Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis
BackgroundProblematic smartphone use, like problematic internet use, is a condition for which treatment is being sought on the web. In the absence of established treatments, smartphone-provided tools that monitor or control smartphone use have become increasingly popular, and...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2022-10-01
|
| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2022/10/e38963 |
| _version_ | 1797734621739220992 |
|---|---|
| author | Elias Aboujaoude Germano Vera Cruz Lucien Rochat Robert Courtois Farah Ben Brahim Riaz Khan Yasser Khazaal |
| author_facet | Elias Aboujaoude Germano Vera Cruz Lucien Rochat Robert Courtois Farah Ben Brahim Riaz Khan Yasser Khazaal |
| author_sort | Elias Aboujaoude |
| collection | DOAJ |
| description |
BackgroundProblematic smartphone use, like problematic internet use, is a condition for which treatment is being sought on the web. In the absence of established treatments, smartphone-provided tools that monitor or control smartphone use have become increasingly popular, and their dissemination has largely occurred without oversight from the mental health field.
ObjectiveWe aimed to assess the popularity and perceived effectiveness of smartphone tools that track and limit smartphone use. We also aimed to explore how a set of variables related to mental health, smartphone use, and smartphone addiction may influence the use of these tools.
MethodsFirst, we conducted a web-based survey in a representative sample of 1989 US-based adults using the crowdsourcing platform Prolific. Second, we used machine learning and other statistical tools to identify latent user classes; the association between latent class membership and demographic variables; and any predictors of latent class membership from covariates such as daily average smartphone use, social problems from smartphone use, smartphone addiction, and other psychiatric conditions.
ResultsSmartphone tools that monitor and control smartphone use were popular among participants, including parents targeting their children; for example, over two-thirds of the participants used sleep-related tools. Among those who tried a tool, the highest rate of perceived effectiveness was 33.1% (58/175). Participants who experienced problematic smartphone use were more likely to be younger and more likely to be female. Finally, 3 latent user classes were uncovered: nonusers, effective users, and ineffective users. Android operating system users were more likely to be nonusers, whereas younger adults and females were more likely to be effective users. The presence of psychiatric symptoms did not discourage smartphone tool use.
ConclusionsIf proven effective, tools that monitor and control smartphone use are likely to be broadly embraced. Our results portend well for the acceptability of mobile interventions in the treatment of smartphone-related psychopathologies and, potentially, non–smartphone-related psychopathologies. Better tools, targeted marketing, and inclusive design, as well as formal efficacy trials, are required to realize their potential. |
| first_indexed | 2024-03-12T12:46:01Z |
| format | Article |
| id | doaj.art-0141cc7a395e4bf2b0f8bc2d86a4af1f |
| institution | Directory Open Access Journal |
| issn | 1438-8871 |
| language | English |
| last_indexed | 2024-03-12T12:46:01Z |
| publishDate | 2022-10-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj.art-0141cc7a395e4bf2b0f8bc2d86a4af1f2023-08-28T23:17:49ZengJMIR PublicationsJournal of Medical Internet Research1438-88712022-10-012410e3896310.2196/38963Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning AnalysisElias Aboujaoudehttps://orcid.org/0000-0003-1216-8313Germano Vera Cruzhttps://orcid.org/0000-0002-8297-6933Lucien Rochathttps://orcid.org/0000-0002-9992-2720Robert Courtoishttps://orcid.org/0000-0002-3557-5264Farah Ben Brahimhttps://orcid.org/0000-0002-0269-0848Riaz Khanhttps://orcid.org/0000-0002-4520-7465Yasser Khazaalhttps://orcid.org/0000-0002-8549-6599 BackgroundProblematic smartphone use, like problematic internet use, is a condition for which treatment is being sought on the web. In the absence of established treatments, smartphone-provided tools that monitor or control smartphone use have become increasingly popular, and their dissemination has largely occurred without oversight from the mental health field. ObjectiveWe aimed to assess the popularity and perceived effectiveness of smartphone tools that track and limit smartphone use. We also aimed to explore how a set of variables related to mental health, smartphone use, and smartphone addiction may influence the use of these tools. MethodsFirst, we conducted a web-based survey in a representative sample of 1989 US-based adults using the crowdsourcing platform Prolific. Second, we used machine learning and other statistical tools to identify latent user classes; the association between latent class membership and demographic variables; and any predictors of latent class membership from covariates such as daily average smartphone use, social problems from smartphone use, smartphone addiction, and other psychiatric conditions. ResultsSmartphone tools that monitor and control smartphone use were popular among participants, including parents targeting their children; for example, over two-thirds of the participants used sleep-related tools. Among those who tried a tool, the highest rate of perceived effectiveness was 33.1% (58/175). Participants who experienced problematic smartphone use were more likely to be younger and more likely to be female. Finally, 3 latent user classes were uncovered: nonusers, effective users, and ineffective users. Android operating system users were more likely to be nonusers, whereas younger adults and females were more likely to be effective users. The presence of psychiatric symptoms did not discourage smartphone tool use. ConclusionsIf proven effective, tools that monitor and control smartphone use are likely to be broadly embraced. Our results portend well for the acceptability of mobile interventions in the treatment of smartphone-related psychopathologies and, potentially, non–smartphone-related psychopathologies. Better tools, targeted marketing, and inclusive design, as well as formal efficacy trials, are required to realize their potential.https://www.jmir.org/2022/10/e38963 |
| spellingShingle | Elias Aboujaoude Germano Vera Cruz Lucien Rochat Robert Courtois Farah Ben Brahim Riaz Khan Yasser Khazaal Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis Journal of Medical Internet Research |
| title | Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis |
| title_full | Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis |
| title_fullStr | Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis |
| title_full_unstemmed | Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis |
| title_short | Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis |
| title_sort | assessment of the popularity and perceived effectiveness of smartphone tools that track and limit smartphone use survey study and machine learning analysis |
| url | https://www.jmir.org/2022/10/e38963 |
| work_keys_str_mv | AT eliasaboujaoude assessmentofthepopularityandperceivedeffectivenessofsmartphonetoolsthattrackandlimitsmartphoneusesurveystudyandmachinelearninganalysis AT germanoveracruz assessmentofthepopularityandperceivedeffectivenessofsmartphonetoolsthattrackandlimitsmartphoneusesurveystudyandmachinelearninganalysis AT lucienrochat assessmentofthepopularityandperceivedeffectivenessofsmartphonetoolsthattrackandlimitsmartphoneusesurveystudyandmachinelearninganalysis AT robertcourtois assessmentofthepopularityandperceivedeffectivenessofsmartphonetoolsthattrackandlimitsmartphoneusesurveystudyandmachinelearninganalysis AT farahbenbrahim assessmentofthepopularityandperceivedeffectivenessofsmartphonetoolsthattrackandlimitsmartphoneusesurveystudyandmachinelearninganalysis AT riazkhan assessmentofthepopularityandperceivedeffectivenessofsmartphonetoolsthattrackandlimitsmartphoneusesurveystudyandmachinelearninganalysis AT yasserkhazaal assessmentofthepopularityandperceivedeffectivenessofsmartphonetoolsthattrackandlimitsmartphoneusesurveystudyandmachinelearninganalysis |