scholarly journals Factors that Influence the Adoption of Contact Tracing Applications: A Protocol for a Systematic Review (Preprint)

2021 ◽  
Author(s):  
Kiemute Oyibo ◽  
Kirti Sundar Sahu ◽  
Arlene Oetomo ◽  
Plinio Pelegrini Morita
Keyword(s):  
Systematic Review ◽  
Technology Acceptance ◽  
Systematic Reviews ◽  
Early Stage ◽  
Close Contact ◽  
Empirical Studies ◽  
Contact Tracing ◽  
Privacy Concerns ◽  
Number Of Factors ◽  
Barriers And Challenges

UNSTRUCTURED Digital contact tracing apps (CTAs) have become prevalent worldwide due to the COVID-19 pandemic, which began in the first quarter of 2020. Specifically, they have been developed to fast-track the identification and self-isolation of individuals who must have been exposed to the COVID-19 coronavirus by being in close contact with infected persons. However, their uptake has been low and slow due to a number of factors, which have been speculated in the gray and academic literature, for example, privacy concerns, lack of trust, poor persuasive design, etc. However, there is little understanding of the overall factors that hinder or facilitate the acceptance and adoption of CTAs from the viewpoint of the users. According to Zhang et al., “There is a dearth of evidence [especially based on systematic reviews] regarding the barriers and facilitators to uptake and engagement with COVID-19 digital contact tracing applications.” Although a handful of systematic reviews have been carried out, the majority of them were not related to technology acceptance. Moreover, they were conducted at the early stage of the pandemic in 2020 when only few peer-reviewed empirical studies had been conducted and published. Specifically, systematic reviews such as Braithwaite et al., Davalbhakta et al. and Juneau et al. were not particularly focused on technology acceptance aimed to uncover the facilitators and barriers militating against CTA adoption. Hence, a systematic review of the existing literature is necessary to understand users’ perceptions, including the factors that facilitate the adoption of CTAs, the barriers and challenges militating against their adoption, the measures being taken to tackle the challenges, and the moderating effect of demographic/human factors. The findings will uncover available opportunities to increase the design, adoption and effectiveness of CTAs in future iterations.

scholarly journals Technology Acceptance in Healthcare: A Systematic Review

2021 ◽  
Vol 11 (22) ◽  
pp. 10537
Author(s):  
Adi A. AlQudah ◽  
Mostafa Al-Emran ◽  
Khaled Shaalan
Keyword(s):  
Systematic Review ◽  
Technology Acceptance ◽  
Large Scale ◽  
Empirical Studies ◽  
Influential Factors ◽  
Full Potential ◽  
Eligibility Criteria ◽  
Factors Affecting ◽  
The Usa ◽  
Healthcare Technologies

Understanding the factors affecting the use of healthcare technologies is a crucial topic that has been extensively studied, specifically during the last decade. These factors were studied using different technology acceptance models and theories. However, a systematic review that offers extensive understanding into what affects healthcare technologies and services and covers distinctive trends in large-scale research remains lacking. Therefore, this review aims to systematically review the articles published on technology acceptance in healthcare. From a yield of 1768 studies collected, 142 empirical studies have met the eligibility criteria and were extensively analyzed. The key findings confirmed that TAM and UTAUT are the most prevailing models in explaining what affects the acceptance of various healthcare technologies through different user groups, settings, and countries. Apart from the core constructs of TAM and UTAUT, the results showed that anxiety, computer self-efficacy, innovativeness, and trust are the most influential factors affecting various healthcare technologies. The results also revealed that Taiwan and the USA are leading the research of technology acceptance in healthcare, with a remarkable increase in studies focusing on telemedicine and electronic medical records solutions. This review is believed to enhance our understanding through a number of theoretical contributions and practical implications by unveiling the full potential of technology acceptance in healthcare and opening the door for further research opportunities.

scholarly journals The Rise of Wearable Devices during the COVID-19 Pandemic: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5787 ◽  
Author(s):  
Asma Channa ◽  
Nirvana Popescu ◽  
Justyna Skibinska ◽  
Radim Burget
Keyword(s):  
Systematic Review ◽  
Healthcare System ◽  
Close Contact ◽  
Developed Countries ◽  
Contact Tracing ◽  
Prodromal Phase ◽  
Remote Management ◽  
Problems And Solutions ◽  
Body Sensors ◽  
The Usa

