scholarly journals A novel framework for classification of selection mechanisms in epidemiological research

2019 ◽  
Author(s):  
Jonas Bjork ◽  
Anton Nilsson ◽  
Carl Bonander ◽  
Ulf Strömberg
Keyword(s):  
General Framework ◽  
Empirical Studies ◽  
Population Level ◽  
Epidemiological Studies ◽  
Three Dimensions ◽  
Epidemiological Research ◽  
Selection Processes ◽  
Selection Mechanisms

Abstract Background: Non-participation, losses to follow up and other types of study-specific selection mechanisms can be serious concerns in epidemiological studies. There are also selection processes that result in non-random groupings and changes in the composition of populations. These are continuously on-going irrespectively of whether they are subject to sampling in empirical studies. Such population selections are often overlooked, but may lead to lack of comparability of exposed and unexposed populations or decrease study validity in other ways. The overall aim of this study was to develop a simple but general framework for classifying various types of selection mechanisms of relevance for epidemiological research. Methods: We classify selection mechanisms in three dimensions: i) selection at the population level vs. selection that is study-specific, ii) type of mechanism (selection causing exposure vs. selection in population at risk), iii) timing of the selection (pre-exposure, during exposure or post-outcome). Results: Examples from the epidemiological literature of selection mechanisms are discussed and classified according to the three dimensions of the proposed framework. Conclusions: Increased mechanistic understanding of when, how, and why confusion of effects can occur because of selection is an important step towards improved validity of epidemiological research.

scholarly journals A novel framework for classification of selection processes in epidemiological research

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jonas Björk ◽  
Anton Nilsson ◽  
Carl Bonander ◽  
Ulf Strömberg
Keyword(s):  
Research Question ◽  
Population Level ◽  
Three Dimensions ◽  
Observational Research ◽  
Epidemiological Research ◽  
Selection Processes ◽  
Underlying Mechanisms ◽  
Case Basis

Abstract Background Selection and selection bias are terms that lack consistent definitions and have varying meaning and usage across disciplines. There is also confusion in current definitions between underlying mechanisms that lead to selection and their consequences. Consequences of selection on study validity must be judged on a case-by-case basis depending on research question, study design and analytical decisions. The overall aim of the study was to develop a simple but general framework for classifying various types of selection processes of relevance for epidemiological research. Methods Several original articles from the epidemiological literature and from related areas of observational research were reviewed in search of examples of selection processes, used terminology and description of the underlying mechanisms. Results We classified the identified selection processes in three dimensions: i) selection level (selection at the population level vs. study-specific selection), ii) type of mechanism (selection in exposure vs. selection in population composition), iii) timing of the selection (at exposure entry, during exposure/follow-up or post-outcome). Conclusions Increased understanding of when, how, and why selection occur is an important step towards improved validity of epidemiological research.

scholarly journals A novel framework for classification of selection processes in epidemiological research

2020 ◽  
Author(s):  
Jonas Bjork ◽  
Anton Nilsson ◽  
Carl Bonander ◽  
Ulf Strömberg
Keyword(s):  
Research Question ◽  
Population Level ◽  
Three Dimensions ◽  
Observational Research ◽  
Epidemiological Research ◽  
Selection Processes ◽  
Underlying Mechanisms ◽  
Case Basis

Abstract Background: Selection and selection bias are terms that lack consistent definitions and have varying meaning and usage across disciplines. There is also confusion in current definitions between underlying mechanisms that lead to selection and their consequences. Consequences of selection on study validity must be judged on a case-by-case basis depending on research question, study design and analytical decisions. The overall aim of the study was to develop a simple but general framework for classifying various types of selection processes of relevance for epidemiological research. Methods: Several original articles from the epidemiological literature and from related areas of observational research were reviewed in search of examples of selection processes, used terminology and description of the underlying mechanisms. Results: We classified the identified selection processes in three dimensions: i) selection level (selection at the population level vs. study-specific selection), ii) type of mechanism (selection in exposure vs. selection in population composition), iii) timing of the selection (at exposure entry, during exposure/follow-up or post-outcome). Conclusions: Increased understanding of when, how, and why selection occur is an important step towards improved validity of epidemiological research.

scholarly journals A novel framework for classification of selection processes in epidemiological research

2020 ◽  
Author(s):  
Jonas Bjork ◽  
Anton Nilsson ◽  
Carl Bonander ◽  
Ulf Strömberg
Keyword(s):  
Research Question ◽  
Population Level ◽  
Three Dimensions ◽  
Observational Research ◽  
Population Composition ◽  
Epidemiological Research ◽  
Selection Processes ◽  
Underlying Mechanisms ◽  
Case Basis

