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1.
Sci Rep ; 12(1): 793, 2022 01 17.
Article in English | MEDLINE | ID: covidwho-1630881

ABSTRACT

Pharmacological and non-pharmacological measures will overlap for a period after the onset of the pandemic, playing a strong role in virus containment. We explored which factors influence the likelihood to adopt two different preventive measures against the COVID-19 pandemic. An online snowball sampling (May-June 2020) collected a total of 448 questionnaires in Italy. A Bayesian bivariate Gaussian regression model jointly investigated the willingness to get vaccinated against COVID-19 and to download the national contact tracing app. A mixed-effects cumulative logistic model explored which factors affected the motivation to adopt one of the two preventive measures. Despite both COVID-19 vaccines and tracing apps being indispensable tools to contain the spread of SARS-CoV-2, our results suggest that adherence to the vaccine or to the national contact tracing app is not predicted by the same factors. Therefore, public communication on these measures needs to take in consideration not only the perceived risk associated with COVID-19, but also the trust people place in politics and science, their concerns and doubts about vaccinations, and their employment status. Further, the results suggest that the motivation to comply with these measurements was predominantly to protect others rather than self-protection.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Contact Tracing/methods , Mobile Applications/statistics & numerical data , Pandemics/prevention & control , Humans , Intention , Italy/epidemiology , Surveys and Questionnaires , Vaccination
3.
J Med Internet Res ; 23(2): e24893, 2021 02 18.
Article in English | MEDLINE | ID: covidwho-1574527

ABSTRACT

BACKGROUND: Suboptimal adherence to 6-mercaptopurine (6-MP) is prevalent in pediatric acute lymphoblastic leukemia (ALL) and associated with increased risk of relapse. Rapid uptake of personal technology makes mobile health (mHealth) an attractive platform to promote adherence. OBJECTIVE: Study objectives were to examine access to mobile technology and preferences for an mHealth intervention to improve medication adherence in pediatric ALL. METHODS: A cross-sectional survey was administered in oncology clinic to parents of children with ALL as well as adolescents and young adults (AYAs) with ALL receiving maintenance chemotherapy. RESULTS: A total of 49 parents (median age [IQR] 39 [33-42] years; female 76% [37/49]) and 15 patients (median age [IQR] 17 [16-19]; male 80% [12/15]) participated. All parents and AYAs owned electronic tablets, smartphones, or both. Parents' most endorsed mHealth app features included a list of medications (71%, 35/49), information about 6-MP (71%, 35/49), refill reminders (71%, 35/49), and reminders to take 6-MP (71%, 35/49). AYAs' most endorsed features included refill reminders (73%, 11/15), reminders to take 6-MP (73%, 11/15), and tracking 6-MP (73%, 11/15). CONCLUSIONS: Parents and AYAs reported ubiquitous access to mobile technology and strong interest in multiple adherence-specific mHealth app features. Parents and AYAs provided valuable insight into preferred features for a multifunctional behavioral intervention (mHealth app) to promote medication adherence in pediatric ALL.


Subject(s)
Behavior Therapy/methods , Medication Adherence/statistics & numerical data , Precursor Cell Lymphoblastic Leukemia-Lymphoma/therapy , Technology/methods , Telemedicine/methods , Adolescent , Adult , Child , Child, Preschool , Cross-Sectional Studies , Female , Humans , Male , Mobile Applications/statistics & numerical data , Smartphone , Surveys and Questionnaires , Young Adult
4.
CMAJ ; 193(24): E921-E930, 2021 06 14.
Article in French | MEDLINE | ID: covidwho-1551317

ABSTRACT

CONTEXTE: Les interventions non pharmacologiques demeurent le principal moyen de maîtriser le coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) d'ici à ce que la couverture vaccinale soit suffisante pour donner lieu à une immunité collective. Nous avons utilisé des données de mobilité anonymisées de téléphones intelligents afin de quantifier le niveau de mobilité requis pour maîtriser le SRAS-CoV-2 (c.-à-d., seuil de mobilité), et la différence par rapport au niveau de mobilité observé (c.-à-d., écart de mobilité). MÉTHODES: Nous avons procédé à une analyse de séries chronologiques sur l'incidence hebdomadaire du SRAS-CoV-2 au Canada entre le 15 mars 2020 et le 6 mars 2021. Le paramètre mesuré était le taux de croissance hebdomadaire, défini comme le rapport entre les cas d'une semaine donnée et ceux de la semaine précédente. Nous avons mesuré les effets du temps moyen passé hors domicile au cours des 3 semaines précédentes à l'aide d'un modèle de régression log-normal, en tenant compte de la province, de la semaine et de la température moyenne. Nous avons calculé le seuil de mobilité et l'écart de mobilité pour le SRAS-CoV-2. RÉSULTATS: Au cours des 51 semaines de l'étude, en tout, 888 751 personnes ont contracté le SRAS-CoV-2. Chaque augmentation de 10 % de l'écart de mobilité a été associée à une augmentation de 25 % du taux de croissance des cas hebdomadaires de SRAS-CoV-2 (rapport 1,25, intervalle de confiance à 95 % 1,20­1,29). Comparativement à la mobilité prépandémique de référence de 100 %, le seuil de mobilité a été plus élevé au cours de l'été (69 %, écart interquartile [EI] 67 %­70 %), et a chuté à 54 % pendant l'hiver 2021 (EI 52 %­55 %); un écart de mobilité a été observé au Canada entre juillet 2020 et la dernière semaine de décembre 2020. INTERPRÉTATION: La mobilité permet de prédire avec fiabilité et constance la croissance des cas hebdomadaires et il faut maintenir des niveaux faibles de mobilité pour maîtriser le SRAS-CoV-2 jusqu'à la fin du printemps 2021. Les données de mobilité anonymisées des téléphones intelligents peuvent servir à guider le relâchement ou le resserrement des mesures de distanciation physique provinciales et régionales.


