The Demographic Improvement Guideline to Reduce Bias Resulting from Bring-Your-Own-Device Study Design (Preprint)

2021 ◽  
Author(s):  
Peter Jaeho Cho ◽  
Jaehan Jeremy Yi ◽  
Ethan Ho ◽  
Yen Hai Dinh ◽  
Aneesh Patil ◽  
...  
Keyword(s):  
Study Design ◽  
Technology Development ◽  
Digital Health ◽  
Target Population ◽  
Bring Your Own Device ◽  
Health Technologies ◽  
Study Results ◽  
Representative Random Sample ◽  
Health Studies ◽  
Study Population

UNSTRUCTURED Digital health technologies such as smartphones and wearable devices promise to revolutionize disease prevention, detection, and treatment. Recently, there has been a surge of digital health studies where data is collected through a Bring-Your-Own-Device (BYOD) approach, in which participants who already own a specific technology may voluntarily sign up for the study and provide their digital health data. BYOD study design accelerates the collection of data on a larger number of participants than cohort design because researchers are not limited in the study population size based on the number of devices afforded by their budget. However, the BYOD study design may not support collecting data from a representative random sample of the target population where digital health technologies are intended to be deployed. This may result in biased study results and biased downstream technology development. In this viewpoint, we describe demographic imbalances discovered in existing BYOD studies, including our own, and we propose a Demographic Improvement Guideline to offset these imbalances.

scholarly journals Utilizing Digital Health Technologies for Patient Education in Lifestyle Medicine

2019 ◽  
Vol 14 (2) ◽  
pp. 137-142
Author(s):  
Anne Kuwabara ◽  
Sharlene Su ◽  
Jeffrey Krauss
Keyword(s):  
Patient Education ◽  
Learning Styles ◽  
Health Information ◽  
Technology Development ◽  
Care Delivery ◽  
Digital Health ◽  
Health Technology ◽  
Sufficient Evidence ◽  
Lifestyle Medicine ◽  
Health Technologies

Technology has redefined the way patients and providers communicate and obtain health information. The realm of digital health encompasses a diverse set of technologies, including mobile health, health information technology, wearable devices, telehealth and telemedicine, and personalized medicine. These technologies have begun to improve care delivery without the traditional constraints of distance, location, and time. A growing body of evidence supports the use of digital health technology for improving patient education and implementation of skills and behaviors integral to lifestyle medicine. Patient education can now be delivered in standard formats (eg, articles, written messages) as well a wide array of multimedia (video, audio, interactive games, etc), which may be more appropriate for certain topics and learning styles. In addition, patient engagement in their care plays an important role in improving health outcomes. Despite digital health technology development often outpacing its research, there is sufficient evidence to support the use of many current technologies in clinical practice. Digital health tools will continue to grow in their ability to cost-effectively monitor and encourage healthy behaviors at scale, and better methods of evaluation will likely increase clinician confidence in their use.

scholarly journals Design of a prospective follow-up study on early parenthood and smoking behaviour during pregnancy in Finnish primary healthcare

2021 ◽  
pp. 140349482110224
Author(s):  
Mikael O. Ekblad ◽  
Hanna P. Wallin ◽  
Marjukka Pajulo ◽  
Päivi E. Korhonen
Keyword(s):  
Pregnant Women ◽  
Study Design ◽  
Primary Healthcare ◽  
Routine Data ◽  
Smoking Behaviour ◽  
Self Report ◽  
Health Clinic ◽  
Follow Up Study ◽  
Study Population

Aims: The primary aim of the study is to explore different factors affecting parents’ smoking behaviour, and especially how smoking may be connected with individual differences in the psychological process of becoming a parent. In the current paper, we present the study design together with basic information on the study population. Methods: The Central Satakunta Maternity and Child Health Clinic (KESALATU) Study is an ongoing prospective follow-up study in primary healthcare of the Satakunta region of southwest Finland. Families were recruited during their first maternity clinic visit between 1 September 2016 and 31 December 2019, and participation will continue until the child is 1.5 years of age. The study combines different sources and types of data: e.g. routine data obtained from primary healthcare clinic records, specific parental self-report data and data from a new exhaled carbon monoxide meter indicating maternal smoking. The data are collected using frequently repeated assessments both during pregnancy and postnatally. The methods cover the following areas of interest: family background factors (including smoking and alcohol use), self-reported parental–foetal/infant attachment and mentalization, self-reported stress, depression and quality of life. Results: 589 pregnant women and their partners were asked to participate in the study during the collection time period. The final study population consisted of 248 (42.1%) pregnant women and 160 (27.1%) partners. Conclusions: The new methods and study design have the potential to increase our understanding about the link between early parenting psychology, prenatal psychosocial risk factors and parental health behaviour.

