Grocery purchase data in the study of alcohol use - A validity study

BACKGROUND

Alcohol use epidemiology is facing challenges as survey response rates decline. In addition, population surveys fail to capture a large proportion of alcohol consumed and are expensive to conduct. This study aims to aid in complementing traditional epidemiological methods by validate grocery purchase data in the research on population alcohol use.

METHODS

The LoCard study subjects were loyalty card holders of a grocery retail co-operative, which possessed more than 45 % market share in Finland. One third of those who consented to the analyses of their grocery purchases were presented a questionnaire including a Food Frequency Questionnaire on the web; N = 11,818 responded. The relationship between beer purchase frequency and self-reported beer drinking frequency was studied for association and agreement in different subgroups using crosstabulations and Poisson regression modeling.

RESULTS

The association between beer purchase frequency and self-reported beer drinking frequency was good (Gamma = .556). The agreement between beer purchase frequency and drinking frequency was only fair (Kappa = .189). Limiting the data to those single adult households that reported making at least 61 % of their grocery purchases from this grocery retailer and collapsing the frequency categories to three instead of six increased the agreement to good (Kappa = .463).

CONCLUSIONS

Information on beer purchase frequency from the loyalty card database can be used to rank people according to their drinking frequency and to estimate beer drinking frequency with fair to good accuracy, depending on what share of grocery purchases they make from the grocery retailer in question.

Profile of the use of dermoscopy among dermatologists in Brazil (2018)

BACKGROUND

Dermoscopy increases the diagnostic accuracy in dermatology. The aspects related to training, usage profile, or perceptions of usefulness of dermoscopy among dermatologists in Brazil have not been described.

OBJECTIVES

To evaluate the profile of the use of dermoscopy and the perception of the impact of the technique on clinical practice.

METHODS

The Brazilian Society of Dermatology invited all members to complete an online form with 20 items regarding demographic data, dermatological assistance, use of dermoscopy, and perceptions of the impact of the technique on clinical practice. The proportions between the categories were compared by analysis of residuals in contingency tables, and p-values < 0.01 were considered significant.

RESULTS

The answers from 815 associates (9.1% of those invited to participate) were assessed, 84% of whom were female, and 71% of whom were younger than 50 years of age. The use of dermoscopy was reported in the daily practice of 98% of dermatologists: 88% reported using it more than once a day. Polarized light dermoscopy was the most used method (83%) and pattern analysis was the most used algorithm (63%). The diagnosis and follow-up of melanocytic lesions was identified as the main use of the technique, while the benefit for the diagnosis of inflammatory lesions was acknowledged by less than half of the sample (42%).

STUDY LIMITATIONS

This was a non-randomized study.

CONCLUSION

Dermoscopy is incorporated into the clinical practice of almost all Brazilian dermatologists, and it is recognized for increasing diagnostic certainty in different contexts, especially for pigmented lesions.

Quality assurance in primary total hip arthroplasty

OBJECTIVE

To compare two different methods of clinical outcomes documentation and investigate the potential impact of a quality assurance program.

METHODS

Data on primary hip arthroplasties conducted between 2004 and 2014 were prospectively collected and analyzed.

RESULTS

A total of 262/3395 patients suffered a postoperative complication. A reduction of complication rate was observed between 2010 and 2014. A significant difference between the two documentation methods was found in: "cardiovascular complications", "hematoma and postoperative hemorrhage" and "reintervention". Finally, the "normalized length of hospital stay" predicted the occurrence of complications.

CONCLUSION

Reduction of the incidence of complications through time may be attributed to accumulated surgical experience.

Comparison of self-reported and accelerometer-measured physical activity among Canadian youth

BACKGROUND

Generally, correlation and agreement between self-reported and accelerometer-measured physical activity are low. The objective of this study is to compare estimates of physical activity from a newly developed Canadian questionnaire with measurements by accelerometer among 12- to 17-year-olds.