Subject(s)
COVID-19/prevention & control , Geographic Mapping , Mobile Applications/standards , Patient Identification Systems/methods , COVID-19/epidemiology , COVID-19/transmission , Canada/epidemiology , Humans , Mobile Applications/statistics & numerical data , Patient Identification Systems/statistics & numerical data , Quarantine/methods , Quarantine/standards , Quarantine/statistics & numerical data , Regression Analysis , Time Factors
5.
Int J Public Health ; 66: 1603992, 2021.
Article in English | MEDLINE | ID: covidwho-1533731

ABSTRACT

Objectives: We aimed to evaluate the effectiveness of the SwissCovid digital proximity tracing (DPT) app in notifying exposed individuals and prompting them to quarantine earlier compared to individuals notified only by manual contact tracing (MCT). Methods: A population-based sample of cases and close contacts from the Zurich SARS-CoV-2 Cohort was surveyed regarding SwissCovid app use and SARS-CoV-2 exposure. We descriptively analyzed app adherence and effectiveness, and evaluated its effects on the time between exposure and quarantine among contacts using stratified multivariable time-to-event analyses. Results: We included 393 SARS-CoV-2 infected cases and 261 close contacts. 62% of cases reported using SwissCovid and among those, 88% received and uploaded a notification code. 71% of close contacts were app users, of which 38% received a warning. Non-household contacts notified by SwissCovid started quarantine 1 day earlier and were more likely to quarantine earlier than those not warned by the app (HR 1.53, 95% CI 1.15-2.03). Conclusion: These findings provide evidence that DPT may reach exposed contacts faster than MCT, with earlier quarantine and potential interruption of SARS-CoV-2 transmission chains.


Subject(s)
COVID-19 , Contact Tracing , Mobile Applications , Quarantine , Adult , COVID-19/epidemiology , COVID-19/prevention & control , Cohort Studies , Contact Tracing/methods , Female , Humans , Male , Middle Aged , Mobile Applications/statistics & numerical data , Quarantine/statistics & numerical data , Switzerland/epidemiology , Time Factors
6.
Lancet Infect Dis ; 22(1): 43-55, 2022 01.
Article in English | MEDLINE | ID: covidwho-1500361

ABSTRACT

BACKGROUND: COVID-19 vaccines show excellent efficacy in clinical trials and effectiveness in real-world data, but some people still become infected with SARS-CoV-2 after vaccination. This study aimed to identify risk factors for post-vaccination SARS-CoV-2 infection and describe the characteristics of post-vaccination illness. METHODS: This prospective, community-based, nested, case-control study used self-reported data (eg, on demographics, geographical location, health risk factors, and COVID-19 test results, symptoms, and vaccinations) from UK-based, adult (≥18 years) users of the COVID Symptom Study mobile phone app. For the risk factor analysis, cases had received a first or second dose of a COVID-19 vaccine between Dec 8, 2020, and July 4, 2021; had either a positive COVID-19 test at least 14 days after their first vaccination (but before their second; cases 1) or a positive test at least 7 days after their second vaccination (cases 2); and had no positive test before vaccination. Two control groups were selected (who also had not tested positive for SARS-CoV-2 before vaccination): users reporting a negative test at least 14 days after their first vaccination but before their second (controls 1) and users reporting a negative test at least 7 days after their second vaccination (controls 2). Controls 1 and controls 2 were matched (1:1) with cases 1 and cases 2, respectively, by the date of the post-vaccination test, health-care worker status, and sex. In the disease profile analysis, we sub-selected participants from cases 1 and cases 2 who had used the app for at least 14 consecutive days after testing positive for SARS-CoV-2 (cases 3 and cases 4, respectively). Controls 3 and controls 4 were unvaccinated participants reporting a positive SARS-CoV-2 test who had used the app for at least 14 consecutive days after the test, and were matched (1:1) with cases 3 and 4, respectively, by the date of the positive test, health-care worker status, sex, body-mass index (BMI), and age. We used univariate logistic regression models (adjusted for age, BMI, and sex) to analyse the associations between risk factors and post-vaccination infection, and the associations of individual symptoms, overall disease duration, and disease severity with vaccination status. FINDINGS: Between Dec 8, 2020, and July 4, 2021, 1 240 009 COVID Symptom Study app users reported a first vaccine dose, of whom 6030 (0·5%) subsequently tested positive for SARS-CoV-2 (cases 1), and 971 504 reported a second dose, of whom 2370 (0·2%) subsequently tested positive for SARS-CoV-2 (cases 2). In the risk factor analysis, frailty was associated with post-vaccination infection in older adults (≥60 years) after their first vaccine dose (odds ratio [OR] 1·93, 95% CI 1·50-2·48; p<0·0001), and individuals living in highly deprived areas had increased odds of post-vaccination infection following their first vaccine dose (OR 1·11, 95% CI 1·01-1·23; p=0·039). Individuals without obesity (BMI <30 kg/m2) had lower odds of infection following their first vaccine dose (OR 0·84, 95% CI 0·75-0·94; p=0·0030). For the disease profile analysis, 3825 users from cases 1 were included in cases 3 and 906 users from cases 2 were included in cases 4. Vaccination (compared with no vaccination) was associated with reduced odds of hospitalisation or having more than five symptoms in the first week of illness following the first or second dose, and long-duration (≥28 days) symptoms following the second dose. Almost all symptoms were reported less frequently in infected vaccinated individuals than in infected unvaccinated individuals, and vaccinated participants were more likely to be completely asymptomatic, especially if they were 60 years or older. INTERPRETATION: To minimise SARS-CoV-2 infection, at-risk populations must be targeted in efforts to boost vaccine effectiveness and infection control measures. Our findings might support caution around relaxing physical distancing and other personal protective measures in the post-vaccination era, particularly around frail older adults and individuals living in more deprived areas, even if these individuals are vaccinated, and might have implications for strategies such as booster vaccinations. FUNDING: ZOE, the UK Government Department of Health and Social Care, the Wellcome Trust, the UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare, the UK National Institute for Health Research, the UK Medical Research Council, the British Heart Foundation, and the Alzheimer's Society.