Study design, result reporting and publication of late-stage cardiovascular trials

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
C Kapelios ◽  
H Naci ◽  
P Vardas ◽  
E Mossialos
Keyword(s):  
Study Design ◽  
Late Stage ◽  
Late Phase ◽  
Phase Iii ◽  
Open Label ◽  
Explanatory Factors ◽  
Study Protocols ◽  
Study Results ◽  
Artery Disease ◽  
Design Result

Abstract Introduction Preregistration of study protocols in publicly accessible databases is required for publication of study results in high-impact medical journals. Nonetheless, data on the characteristics of clinical trials registered in these databases and their outcome, in terms of result reporting and publication are limited. Methods The purpose of this study was to perform a comprehensive analysis of the characteristics of late-stage, cardiovascular disease (CVD) trials registered in Clinicaltrials.gov. We searched for interventional, late-phase (annotated as phase III) CVD studies in adults first posted after 1/1/2013 and completed up to 31/12/2018. Data on study design, result reporting, result spinning and publication were collected, and potential associations with a pre-defined set of explanatory factors were examined. Results The search yielded 352 studies. One hundred were excluded from further analysis because they were misclassified as CVD studies, while 2 were excluded as duplicate entries. In total, 250 CVD trials were included in the analysis. The most commonly studied fields were hypertension, coronary artery disease and heart failure. Of these, 193 (77.2%) were randomized studies, 99 (39.6%) open label designs, and 126 (50.4%) had industry as main sponsor. 179 trials (71.6%) evaluated the effect of drugs and 27 (10.8%) evaluated devices. Industry-funded trials focused on patent-protected drugs and devices more often than non-industry-funded trials (72.0% vs. 30.6%, P<0.001 and 55.0% vs. 26.3%, P=0.033, respectively). Sixty three studies (25.2%) had results posted on clinicaltrials.gov, and 116 (46.4%) had results published in the scientific literature. No clear indication of result spinning was found in 96 (85%) of published studies. In multivariate analysis, industry sponsorship was statistically significantly associated with results posting (OR: 3.56; 95% CI:1.67–7.60, P=0.001) and publication (OR: 0.41; 95% CI:0.23–0.75, P=0.004). Results spinning was associated with confirmation of the primary hypothesis (OR: 0.23; 95% CI: 0.07–0.75, P=0.015) and results posting (OR: 0.08; 95% CI: 0.01–0.65, P=0.018). Conclusions Among late-stage cardiovascular trials only 1/4 had their results posted on clinicaltrials.gov and less than half had results published. Industry sponsors were more likely to invest in research on patent-protected drugs and devices than were non-industry sponsors. Having industry as a sponsor was independently associated with increased likelihood of results posting, but decreased likelihood of results publication. Results reporting was significantly associated with lower risk of results spinning. Funding Acknowledgement Type of funding source: None

scholarly journals The role of economic, educational and social resources in supporting the use of digital health technologies by people with T2D: a qualitative study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sophie Turnbull ◽  
Patricia J. Lucas ◽  
Alastair D. Hay ◽  
Christie Cabral
Keyword(s):  
Social Networks ◽  
Social Status ◽  
Digital Health ◽  
Self Care ◽  
Social Resources ◽  
Health Interventions ◽  
Structured Interviews ◽  
Health Technologies ◽  
Digital Skills ◽  
Care Support

