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Exclusive Corporate feature. Corporate Account. Statista Accounts: Access All Statistics. Basic Account. The ideal entry-level account for individual users. Corporate solution including all features. Statistics on " Smartphone market in Australia " The most important statistics. Similarly, as the capabilities of mobile phones continue to increase, certain individuals may be more prone to abusing functions offered by these devices e. The need to study these potentially negative impacts of mobile phone misuse has required the development of a number of tools to identify maladaptive mobile phone use.

The Problematic Mobile Phone Use Questionnaire [PMPUQ; 27 ] was developed to measure problematic phone use based on four factors: prohibited use, dangerous use, dependence symptoms, and financial problems associated with its use. Additionally, the Problematic Cellular Phone Use Questionnaire [PCPU-Q; 28 ] is another scale that has been developed to measure problematic cell phone use based on the taxonomies of substances use dependence e.

According to 29 problem mobile phone use in the MPPUS is measured based on potential predictors of behavioral and technological addiction. Since the development of the MPPUS in , countries around the world have witnessed the speed at which mobile phone technology has changed over the past decade. Hence, it is of utmost importance to revisit and update the literature, in order to determine whether problematic mobile phone use has become a pervasive issue in today's world.

Currently, there is a gap in the literature regarding the current trends of problem mobile phone use in Australia. In addition, it is also unclear whether problem mobile phone use, as originally defined by Bianchi and Phillips 29 , has changed since Thus, in order to address these gaps in the literature, the present study has two main objectives:.

This time comparison is relevant given the changing nature of mobile phones and growing pervasiveness of mobile phones in Australian society. In comparisons of samples collected in and , it is expected that the proportions of the sample reporting high levels of problem mobile phone use has increased from the first data collected in The following sections describe the methods used in this study.

The present study included a total of participants males and females. Table 1. Personal Characteristics of Participants in the a and studies conducted in Australia. Participants provided consent through the online submission of the survey.

Items in the MPPUS 29 assess symptoms of behavioral and technological addiction such as issues of tolerance, escaping from problems, withdrawal, craving, and negative life consequences e. In addition, the MPPUS 29 also consisted of items that examined loss of control over mobile phone usage e. The MPPUS 29 was validated based on moderately strong positive correlations reported between the scale and other measures of mobile phone use such as self-reported time spent using the mobile phone during the week, average monthly expenditure, and the number of calls made to people on a regular basis.

In addition to the MPPUS, participants were asked about their handheld and hands-free mobile phone use while driving a moving vehicle based on scales designed for this study. The questions pertained to the frequency with which they performed visual-manual interactions e. The data analysis plan was designed to meet two objectives, the first objective being to investigate the current problem mobile phone use in Australia and its potential implications for road safety.

To meet this objective, the following steps were taken. Firstly, the reliability and validity of the MPPUS 29 were analyzed to understand the current psychometric properties. However, societal and technological changes surrounding mobile phone use in the last 10 years necessitates confirmation of the psychometric properties, factorial structure and internal consistency of the MPPUS To assess the factorial structure, a statistical technique known as an exploratory factorial analysis was conducted via principal components analysis to replicate the analysis in the original study.

Finally, the reliability of the MPPUS was evaluated using measures of internal consistency by means of Cronbach's alpha coefficient. Secondly, the psychometric properties of the MPPUS were confirmed: the prevalence, user categories, and cut-off points in the MPPUS were determined following the methodology developed by de -Sola et al.

Differences by sex, age, education level, and mobile phone distracted driving among phone user categories were studied using ANOVA and correlation analyses. Thirdly, the influence of socio-demographic and mobile phone distracted driving factors on the user categories was studied using logistic regression, a statistical analysis which involves determining the probability of an outcome through its relationship to one or more predictors The statistical model predicted associations with two user categories: normal phone users the sum of casual and habitual and regular users and users with problematic phone usage including the sum of at risk users and problem users.

The second objective was to use the original Bianchi and Phillips 29 study to identify trends of change related to mobile phone misuse across the Australian population. An item-level analysis was conducted using the Mann-Whitney U test. This nonparametric test is used to compare two independent samples In this study, the Mann-Whitney U test was used to establish differences between the and samples by age and gender. Additionally, to illustrate changes in the prevalence of larger responses over time, the percentage of participants who marked a value of 6 or higher in each item was calculated for each age and gender and compared.

First, a principal component analysis was conducted to validate the factorial structure of the MPPUS. Although the final solution showed three factors explained variance of However, cross-loading items were retained as they fitted theoretically into a single main factor where they loaded the strongest Table A1 further illustrates the individual items' loadings.

