that the PSUMS has good reliability and adequate validity, and therefore could be used as a tool for developing smartphone addiction prevention programmes for adolescents with ADHD. As the internet and smartphones are widely used and becoming an important part of an individual’s daily life, traditional parenting and educational programmes should be enhanced to manage adolescents’ smartphone use.

Read more about the development and validation of a parental management scale for adolescent ADHD and smartphone addiction here


*Multiple data sources including clinical observations of each adolescent’s behaviour and parental ratings of ADHD symptoms on the short version of the SNAP-IV (Chinese version) were used to support the diagnoses of ADHD. Adolescents with autism spectrum disorders, an intellectual disability or difficulties in communication were excluded from the study. Parents with bipolar disorder, an intellectual disability, schizophrenia or any cognitive deficits that resulted in significant communication difficulties were excluded from the study
Before the development of the PSUMS, an item pool of 20 items was established by conducting a literature review and by a focus group. A seven-point Likert scale was used to rate the level of agreement with each item which ranged from 0 (no efficacy at all) to 6 (very strong efficacy). Psychiatrists, psychologists and parenting specialists were consulted to ensure face validity of the scale, and the scale was revised to use culture-sensitive wording and irrelevant content was removed. Parents were asked to rate their self-perceived efficacy in managing their adolescents’ smartphone use over a month with high PSUMS scores indicating high levels of self-efficacy
The PCPU-Q was used to assess the criterion-related validity of the PSUMS. It measures an adolescent’s problematic smartphone use and comprised 12 items which are rated on a four-point Likert scale. The PCPU-Q comprises two subscales: symptoms of problematic cellular phone use and functional impairment caused by cellular phone use. Higher overall scores indicate more severe levels of symptoms of problematic cellular phone use and associated functional impairments. The internal reliability (Cronbach’s α) of the PCPU-Q subscales was 0.92
§The severity of ADHD was assessed by the SNAP-IV (Chinese version) which comprises 26 items encompassing the core subscales of ADHD (inattention, hyperactivity and impulsivity) and the oppositional symptoms of oppositional defiant disorder derived from DSM-IV. Each item is rated on a four-point Likert scale ranging from 0 (not at all) to 3 (very much). The Cronbach’s α for inattention, hyperactivity and impulsivity, and oppositional behaviour were 0.91, 0.90 and 0.93, respectively

Chóliz M. Mobile-phone addiction in adolescence: The Test of Mobile Phone Dependence (TMD). Prog Health Sci 2012; 2: 33-44.

Hsieh YP, Yen CF, Chou WJ. Development and validation of the Parental Smartphone Use Management Scale (PSUMS): parents’ perceived self-efficacy with adolescents with attention deficit hyperactivity disorder. Int J Environ Res Public Health 2019; 16: pii: E1423.

Yen JY, Ko CH, Yen CF, et al. The comorbid psychiatric symptoms of Internet addiction: attention deficit hyperactivity disorder (ADHD), depression, social phobia, and hostility. J Adolesc Health 2007; 41: 93-98.

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