Abstract Background Type 2 Diabetes (T2D) is a common chronic disease, with socially patterned incidence and severity. Digital self-care interventions have the potential to reduce health disparities, by providing personalised low-cost reusable resources that can increase access to health interventions. However, if under-served groups are unable to access or use digital technologies, Digital Health Technologies (DHTs) might make no difference, or worse, exacerbate health inequity. Study aims To gain insights into how and why people with T2D access and use DHTs and how experiences vary between individuals and social groups. Methods A purposive sample of people with experience of using a DHT to help them self-care for T2D were recruited through diabetes and community groups. Semi-structured interviews were conducted in person and over the phone. Data were analysed thematically. Results A diverse sample of 21 participants were interviewed. Health care practitioners were not viewed as a good source of information about DHTs that could support T2D. Instead participants relied on their digital skills and social networks to learn about what DHTs are available and helpful. The main barriers to accessing and using DHT described by the participants were availability of DHTs from the NHS, cost and technical proficiency. However, some participants described how they were able to draw on social resources such as their social networks and social status to overcome these barriers. Participants were motivated to use DHTs because they provided self-care support, a feeling of control over T2D, and personalised advice or feedback. The selection of technology was also guided by participants’ preferences and what they valued in relation to DHTs and self-care support, and these in turn were influenced by age and gender. Conclusion This research indicates that low levels of digital skills and high cost of digital health interventions can create barriers to the access and use of DHTs to support the self-care of T2D. However, social networks and social status can be leveraged to overcome some of these challenges. If digital interventions are to decrease rather than exacerbate health inequalities, these barriers and facilitators to access and use must be considered when DHTs are developed and implemented.

scholarly journals Digital Progression Biomarkers as Novel Endpoints in Clinical Trials: A Multistakeholder Perspective

2021 ◽  
pp. 1-7
Author(s):  
Diane Stephenson ◽  
Reham Badawy ◽  
Soania Mathur ◽  
Maria Tome ◽  
Lynn Rochester
Keyword(s):  
Disease Progression ◽  
Digital Health ◽  
Low Cost ◽  
Unmet Need ◽  
Disease Status ◽  
Standard Test ◽  
Imaging Biomarkers ◽  
Health Technologies ◽  
Therapeutic Development ◽  
The Rich

The burden of Parkinson’s disease (PD) continues to grow at an unsustainable pace particularly given that it now represents the fastest growing brain disease. Despite seminal discoveries in genetics and pathogenesis, people living with PD oftentimes wait years to obtain an accurate diagnosis and have no way to know their own prognostic fate once they do learn they have the disease. Currently, there is no objective biomarker to measure the onset, progression, and severity of PD along the disease continuum. Without such tools, the effectiveness of any given treatment, experimental or conventional cannot be measured. Such tools are urgently needed now more than ever given the rich number of new candidate therapies in the pipeline. Over the last decade, millions of dollars have been directed to identify biomarkers to inform progression of PD typically using molecular, fluid or imaging modalities). These efforts have produced novel insights in our understanding of PD including mechanistic targets, disease subtypes and imaging biomarkers. While we have learned a lot along the way, implementation of robust disease progression biomarkers as tools for quantifying changes in disease status or severity remains elusive. Biomarkers have improved health outcomes and led to accelerated drug approvals in key areas of unmet need such as oncology. Quantitative biomarker measures such as HbA1c a standard test for the monitoring of diabetes has impacted patient care and management, both for the healthcare professionals and the patient community. Such advances accelerate opportunities for early intervention including prevention of disease in high-risk individuals. In PD, progression markers are needed at all stages of the disease in order to catalyze drug development—this allows interventions aimed to halt or slow disease progression, very early, but also facilitates symptomatic treatments at moderate stages of the disease. Recently, attention has turned to the role of digital health technologies to complement the traditional modalities as they are relatively low cost, objective and scalable. Success in this endeavor would be transformative for clinical research and therapeutic development. Consequently, significant investment has led to a number of collaborative efforts to identify and validate suitable digital biomarkers of disease progression.

scholarly journals A technology-assisted life of recovery from psychosis

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Dror Ben-Zeev ◽  
Benjamin Buck ◽  
Sarah Kopelovich ◽  
Suzanne Meller
Keyword(s):  
Early Detection ◽  
Symptom Management ◽  
Digital Health ◽  
Digital Technologies ◽  
Clinical Population ◽  
Illness Management ◽  
Illness Management And Recovery ◽  
Health Technologies ◽  
Health Innovations ◽  
Schizophrenia Spectrum