The COVID-19 pandemic has wreaked havoc globally and still persists even after a year of its initial outbreak. Several reasons can be considered: people are in close contact with each other, i.e., at a short range (1 m), and the healthcare system is not sufficiently developed or does not have enough facilities to manage and fight the pandemic, even in developed countries such as the USA and the U.K. and countries in Europe. There is a great need in healthcare for remote monitoring of COVID-19 symptoms. In the past year, a number of IoT-based devices and wearables have been introduced by researchers, providing good results in terms of high accuracy in diagnosing patients in the prodromal phase and in monitoring the symptoms of patients, i.e., respiratory rate, heart rate, temperature, etc. In this systematic review, we analyzed these wearables and their need in the healthcare system. The research was conducted using three databases: IEEE Xplore®, Web of Science®, and PubMed Central®, between December 2019 and June 2021. This article was based on the PRISMA guidelines. Initially, 1100 articles were identified while searching the scientific literature regarding this topic. After screening, ultimately, 70 articles were fully evaluated and included in this review. These articles were divided into two categories. The first one belongs to the on-body sensors (wearables), their types and positions, and the use of AI technology with ehealth wearables in different scenarios from screening to contact tracing. In the second category, we discuss the problems and solutions with respect to utilizing these wearables globally. This systematic review provides an extensive overview of wearable systems for the remote management and automated assessment of COVID-19, taking into account the reliability and acceptability of the implemented technologies.

scholarly journals Effectiveness of contact tracing apps for SARS-CoV-2: a rapid systematic review

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e050519
Author(s):  
Kevin Jenniskens ◽  
Martin C J Bootsma ◽  
Johanna A A G Damen ◽  
Michiel S Oerbekke ◽  
Robin W M Vernooij ◽  
...  
Keyword(s):  
Systematic Review ◽  
Mortality Rate ◽  
Clinical Outcomes ◽  
Effect Size ◽  
Data Extraction ◽  
Empirical Studies ◽  
Risk Of Bias ◽  
Contact Tracing ◽  
Model Parameters ◽  
Model Based

ObjectiveTo systematically review evidence on effectiveness of contact tracing apps (CTAs) for SARS-CoV-2 on epidemiological and clinical outcomes.DesignRapid systematic review.Data sourcesEMBASE (OVID), MEDLINE (PubMed), BioRxiv and MedRxiv were searched up to 28 October 2020.Study selectionStudies, both empirical and model-based, assessing effect of CTAs for SARS-CoV-2 on reproduction number (R), total number of infections, hospitalisation rate, mortality rate, and other epidemiologically and clinically relevant outcomes, were eligible for inclusion.Data extractionEmpirical and model-based studies were critically appraised using separate checklists. Data on type of study (ie, empirical or model-based), sample size, (simulated) time horizon, study population, CTA type (and associated interventions), comparator and outcomes assessed, were extracted. The most important findings were extracted and narratively summarised. Specifically for model-based studies, characteristics and values of important model parameters were collected.Results2140 studies were identified, of which 17 studies (2 empirical, 15 model-based studies) were eligible and included in this review. Both empirical studies were observational (non-randomised) studies and at high risk of bias, most importantly due to risk of confounding. Risk of bias of model-based studies was considered low for 12 out of 15 studies. Most studies demonstrated beneficial effects of CTAs on R, total number of infections and mortality rate. No studies assessed effect on hospitalisation. Effect size was dependent on model parameters values used, but in general, a beneficial effect was observed at CTA adoption rates of 20% or higher.ConclusionsCTAs have the potential to be effective in reducing SARS-CoV-2 related epidemiological and clinical outcomes, though effect size depends on other model parameters (eg, proportion of asymptomatic individuals, or testing delays), and interventions after CTA notification. Methodologically sound comparative empirical studies on effectiveness of CTAs are required to confirm findings from model-based studies.

scholarly journals Utilizing Health Behavior Change and Technology Acceptance Models to Predict the Adoption of COVID-19 Contact Tracing Apps: Cross-sectional Survey Study (Preprint)

2020 ◽  
Author(s):  
Samuel Tomczyk ◽  
Simon Barth ◽  
Silke Schmidt ◽  
Holger Muehlan
Keyword(s):  
General Population ◽  
Health Behavior ◽  
Behavior Change ◽  
Social Norms ◽  
Technology Acceptance ◽  
Health Behavior Change ◽  
Contact Tracing ◽  
Cross Sectional ◽  
Privacy Concerns ◽  
Technology Acceptance Models