Abstract Background: Selection and selection bias are terms that lack consistent definitions and have varying meaning and usage across disciplines. There is also confusion in current definitions between underlying mechanisms that lead to selection and their consequences. Consequences of selection on study validity must be judged on a case-by-case basis depending on research question, study design and analytical decisions. The overall aim of the study was to develop a simple but general framework for classifying various types of selection processes of relevance for epidemiological research. Methods: Several original articles from the epidemiological literature and from related areas of observational research were reviewed in search of examples of selection processes, used terminology and description of the underlying mechanisms. Results: We classified the identified selection processes in three dimensions: i) selection level (selection at the population level vs. study-specific selection), ii) type of mechanism (selection in exposure vs. selection in population composition), iii) timing of the selection (at exposure entry, during exposure or post-outcome). Conclusions: Increased understanding of when, how, and why selection occur is an important step towards improved validity of epidemiological research.

scholarly journals Using Models to Predict Cultural Evolution From Emotional Selection Mechanisms

2019 ◽  
Vol 12 (2) ◽  
pp. 79-92
Author(s):  
Kimmo Eriksson ◽  
Pontus Strimling
Keyword(s):  
Empirical Research ◽  
Cultural Evolution ◽  
Empirical Studies ◽  
Population Level ◽  
Research Paradigm ◽  
Modeling Framework ◽  
Level Change ◽  
Selection Mechanisms ◽  
Directing Attention

Cultural variants may spread by being more appealing, more memorable, or less offensive than other cultural variants. Empirical studies suggest that such “emotional selection” is a force to be reckoned with in cultural evolution. We present a research paradigm that is suitable for the study of emotional selection. It guides empirical research by directing attention to the circumstances under which emotions influence the likelihood that an individual will influence another individual to acquire a cultural variant. We present a modeling framework to translate such knowledge into specific and testable predictions of population-level change. A set of already analyzed basic cases can serve as a toolbox.

scholarly journals Depressive symptoms and non-adherence to treatable cardiovascular risk factors’ medications in the CONSTANCES cohort

2020 ◽  
Author(s):  
Nadine Hamieh ◽  
Sofiane Kab ◽  
Marie Zins ◽  
Jacques Blacher ◽  
Pierre Meneton ◽  
...  
Keyword(s):  
Risk Factors ◽  
Depressive Symptoms ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Depression Scale ◽  
Population Level ◽  
Epidemiological Studies ◽  
Healthcare Database ◽  
Increased Risk

Abstract Aims Depression is associated with increased risk of cardiovascular disease (CVD) and the role of poor medical adherence is mostly unknown. We studied the association between depressive symptoms and non-adherence to medications targeting treatable cardiovascular risk factors in the CONSTANCES population-based French cohort. Methods and results We used CONSTANCES data linked to the French national healthcare database to study the prospective association between depressive symptoms (assessed at inclusion with the Center for Epidemiological Studies Depression scale) and non-adherence to medications (less than 80% of trimesters with at least one drug dispensed) treating type 2 diabetes, hypertension, and dyslipidaemia over 36 months of follow-up. Binary logistic regression models were adjusted for socio-demographics, body mass index, and personal history of CVD at inclusion. Among 4998 individuals with hypertension, 793 with diabetes, and 3692 with dyslipidaemia at baseline, respectively 13.1% vs. 11.5%, 10.5% vs. 5.8%, and 29.0% vs. 27.1% of those depressed vs. those non-depressed were non-adherent over the first 18 months of follow-up (15.9% vs. 13.6%, 11.1% vs. 7.4%, and 34.8% vs. 36.6% between 19 and 36 months). Adjusting for all covariates, depressive symptoms were neither associated with non-adherence to medications for hypertension, diabetes, and dyslipidaemia over the first 18 months of follow-up, nor afterwards. Depressive symptoms were only associated with non-adherence to anti-diabetic medications between the first 3–6 months of follow-up. Conclusion Non-adherence to medications targeting treatable cardiovascular risk factors is unlikely to explain much of the association between depressive symptoms and CVD at a population level. Clinicians are urged to search for and treat depression in individuals with diabetes to foster medications adherence.

scholarly journals Outcome Assessment in Epidemiological Studies of Low-Dose Radiation Exposure and Cancer Risks: Sources, Level of Ascertainment, and Misclassification

