Aims: The present theoretical paper introduces the smartphone technology as a challenge for diagnostics in the study of Internet use disorders and reflects on the term “smartphone addiction.” ...Methods: Such a reflection is carried out against the background of a literature review and the inclusion of Gaming Disorder in ICD-11. Results: We believe that it is necessary to divide research on Internet use disorder (IUD) into a mobile and non-mobile IUD branch. This is important because certain applications such as the messenger application WhatsApp have originally been developed for smartphones and enfold their power and attractiveness mainly on mobile devices. Discussion and conclusions: Going beyond the argumentation for distinguishing between mobile and non-mobile IUD, it is of high relevance for scientists to better describe and understand what persons are actually (over-)using. This is stressed by a number of examples, explicitly targeting not only the diverse contents used in the online world, but also the exact behavior on each platform. Among others, it matters if a person is more of an active producer of content or passive consumer of social media.
Smartphones are ubiquitous and offer numerous benefits in daily life. However, the ongoing excessive use of smartphones has been associated with a range of adverse effects, capturing the attention of ...researchers worldwide. While higher smartphone use is often seen as potentially compulsive or addictive, it is essential to recognise that not all smartphone use is inherently problematic; practical reasons can also contribute to increased or excessive usage. Consequently, distinguishing between purposeful or productive use and excessive or potentially harmful smartphone behaviours is essential. Existing research recognises differences in smartphone usage but lacks depth in its exploration. There is a notable demand for in-depth studies that distinguish between productive and problematic use of smartphones and examine what drives the transition between these behaviours. Therefore, this review critically examines prior research to explain the distinctions among various types of smartphone use and explore the characteristics, reasons, causes, effects, and consequences associated with these behaviours. This article introduces an Integrative Pathways Model (IPM), a conceptual framework designed to explore the reasons behind individuals' active smartphone use. It delves into the specific gratifications users seek from their smartphone use and investigates the various factors that may influence these motivations and, thereby, affect their behaviours. It highlights three distinct yet not mutually exclusive smartphone use-related pathways: effectual use, ineffectual use, and problematic use. This research contributes to enhancing understanding of Problematic Smartphone Use and Dependence (PSUD) by probing into the multifaceted interplay of individual characteristics, social dynamics, and environmental factors. This article underscores the need for a multi-dimensional approach to better understand smartphone usage, acknowledging that increased usage does not always signify problematic behaviour. It also emphasises the increasing demand for practical strategies to effectively manage PSUD.
The present study investigates the role of process and social oriented smartphone usage, emotional intelligence, social stress, self-regulation, gender, and age in relation to habitual and addictive ...smartphone behavior. We conducted an online survey among 386 respondents. The results revealed that habitual smartphone use is an important contributor to addictive smartphone behavior. Process related smartphone use is a strong determinant for both developing habitual and addictive smartphone behavior. People who extensively use their smartphones for social purposes develop smartphone habits faster, which in turn might lead to addictive smartphone behavior. We did not find an influence of emotional intelligence on habitual or addictive smartphone behavior, while social stress positively influences addictive smartphone behavior, and a failure of self-regulation seems to cause a higher risk of addictive smartphone behavior. Finally, men experience less social stress than women, and use their smartphones less for social purposes. The result is that women have a higher chance in developing habitual or addictive smartphone behavior. Age negatively affects process and social usage, and social stress. There is a positive effect on self-regulation. Older people are therefore less likely to develop habitual or addictive smartphone behaviors.
Smartphones are becoming a daily necessity for most undergraduates in Mainland China. Because the present scenario of problematic smartphone use (PSU) is largely unexplored, in the current study we ...aimed to estimate the prevalence of PSU and to screen suitable predictors for PSU among Chinese undergraduates in the framework of the stress-coping theory.
A sample of 1062 undergraduate smartphone users was recruited by means of the stratified cluster random sampling strategy between April and May 2015. The Problematic Cellular Phone Use Questionnaire was used to identify PSU. We evaluated five candidate risk factors for PSU by using logistic regression analysis while controlling for demographic characteristics and specific features of smartphone use.