Subject(s)
COVID-19/epidemiology , Mobile Applications/statistics & numerical data , Vaccination/statistics & numerical data , Adult , Aged , COVID-19/prevention & control , COVID-19 Testing/statistics & numerical data , Case-Control Studies , Female , Humans , Male , Middle Aged , Prospective Studies , Risk Factors , Self Report , United Kingdom/epidemiology , Young Adult
7.
Environ Health Prev Med ; 26(1): 94, 2021 Sep 21.
Article in English | MEDLINE | ID: covidwho-1435220

ABSTRACT

BACKGROUND: To combat coronavirus disease 2019 (COVID-19), many countries have used contact tracing apps, including Japan's voluntary-use contact-confirming application (COCOA). The current study aimed to identify industry and workplace characteristics associated with the downloading of this COVID-19 contact tracing app. METHODS: This cross-sectional study of full-time workers used an online survey. Multiple logistic regression analysis was used to evaluate the associations of industry and workplace characteristics with contact tracing app use. RESULTS: Of the 27,036 participants, 25.1% had downloaded the COCOA. Workers in the public service (adjusted odds ratio [aOR] = 1.29, 95% confidence interval [CI] 1.14-1.45) and information technology (aOR = 1.38, 95% CI 1.20-1.58) industries were more likely to use the app than were those in the manufacturing industry. In contrast, app usage was less common among workers in the retail and wholesale (aOR = 0.87, 95% CI 0.76-0.99) and food/beverage (aOR = 0.81, 95% CI 0.70-0.94) industries, but further adjustment for company size attenuated these associations. Workers at larger companies were more likely to use the app. Compared with permanent employees, the odds of using the app were higher for managers and civil servants but lower for those who were self-employed. CONCLUSIONS: Downloading of COCOA among Japanese workers was insufficient; thus, the mitigating effect of COCOA on the COVID-19 pandemic is considered to be limited. One possible reason for the under-implementation of the contact tracing app in the retail and wholesale and food/beverage industries is small company size, as suggested by the fully adjusted model results. An awareness campaign should be conducted to promote the widespread use of the contact tracing app in these industries.


Subject(s)
COVID-19/prevention & control , Contact Tracing/methods , Industry/classification , Mobile Applications/statistics & numerical data , Workplace/statistics & numerical data , Adult , Cross-Sectional Studies , Female , Humans , Japan/epidemiology , Male , Middle Aged , SARS-CoV-2 , Smartphone
8.
PLoS One ; 16(9): e0257035, 2021.
Article in English | MEDLINE | ID: covidwho-1398938

ABSTRACT

In several nations, caries in pre-school children remain a significant oral health issue. In an outbreak period such as the Coronavirus disease 2019 (COVID-19), remote contact and education aimed at the prevention of oral diseases and the preservation of children's oral health are more relevant than ever. Currently, the amount of published applications is far higher than the published scientific studies while the problems of usability remains vulnerable. The goal of this paper was to comprehensively document the phase of development and usability testing of a mobile application for diet and oral health, namely Gigiku Sihat, which was primarily intended to be used by parents and guardians of pre-school children. The mobile application was developed using the System Development Life Cycle principle. Apart from searching for the available oral health application on Android platform, the initial requirement gathering process consisted of situational analysis, concept generation, content development, and features and functional requirement determination. The mobile application design and implementation evolved at each phase before being finalised. Gigiku Sihat was successfully developed in the Bahasa Malaysia. Finalised Gigiku Sihat was installed on mobile devices to determine the usability using translated and validated System Usability Scale questionnaire namely Skala Kebolehgunaan Aplikasi Mudah Alih (SKAMA). The mean score usability with score of 68 and above was deemed to have good usability. This study found that Gigiku Sihat mean (SD) usability score was 77.0 (14.18). The results were promising as they showed that Gigiku Sihat had a good usability. Thus, the development of this mobile application focusing on diet and oral health served as a new source of oral health education and provided a necessary foundation in developing future improved mobile application development for parents in the prevention of early childhood caries.


