Using Machine Learning to Explore the Risk Factors of Problematic Smartphone Use among Canadian Adolescents during COVID-19: The Important Role of Fear of Missing Out (FoMO)

Round 1

Reviewer 1 Report

Dear Authors,

 Thank you for the opportunity to review an interesting article entitled: ‘Using Machine Learning to Explore the Risk Factors of Problematic Smartphone Use among Canadian Adolescents During COVID-19: The Important Role of Fear of Missing Out (FoMO)'. The aim of this article is to investigate prominent statistical predictors of smartphone addiction among adolescents during the COVID-19 pandemic. This topic is of a great interest to both education professionals and smartphone industry. Overall this article will make a contribution to the literature that can be used and cited by future researchers. However, the following comments, which aim to improve the text, are worth considering:

 

Comment 1: Although many similar studies have investigated various risk factors regarding the smartphone addiction and thus reduced certain degrees of originality, this study uses I-PACE as a guide to take all possible factors into account. I suggest the authors to elaborate the I-PACE model and correlate them with risk factors in the study.

 

Comment 2: This study indicate FoMO plays the most important role and the authors even list it in the title. However, anxiety is categorized as an internalizing problem in this study but also an antecedent or result of FoMO in some studies. They are highly correlated.

 

Comment 3: Please make it clear to state some information about the paper, such as Author Contributions, Institutional Review Board Statement, Informed Consent Statement, Data Availability Statement, Acknowledgments, etc.

 

Comment 4: Reference: Please follow the format of the journal. Besides, there are still some missing information (e.g., volume information of Cohen et al. (2021)) or insistent format (e.g., Journal information of de Freitas (2022)). Please recheck the reference.

Author Response

Comment 1: Although many similar studies have investigated various risk factors regarding the smartphone addiction and thus reduced certain degrees of originality, this study uses I-PACE as a guide to take all possible factors into account. I suggest the authors to elaborate the I-PACE model and correlate them with risk factors in the study.

Response: Thank you so much for your suggestion, we have now added this. Please see page 5: “Contrarily, the Interaction of Person-Affect-Cognition Execution model (I-PACE) (Brand et al., 2019) provides a more wholistic model within which to conceptualize adolescent problematic smartphone use. Specifically, it is a theoretical framework used to explain the development and maintenance of problematic smartphone use. This model proposes that various factors interact to contribute to internet addiction, including individual characteristics (such as personality traits), affective processes (such as mood and emotions), cognitive processes (such as decision-making and attentional biases), and executive functions (such as self-regulation and impulse control) (Brand et al., 2019). According to the I-PACE model, these factors work together in a dynamic manner and can lead to a vicious cycle of problematic smartphone use. For example, individuals with low level of executive functions (e.g., self-regulation) and psychopathology (such as anxiety or depression) may be more likely to use the internet excessively as a way to cope with negative emotions (Brand et al., 2016). Drawing upon the I-PACE model, we proposed several potential risk factors for problematic smartphone use. These factors include gender as an individual characteristic, internalizing problems as affective processes, self-regulation and fear of missing out as cognitive processes and executive functions, and screen time. Our study utilized these factors to guide our analysis and predictions of problematic smartphone use.”

Comment 2: This study indicate FoMO plays the most important role and the authors even list it in the title. However, anxiety is categorized as an internalizing problem in this study but also an antecedent or result of FoMO in some studies. They are highly correlated.

Response: Thank you for pointing this out. We have added a discussion about the relationship between FoMO and internalizing problems. Please see page18: “It should be noted that internalizing problems and FoMO are highly correlated. Researchers also suggested that there may be a link between internalizing problems and FoMO. For example, researchers have found that individuals who experience higher levels of anxiety and depression may be more likely to experience FOMO as a result of feeling socially disconnected or isolated (e.g., Elhai et al., 2020). Similarly, individuals who experience FOMO may be more likely to experience anxiety or depression as a result of the constant comparison and pressure to keep up with others (e.g., Fitzgerald et al., 2023). Therefore, future studies should keep investigating the complex relationships among internalizing problems, FoMO, and problematic smartphone use.”

Comment 3: Please make it clear to state some information about the paper, such as Author Contributions, Institutional Review Board Statement, Informed Consent Statement, Data Availability Statement, Acknowledgments, etc.

Response: Thank you for your suggestion, we have now added this information to the “Declarations” section, please see page 21.

