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Objective: To assess the efficacy of an interactive smoking cessation decision-aid application (pp) compared with a smoking cessation static information app on continuous abstinence., Design: Automated double-blind randomised controlled trial with 6 months follow-up (2014-2015)., Setting: Smartphone-based., Participants: 684 participants (daily smokers of cigarettes, 18 years old or over) recruited passively from app stores in the USA, Australia, UK and Singapore, and randomised to one of two sub-apps., Interventions: Behavioural, decision-aid, smartphone application., Main Outcomes: Continuous abstinence at 10 days, 1 month, 3 months and 6 months., Results: Smokers who received the decision-aid app were more likely to be continuously abstinent at 1 month compared with the information-only app (28.5% vs 16.9%; relative risk (RR) 1.68; 95% CI 1.25 to 2.28). The effect was sustained at 3 months (23.8% vs 10.2%; RR 2.08; 95% CI 1.38 to 3.18) and 6 months (10.2% vs 4.8%; RR 2.02; 95% CI 1.08 to 3.81). Participants receiving the decision-aid app were also more likely to have made an informed choice (31.9% vs 19.6%) and have lower decisional conflict (19.5% vs 3.9%)., Conclusion: A smartphone decision-aid app with support features significantly increased smoking cessation and informed choice. With an increasing number of smokers attempting to quit, unassisted evidence-based decision-aid apps can provide an effective and user-friendly option to many who are making quit decisions without healthcare professionals., Trial Registration Number: ACTRN12613000833763., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

This study examines the feasibility of using a smartphone application (app) to conduct surveys among travellers during the Hajj pilgrimage, where the use of apps has not been evaluated for infectious disease surveillance. A longitudinal study was conducted among pilgrims at the Hajj 2014 using an iPhone app with separate questionnaires for three study phases covering before, during, and after Hajj. Forty-eight pilgrims from 13 countries downloaded the app. Respondents were aged between 21 and 61 (median 36) years and 58.5% (24/41) were male. Of these, 85% (41/48) completed the first phase, 52% (25/41) completed both the second and third phases, and 25 of these reported meningococcal vaccination, with 36% (9/25) receiving other vaccines. All (25) reported hand hygiene use and 64% (16/25) wore a facemask at some point during the pilgrimage. Four (6%) reported close contact with camels. Respiratory symptoms commenced from the 4th day of Hajj, with sore throat (20%) and cough (12%) being the most common. Three participants (12%) reported respiratory symptoms after returning home. Conducting a prospective survey using a smartphone app to collect data on travel-associated infections and traveller compliance to prevention is feasible at mass gatherings and can provide useful data associated with health-related behaviour., (Copyright © 2015 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.)

Background: The objective of disease screening is to encourage high-risk subjects to seek health care diagnosis and treatment. Mobile phone apps can effectively screen mental health conditions, including depression. However, it is not known how effective such screening methods are in motivating users to discuss the obtained results of such apps with health care professionals. Does a mobile phone depression-screening app motivate users with high depressive symptoms to seek health care professional advice? This study aimed to address this question., Method: This was a single-cohort, prospective, observational study of a free mobile phone depression app developed in English and released on Apple's App Store. Apple App Store users (aged 18 or above) in 5 countries, that is, Australia, Canada, New Zealand (NZ), the United Kingdom (UK), and the United States (US), were recruited directly via the app's download page. The participants then completed the Patient Health Questionnaire (PHQ-9), and their depression screening score was displayed to them. If their score was 11 or above and they had never been diagnosed with depression before, they were advised to take their results to their health care professional. They were to follow up after 1 month., Results: A group of 2538 participants from the 5 countries completed PHQ-9 depression screening with the app. Of them, 322 participants were found to have high depressive symptoms and had never been diagnosed with depression, and received advice to discuss their results with health care professionals. About 74% of those completed the follow-up; approximately 38% of these self-reported consulting their health care professionals about their depression score. Only positive attitude toward depression as a real disease was associated with increased follow-up response rate (odds ratio (OR) 3.2, CI 1.38-8.29)., Conclusions: A mobile phone depression-screening app motivated some users to seek a depression diagnosis. However, further study should investigate how other app users use the screening results provided by such apps.

Background: Pro-smoking applications (app) provide information about brands of tobacco products, where to buy them, and encourage their use. It is unclear in which countries these apps are being downloaded, or whether app stores play a role in promoting or regulating these apps, particularly those that appear to target children., Method: The lifetime popularity of 107 pro-smoking apps was investigated, using a third-party app metrics service that aggregates data from app stores about app download popularity by country. Apps were deemed popular if at any time in their lifespan they achieved a top 25 ranking overall across all apps, or a top 25 ranking in any particular category of apps, such as 'educational games'., Results: Fifty-eight pro-smoking apps reached 'popularity' status in Apple and Android stores in one or more of 49 countries, particularly Italy, Egypt, Germany, Belgium and the USA. The daily downloads in each country ranged from approximately 2000 to 80 000. The Apple store featured five of the pro-smoking apps in various categories, and two apps were featured by the Android market. Two pro-smoking apps in the Apple store were extremely popular in the 'Educational Games' and 'Kids' Games' categories., Conclusions: Pro-smoking apps were popular in many countries. Most apps were assigned to entertainment and games categories, with some apps specifically targeting children through placement in categories directed at children. App stores that feature pro-smoking apps may be in violation of tobacco control laws., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Introduction: There are large numbers of health-related applications (apps) available in various app stores for many smartphone devices. Consequently, increasing numbers of articles are attempting to evaluate the content and the quality of health-related smartphone apps for specific health conditions. The aim of this article is to describe and summarize the methodologies used to determine the quality of health-related apps targeting health consumers and to propose a set of criteria for evaluating the quality of smartphone health-related apps., Materials and Methods: In 2013, literature searches were performed using Medline and CINAHL, and we included all articles that had the aim of assessing the quality of health-related smartphone apps. The assessment method used in these studies was summarized and scored using a set of quality criteria developed for this study., Results: From 606 articles generated by the search, only 10 met the inclusion criteria. Based on our quality criteria, the mean score was 5.05 out of 8 (range, 2-7). Eighty percent of the studies did not identify the app store country in which the apps were found. Forty percent of the studies did not clearly mention whether they only had assessed the app description or had downloaded the app content for evaluation. Sixty percent of the studies did not provide a list of the apps they had evaluated. Overall, we identified six evaluation methodologies used to assess the quality of health-related apps described in RESULTS., Conclusions: This article provides a summary of currently used methods for assessing the quality of smartphone health-related apps and proposes a set of criteria to enable future studies to consistently review health-related app quality in a standardized manner.

