Nasser F BinDhim

A Systematic Review of Quality Assessment Methods for Smartphone Health Apps

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.

Depression screening via a smartphone app: cross-country user characteristics and feasibility

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 participants results, and links to depression-relevant websites. The free app was released globally via Apples 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.

Who Uses Smoking Cessation Apps? A Feasibility Study Across Three Countries via Smartphones

Background Smartphone use is growing worldwide. While hundreds of smoking cessation apps are currently available in the app stores, there is no information about who uses them. Smartphones also offer potential as a research tool, but this has not previously been explored. Objective This study aims to measure and compare the uptake of a smoking cessation app over one year in Australia, the United Kingdom, and the United States. It also assesses the feasibility of conducting research via an app, describing respondents’ characteristics (demographics, smoking status, and other health related app use), and examining differences across countries. Methods This is a cross-sectional exploratory study of adults 18 years and older, passively recruited over one year in 2012, who downloaded this study app (Quit Advisor) via the two largest app stores (Apple and Android). Results The total number of app downloads after one year was 1751, 72.98% (1278/1751) of them were Apple operation system users. Of these 1751 participants, 47.68% (835/1751) were from the United States, 29.18% (511/1751) were from the United Kingdom, and 16.68% (292/1751) were from Australia. There were 602 participants, 36.75% (602/1638) that completed a questionnaire within the app. Of these 602 participants, 58.8% (354/602) were female and the mean age was 32 years. There were no significant differences between countries in terms of age, operation system used, number of quitting attempts, and language spoken at home. However, there were significant differences between countries in terms of gender and stage of change. There were 77.2% (465/602) of the respondents that were ready to quit in the next 30 days and the majority of these had never sought professional help (eg, “Quitline”). More than half had downloaded smoking cessation apps in the past and of these, three-quarters had made quitting attempts (lasted at least 24 hours) using an app before. Respondents who had attempted to quit three times or more in the previous year were more likely to have tried smoking cessation apps (OR 3.3, 95% CI 2.1-5.2). There were 50.2% (302/602) of the respondents that had used other health related apps before. Of these, 89.4% (270/302) were using health related apps at least once a week, but 77.5% (234/302) never checked the credibility of the health app publishers before downloading. Conclusions A smartphone app was able to reach smokers across three countries that were not seeking professional help, but were ready to quit within the next 30 days. Respondents were relatively young and almost demographically similar across all three countries. They also frequently used other health related apps, mostly without checking the credibility of their publishers.

Pro-smoking apps for smartphones: the latest vehicle for the tobacco industry?

Background Smartphone use is growing exponentially and will soon become the only mobile phone handset for about 6 billion users. Smartphones are ideal marketing targets as consumers can be reached anytime, anywhere. Smartphone application (app) stores are global shops that sell apps to users all around the world. Although smartphone stores have a wide collection of health-related apps they also have a wide set of harmful apps. In this study, the availability of ‘pro-smoking’ apps in two of the largest smartphone app stores (Apple App store and Android Market) was examined. Method In February 2012, we searched the Apple App Store and Android Market for pro-smoking apps, using the keywords Smoke, Cigarette, Cigar, Smoking and Tobacco. We excluded apps that were not tobacco-related and then assessed the tobacco-related apps against our inclusion criteria. Result 107 pro-smoking apps were identified and classified into six categories based on functionality.42 of these apps were from the Android Market and downloaded by over 6 million users. Some apps have explicit images of cigarette brands. Conclusions Tobacco products are being promoted in the new ‘smartphone app’ medium which has global reach, a huge consumer base of various age groups and underdeveloped regulation. The paper also provides two examples of app store responses to country-specific laws and regulations that could be used to control the harmful contents in the app stores for individual countries.

The Stroke RiskometerTM App: Validation of a data collection tool and stroke risk predictor

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™, 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™) 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, R2 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™ performed well against the FSRS five-year AUROC for both males (FSRS = 75·0% (95% CI 72·3%–77·6%), Stroke Riskometer™ = 74·0(95% CI 71·3%–76·7%) and females [FSRS = 70·3% (95% CI 67·9%–72·8%, Stroke Riskometer™ = 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™ is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke Riskometer™ 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.

Assessing the effect of an interactive decision-aid smartphone smoking cessation application (app) on quit rates: a double-blind automated randomised control trial protocol

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 Sydneys 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.

Australian Hajj pilgrims' knowledge, attitude and perception about Ebola, November 2014 to February 2015.

Upon return from Hajj 2014, 150 Australian pilgrims were interviewed about their understanding of the Ebola epidemic. Most (89%, 134/150) knew of the epidemic before travelling and 60% (80/134) of those knew Ebola transmits through body fluids. Pilgrims who received pre-travel health advice were more conscious of Ebola (69% vs 31%, p = 0.01) and adhered better to hand hygiene after touching an ill person (68% vs 31%, p < 0.01). Mass media was the main information source (78%).

Does a Mobile Phone Depression-Screening App Motivate Mobile Phone Users With High Depressive Symptoms to Seek a Health Care Professional’s Help?

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.

Pro-smoking apps: where, how and who are most at risk

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.

Pilot use of a novel smartphone application to track traveller health behaviour and collect infectious disease data during a mass gathering: Hajj pilgrimage 2014

Abstract 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.