The prevalence of PSU among Chinese undergraduates was estimated to be 21.3%. The risk factors for PSU were majoring in the humanities, high monthly income from the family (≥1500 RMB), serious emotional symptoms, high perceived stress, and perfectionism-related factors (high doubts about actions, high parental expectations).
PSU among undergraduates appears to be ubiquitous and thus constitutes a public health issue in Mainland China. Although further longitudinal studies are required to test whether PSU is a transient phenomenon or a chronic and progressive condition, our study successfully identified socio-demographic and psychological risk factors for PSU. These results, obtained from a random and thus representative sample of undergraduates, opens up new avenues in terms of prevention and regulation policies.
Previous research has shown that problematic smartphone use (PSU) is related to several affect-related psychopathology variables. Emotion dysregulation has been regarded as a central psychological ...factor associated with that type of psychopathology. In this paper, the association between expressive emotional suppression, a form of emotion dysregulation, with PSU was investigated. Furthermore, we tested if types of smartphone use (process and social use) mediated that association. Three hundred American college students participated in a web-based survey that included the Smartphone Addiction Scale (for problematic smartphone use), Emotion Regulation Questionnaire (assessing suppression), and Process vs. Social Smartphone Usage scale. We found that expressive suppression was correlated with both process smartphone use and PSU severity. Mediation analysis showed that process smartphone use completely mediated relations between suppression and PSU severity. The findings suggest that dysfunctional emotion regulation could lead to more process smartphone use that, in turn, may manifest in PSU severity. Contributions and limitations of the study are discussed.
Despite numerous favourable consequences, excessive smartphone usage has been linked to behaviours that might be detrimental or unsettling, at least for some individuals. Accordingly, it becomes ...fundamental to re-evaluate the classifications and metrics used to identify problematic smartphone use and dependence (PSUD) due to their diverse negative impacts on users. This necessity is driven by factors such as the availability of numerous apps, changes in behaviour resulting from widespread adoption, and the recent impact of COVID-19. The distinction between smartphone dependence and other technological dependencies is a critical aspect explored in this narrative review. Additionally, it clarifies the difference between habitual and discretionary smartphone use. It is worth noting that increased reliance on smartphones has brought about both positive and negative outcomes. On one hand, it has facilitated better management of professional, familial, and social obligations. Conversely, it has led to adverse aspects, including inappropriate usage, excessive engagement, and ineffective use. However, assessing PSUD based exclusively on frequency and duration is an overly simplistic approach. It is essential to investigate the motivations behind smartphone engagement and differentiate between purposeful, productive, goal-oriented utilisation (effectual use) and impulsive, unnecessary interactions (ineffectual use). The terminologies associated with PSUD often complicate the precise definition, identification, and measurement of accompanying behaviours. Moreover, the ever-evolving technological landscape and shifting usage patterns combine these challenges. To address these complexities, this review suggests establishing a standardised framework that investigates the impact of technological shifts, evolving smartphone usage patterns, and behavioural effects. This review examines the causes, effects, and factors that contribute to PSUD, proposing the need to study strategies for effectively identifying and managing challenges related to PSUD.
Smartphone ownership and screen time are increasing across the world, but there have been few attempts to quantify smartphone addiction on a global scale. We conducted a meta-analysis of studies ...published between 2014 and 2020 that used the Smartphone Addiction Scale, the most common measure of problematic smartphone use. We focused on adolescents and young adults (aged 15 to 35) since they tend to have the highest screen time and smartphone ownership rates. Across 24 countries, 83 samples, and 33,831 participants, we demonstrate that problematic smartphone use is increasing across the world. China, Saudi Arabia, and Malaysia had the highest scores while Germany and France had the lowest. We suggest that the clinical interpretation of these scores should be updated given current global trends.