Background: The greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the 'mass' approach), the 'high risk' approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer(TM) , has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods., Methods: 752 stroke outcomes from a sample of 9501 individuals across three countries (New Zealand, Russia and the Netherlands) were utilized to investigate the performance of a novel stroke risk prediction tool algorithm (Stroke Riskometer(TM) ) compared with two established stroke risk score prediction algorithms (Framingham Stroke Risk Score [FSRS] and QStroke). We calculated the receiver operating characteristics (ROC) curves and area under the ROC curve (AUROC) with 95% confidence intervals, Harrels C-statistic and D-statistics for measure of discrimination, R(2) statistics to indicate level of variability accounted for by each prediction algorithm, the Hosmer-Lemeshow statistic for calibration, and the sensitivity and specificity of each algorithm., Results: The Stroke Riskometer(TM) performed well against the FSRS five-year AUROC for both males (FSRS = 75.0% (95% CI 72.3%-77.6%), Stroke Riskometer(TM) = 74.0(95% CI 71.3%-76.7%) and females [FSRS = 70.3% (95% CI 67.9%-72.8%, Stroke Riskometer(TM)  = 71.5% (95% CI 69.0%-73.9%)], and better than QStroke [males - 59.7% (95% CI 57.3%-62.0%) and comparable to females = 71.1% (95% CI 69.0%-73.1%)]. Discriminative ability of all algorithms was low (C-statistic ranging from 0.51-0.56, D-statistic ranging from 0.01-0.12). Hosmer-Lemeshow illustrated that all of the predicted risk scores were not well calibrated with the observed event data (P < 0.006)., Conclusions: The Stroke Riskometer(TM) is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke Riskometer(TM) will be continually developed and validated to address the need to improve the current stroke risk scoring systems to more accurately predict stroke, particularly by identifying robust ethnic/race ethnicity group and country specific risk factors., (© 2014 The Authors. International Journal of Stroke published by John Wiley & Sons Ltd on behalf of World Stroke Organization.)

Background and Objective: Smartphone applications (apps) have the potential to be valuable self-help interventions for depression screening. However, information about their feasibility and effectiveness and the characteristics of app users is limited. The aim of this study is to explore the uptake, utilization, and characteristics of voluntary users of an app for depression screening., Methods: This was a cross-sectional study of a free depression screening smartphone app that contains the demographics, patient health questionnaire (PHQ-9), brief anxiety test, personalized recommendation based on the participant's results, and links to depression-relevant websites. The free app was released globally via Apple's App Store. Participants aged 18 and older downloaded the study app and were recruited passively between September 2012 and January 2013., Findings: 8241 participants from 66 countries had downloaded the app, with a response rate of 73.9%. While one quarter of the participants had a previous diagnosis of depression, the prevalence of participants with a higher risk of depression was 82.5% and 66.8% at PHQ-9 cut-off 11 and cut-off 15, respectively. Many of the participants had one or more physical comorbid conditions and suicidal ideation. The cut-off 11 (OR: 1.4; 95% CI 1.2 to 1.6), previous depression diagnosis (OR: 1.3; 95% CI1.2 to 1.5), and postgraduate educational level (OR: 1.2; 95% CI 1.0 to 1.5) were associated with completing the PHQ-9 questionnaire more than once., Conclusions: Smartphone apps can be used to deliver a screening tool for depression across a large number of countries. Apps have the potential to play a significant role in disease screening, self-management, monitoring, and health education, particularly among younger adults., (© The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.comFor numbered affiliations see end of article.)

Introduction: In a previous study exploring the feasibility of a smoking cessation application (app), we found that about 77% of the respondents from three countries were ready to quit in the next 30 days without significant differences between countries in terms of age, operating system and number of quitting attempts. However, the efficacy of smartphone apps for smoking cessation has not yet been established. This study tests the efficacy of a smartphone smoking cessation decision-aid app compared with an app that contains only smoking cessation information., Methods and Analysis: This is an automated double-blind, randomised controlled trial of a smoking cessation app that contains the eligibility requirements and baseline questionnaire and will randomise the participants into one of the two subapps (the intervention and the control). Participants will be recruited directly from the Apple app stores in Australia, Singapore, the UK and the USA. Daily smokers aged 18 and above will be randomised into one of the subapps after completing the baseline questionnaire. Abstinence rates will be measured at 10 days, 1 month, 3 months and 6 months, with the 1-month follow-up abstinence rate as the primary outcome. Logistic regression mixed models will be used to analyse the primary outcome., Ethics and Dissemination: This study was approved by the University of Sydney's Human Ethics Committee. The results of the trial will be published in peer-reviewed journals according to the CONSORT statement., Trial Registration Number: Australian New Zealand ClinicalTrial RegistryACTRN12613000833763., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)