Abstract Developments in digital health technologies have the potential to expedite and strengthen the path towards recovery for people with psychosis. This perspective piece provides a snapshot of how a range of digital technologies can be deployed to support a young adult’s efforts to cope with schizophrenia-spectrum illness. In conjunction with a day in the life of this individual, we provide examples of innovations in digital health research designed for this clinical population, as well as brief summaries of the evidence supporting the usability, feasibility, or effectiveness of each approach. From early detection to ongoing symptom management and vocational rehabilitation, this day-in-the-life vignette provides an overview of the ways in which digital health innovations could be used in concert to augment, scaffold, and enhance schizophrenia-spectrum illness management and recovery.

scholarly journals Accuracy of theoretical IOL formulas for Panoptix intraocular lens according to axial length

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ayoung Choi ◽  
Hyunggoo Kwon ◽  
Sohee Jeon
Keyword(s):  
Intraocular Lens ◽  
Axial Length ◽  
Mean Absolute Error ◽  
Visual Quality ◽  
Absolute Error ◽  
Fort Worth ◽  
Iol Implantation ◽  
Multifocal Iol ◽  
Study Results ◽  
Study Population

AbstractThe accuracy of intraocular lens (IOL) calculations is suboptimal for long or short eyes, which results in a low visual quality after multifocal IOL implantation. The purpose of the present study is to evaluate the accuracy of IOL formulas (Barrett Universal II, SRK/T, Holladay 1, Hoffer Q, and Haigis) for the Acrysof IQ Panoptix TFNT IOL (Alcon Laboratories, Inc, Fort Worth, Texas, United States) implantation based on the axial length (AXL) from a large cohort of 2018 cases and identify the factors that are associated with a high mean absolute error (MAE). The Barrett Universal II showed the lowest MAE in the normal AXL group (0.30 ± 0.23), whereas the Holladay 1 and Hoffer Q showed the lowest MAE in the short AXL group (0.32 ± 0.22 D and 0.32 ± 0.21 D, respectively). The Haigis showed the lowest MAE in the long AXL group (0.24 ± 0.19 D). The Barrett Universal II did not perform well in short AXL eyes with higher astigmatism (P = 0.013), wider white-to-white (WTW; P < 0.001), and shorter AXL (P = 0.016). Study results suggest that the Barrett Universal II performed best for the TFNT IOL in the overall study population, except for the eyes with short AXL, particularly when the eyes had higher astigmatism, wider WTW, and shorter AXL.

Exclusion by Design: Lack of Information about Community Participation in COVID-19-related Mobile Apps and its Relationship to Digital Health Disparities (Preprint)

2021 ◽  
Author(s):  
Muhammed Yassin Idris ◽  
Maya Korin ◽  
Faven Araya ◽  
Sayeeda Chowdhury ◽  
Humberto Brown ◽  
...  
Keyword(s):  
Community Participation ◽  
Mobile Health ◽  
Medical Information ◽  
Mobile Apps ◽  
Digital Health ◽  
Community Based ◽  
Health Technologies ◽  
Community Needs ◽  
App Development ◽  
Communities Of Color

UNSTRUCTURED The rate and scale of transmission of COVID-19 overwhelmed healthcare systems worldwide, particularly in under-resourced communities of color that already faced a high prevalence of pre-existing health conditions. One way the health ecosystem has tried to address the pandemic is by creating mobile apps for telemedicine, dissemination of medical information, and disease tracking. As these new mobile health tools continue to be a primary format for healthcare, more attention needs to be given to their equitable distribution, usage, and accessibility. In this viewpoint collaboratively written by a community-based organization and a health app development research team, we present results of our systematic search and analysis of community engagement in mobile apps released between February and December 2020 to address the COVID-19 pandemic. We provide an overview of apps’ features and functionalities but could not find any publicly available information regarding whether these apps incorporated participation from communities of color disproportionately impacted by the pandemic. We argue that while mobile health technologies are a form of intellectual property, app developers should make public the steps taken to include community participation in app development. These steps could include community needs assessment, community feedback solicited and incorporated, and community participation in evaluation. These are factors that community-based organizations look for when assessing whether to promote digital health tools among the communities they serve. Transparency about the participation of community organizations in the process of app development would increase buy-in, trust, and usage of mobile health apps in communities where they are needed most.

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