Subject(s)
Mobile Applications/statistics & numerical data , Oral Health/statistics & numerical data , Adult , COVID-19/epidemiology , Diet/statistics & numerical data , Female , Humans , Malaysia , SARS-CoV-2/pathogenicity , Surveys and Questionnaires/statistics & numerical data , User-Centered Design , User-Computer Interface
9.
PLoS One ; 16(9): e0256660, 2021.
Article in English | MEDLINE | ID: covidwho-1398935

ABSTRACT

During the SARS-CoV-2 pandemic mobile health applications indicating risks emerging from close contacts to infected persons have a large potential to interrupt transmission chains by automating contact tracing. Since its dispatch in Germany in June 2020 the Corona Warn App has been downloaded on 25.7 Mio smartphones by February 2021. To understand barriers to download and user fidelity in different sociodemographic groups we analysed data from five consecutive cross-sectional waves of the COVID-19 Snapshot Monitoring survey from June to August 2020. Questions on the Corona Warn App included information on download, use, functionality, usability, and consequences of the app. Of the 4,960 participants (mean age 45.9 years, standard deviation 16.0, 50.4% female), 36.5% had downloaded the Corona Warn App. Adjusted analysis found that those who had downloaded the app were less likely to be female (Adjusted Odds Ratio for men 1.16 95% Confidence Interval [1.02;1.33]), less likely to be younger (Adjusted Odds Ratio for age 18 to 39 0.47 [0.32;0.59] Adjusted Odds Ratio for age 40 to 64 0.57 [0.46;0.69]), less likely to have a lower household income (AOR 0.55 [0.43;0.69]), and more likely to live in one of the Western federal states including Berlin (AOR 2.31 [1.90;2.82]). Willingness to disclose a positive test result and trust in data protection compliance of the Corona Warn App was significantly higher in older adults. Willingness to disclose also increased with higher educational degrees and income. This study supports the hypothesis of a digital divide that separates users and non-users of the Corona Warn App along a well-known health gap of education, income, and region.


Subject(s)
COVID-19/prevention & control , Contact Tracing/methods , Mobile Applications/statistics & numerical data , Smartphone/statistics & numerical data , Surveys and Questionnaires , Adult , COVID-19/epidemiology , COVID-19/virology , Cross-Sectional Studies , Female , Germany/epidemiology , Humans , Male , Middle Aged , Pandemics/prevention & control , Reproducibility of Results , SARS-CoV-2/physiology
10.
Eur J Public Health ; 31(1): 49-51, 2021 02 01.
Article in English | MEDLINE | ID: covidwho-1387872

ABSTRACT

To slow the spread of SARS-CoV-2, the German government released the 'Corona-Warn-App', a smartphone application that warns users if they have come into contact with other users tested positive for SARS-CoV-2. Since using the 'Corona-Warn-App' is health-relevant behavior, it is essential to understand who is (and who is not) using it and why. In N = 1972 German adults, we found that non-users were on average older, female, healthier, in training and had low general trust in others. The most frequently named reasons by non-users were privacy concerns, doubts about the effectiveness of the app and lack of technical equipment.


Subject(s)
COVID-19/prevention & control , Communicable Disease Control/methods , Contact Tracing/methods , Disease Outbreaks/prevention & control , Population Surveillance/methods , Smartphone/statistics & numerical data , Adult , Age Factors , COVID-19/epidemiology , Female , Germany , Health Status , Humans , Mobile Applications/statistics & numerical data , Pandemics , SARS-CoV-2 , Sex Factors , Surveys and Questionnaires
11.
JMIR Public Health Surveill ; 7(8): e27892, 2021 08 18.
Article in English | MEDLINE | ID: covidwho-1362201

ABSTRACT

BACKGROUND: Contact tracing apps are considered useful means to monitor SARS-CoV-2 infections during the off-peak stages of the COVID-19 pandemic. Their effectiveness is, however, dependent on the uptake of such COVID-19 apps. OBJECTIVE: We examined the role of individuals' general health status in their willingness to use a COVID-19 tracing app as well as the roles of socioeconomic characteristics and COVID-19 proximity. METHODS: We drew data from the WageIndicator Foundation Living and Working in Coronavirus Times survey. The survey collected data on labor market status as well as the potential confounders of the relationship between general health and COVID-19 tracing app usage, such as sociodemographics and regular smartphone usage data. The survey also contained information that allowed us to examine the role of COVID-19 proximity, such as whether an individual has contracted SARS-CoV-2, whether an individual has family members and colleagues with COVID-19, and whether an individual exhibits COVID-19 pandemic-induced depressive and anxiety symptoms. We selected data that were collected in Spain, Italy, Germany, and the Netherlands from individuals aged between 18 and 70 years (N=4504). Logistic regressions were used to measure individuals' willingness to use a COVID-19 tracing app. RESULTS: We found that the influence that socioeconomic factors have on COVID-19 tracing app usage varied dramatically between the four countries, although individuals experiencing forms of not being employed (ie, recent job loss and inactivity) consistently had a lower willingness to use a contact tracing app (effect size: 24.6%) compared to that of employees (effect size: 33.4%; P<.001). Among the selected COVID-19 proximity indicators, having a close family member with SARS-CoV-2 infection was associated with higher contact tracing app usage (effect size: 36.3% vs 27.1%; P<.001). After accounting for these proximity factors and the country-based variations therein, we found that having a poorer general health status was significantly associated with a much higher likelihood of contact tracing app usage; compared to a self-reported "very good" health status (estimated probability of contact tracing app use: 29.6%), the "good" (estimated probability: +4.6%; 95% CI 1.2%-8.1%) and "fair or bad" (estimated probability: +6.3%; 95% CI 2.3%-10.3%) health statuses were associated with a markedly higher willingness to use a COVID-19 tracing app. CONCLUSIONS: Current public health policies aim to promote the use of smartphone-based contact tracing apps during the off-peak periods of the COVID-19 pandemic. Campaigns that emphasize the health benefits of COVID-19 tracing apps may contribute the most to the uptake of such apps. Public health campaigns that rely on digital platforms would also benefit from seriously considering the country-specific distribution of privacy concerns.