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 (R<sup>2</sup>=56%-63%) and frequency of current app use (R<sup>2</sup>=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. CLINICALTRIAL

scholarly journals Effective Contact Tracing for COVID-19: A Systematic Review

2020 ◽  
Author(s):  
Carl-Etienne Juneau ◽  
Anne-Sara Briand ◽  
Tomas Pueyo ◽  
Pablo Collazzo ◽  
Louise Potvin
Keyword(s):  
Systematic Review ◽  
Contact Tracing ◽  
Number Of Factors ◽  
Effective Contact ◽  
Health Practitioners ◽  
Modelling Studies ◽  
Cautious Interpretation ◽  
Public Health Practitioners ◽  
Or Modelling

Background: Contact tracing is commonly recommended to control outbreaks of COVID-19, but its effectiveness is unclear. This systematic review aimed to examine contact tracing effectiveness in the context of COVID-19. Methods: Following PRISMA guidelines, MEDLINE, Embase, Global Health, and All EBM Reviews were searched using a range of terms related to contact tracing for COVID-19. Articles were included if they reported on the ability of contact tracing to slow or stop the spread of COVID-19 or on characteristics of effective tracing efforts. Two investigators screened all studies. Results: A total of 32 articles were found. All were observational or modelling studies, so the quality of the evidence was low. Observational studies (n=14) all reported that contact tracing (alone or in combination with other interventions) was associated with better control of COVID-19. Results of modelling studies (n=18) depended on their assumptions. Under assumptions of prompt and thorough tracing with no further transmission, they found that contact tracing could stop an outbreak (e.g. by reducing the reproduction number from 2.2 to 0.57) or that it could reduce infections (e.g. by 24%-71% with a mobile tracing app). Under assumptions of slower, less efficient tracing, modelling studies suggested that tracing could slow, but not stop COVID-19. Conclusions: Observational and modelling studies suggest that contact tracing is associated with better control of COVID-19. Its effectiveness likely depends on a number of factors, including how many and how fast contacts are traced and quarantined, and how effective quarantines are at preventing further transmission. A cautious interpretation suggests that to stop the spread of COVID-19, public health practitioners have 2-3 days from the time a new case develops symptoms to isolate the case and quarantine at least 80% of its contacts, and that once isolated, cases and contacts should infect zero new cases. Less efficient tracing may slow, but not stop, the spread of COVID-19. Inefficient tracing (with delays of 4-5+ days or less than 60% of contacts quarantined with no further transmission) may not contribute meaningfully to control of COVID-19.

A Systematic Literature Review of The Importance of Sustainable Business Strategy

2021 ◽  
Vol 17 ◽  
pp. 829-839
Author(s):  
Kurniawan Kurniawan ◽  
Yusuf Iskandar
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Business Strategy ◽  
Empirical Studies ◽  
Relevant Literature ◽  
Business Practices ◽  
Review Of The Literature ◽  
Sustainable Business ◽  
Sustainability Research ◽  
The Status

This study undertakes a systematic review of the literature concerning the importance of a sustainable business strategy for any business. While systematic reviews are a vital source of information and are widely utilized in the health sciences, they are seldom employed in sustainability research. Systematic reviews are a type of scientific research that aims to integrate the results of empirical studies objectively and systematically to determine the status of the question in its field of study. This study provides a brief survey of literature reviews in sustainability in business and proposes a systematic review as a method of recovering, analyzing, evaluating, and appraising relevant literature on sustainability in business. This systematic review of the literature suggests that interest in sustainable business practices has increased in recent years. It discusses the subject of sustainability in the perspective of business.

scholarly journals Behavioural pre-testing of COVID Tracker, Ireland’s contact-tracing app

2020 ◽  
Author(s):  
Hannah Julienne ◽  
Ciarán Lavin ◽  
Cameron Belton ◽  
Martina Barjakova ◽  
Shane Timmons ◽  
...  
Keyword(s):  
Online Survey ◽  
Close Contact ◽  
Contact Tracing ◽  
Privacy Concerns ◽  
The Public ◽  
Beneficial Effects ◽  
Department Of Health ◽  
Goal Framing ◽  
Subtle Effect ◽  
To Receive