To put the items into context, previous studies using the MPPUS were identified in a literature review search. As can be seen in Table 2 , Britain 36 consistently demonstrated higher means in comparison to Spain, Switzerland, and Australia It should also be noted that although 39 used fewer MPPUS items in the USA version, each one of their items revealed the highest means in comparison to the other countries.

Mobile phone users in the Australian sample were categorized based on the criteria by de -Sola et al. Table 3. This finding is consistent with the distribution of sex across user categories, which revealed that This finding is consistent with the distribution of age across user categories, such that the proportion of Problematic Users within the 18—24 year old age group was To understand the impact that problematic phone use has on health, this study explored the relationship between the item MPPUS and mobile phone use while driving.

Post-hoc comparison tests revealed that Problem Users significantly differ from Casual or Habitual and Regular Users for both handheld and hands-free phones while driving, such that Problem Users engage in more handheld and hands-free mobile use whilst driving compared to Casual or Habitual and Regular Users. A binary logistic regression was performed to identify the variables that predict Normal Users and Problematic Users.

The independent variables used in this analysis were age, sex, level of education, and mobile phone use while driving handheld and hands-free phone use while driving. The dependent variables comprised of the two categories used in the de -Sola et al. As can be seen in Table 4 , the results revealed that three variables: age, handheld mobile phone use while driving, and education level, were capable of differentiating between Normal Users and Problematic Users.

More specifically, it was found that an individual is more likely to be a deemed as a Problematic User if they use a handheld mobile phone while driving and belong to either the 18—24 or 25—59 year old age group.

However, participants currently enrolled in or who completed TAFE education compared to those who are studying or graduated from university are less likely to be classified as Problematic Users. An item-level analysis was conducted comparing scores from the study conducted by Bianchi and Phillips 29 and the current study.

As can be seen in Table 2 , the average MPPUS individual item scores have increased from when the scale was first used within the Australian population in Mann-Whitney U tests of independent samples were conducted to study differences between the and original item MPPUS based on sex and age.

With regards to sex, average MPPUS item scores increased for eight items within the male population between and see Table 5. In relation to the female population, the analysis revealed an increase in the average MPPUS item scores for more than half of the items in the scale between and i.

Table 5. Table 6. To illustrate changes in the prevalence of larger responses over time, the percentage of participants who marked a value of 6 or higher in each item was calculated for sex and age, as can be seen in Table A2. With regards to age, the sample consistently showed increases in selecting a value of 6 or higher for a majority of the MPPUS items.

The proportion of participants who reported a score of 6 or higher for Item 21 in the 18—25 years old age group was Likewise, the proportion of participants in 26—35 years old age group that reported scores of 6 or higher was 7. The proportion of participants who reported a score of 6 or higher for Item 17 in the 36—45 years old group was With regards to sex, higher percentages of prevalence were also found in the sample, with more participants in this study selecting a value of 6 or higher for most of the MPPUS items.

The first objective of this study was to investigate the current misuse of mobile phone technology in Australia and its potential implications on the health of Australians.

Specifically, this study examined the relationship between problematic mobile phone use at risk and problem users , sex, age, and education levels. The road safety implications of problematic mobile phone use were determined through the examination of the relationship between the MPPUS scores and mobile phone use while driving.

Using a mobile phone while driving has been established as one of the riskiest behaviors with serious potential consequences such as property damage, injury, and death 40 , Additionally, differences were investigated between the scores of the current Australian sample and the original Australian sample studied by Bianchi and Phillips This statistic is not included in your account.

Skip to main content Try our corporate solution for free! Single Accounts Corporate Solutions Universities. Premium statistics. Read more. In , the number of smartphone users in Australia was around This number was forecasted to reach This represented a smartphone penetration rate of over 80 percent in the country. A good data allowance facilitated the use of more than just the basic features of smartphones and nearly half of Australians said that they used the more advanced features of their phones, such as mobile email and internet.

By comparison, a small share said that they used their phone only for making calls. Additionally, mobiles were used for everyday activities such as transferring money to friends or family, as a boarding pass, and as a casting device. You need a Single Account for unlimited access.

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Register for free Already a member? At the same time, six-month sales of smartwatches grew 29 per cent, compared to 2H , as health and fitness features on smartwatches cannibalise other smart wrist bands. Almost three quarters of smartwatches sold during 2H were Apple Watches, accounting for , units, compared to just over half a year ago. Sign up to gain exclusive access to email subscriptions, event invitations, competitions, giveaways, and much more.

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