Subject(s)
COVID-19/epidemiology , Contact Tracing/methods , Diagnostic Self Evaluation , Mobile Applications/statistics & numerical data , Pandemics , Adolescent , Adult , Aged , Cross-Sectional Studies , Female , Germany/epidemiology , Humans , Italy/epidemiology , Male , Middle Aged , Netherlands/epidemiology , Privacy , Smartphone/statistics & numerical data , Socioeconomic Factors , Spain/epidemiology , Surveys and Questionnaires , Young Adult
12.
Am J Public Health ; 111(7): 1348-1351, 2021 07.
Article in English | MEDLINE | ID: covidwho-1360669

ABSTRACT

Objectives. To examine prevalence and predictors of digital health engagement among the US population. Methods. We analyzed nationally representative cross-sectional data on 7 digital health engagement behaviors, as well as demographic and socioeconomic predictors, from the Health Information National Trends Survey (HINTS 5, cycle 2, collected in 2018; n = 2698-3504). We fitted multivariable logistic regression models using weighted survey responses to generate population estimates. Results. Digitally seeking health information (70.14%) was relatively common, whereas using health apps (39.53%) and using a digital device to track health metrics (35.37%) or health goal progress (38.99%) were less common. Digitally communicating with one's health care providers (35.58%) was moderate, whereas sharing health data with providers (17.20%) and sharing health information on social media (14.02%) were uncommon. Being female, younger than 65 years, a college graduate, and a smart device owner positively predicted several digital health engagement behaviors (odds ratio range = 0.09-4.21; P value range < .001-.03). Conclusions. Many public health goals depend on a digitally engaged populace. These data highlight potential barriers to 7 key digital engagement behaviors that could be targeted for intervention.


Subject(s)
Consumer Health Information/methods , Digital Technology/statistics & numerical data , Health Behavior , Adult , Age Factors , Aged , Aged, 80 and over , Cross-Sectional Studies , Female , Fitness Trackers/statistics & numerical data , Humans , Male , Middle Aged , Mobile Applications/statistics & numerical data , Public Health , Sex Factors , Socioeconomic Factors
13.
Matern Child Health J ; 25(7): 1057-1068, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1291367

ABSTRACT

OBJECTIVE: Pregnancy and postpartum periods require continuity in care and counseling. During the pandemic process, telemedicine and telenursing applications have been used to meet the need for healthcare throughout the world, and skills in this area have been developed. This study aimed to identify the use of mobile applications by pregnant women in receiving health information, counseling, and healthcare during the COVID-19 pandemic and their distress levels during pregnancy. METHODS: This research was a descriptive cross-sectional study. The study was designed as an online survey administered between August 2020 and November 2020 via a questionnaire and the Tilburg Pregnancy Distress Scale (TPDS). A total of 376 women agreed to participate in the study. Women were included if they were literate, had a gestational age of ≥ 12th weeks, and accommodated within the Republic of Turkey's boundaries. RESULTS: A total of 77.9% of participants reported using pregnancy-related mobile applications during the pandemic. The mean total Tilburg Pregnancy Distress Scale score was 24.09, and 37.2% of the participants were found to be at risk for high distress according to the cut-off point. There was a significant difference between the change in receiving health services and the anxiety about coronavirus transmission and the Tilburg Pregnancy Distress Scale total score. (p ≤ 0.05). CONCLUSIONS: This study helped understand the pandemic's impact on pregnancy distress and usage of mobile health applications by pregnant women during the pandemic. Also, our results indicate that a decrease in pregnant women receiving health services during this period. Mobile health applications appear to be usable for prenatal follow-ups because mobile applications are common among pregnant women during the COVID-19 pandemic.