2020 ◽  
Vol 2020 (56) ◽  
pp. 154-175 ◽  
Author(s):  
Martha S Linet ◽  
Mary K Schubauer-Berigan ◽  
Amy Berrington de González
Keyword(s):  
Outcome Assessment ◽  
Low Dose ◽  
International Classification Of Diseases ◽  
Epidemiological Studies ◽  
Cancer Risks ◽  
Low Dose Radiation ◽  
Loss To Follow Up ◽  
Classification Of Diseases

Abstract Background Outcome assessment problems and errors that could lead to biased risk estimates in low-dose radiation epidemiological studies of cancer risks have not been systematically evaluated. Methods Incidence or mortality risks for all cancers or all solid cancers combined and for leukemia were examined in 26 studies published in 2006–2017 involving low-dose (mean dose ≤100 mGy) radiation from environmental, medical, or occupational sources. We evaluated the impact of loss to follow-up, under- or overascertainment, outcome misclassification, and changing classifications occurring similarly or differentially across radiation dose levels. Results Loss to follow-up was not reported in 62% of studies, but when reported it was generally small. Only one study critically evaluated the completeness of the sources of vital status. Underascertainment of cancers (“false negatives”) was a potential shortcoming for cohorts that could not be linked with high-quality population-based registries, particularly during early years of exposure in five studies, in two lacking complete residential history, and in one with substantial emigration. False positives may have occurred as a result of cancer ascertainment from self- or next-of-kin report in three studies or from enhanced medical surveillance of exposed patients that could lead to detection bias (eg, reporting precancer lesions as physician-diagnosed cancer) in one study. Most pediatric but few adult leukemia studies used expert hematopathology review or current classifications. Only a few studies recoded solid cancers to the latest International Classification of Diseases or International Classification of Diseases for Oncology codes. These outcome assessment shortcomings were generally nondifferential in relation to radiation exposure level except possibly in four studies. Conclusion The majority of studies lacked information to enable comprehensive evaluation of all major sources of outcome assessment errors, although reported data suggested that the outcome assessment limitations generally had little effect on risk or biased estimates towards the null except possibly in four studies.

Die Wirksamkeit eines Frühinterventionsprogramms für Jugendliche mit Computerspiel- und Internetabhängigkeit: Mittelfristige Effekte der PROTECT+ Studie

2020 ◽  
Vol 48 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Carolin Szász-Janocha ◽  
Eva Vonderlin ◽  
Katajun Lindenberg
Keyword(s):  
Internet Use ◽  
Health Problems ◽  
Reliable Change Index ◽  
Gaming Disorder ◽  
Statistical Classification ◽  
Reliable Change ◽  
Classification Of Diseases ◽  
International Statistical Classification

Zusammenfassung. Fragestellung: Das junge Störungsbild der Computerspiel- und Internetabhängigkeit hat in den vergangenen Jahren in der Forschung zunehmend an Aufmerksamkeit gewonnen. Durch die Aufnahme der „Gaming Disorder“ in die ICD-11 (International Statistical Classification of Diseases and Related Health Problems) wurde die Notwendigkeit von evidenzbasierten und wirksamen Interventionen avanciert. PROTECT+ ist ein kognitiv-verhaltenstherapeutisches Gruppentherapieprogramm für Jugendliche mit Symptomen der Computerspiel- und Internetabhängigkeit. Die vorliegende Studie zielt auf die Evaluation der mittelfristigen Effekte nach 4 Monaten ab. Methodik: N = 54 Patientinnen und Patienten im Alter von 9 bis 19 Jahren (M = 13.48; SD = 1.72) nahmen an der Frühinterventionsstudie zwischen April 2016 und Dezember 2017 in Heidelberg teil. Die Symptomschwere wurde zu Beginn, zum Abschluss der Gruppentherapie sowie nach 4 Monaten anhand von standardisierten Diagnostikinstrumenten erfasst. Ergebnisse: Mehrebenenanalysen zeigten eine signifikante Reduktion der Symptomschwere anhand der Computerspielabhängigkeitsskala (CSAS) nach 4 Monaten. Im Selbstbeurteilungsbogen zeigte sich ein kleiner Effekt (d = 0.35), im Elternurteil ein mittlerer Effekt (d = 0.77). Der Reliable Change Index, der anhand der Compulsive Internet Use Scale (CIUS) berechnet wurde, deutete auf eine starke Heterogenität im individuellen Symptomverlauf hin. Die Patientinnen und Patienten bewerteten das Programm zu beiden Follow-Up-Messzeitpunkten mit einer hohen Zufriedenheit. Schlussfolgerungen: Die vorliegende Arbeit stellt international eine der wenigen Studien dar, die eine Reduktion der Symptome von Computerspiel- und Internetabhängigkeit im Jugendalter über 4 Monate belegen konnte.

