Online technologies, such as the smartphone, are pervasive across our society and are growing at a rate that exceeds our understanding of their implications. Much of the technology relies on methods of operant conditioning (based on a system of rewards and punishments for prior actions) to keep the user engaged through pleasurable and rewarding experiences, or even as a means of relief from negative moods (Wang, 2020). Over 82% of Australians own a smartphone (Winskel et al., 2019), therefore as rates of smartphone usage increase there can be subsequent behavioural addiction implications. Research is sparse, but some studies have reported how smartphone apps generate self-awareness of usage through Ecological Momentary Assessment/Intervention (EMA/EMI), decreasing addictive habits and behaviours (Runyan et al., 2013). Mindfulness behaviour implemented through apps may be more effective in reversing operant conditioning smartphone technology than traditional Cognitive Behavioural Theory (CBT) treatments which are not implemented through the technology itself (Brewer, 2019).
Andreassen and Pallesen (2014) posit that the motivation to use online technologies can be so strong that it impairs other social activities, studies/job, interpersonal relationships, and/or psychological health and well-being, causing addictive behaviours. The World Health Organisation (WHO) has now recognised the importance of online addictive treatment tools, defining mobile health (mHealth) as representing the promotion of mental health, wellbeing, and treatment through the mobile phone (Lam and Lam, 2016). Research has shown that smartphone addictive behaviours can be treated through software tools, using the principles of operant conditioning. Ko et al.(2015) implemented an incentivized goal setting and rewards group based software tool called NUGU (when No Use is Good Use) on participant’s smartphones. This software elicited significant positive results in addressing over-use and addictive tendencies by making participant’s usage habits socially accountable and also through reinforcing positive usage behaviour. This generated self-awareness and mitigated uncontrolled and impulsive usage.
Research into the assessment and measurement of smartphone usage has found real-time EMA/EMI app-generated data, rather than self-reported questionnaires (which often are subject to self-reflexive bias) more effective in providing accurate usage data (Wu et al., 2020). A study conducted by Runyan et al. (2013) provided smartphone users with real-time insight into their usage behaviour through the app iHabit. This elicited positive behavioural change through self-awareness, with 80.49% of participants reporting that the app made them more aware of how they spent their time, and 44% of participants agreed they had changed their behaviour because of the app. Recent research conducted by Schmuck (2020) found that 41.7 percent of young adults now use digital detox apps. EMA/EMI and mHealth apps elicit a greater understanding of smartphone usage and draw self-awareness to user habits, therefore decreasing addictive behaviours.
Studies have found that it can be difficult to ascertain if addictive smartphone usage is separate from the experience of actual pathological symptoms of the smartphone user (Kuss & Griffiths, 2017). There is even strong conjecture regarding the definition of smartphone addiction due to its eclectic nature (Wu et al., 2020). The current inability to identify smartphone addiction within a nosological capacity is one of the reasons why traditional CBT methods in clinical treatment settings are preferred. In addressing maladaptive cognitions exacerbated through external issues, CBT treatments address smartphone addiction through therapy sessions in support groups, setting goals and selective abstinence (Sharma and Palanichamy, 2018). Brewer (2019) however, argues that the pervasiveness of online technologies makes CBT methods such as abstinence, outdated and ineffective. Instead, he focuses upon the need to treat smartphone addiction through the technology itself as supported by the meta-analysis of neuroimaging data that display how the value of positively reinforcing behaviours encoded in the orbitofrontal cortex (OFC) of the brain can be harnessed by mindfulness technology.
There are various limitations within the studies, exacerbated by the research field being so young. As outlined by Kuss & Griffiths (2017), differing diagnostic criteria, and addiction scales based on varying theoretical frameworks and self-awareness assessment methods, continue to question the validity and correlational veracity of the research. App glitches with EMA/EMI technology and small socio-demographic sample sizes (Runyan et al., 2013) may not translate in different target populations. Gower and Moreno (2018) labeled EMA apps as burdensome to participants and sought to study new methodologies. Furthermore, research would benefit from in-depth analysis of longitudinal studies (Ko et al., 2015). Caution must also be used when ascertaining the effectiveness of apps and software as some researchers are the developers and have vested interest in their success.
In conclusion, research into varying aspects of smartphone addiction and its different fields of specificity is sparse and complex. Traditional CBT treatments are challenged by smartphone apps that use EMA/EMI to obtain real-time data and treat addictive behaviours through self-awareness, mindfulness, and operant conditioning principles to elicit positive change in behaviour and habits. These apps therefore, may reverse addiction through greater self-awareness generated by operant conditioning processes. As smartphones are now an integral part of life, it is imperative that further smartphone addiction studies are conducted to ascertain the implications this technology has on individual behaviour and society as a whole.
The direction of future research needs to include the creation of a comprehensive taxonomy of online addiction to raise clinical significance, targeted treatment, and validity of measurement tools (Wu et al., 2020). Further research requires the inclusion of psychopathological influences on addictive smartphone behaviour, ideally with CBT conceptual understandings coupled with mindfulness apps, to draw attention to addictive smartphone usage (Lam and Lam, 2016). The use of the smartphone has proliferated through most demographic groups, and for many people of lower socio-economic status, the smartphone is their only access to technology (Lucas-Thompson et al., 2019). Therefore, EMA/EMI apps and their associated operant conditioning treatment interventions, implemented through smartphone technology, are the most accessible and relevant way in which to assess, intervene and treat all manner of addictions. mHealth requires continual research and refinement to effectively utilise such a pervasive and easily accessible tool that has the ability to generate the best outcomes for society.
References
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