Subject(s)
COVID-19/epidemiology , Maternal Health Services , Mobile Applications/statistics & numerical data , Psychological Distress , Telemedicine/methods , Adolescent , Adult , COVID-19/psychology , Cross-Sectional Studies , Educational Status , Female , Humans , Maternal Health Services/statistics & numerical data , Middle Aged , Pregnancy/psychology , Surveys and Questionnaires , Telemedicine/statistics & numerical data , Turkey/epidemiology , Young Adult
14.
J Med Internet Res ; 23(6): e27989, 2021 06 02.
Article in English | MEDLINE | ID: covidwho-1273311

ABSTRACT

BACKGROUND: Simulation study results suggest that COVID-19 contact tracing apps have the potential to achieve pandemic control. Concordantly, high app adoption rates were a stipulated prerequisite for success. Early studies on potential adoption were encouraging. Several factors predicting adoption rates were investigated, especially pertaining to user characteristics. Since then, several countries have released COVID-19 contact tracing apps. OBJECTIVE: This study's primary aim is to investigate the quality characteristics of national European COVID-19 contact tracing apps, thereby shifting attention from user to app characteristics. The secondary aim is to investigate associations between app quality and adoption. Finally, app features contributing to higher app quality were identified. METHODS: Eligible COVID-19 contact tracing apps were those released by national health authorities of European Union member states, former member states, and countries of the European Free Trade Association, all countries with comparable legal standards concerning personal data protection and app use voluntariness. The Mobile App Rating Scale was used to assess app quality. An interdisciplinary team, consisting of two health and two human-computer interaction scientists, independently conducted Mobile App Rating Scale ratings. To investigate associations between app quality and adoption rates and infection rates, Bayesian linear regression analyses were conducted. RESULTS: We discovered 21 national COVID-19 contact tracing apps, all demonstrating high quality overall and high-level functionality, aesthetics, and information quality. However, the average app adoption rate of 22.9% (SD 12.5%) was below the level recommended by simulation studies. Lower levels of engagement-oriented app design were detected, with substantial variations between apps. By regression analyses, the best-case adoption rate was calculated by assuming apps achieve the highest ratings. The mean best-case adoption rates for engagement and overall app quality were 39.5% and 43.6%, respectively. Higher adoption rates were associated with lower cumulative infection rates. Overall, we identified 5 feature categories (symptom assessment and monitoring, regularly updated information, individualization, tracing, and communication) and 14 individual features that contributed to higher app quality. These 14 features were a symptom checker, a symptom diary, statistics on COVID-19, app use, public health instructions and restrictions, information of burden on health care system, assigning personal data, regional updates, control over tracing activity, contact diary, venue check-in, chats, helplines, and app-sharing capacity. CONCLUSIONS: European national health authorities have generally released high quality COVID-19 contact tracing apps, with regard to functionality, aesthetics, and information quality. However, the app's engagement-oriented design generally was of lower quality, even though regression analyses results identify engagement as a promising optimization target to increase adoption rates. Associations between higher app adoption and lower infection rates are consistent with simulation study results, albeit acknowledging that app use might be part of a broader set of protective attitudes and behaviors for self and others. Various features were identified that could guide further engagement-enhancing app development.


Subject(s)
COVID-19/epidemiology , Contact Tracing/methods , Mobile Applications/statistics & numerical data , Europe/epidemiology , Humans , Interdisciplinary Studies , Pandemics , Quality of Health Care , SARS-CoV-2/isolation & purification
15.
J Med Internet Res ; 23(5): e25447, 2021 05 19.
Article in English | MEDLINE | ID: covidwho-1259297

ABSTRACT

BACKGROUND: To combat the global COVID-19 pandemic, contact tracing apps have been discussed as digital health solutions to track infection chains and provide appropriate information. However, observational studies point to low acceptance in most countries, and few studies have yet examined theory-based predictors of app use in the general population to guide health communication efforts. OBJECTIVE: This study utilizes established health behavior change and technology acceptance models to predict adoption intentions and frequency of current app use. METHODS: We conducted a cross-sectional online survey between May and July 2020 in a German convenience sample (N=349; mean age 35.62 years; n=226, 65.3% female). To inspect the incremental validity of model constructs as well as additional variables (privacy concerns, personalization), hierarchical regression models were applied, controlling for covariates. RESULTS: The theory of planned behavior and the unified theory of acceptance and use of technology predicted adoption intentions (R2=56%-63%) and frequency of current app use (R2=33%-37%). A combined model only marginally increased the predictive value by about 5%, but lower privacy concerns and higher threat appraisals (ie, anticipatory anxiety) significantly predicted app use when included as additional variables. Moreover, the impact of perceived usefulness was positive for adoption intentions but negative for frequency of current app use. CONCLUSIONS: This study identified several theory-based predictors of contact tracing app use. However, few constructs, such as social norms, have a consistent positive effect across models and outcomes. Further research is required to replicate these observations, and to examine the interconnectedness of these constructs and their impact throughout the pandemic. Nevertheless, the findings suggest that promulgating affirmative social norms and positive emotional effects of app use, as well as addressing health concerns, might be promising strategies to foster adoption intentions and app use in the general population.