Contact-tracing mobile phone apps have the potential to play a role in controlling the spread of COVID-19, but their success hinges on widespread uptake by the public. We report a study that behaviourally pre-tested COVID Tracker, Ireland's contact-tracing app, prior to its launch with a large sample of smartphone users. The study was funded by the Department of Health and run in cooperation with the app's developers, NearForm. Participants were randomised to receive different versions of a trial app. They responded to an online survey while downloading and using the app on their phones in real time. The experimental manipulations focused on three broad areas: (i) the level of privacy assurance provided in the app, (ii) the goal-framing of the purpose of the app and (iii) the structuring of the exposure notification received by users if they are recorded as a close contact. Almost one in five participants mentioned privacy concerns in relation to their likelihood of downloading the app. Including additional assurances regarding the privacy of users' data in the app successfully lowered participants' privacy concerns and boosted engagement. This finding fed into the final version of the app released in July 2020. We also found minor beneficial effects of restructuring the exposure notification, but did not find any significant differences between two different types of goal-framing, other than a subtle effect on how the exposure notification is interpreted. Overall, our results demonstrate the value of pre-testing contact-tracing apps from a behavioural perspective to boost uptake, trust and participation.

scholarly journals Using systematic review and meta-analysis in order to obtain different empirical-informative prior for bayesian binomial proportion

2021 ◽  
pp. 195-202
Author(s):  
Esin AVCI
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Bayesian Approach ◽  
Prior Information ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Sources Of Information ◽  
Informative Priors ◽  
Informative Prior ◽  
The Impact

The Bayesian approach provides a direct and useful inference about parameters better so than the frequentist (likelihood-only based) approach. This is because Bayesian approach uses both sources of information: prior information and likelihood. The eliciting of prior information is important because of a visible impact on the posterior inference. The motivation of this study is to avoid the subjectivity in obtaining informative prior. In order to elicit informative priors, this study proposed using systematic reviews, and the meta-analysis which is a statistical syn- thesis of the results from a series of empirical studies. Even though the systematic review and meta-analysis may include publication bias, may give more objective information from expert opinion due to the publishing process. This study also aimed to present the impact of domes- tic information obtained from domestic systematic reviews and meta-analysis on estimation proportion. Systematic reviews and meta-analysis of proportion used in order to obtain dis- crete, histogram, and conjugate (Beta) informative priors. The effectiveness of the Bayesian inference of proposed different informative prior distributions compared within and between (all-domestic) prior distribution. The results revealed that the discrete and histogram priors were more effective than the conjugate and non-informative priors. On the other hand, the importance of using systematic reviews and meta-analysis for domestic studies was observed.

scholarly journals Acting in the Face of Evidentiary Ambiguity, Bias, and Absence Arising from Systematic Reviews in Applied Environmental Science

2021 ◽  
Author(s):  
Trina Rytwinski ◽  
Steven J Cooke ◽  
Jessica J Taylor ◽  
Dominique Roche ◽  
Paul A Smith ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Systematic Reviews ◽  
Environmental Science ◽  
Evidence Synthesis ◽  
Empirical Studies ◽  
Synthesis Method ◽  
Evidence Base ◽  
Evidence Based ◽  
Evidence Based Decision Making

Evidence-based decision-making often depends on some form of a synthesis of previous findings. There is growing recognition that systematic reviews, which incorporate a critical appraisal of evidence, are the gold standard synthesis method in applied environmental science. Yet, on a daily basis, environmental practitioners and decision-makers are forced to act even if the evidence base to guide them is insufficient. For example, it is not uncommon for a systematic review to conclude that an evidence base is large but of low reliability. There are also instances where the evidence base is sparse (e.g., one or two empirical studies on a particular taxa or intervention), and no additional evidence arises from a systematic review. In some cases, the systematic review highlights considerable variability in the outcomes of primary studies, which in turn generates ambiguity (e.g., potentially context specific). When the environmental evidence base is ambiguous, biased, or lacking of new information, practitioners must still make management decisions. Waiting for new, higher validity research to be conducted is often unrealistic as many decisions are urgent. Here, we identify the circumstances that can lead to ambiguity, bias, and the absence of additional evidence arising from systematic reviews and provide practical guidance to resolve or handle these scenarios when encountered. Our perspective attempts to highlight that, with evidence synthesis, there may be a need to balance the spirit of evidence-based decision-making and the practical reality that management and conservation decisions and action is often time sensitive.

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