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Mobile Phone Comparison Biography

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1 Drug Policy Modelling Program, National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia

2 Centre for Alcohol Policy Research, Turning Point Alcohol and Drug Centre, Melbourne, Australia

3 Centre for Population Health, Burnet Institute, Melbourne, Australia

4 ARC Centre for Excellence in Policing, Brisbane, Australia

5 Institute for Social Science Research, University of Queensland, Queensland, Australia

6 Social Research Centre, Melbourne, Australia

7 Centre for Behavioural Research in Cancer, Cancer Council Victoria, Victoria, Australia

8 National Drug Research Institute, Curtin University, Perth, Australia

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BMC Medical Research Methodology 2013, 13:41 doi:10.1186/1471-2288-13-41

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2288/13/41

Received: 18 October 2012

Accepted: 11 March 2013

Published: 16 March 2013

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Telephone surveys based on samples of landline telephone numbers are widely used to measure the prevalence of health risk behaviours such as smoking, drug use and alcohol consumption. An increasing number of households are relying solely on mobile telephones, creating a potential bias for population estimates derived from landline-based sampling frames which do not incorporate mobile phone numbers. Studies in the US have identified significant differences between landline and mobile telephone users in smoking and alcohol consumption, but there has been little work in other settings or focussed on illicit drugs.

Methods

This study examined Australian prevalence estimates of cannabis use, tobacco smoking and risky alcohol consumption based on samples selected using a dual-frame (mobile and landline) approach. Respondents from the landline sample were compared both to the overall mobile sample (including respondents who had access to a landline) and specifically to respondents who lived in mobile-only households. Bivariate comparisons were complemented with multivariate logistic regression models, controlling for the effects of basic demographic variables.

Results

The landline sample reported much lower prevalence of tobacco use, cannabis use and alcohol consumption than the mobile samples. Once demographic variables were adjusted for, there were no significant differences between the landline and mobile respondents on any of the alcohol measures examined. In contrast, the mobile samples had significantly higher rates of cannabis and tobacco use, even after adjustment. Weighted estimates from the dual-frame sample were generally higher than the landline sample across all substances, but only significantly higher for tobacco use.

Conclusions

Landline telephone surveys in Australia are likely to substantially underestimate the prevalence of tobacco smoking by excluding potential respondents who live in mobile-only households. In contrast, estimates of alcohol consumption and cannabis use from landline surveys are likely to be broadly accurate, once basic demographic weighting is undertaken.

Background

Licit and illicit drug use is linked to a wide range of negative health and social outcomes [1-3] and has become a key concern for public health research. Survey research is a key component of the work in this area, with population surveys used to measure prevalence of use and risky use, to assess predictors of use and to monitor trends over time e.g. [4-7].

A key limitation of survey methods relates to the potential bias due to non-response. This occurs when respondents to a particular survey differ systematically from non-responders [8]. A number of studies have demonstrated that people who choose not to respond to surveys or who take more effort to recruit report higher rates of tobacco, alcohol and illicit drug use [9-12]. Increasingly, there are concerns that further bias is being introduced into survey estimates of these behaviours by the exclusion of otherwise eligible respondents who are not contactable because they do not have access to a landline telephone.

A substantial amount of health survey research makes use of samples drawn from landline telephone numbers using random digit dialling (RDD) [5,7]. However, there are increasing concerns about the representativeness of samples selected using landline RDD sampling frames due to the rapidly increasing number of households without landlines [13]. In 2011, estimates reported by the Australian Communications and Media Authority [14] suggest that around one-fifth of adults live in mobile phone only households and would thus be excluded for any surveys based on landlines alone. Internationally, this issue is a growing concern – around a third of households in the USA have no landline [15], while mobile-phone only households outnumber those with a landline in at least nine countries in the EU [16].

These changes in the representativeness of landline-based samples will result in substantial non-response bias in survey estimates if there are significant behavioural differences between those that are accessible via landline telephone and that are not.

In the USA, the recent decline in the prevalence of binge drinking, heavy alcohol consumption and smoking among young adults found in the Behavioural Risk Factor Surveillance System (a landline-based RDD telephone survey) has been attributed to the increasing numbers of young people living in mobile-only households and thus excluded from the sampling frame [17]. Only a handful of studies have directly compared estimates of health behaviours derived from mobile-phone and landline samples. Hu et al. [18] estimated that landline samples in the USA underestimate the prevalence of heavy episodic drinking by 14.8% and of smoking by 10.3%, even after adjustment for age, sex and education levels. Similarly, Blumberg and Luke found significantly higher rates of heavy drinking and smoking among a sample of young adults reached on mobile phones, compared with a similar landline based sample [19].

This issue has received less attention in Australia. A face-to-face study of South Australian households between 1999 and 2008 identified a steady increase in the number of mobile-only households, and that increases were particularly sharp amongst young, socio-economically disadvantaged people [20]. A small study of young women compared the prevalence estimates of a range of sexual health related outcomes from mobile- and landline-recruited samples, finding few differences [21]. In a more comprehensive study, Pennay [22] studied the differences between mobile-only and landline households in Australia. Even after weighting the data to account for the different underlying age, sex and region distributions of the two samples, the mobile-only sample had higher prevalence estimates of risky drinking, smoking, illegal drug use and problem gambling. Therefore, this study provided some evidence that undercoverage in landline-based surveys focussed on risky health behaviours is an important issue.

In this study we examine whether there are any differences in the estimates of alcohol, tobacco and illicit drug use obtained from landline versus mobile phone sampling strategies. Importantly, we consider these differences across a range of outcomes and in the context of key control variables typically used for sample weighting in survey research (age, sex, educational attainment). In light of previous research on this issue we expect that our mobile-phone sample would be more likely to report health risk behaviours. We have analysed our data in two ways – firstly comparing the respondents living in mobile-only households with the landline sample and then comparing the prevalence estimates obtained from the dual-frame surveya with those from the landline component only to determine the size of any bias introduced by only sampling landline households. This strategy enables us to answer two key questions: 1) How different are mobile-phone only respondents from respondents sampled using traditional CATI methods?, and 2) How well does the use of a dual-frame sampling regime overcome issues of undercoverage in landline-based telephone surveys?