DATA AND METHODS

Physical activity was self-reported by domain (transportation, recreation, school, and occupational/household) as part of the new Physical Activity Youth Questionnaire (PAYQ) in the Canadian Health Measures Survey (CHMS; 2014-2017; n = 975) and the Canadian Community Health Survey (CCHS; 2015-2016; n=7,619). The CHMS also collected moderate-to-vigorous physical activity (MVPA) data using the Actical accelerometer. Descriptive statistics and correlation and agreement analyses were used to compare and contrast self-reported and accelerometer-measured physical activity variables. Linear regression was used to assess the association between physical activity and obesity.

RESULTS

The average daily MVPA measured by accelerometry was 49.7 minutes per day. According to the PAYQ, Canadian youth reported an average of 78.2 minutes of physical activity per day from all domains, including recreation (31.3 minutes per day), transportation (15.5 minutes per day), school (25.8 minutes per day), and occupational/household (5.6 minutes per day). According to accelerometer-measured MVPA, 23.1% of youth met the physical activity guideline. The inclusion of all domains of self-reported physical activity resulted in a higher percentage of youth meeting the physical activity guideline (58.6%) than was the case for the recreation domain only (18.5%) or the sum of the recreation and school domains (34.0%). Overall, self-reported and accelerometer-measured physical activity estimates were poorly correlated (R ⟨ 0.2).

DISCUSSION

Population-level estimates of physical activity and the percentage of youth meeting the physical activity guideline were well-aligned between the Actical and the PAYQ; however, large differences were evident at the individual level. Therefore, caution should be exercised in using data from these two methods since their values may not be interchangeable.

Secure and Scalable Collection of Biomedical Data for Machine Learning Applications

Recently, digitization of biomedical processes has accelerated, in no small part due to the use of machine learning techniques which require large amounts of labeled data. This chapter focuses on the prerequisite steps to the training of any algorithm: data collection and labeling. In particular, we tackle how data collection can be set up with scalability and security to avoid costly and delaying bottlenecks. Unprecedented amounts of data are now available to companies and academics, but digital tools in the biomedical field encounter a problem of scale, since high-throughput workflows such as high content imaging and sequencing can create several terabytes per day. Consequently data transport, aggregation, and processing is challenging.A second challenge is maintenance of data security. Biomedical data can be personally identifiable, may constitute important trade-secrets, and be expensive to produce. Furthermore, human biomedical data is often immutable, as is the case with genetic information. These factors make securing this type of data imperative and urgent. Here we address best practices to achieve security, with a focus on practicality and scalability. We also address the challenge of obtaining usable, rich metadata from the collected data, which is a major challenge in the biomedical field because of the use of fragmented and proprietary formats. We detail tools and strategies for extracting metadata from biomedical scientific file formats and how this underutilized metadata plays a key role in creating labeled data for use in the training of neural networks.

Success factors for citizen science projects in water quality monitoring

Attempts to monitor the quality of freshwater resources on a global scale unveil huge data lacks. Involving citizens in data collection has potential to resolve this lack of water quality data. However, it is widely unclear which factors drive the success of citizen science activities. Based on a systematic literature review of 56 peer-reviewed research articles, we identify three sets of factors for successful citizen science projects in water quality monitoring: (i) attributes of citizens (knowledge and experience in collecting data, awareness of environmental problems, motivation, and socio-economic background of citizens), (ii) attributes of institutions (motivation, type of organization, consistent and adequate funding), and (iii) the interactions between citizens and institutions (supporting structure, communication and feedback). These three sets of factors enable a systematic analysis and design of citizen science projects in the future.

User behaviour-based approach to define mobility devices needs of disabled person in Algeria: a questionnaire study

PURPOSE

This article showcases the adaptability of existing mobility devices for the Algerian disabled population. It aims to develop a behavior model of disabled Algerian persons through (1) development of a theoretical model based on literature review and (2) improvement of this model by using local collected data from our developed questionnaire.

