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Understanding Digital Well-Being

Understanding Digital Well-Being

Introduction

Today, we're diving into the world of digital well-being features and their impact on our screen time and addiction. With the increasing reliance on digital devices, it's crucial to understand how these features can potentially shape our digital habits. So, let's unravel the findings from a study conducted in Maharashtra, India, and see what it reveals about our knowledge, attitudes, and practices regarding digital well-being features.

Unveiling the Digital Dilemma

The COVID-19 pandemic reshaped our daily routines, leading to a surge in screen usage for work, education, and leisure. This shift has raised concerns about the potential impact of excessive screen time on our mental and physical well-being. Research has linked prolonged screen use to various health issues, including depression, anxiety, and sleep disturbances. This has prompted digital service providers to introduce 'Digital Well-Being Features' aimed at mitigating the adverse effects of screen overuse.

The Rise of Digital Well-Being Features

Digital well-being features, such as 'Digital Wellbeing by Android' and 'Zen Mode' by OnePlus, have emerged as tools to regulate screen time and promote healthier digital habits. These features encompass functionalities like app locking, over-usage warnings, and blue light filters, designed to empower users to manage their digital consumption. However, the effectiveness and awareness of these tools among the user base remain under scrutiny.

Unveiling the Study

A cross-sectional online questionnaire-based study was conducted among 335 participants in Maharashtra, India, to evaluate the knowledge, attitudes, and practices related to digital well-being features. The study also explored the association of using these features with screen time and the degree of screen addiction.

Findings and Insights

The study revealed that 65.4% of the participants were users of digital well-being features, indicating a substantial adoption of these tools. However, the correlation analysis did not demonstrate a significant association between the use of digital well-being features and reduced screen time or lower screen addiction scores. This suggests that while awareness and adoption of these features were adequate, their impact on mitigating screen addiction and reducing screen time was not pronounced.

Understanding User Practices

The study delved into the practices and perceptions of participants regarding the use of digital well-being features. It was observed that app locking features and over-usage warnings were perceived as the most effective tools for controlling screen usage. Additionally, the frequency of usage varied, with blue light filters and time tracking being the most frequently utilized features.

Addressing Screen Addiction

Screen addiction was also a focal point of the study, with 35% of participants identified as addicts based on their smartphone addiction scores. Interestingly, no significant difference was found in the mean screen time and addiction scores between users and non-users of digital well-being features. This sheds light on the complex interplay between digital habits and the efficacy of these features in curbing addiction.

Implications and Future Considerations

While the study highlighted the adequate knowledge and attitudes regarding digital well-being features among the urban population of Maharashtra, it underscored the need for further development and standardization of these features. The findings suggest that, despite their widespread use, these features may require refinement to effectively address screen overuse and addiction.

Wrapping Up

The study provides valuable insights into the landscape of digital well-being features and their association with screen time and addiction. It prompts us to reflect on our digital habits and the role of these features in shaping our interactions with technology. As we navigate the digital realm, understanding the nuances of digital well-being features becomes increasingly vital for fostering a balanced and mindful approach to technology usage.

So, there you have it – a glimpse into the world of digital well-being features and their impact on our digital behaviors. Stay tuned for more insightful explorations into the fascinating intersection of technology and human behavior!


Citation: Amey Ambike et al., “Knowledge, Attitude and Practices Regarding Digital Well-Being Features and Their Association with Screen Time and Addiction in Maharashtra, India,” February 23, 2023, https://doi.org/10.1101/2023.02.21.23286252.

Glossary

  • Screen Time: Screen time refers to the amount of time an individual spends using digital devices such as smartphones, tablets, computers, and televisions. It is a measure of the duration of exposure to screens for various activities, including work, education, leisure, and entertainment.

  • Correlation Analysis: Correlation analysis is a statistical method used to evaluate the strength and direction of the relationship between two or more variables. It assesses the degree to which changes in one variable correspond to changes in another variable, providing insights into potential associations or dependencies.

  • App Locking: App locking is a digital well-being feature that allows users to restrict access to specific applications on their devices. It helps in controlling and managing the usage of certain apps, thereby promoting a balanced digital experience and reducing excessive screen time.

  • Blue Light Filters: Blue light filters are features integrated into digital devices to reduce the exposure to blue light emitted from screens. These filters help in minimizing eye strain and disruptions to sleep patterns caused by prolonged exposure to blue light, thereby supporting healthier digital habits.

  • Time Tracking: Time tracking refers to the functionality within digital well-being features that enables users to monitor and assess the amount of time spent on various activities or applications. It allows users to gain insights into their screen time patterns and make informed decisions about managing their digital usage.