Subject(s)
COVID-19/epidemiology , Contact Tracing/methods , Health Behavior/physiology , Mobile Applications/statistics & numerical data , Adult , Cross-Sectional Studies , Female , Humans , Male , Models, Statistical , Pandemics , SARS-CoV-2/isolation & purification , Surveys and Questionnaires
16.
J Med Internet Res ; 23(5): e26573, 2021 05 20.
Article in English | MEDLINE | ID: covidwho-1236646

ABSTRACT

BACKGROUND: The COVID-19 pandemic has created unprecedented challenges for first responders (eg, police, fire, and emergency medical services) and nonmedical essential workers (eg, workers in food, transportation, and other industries). Health systems may be uniquely suited to support these workers given their medical expertise, and mobile apps can reach local communities despite social distancing requirements. Formal evaluation of real-world mobile app-based interventions is lacking. OBJECTIVE: We aimed to evaluate the adoption, acceptability, and appropriateness of an academic medical center-sponsored app-based intervention (COVID-19 Guide App) designed to support access of first responders and essential workers to COVID-19 information and testing services. We also sought to better understand the COVID-19-related needs of these workers early in the pandemic. METHODS: To understand overall community adoption, views and download data of the COVID-19 Guide App were described. To understand the adoption, appropriateness, and acceptability of the app and the unmet needs of workers, semistructured qualitative interviews were conducted by telephone, by video, and in person with first responders and essential workers in the San Francisco Bay Area who were recruited through purposive, convenience, and snowball sampling. Interview transcripts and field notes were qualitatively analyzed and presented using an implementation outcomes framework. RESULTS: From its launch in April 2020 to September 2020, the app received 8262 views from unique devices and 6640 downloads (80.4% conversion rate, 0.61% adoption rate across the Bay Area). App acceptability was mixed among the 17 first responders interviewed and high among the 10 essential workers interviewed. Select themes included the need for personalized and accurate information, access to testing, and securing personal safety. First responders faced additional challenges related to interprofessional coordination and a "culture of heroism" that could both protect against and exacerbate health vulnerability. CONCLUSIONS: First responders and essential workers both reported challenges related to obtaining accurate information, testing services, and other resources. A mobile app intervention has the potential to combat these challenges through the provision of disease-specific information and access to testing services but may be most effective if delivered as part of a larger ecosystem of support. Differentiated interventions that acknowledge and address the divergent needs between first responders and non-first responder essential workers may optimize acceptance and adoption.


Subject(s)
COVID-19/epidemiology , Emergency Responders/statistics & numerical data , Mobile Applications/statistics & numerical data , Adult , Aged , Female , Humans , Internet-Based Intervention/statistics & numerical data , Male , Middle Aged , Needs Assessment , Pandemics , Qualitative Research , SARS-CoV-2/isolation & purification , Young Adult
17.
Nature ; 594(7863): 408-412, 2021 06.
Article in English | MEDLINE | ID: covidwho-1225509

ABSTRACT

The COVID-19 pandemic has seen the emergence of digital contact tracing to help to prevent the spread of the disease. A mobile phone app records proximity events between app users, and when a user tests positive for COVID-19, their recent contacts can be notified instantly. Theoretical evidence has supported this new public health intervention1-6, but its epidemiological impact has remained uncertain7. Here we investigate the impact of the National Health Service (NHS) COVID-19 app for England and Wales, from its launch on 24 September 2020 to the end of December 2020. It was used regularly by approximately 16.5 million users (28% of the total population), and sent approximately 1.7 million exposure notifications: 4.2 per index case consenting to contact tracing. We estimated that the fraction of individuals notified by the app who subsequently showed symptoms and tested positive (the secondary attack rate (SAR)) was 6%, similar to the SAR for manually traced close contacts. We estimated the number of cases averted by the app using two complementary approaches: modelling based on the notifications and SAR gave an estimate of 284,000 (central 95% range of sensitivity analyses 108,000-450,000), and statistical comparison of matched neighbouring local authorities gave an estimate of 594,000 (95% confidence interval 317,000-914,000). Approximately one case was averted for each case consenting to notification of their contacts. We estimated that for every percentage point increase in app uptake, the number of cases could be reduced by 0.8% (using modelling) or 2.3% (using statistical analysis). These findings support the continued development and deployment of such apps in populations that are awaiting full protection from vaccines.


Subject(s)
COVID-19/epidemiology , COVID-19/prevention & control , Contact Tracing/instrumentation , Contact Tracing/methods , Mobile Applications/statistics & numerical data , Basic Reproduction Number , COVID-19/mortality , COVID-19/transmission , England/epidemiology , Humans , Mortality , National Health Programs , Quarantine , Wales/epidemiology
18.
Aust N Z J Public Health ; 45(4): 344-347, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1221531

ABSTRACT

OBJECTIVE: We report a survey in regional Queensland to understand the reasons for suboptimal uptake of the COVIDSafe app. METHODS: A short five-minute electronic survey disseminated to healthcare professionals, mining groups and school communities in the Central Queensland region. Free text responses and their topics were modelled using natural language processing and a latent Dirichlet model. RESULTS: We received a total of 723 responses; of these, 69% had downloaded the app and 31% had not. The respondents' reasons for not downloading the app were grouped under four topics: lack of perceived risk of COVID-19/lack of perceived need and privacy issues; phone-related issues; tracking and misuse of data; and trust, security and credibility. Among the 472 people who downloaded the app and provided text amenable to text mining, the two topics most commonly listed were: to assist with contact tracing; and to return to normal. CONCLUSIONS: This survey of a regional population found that lack of perceived need, concerns around privacy and technical difficulties were the major barriers to users downloading the application. Implications for public health: Health promotion campaigns aimed at increasing the uptake of the COVIDSafe app should focus on promoting how the app will assist with contact tracing to help return to 'normal'. Additionally, health promotors should address the app's impacts on privacy, people's lack of perceived need for the app and technical barriers.


