The majority of users of an app to help reduce alcohol consumption were relatively young, male, of a high social grade. The mean score of the mobile app users was 12.3 and the mean score was 6.3 indicating hazardous drinking and higher risk consumption.
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The majority of users of an app to help reduce alcohol consumption were relatively young, male, of a high social grade. The mean score of the mobile app users was 12.3 and the mean score was 6.3 indicating hazardous drinking and higher risk consumption. The majority of mobile app users took part in binge drinking at least once a month. When adjusting for other character- is tics, mobile app users were significantly young- germ than the general population of drinkers, and more likely to be of a higher social grade. There was no significant difference in gender after adjustment for other socio-demographic characteristics and score. Mobile app users compared with the general population of drinkers report greater alcohol consumption and more alcohol-related harms. This pattern of results, for socio-demographic and drinking characteristics, was the same when comparing mobile app users against only those drinkers who were digitally engaged though the age gap between groups was smaller in this comparison. These users who accessed the mobile through the app were more likely to be younger and report greater alcohol consumption and harms than those who accessed the intervention via the website. There-fore, individuals in need of support, not the ‘worried well’, are using alcohol reduction apps.
These results suggest that alcohol reduction apps reach people with a wide range of demographic characteristics though some groups of the general population of drinkers (those who are older, from the lower social grade) are less likely to use an alcohol reduction app. Smartphone ownership is more likely among younger age groups and people of a higher socioeconomic status though the differences in socio-demographic and drinking characteristics between app users and the general population remained when selecting only those who owned a smart digital device with internet access. This suggests that it is not simply ownership of a suitable device that is driving differences in demographic characteristics between users of the mobile app and the general population of drinkers. This is an important point to consider in terms of providing interventions equitably to excessive drinkers. One possible way to address this is to ensure that in health care settings with brief advice, GPs know that certain groups of drinkers may need additional prompting as they are less likely to search for and use an alcohol reduction app. Another is for local areas to promote digital interventions as part of their approach to reducing alcohol related harm. Such an initiative has just commenced who are utilizing a bespoke version of the mobile app for identification and brief advice across the region.
A major strength of this study is that it is the first to assess the user characteristics of an alcohol reduction app, and to compare them with the general population of drinkers and website users of the same intervention. The characteristics of patients using an app for support in recovery from alcoholism were assessed and it was found that the majority of patients were male, white and unemployed with a mean age of 38 years. These patients were enrolled into a study that involved using this app after ios app downloads and androind app downloads, so whilst these findings are interesting, they do not indicate who in the general population of drinkers are seeking help with reducing their alcohol consumption. In web-based normative feedback interventions, users in the general population had a mean age of 40, less than half were women and over half were employed. Users of these interventions tended to consume excessive levels of alcohol. Mobile app users were excessive drinkers and the majority were male, which is consistent with the findings from the web-based normative feedback interventions. However, mobile app users had a mean age of 31, younger than most of the mean ages for users of the web-based interventions. Another strength of this study is that the mobile app users were not enrolled or recruited into a trial but found the app on iTunes or the Google Play Store. Therefore, the mobile app users are representative of individuals who want to reduce their alcohol consumption and seek digital support, which mirrors the real-world situation for most users of behavior change apps.
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These results suggest that alcohol reduction apps reach people with a wide range of demographic characteristics though some groups of the general population of drinkers (those who are older, from the lower social grade) are less likely to use an alcohol reduction app. Smartphone ownership is more likely among younger age groups and people of a higher socioeconomic status though the differences in socio-demographic and drinking characteristics between app users and the general population remained when selecting only those who owned a smart digital device with internet access. This suggests that it is not simply ownership of a suitable device that is driving differences in demographic characteristics between users of the mobile app and the general population of drinkers. This is an important point to consider in terms of providing interventions equitably to excessive drinkers. One possible way to address this is to ensure that in health care settings with brief advice, GPs know that certain groups of drinkers may need additional prompting as they are less likely to search for and use an alcohol reduction app. Another is for local areas to promote digital interventions as part of their approach to reducing alcohol related harm. Such an initiative has just commenced who are utilizing a bespoke version of the mobile app for identification and brief advice across the region.
A major strength of this study is that it is the first to assess the user characteristics of an alcohol reduction app, and to compare them with the general population of drinkers and website users of the same intervention. The characteristics of patients using an app for support in recovery from alcoholism were assessed and it was found that the majority of patients were male, white and unemployed with a mean age of 38 years. These patients were enrolled into a study that involved using this app after ios app downloads and androind app downloads, so whilst these findings are interesting, they do not indicate who in the general population of drinkers are seeking help with reducing their alcohol consumption. In web-based normative feedback interventions, users in the general population had a mean age of 40, less than half were women and over half were employed. Users of these interventions tended to consume excessive levels of alcohol. Mobile app users were excessive drinkers and the majority were male, which is consistent with the findings from the web-based normative feedback interventions. However, mobile app users had a mean age of 31, younger than most of the mean ages for users of the web-based interventions. Another strength of this study is that the mobile app users were not enrolled or recruited into a trial but found the app on iTunes or the Google Play Store. Therefore, the mobile app users are representative of individuals who want to reduce their alcohol consumption and seek digital support, which mirrors the real-world situation for most users of behavior change apps.
More about world mobile apps you find on the site company '''AppReviewSubmit'''.
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