Studying Populations of Online Communities

2019 ◽  
pp. 173-193
Author(s):  
Benjamin Mako Hill ◽  
Aaron Shaw
Keyword(s):  
Online Communities ◽  
Information Diffusion ◽  
Diffusion Processes ◽  
Empirical Studies ◽  
Population Level ◽  
Study Groups ◽  
Population Based ◽  
Large Majority ◽  
Community Processes ◽  
Published Research

While the large majority of published research on online communities consists of analyses conducted entirely within individual communities, this chapter argues for a population-based approach, in which researchers study groups of similar communities. For example, although there have been thousands of papers published about Wikipedia, a population-based approach might compare all wikis on a particular topic. Using examples from published empirical studies, the chapter describes five key benefits of this approach. First, it argues that population-level research increases the generalizability of findings. Next, it describes four processes and dynamics that are only possible to study using populations: community-level variables, information diffusion processes across communities, ecological dynamics, and multilevel community processes. The chapter concludes with a discussion of a series of limitations and challenges.

scholarly journals Testing telediagnostic thyroid ultrasound in Peru: a new horizon in expanding access to imaging in rural and underserved areas

2021 ◽  
Author(s):  
T. J. Marini ◽  
S. L. Weiss ◽  
A. Gupta ◽  
Y. T. Zhao ◽  
T. M. Baran ◽  
...  
Keyword(s):  
Thyroid Nodule ◽  
Standard Of Care ◽  
The United States ◽  
Epidemiological Studies ◽  
Thyroid Ultrasound ◽  
Target Region ◽  
Experienced Radiologist ◽  
Significant Difference ◽  
Size Evaluation

Abstract Purpose Thyroid ultrasound is a key tool in the evaluation of the thyroid, but billions of people around the world lack access to ultrasound imaging. In this study, we tested an asynchronous telediagnostic ultrasound system operated by individuals without prior ultrasound training which may be used to effectively evaluate the thyroid and improve access to imaging worldwide. Methods The telediagnostic system in this study utilizes volume sweep imaging (VSI), an imaging technique in which the operator scans the target region with simple sweeps of the ultrasound probe based on external body landmarks. Sweeps are recorded and saved as video clips for later interpretation by an expert. Two operators without prior ultrasound experience underwent 8 h of training on the thyroid VSI protocol and the operation of the telemedicine platform. After training, the operators scanned patients at a health center in Lima. Telediagnostic examinations were sent to the United States for remote interpretation. Standard of care thyroid ultrasound was performed by an experienced radiologist at the time of VSI examination to serve as a reference standard. Results Novice operators scanned 121 subjects with the thyroid VSI protocol. Of these exams, 88% were rated of excellent image quality showing complete or near complete thyroid visualization. There was 98.3% agreement on thyroid nodule presence between VSI teleultrasound and standard of care ultrasound (Cohen’s kappa 0.91, P < 0.0001). VSI measured the thyroid size, on average, within 5 mm compared to standard of care. Readers of VSI were also able to effectively characterize thyroid nodules, and there was no significant difference in measurement of thyroid nodule size (P = 0.74) between VSI and standard of care. Conclusion Thyroid VSI telediagnostic ultrasound demonstrated both excellent visualization of the thyroid gland and agreement with standard of care thyroid ultrasound for nodules and thyroid size evaluation. This system could be deployed for evaluation of palpable thyroid abnormalities, nodule follow-up, and epidemiological studies to promote global health and improve the availability of diagnostic imaging in underserved communities.

scholarly journals Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e043010
Author(s):  
Jane Lyons ◽  
Ashley Akbari ◽  
Fatemeh Torabi ◽  
Gareth I Davies ◽  
Laura North ◽  
...  
Keyword(s):  
Policy Development ◽  
Healthcare Utilisation ◽  
Population Data ◽  
Population Level ◽  
Risk Groups ◽  
Service Utilisation ◽  
Natural Experiments ◽  
Spread Of Infection ◽  
The Impact

IntroductionThe emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions.Methods and analysisTwo privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection.Ethics and disseminationThe Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

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