Abstract

The advances in Mobile Health (M-health) technologies has led to an increase in the numbers of alcohol and drugs applications on the commercial stores. Content analyses and reviews of applications to date have demonstrated that most of these applications are for entertainment or information purposes. More recent content analyses have identified common behavioural change techniques in substance applications. Nevertheless, there remain several limitations of existing content analyses and reviews of applications. There is an increasing prevalence of other substance-related disorders, such as that of stimulants and opioids, but the existing content analyses are limited to an analysis of alcohol and cannabis applications. Only two of the content analyses performed to date have attempted to identify applications that have their basis on a theoretical approach, based on the identification of behavioural change techniques or motivational techniques. There is a need to identify applications on the commercial stores that replicate conventional psychological interventions, or at least provide elements of conventional psychological interventions using behavioural change techniques that are integrated into the application. Further evaluative research could be done on these applications to determine if they are efficacious before using them for patient care. To address the limitation that existing content analyses have only focused on reviews of alcohol and cannabis applications, we propose for there to be updated content analyses for alcohol and cannabis, and new content analyses for other substances of abuse (such as opioids and stimulants). We like to suggest that future reviews consider keywords such as abstinence or recovery, and ones that relate to psychological therapies, such as self-determination or attention bias retraining, as commercial applications that have an underlying psychological basis might be categorised differently, under different keyword terms. We have evidence of how a better search strategy identifies previously unrecognised applications for attentional bias modification.

Highlights

  • M-Health (Mobile Health) refers to the use of mobile technologies, such as mobile phones and their accompanying applications for healthcare interventions [1]

  • The advances in M-health have led to there being a corresponding increase in the number of alcohol and drugs-related applications being marketed on the commercial stores

  • Within the LBMI-A application, the assessment function is a brief motivational intervention tool; the high-risk location functionality is based on principles of relapse prevention; the identification of supportive people is based on the Community Reinforcement and Family Training (CRAFT) approach, and the craving functionality based on cognitive behavioural theory [11]

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Summary

Introduction

M-Health (Mobile Health) refers to the use of mobile technologies, such as mobile phones and their accompanying applications for healthcare interventions [1]. The advances in M-health have led to there being a corresponding increase in the number of alcohol and drugs-related applications being marketed on the commercial stores. Smartphone applications are increasingly popular, as for the healthcare professionals, they serve as good tools for primary and secondary prevention of addictive disorders. Res. Public Health 2018, 15, 1389 help to overcome geographic barriers, and stigma associated with help seeking [2]. Donker T et al (2013) [3] has, in their prior systematic review, highlighted that there are currently applications in the published literature that seek to intervene for psychiatric disorders, that of depression, anxiety, and substance abuse. There has been a series of content analyses undertaken to characterize substance-related applications on the stores, and to determine their underlying evidence base. We can propose methods that could help bridge the gap in the current research literature

Evidence from Existing Content Analyses
Key Findings
Limitations
Bridging the Gaps
Findings
Conclusions
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