Comment 4: Reference: Please follow the format of the journal. Besides, there are still some missing information (e.g., volume information of Cohen et al. (2021)) or insistent format (e.g., Journal information of de Freitas (2022)). Please recheck the reference.

Response: Thanks for bringing this to our attention, we have now gone over our references more thoroughly.

Reviewer 2 Report

This is an interesting study examining the risk factors of problematic smartphone use during COVID-19 by using machine learning. Honestly, I am very impressed by the study. The paper is very well-written. The sample size is huge. The analysis technique is novel and advanced. More importantly, the authors assessed objective screen time. I am sure the paper will contribute to the literature well. I only have a few comments to improve the manuscript further:

1. In the literature review, the authors should be consistent with the term problematic smartphone use rather than smartphone addiction (as indicated in their title). Even though smartphone addiction scale was used as the main measure, it can still be operationalized as a measure of problematic smartphone use.

Is smartphone addiction really an addiction?. (2018). Journal of Behavioral Addictions, 7(2), 252-259.   2. The inclusion and exclusion criteria used in the sampling should be explicitly reported in the method section.   3. I would like to suggest the authors to use a better imputation technique than pairwise imputation. If multiple imputation is too complicated, at least, the authors should consider a single imputation such as using the expectation maximization which can be easily done in SPSS   A comparison of imputation techniques for handling missing data. (2002). Western Journal of Nursing Research, 24(7), 815-829.   4. In the limitation section, the authors highlighted a very important point about the cross-sectional design of the current study and potential reverse causation as a limitation. Another limitation that I can think of in the current study is the reliance on screen time but neglected another aspect of smartphone use which is smartphone checking. Studies have shown that smartphone screen time and smartphone checking may have differential associations, with more negative implications for checking. Perhaps, the lack of assessment on smartphone checking can be highlighted and discussed. See the reference below   Smartphone use and daily cognitive failures: A critical examination using a daily diary approach with objective smartphone measures. (2023). British Journal of Psychology, 114(1), 70-85.

 

Author Response

1. In the literature review, the authors should be consistent with the term problematic smartphone use rather than smartphone addiction (as indicated in their title). Even though smartphone addiction scale was used as the main measure, it can still be operationalized as a measure of problematic smartphone use.

Is smartphone addiction really an addiction?. (2018). Journal of Behavioral Addictions, 7(2), 252-259.  

Response: Thank you so much for this recommendation. We have now changed “smartphone addiction” to “problematic smartphone use” throughout our manuscript.

2. The inclusion and exclusion criteria used in the sampling should be explicitly reported in the method section.  

Response: Thank you for pointing this out. We have now included the criteria used for the sampling in the methods section. Please see page 11: “Initially, 2527 adolescents participated in the study. However, after applying our exclusion criteria (which involved removing adolescents who only completed demographic information such as gender, age, and ethnicity), 427 individuals were excluded from the datafile. As a result, the final analysis was conducted on a sample of 2100 adolescents.”

3. I would like to suggest the authors to use a better imputation technique than pairwise imputation. If multiple imputation is too complicated, at least, the authors should consider a single imputation such as using the expectation maximization which can be easily done in SPSS. A comparison of imputation techniques for handling missing data. (2002). Western Journal of Nursing Research, 24(7), 815-829.  

Response: Thank you for your suggestion. As can be seen on Page 11 (and in the updated tables), we now use the expectation maximization to handle the missing data.

4. In the limitation section, the authors highlighted a very important point about the cross-sectional design of the current study and potential reverse causation as a limitation. Another limitation that I can think of in the current study is the reliance on screen time but neglected another aspect of smartphone use which is smartphone checking. Studies have shown that smartphone screen time and smartphone checking may have differential associations, with more negative implications for checking. Perhaps, the lack of assessment on smartphone checking can be highlighted and discussed. See the reference below   Smartphone use and daily cognitive failures: A critical examination using a daily diary approach with objective smartphone measures. (2023). British Journal of Psychology, 114(1), 70-85.

Response: Thank you for noting this. We have now added information about smartphone checking in our limitations section. Please see page 19: “Moreover, our study only assessed screen time and did not include a measure of smartphone checking, which is another important aspect of smartphone usage. In fact, recent research indicates that smartphone screen time and checking may have distinct associations, with checking having more negative consequences (Hartanto et al., 2023). Therefore, future studies should investigate the relations between smartphone checking and problematic smartphone use.”

 

Round 2

Reviewer 2 Report

The authors have addressed all my comments well. I am impressed by their efforts.