METHODS

The majority of existing mobility devices for disabled persons are adapted developed countries context. The Algerian context (people and environment) has its own specifications and needs. Researchers does not address the disabled people behavior modelling in Algeria, due to the unavailability of data and the difficulty of their collection. In order to overcome this problem and develop adapted mobility devices for this particular population, the deployment of a questionnaire to collect local data, becomes necessary. First, a behavior model is deduced from the literature review then a questionnaire is developed and deployed to complete the missing field of this model. The deployment questionnaire panel is composed of 260 persons including users, their families and staff working in disabled person's aid organization.

RESULTS

The main result of this paper consist in a specific behavior model of Algerian disabled persons. This population are looking for reliable and smart wheelchair (97%) to be able to overcome their daily mobility difficulties due to the infrastructure and the global economic context.

CONCLUSION

The proposed model can generate adapted wheelchair for Algerian context. The results of the questionnaire are an important step to understand disabilities in Algeria and developing countries.Implications for RehabilitationDevelopment of a behavior model for the disabled persons displacement.Development and deployment of questionnaire for disabled persons in Algeria.Review of disabled person situation and existing wheelchair in Algeria.Identification of Algerian disabled persons requirement and demonstrate that are different from European one.Definition of recommendation set for the design of wheelchair adapted to Algerian context.

An evaluation of managed entry agreements in Belgium: A system with threats and (high) potential if properly applied

OBJECTIVE

To evaluate the strengths and weaknesses of managed entry agreements (MEAs) in Belgium.

METHODS

All Belgian MEAs signed between 2010 and 2015 (n = 71) were studied, including the re-evaluations of 16 reimbursement requests for which the initial MEA had ended. The analysis was supported by the findings from a systematic literature review and structured interviews with Belgian stakeholders.

RESULTS

The current application of MEAs provides the short-term advantage of getting a positive reimbursement decision with lower confidential prices. However, it is not clear whether the negotiated prices are in line with the added value of the interventions. Furthermore, the contracts do not provide incentives for manufacturers to gather evidence or to set public prices at an acceptable level.

CONCLUSIONS

Based on our analysis of the Belgian MEAs and discussions with Belgian stakeholders, an overview of various issues and pitfalls related to the current application of the system is given. Recommendations are made related to providing correct incentives to deliver good evidence, establishing a correct link between identified uncertainties/problems and the type and content of the MEA, reducing the risk of making the system non-transparent, the importance of international collaboration, etc. in order to optimize the potential of this system. These recommendations are addressed to both the Belgian policymakers and stakeholders in other countries making use of MEAs.

Detailed registration of care in midwifery practices in the Netherlands: an opportunity for research within a healthy pregnant population

Background

Research in maternity care is often conducted in mixed low and high-risk or solely high-risk populations. This limits generalizability to the low-risk population of pregnant women receiving care from Dutch midwives. To address this limitation, 24 midwifery practices in the Netherlands bring together routinely collected data from medical records of pregnant women and their offspring in the VeCaS database. This database offers possibilities for research of physiological pregnancy and childbirth. This study explores if the pregnant women in VeCaS are a representative sample for the national population of women who receive primary midwife-led care in the Netherlands.

Methods

In VeCaS we selected a low risk population in midwife-led care who gave birth in 2015. We compared population characteristics and birth outcomes in this study cohort with a similarly defined national cohort, using Chi Square and two side t-test statistics. Additionally, we describe some birth outcomes and lifestyle factors.

Results

Midwifery practices contributing to VeCaS are spread over the Netherlands, although the western region is underrepresented. For population characteristics, the VeCaS cohort is similar to the national cohort in maternal age (mean 30.4 years) and parity (nulliparous women: 47.1% versus 45.9%). Less often, women in the VeCaS cohort have a non-Dutch background (15.7% vs 24.4%), a higher SES (9.9% vs 23.7%) and live in an urbanised surrounding (4.9% vs 24.8%). Birth outcomes were similar to the national cohort, most women gave birth at term (94.9% vs 94.5% between 37 + ⁰–41+ ⁶ weeks), started labour spontaneously (74.5% vs 75.5%) and had a spontaneous vaginal birth (77.4% vs 77.6%), 16.9% had a home birth. Furthermore, 61.1% had a normal pre-pregnancy BMI, and 81.0% did not smoke in pregnancy.