•We conducted a meta-analysis of problematic smartphone use, focusing on young adults.•The analysis (2014–2020) included 24 countries, 83 samples, and 33,831 participants.•The results showed that problematic smartphone use is increasing across the world.•China and Saudi Arabia had the highest rates while Germany and France had the lowest.•Updating the clinical interpretation of these scores may be needed in some countries.
The aim of the current work was to investigate relations between problematic smartphone use (PSU) severity and intolerance of uncertainty, a transdiagnostic psychopathology construct reflecting ...individual differences in reacting to uncertain situations and events. In addition, it was tested if use of social and/or non-social smartphone use mediated associations between intolerance of uncertainty and PSU. The effective sample comprised 261 college students. Participants completed a web survey using the Smartphone Addiction Scale-Short Version (measuring PSU), Social and Process Smartphone Use Scale, and Intolerance of Uncertainty Scale-Short Form. The survey was administered twice, with approximately one month separating two measurement waves. In this paper, the measures of intolerance of uncertainty and social/non-social smartphone use from Time 1 and the PSU score from Time 2 were used. Correlation analyses showed that intolerance of uncertainty and both social and non-social smartphone use are related to Time 2 levels of PSU. In a structural equation model, intolerance of uncertainty was positively associated with non-social smartphone use, but not with social smartphone use. Non-social smartphone use was related to Time 2 PSU severity. Mediation analysis showed that only non-social smartphone use mediated the relationship between intolerance of uncertainty and levels of PSU. The study contributes to PSU research by demonstrating that intolerance of uncertainty and PSU are associated, and that non-social smartphone use may drive that relationship. This study emphasizes the need to understand the potential causes for excessive technology use.
•Problematic smartphone use (PSU) and intolerance of uncertainty (IU) were examined.•261 college students responded to a web survey twice, with one month apart.•IU was related to non-social smartphone use and PSU.•Non-social smartphone use mediated relations between IU and PSU.
Imaging devices in ophthalmology are numerous, and most of them are sophisticated and specialized for specific regions of the eye. In addition, these are fixed and involve close interaction of the ...patient and the examiner; therefore, simple, portable and tele facility–imbibed imaging tools can be considered optimal alternatives to routine exercises. In the last 10 years, utility of smartphones in ophthalmology is being continuously explored to unearth their potential benefits. In this direction, a smartphone device with/without simple attachments has been noted to aid in detailed, high-quality imaging of the ocular adnexa, cornea, angle, iris, lens, optic disc, and the retina including its periphery. In addition, such utility has also been extended in strabismology workup and intraocular pressure measurements. Hence, using these clinician friendly tools and techniques or by devising newer and more comprehensive tool kits, ophthalmic care can be well-managed with apt use of technology. Also, the smartphone companies are encouraged to collaborate with the medical experts to endeavor more, and help and serve the people better.
Smartphones are becoming increasingly indispensable in everyday life for most undergraduates in China, and this has been associated with problematic use or addiction. The aim of the current study was ...to investigate the prevalence of smartphone addiction and the associated factors in male and female undergraduates.
This cross-sectional study was conducted in 2016 and included 1441 undergraduate students at Wannan Medical College, China. The Smartphone Addiction Scale short version (SAS-SV) was used to assess smartphone addiction among the students, using accepted cut-offs. Participants' demographic, smartphone usage, and psycho-behavioral data were collected. Multivariate logistic regression models were used to seek associations between smartphone addiction and independent variables among the males and females, separately.
The prevalence of smartphone addiction among participants was 29.8% (30.3% in males and 29.3% in females). Factors associated with smartphone addiction in male students were use of game apps, anxiety, and poor sleep quality. Significant factors for female undergraduates were use of multimedia applications, use of social networking services, depression, anxiety, and poor sleep quality.
Smartphone addiction was common among the medical college students investigated. This study identified associations between smartphone usage, psycho-behavioral factors, and smartphone addiction, and the associations differed between males and females. These results suggest the need for interventions to reduce smartphone addiction among undergraduate students.
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