Subject(s)
Attitude to Computers , COVID-19/prevention & control , Confidentiality/psychology , Data Accuracy , Mobile Applications/statistics & numerical data , Preventive Medicine/statistics & numerical data , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Queensland , Risk Factors , SARS-CoV-2 , Surveys and Questionnaires
19.
J Med Internet Res ; 23(6): e27989, 2021 06 02.
Article in English | MEDLINE | ID: covidwho-1200039

ABSTRACT

BACKGROUND: Simulation study results suggest that COVID-19 contact tracing apps have the potential to achieve pandemic control. Concordantly, high app adoption rates were a stipulated prerequisite for success. Early studies on potential adoption were encouraging. Several factors predicting adoption rates were investigated, especially pertaining to user characteristics. Since then, several countries have released COVID-19 contact tracing apps. OBJECTIVE: This study's primary aim is to investigate the quality characteristics of national European COVID-19 contact tracing apps, thereby shifting attention from user to app characteristics. The secondary aim is to investigate associations between app quality and adoption. Finally, app features contributing to higher app quality were identified. METHODS: Eligible COVID-19 contact tracing apps were those released by national health authorities of European Union member states, former member states, and countries of the European Free Trade Association, all countries with comparable legal standards concerning personal data protection and app use voluntariness. The Mobile App Rating Scale was used to assess app quality. An interdisciplinary team, consisting of two health and two human-computer interaction scientists, independently conducted Mobile App Rating Scale ratings. To investigate associations between app quality and adoption rates and infection rates, Bayesian linear regression analyses were conducted. RESULTS: We discovered 21 national COVID-19 contact tracing apps, all demonstrating high quality overall and high-level functionality, aesthetics, and information quality. However, the average app adoption rate of 22.9% (SD 12.5%) was below the level recommended by simulation studies. Lower levels of engagement-oriented app design were detected, with substantial variations between apps. By regression analyses, the best-case adoption rate was calculated by assuming apps achieve the highest ratings. The mean best-case adoption rates for engagement and overall app quality were 39.5% and 43.6%, respectively. Higher adoption rates were associated with lower cumulative infection rates. Overall, we identified 5 feature categories (symptom assessment and monitoring, regularly updated information, individualization, tracing, and communication) and 14 individual features that contributed to higher app quality. These 14 features were a symptom checker, a symptom diary, statistics on COVID-19, app use, public health instructions and restrictions, information of burden on health care system, assigning personal data, regional updates, control over tracing activity, contact diary, venue check-in, chats, helplines, and app-sharing capacity. CONCLUSIONS: European national health authorities have generally released high quality COVID-19 contact tracing apps, with regard to functionality, aesthetics, and information quality. However, the app's engagement-oriented design generally was of lower quality, even though regression analyses results identify engagement as a promising optimization target to increase adoption rates. Associations between higher app adoption and lower infection rates are consistent with simulation study results, albeit acknowledging that app use might be part of a broader set of protective attitudes and behaviors for self and others. Various features were identified that could guide further engagement-enhancing app development.


Subject(s)
COVID-19/epidemiology , Contact Tracing/methods , Mobile Applications/statistics & numerical data , Europe/epidemiology , Humans , Interdisciplinary Studies , Pandemics , Quality of Health Care , SARS-CoV-2/isolation & purification
20.
J Med Internet Res ; 23(5): e25447, 2021 05 19.
Article in English | MEDLINE | ID: covidwho-1197472

ABSTRACT

BACKGROUND: To combat the global COVID-19 pandemic, contact tracing apps have been discussed as digital health solutions to track infection chains and provide appropriate information. However, observational studies point to low acceptance in most countries, and few studies have yet examined theory-based predictors of app use in the general population to guide health communication efforts. OBJECTIVE: This study utilizes established health behavior change and technology acceptance models to predict adoption intentions and frequency of current app use. METHODS: We conducted a cross-sectional online survey between May and July 2020 in a German convenience sample (N=349; mean age 35.62 years; n=226, 65.3% female). To inspect the incremental validity of model constructs as well as additional variables (privacy concerns, personalization), hierarchical regression models were applied, controlling for covariates. RESULTS: The theory of planned behavior and the unified theory of acceptance and use of technology predicted adoption intentions (R2=56%-63%) and frequency of current app use (R2=33%-37%). A combined model only marginally increased the predictive value by about 5%, but lower privacy concerns and higher threat appraisals (ie, anticipatory anxiety) significantly predicted app use when included as additional variables. Moreover, the impact of perceived usefulness was positive for adoption intentions but negative for frequency of current app use. CONCLUSIONS: This study identified several theory-based predictors of contact tracing app use. However, few constructs, such as social norms, have a consistent positive effect across models and outcomes. Further research is required to replicate these observations, and to examine the interconnectedness of these constructs and their impact throughout the pandemic. Nevertheless, the findings suggest that promulgating affirmative social norms and positive emotional effects of app use, as well as addressing health concerns, might be promising strategies to foster adoption intentions and app use in the general population.


Subject(s)
COVID-19/epidemiology , Contact Tracing/methods , Health Behavior/physiology , Mobile Applications/statistics & numerical data , Adult , Cross-Sectional Studies , Female , Humans , Male , Models, Statistical , Pandemics , SARS-CoV-2/isolation & purification , Surveys and Questionnaires
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