Conclusions

The VeCaS database contains data of a population that is mostly comparable to the national population in primary midwife-led care in the Netherlands. Therefore, the VeCaS database is suitable for research in a healthy pregnant population and is valuable to improve knowledge of the physiological course of pregnancy and birth. Representativeness of maternal characteristics may be improved by including midwifery practices from the urbanised western region in the Netherlands.

Performances of a Solution to Semi-Automatically Fill eCRF with Data from the Electronic Health Record: Protocol for a Prospective Individual Participant Data Meta-Analysis

Clinical trial data collection still relies on a manual entry from information available in the medical record. This process introduces delay and error risk. Automating data transfer from Electronic Health Record (EHR) to Electronic Data Capture (EDC) system, under investigators' supervision, would gracefully solve these issues. The present paper describes the design of the evaluation of a technology allowing EHR to act as eSource for clinical trials. As part of the EHR2EDC project, for 6 ongoing clinical trials, running at 3 hospitals, a parallel semi-automated data collection using such technology will be conducted focusing on a limited scope of data (demographic data, local laboratory results, concomitant medication and vital signs). The evaluation protocol consists in an individual participant data prospective meta-analysis comparing regular clinical trial data collection to the semi-automated one. The main outcome is the proportion of data correctly entered. Data quality and associated workload for hospital staff will be compared as secondary outcomes. Results should be available in 2020.

[Evaluation of lower facial esthetics in females with different skeletal patterns]

Objective: To evaluate lower facial profile in females in different skeletal patterns. Methods: Investigation pictures of three females with beautiful lower facial profiles from Department of Orthodontics, Henan Stomatological Hospital were collected. The skeletal patterns of these females were classified as average, low and high angle, respectively.Upper lip process point (UL) was moved backwards horizontally to reach towards the E line and go even further gradually in above pictures. The distance changed according to E line was defined as DE value. If UL was in front of E line,DE value was denoted as positive, or else negative. Collectively, we obtained 30 pictures (10 pictures in each skeletal facial type) with different DE values (-5, -4, -3, -2, -1, 0, 1, 2, 3, 4 mm), which were divided into average, low and high angle group according to the skeletal facial type. The pictures were evaluated by 144 randomly-selected adult orthodontic patients [66 males, 78 females, aged (29.4±7.7) years] who visited Department of Orthodontics, Henan Stomatological Hospital from June to September, 2019 and 138 orthodontists (including qualified orthodontists and postgraduate orthodontic students [60 males, 78 females, aged (32.2±7.1) years] who participated orthodontics conferences in Henan Stomatological Hospital in June, 2019. The acceptance rate was calculated and rate above 60% was deemed as acceptable DE range. Evaluators were also asked to choose the most esthetic profiles for the best DE value in each skeletal facial type.Data discrepancy was analyzed using Kruskal-Wallis analysis and chi-square test. Results: Most accepted DE was -2 mm among total investigators including orthodonticpatients and orthodontists. There was no difference in total acceptance rate between orthodontists and patients (P>0.05). There was statistic difference in total acceptance rate in different skeletal patterns between orthodontic patients and orthodontists (P<0.05). In total investigators, total acceptance rate was 62.1% (1 752/2 820) in average angle group, 55.4%(1 563/2 820) in high angle group and 33.5%(946/2 820) in low angle group, respectively. Acceptable DE range in three facial types was -4~2 mm (average angle), -2~2 mm (high angle) and -2~-1 mm (low angle), respectively. Conclusions: According to the evaluation of both orthodontic patients and orthodontists, the best DE was-2 mm.Total acceptance rate and acceptable DE range ranked first in average angle group, second in high angle group and third in low angle group.

Obtaining and managing data sets for individual participant data meta-analysis: scoping review and practical guide

BACKGROUND

Shifts in data sharing policy have increased researchers' access to individual participant data (IPD) from clinical studies. Simultaneously the number of IPD meta-analyses (IPDMAs) is increasing. However, rates of data retrieval have not improved. Our goal was to describe the challenges of retrieving IPD for an IPDMA and provide practical guidance on obtaining and managing datasets based on a review of the literature and practical examples and observations.

METHODS

We systematically searched MEDLINE, Embase, and the Cochrane Library, until January 2019, to identify publications focused on strategies to obtain IPD. In addition, we searched pharmaceutical websites and contacted industry organizations for supplemental information pertaining to recent advances in industry policy and practice. Finally, we documented setbacks and solutions encountered while completing a comprehensive IPDMA and drew on previous experiences related to seeking and using IPD.

RESULTS

Our scoping review identified 16 articles directly relevant for the conduct of IPDMAs. We present short descriptions of these articles alongside overviews of IPD sharing policies and procedures of pharmaceutical companies which display certification of Principles for Responsible Clinical Trial Data Sharing via Pharmaceutical Research and Manufacturers of America or European Federation of Pharmaceutical Industries and Associations websites. Advances in data sharing policy and practice affected the way in which data is requested, obtained, stored and analyzed. For our IPDMA it took 6.5 years to collect and analyze relevant IPD and navigate additional administrative barriers. Delays in obtaining data were largely due to challenges in communication with study sponsors, frequent changes in data sharing policies of study sponsors, and the requirement for a diverse skillset related to research, administrative, statistical and legal issues.

CONCLUSIONS

Knowledge of current data sharing practices and platforms as well as anticipation of necessary tasks and potential obstacles may reduce time and resources required for obtaining and managing data for an IPDMA. Sufficient project funding and timeline flexibility are pre-requisites for successful collection and analysis of IPD. IPDMA researchers must acknowledge the additional and unexpected responsibility they are placing on corresponding study authors or data sharing administrators and should offer assistance in readying data for sharing.

COllaborative open platform E-cohorts for research acceleration in trials and epidemiology

BACKGROUND

The current clinical research system relies on a "one-off" project-by-project model involving a costly and time-wasting permanent construction and deconstruction of the research infrastructure. We propose a new model of research relying on collaborative principles: the COllaborative Open Platform (COOP') e-cohort.

DEVELOPMENT

The COOP' e-cohort aims at building a large community of patients willing to participate in research by contributing to the generation of a large database of patient-reported data, passively enriched, at the individual level, by linkage with routinely collected care and/or medico-administrative data. Approved teams can use the platform and benefit from already enrolled participants or collected data or add new online questionnaires to perform observational or interventional studies to answer a broad range of research questions.

APPLICATION

The Community of Patients for Research (ComPaRe) is a proof-of-concept COOP' e-cohort in the field of chronic conditions that was launched in 2017. As of April 2020, 36,000 patients have joined the project and contributed to more than 4 million data points. Patient-reported data will be enriched by linkage with the French national health system databases and with hospital data for patients receiving care in the Paris region. Since 2017, 150 researchers have used the platform for research projects. Three clinical trials nested in ComPaRe have been funded.

CONCLUSION

By moving from myriad independent studies to a large collaborative infrastructure of research, COOP' e-cohorts will accelerate the research process by avoiding the redundancy of many steps common to all research projects and by limiting waste of research.

Missed opportunities to advance knowledge on traffic safety: Accessibility of driver licensing and crash data for scientific research

OBJECTIVE

Identifiable individual-level driver licensing and motor vehicle crash data are essential to advancing transportation safety research. However, epidemiologic studies using such data are rare, which may reflect their inaccessibility. We conducted a legal mapping study to evaluate US state laws regulating access to driver licensing and motor vehicle crash data for use in scientific research.

METHODS

Legal statutes regulating the release of driver licensing and motor vehicle crash data for all 50 US states and the District of Columbia (D.C.) were retrieved. Legal text was evaluated to determine whether these jurisdictions authorize release of identifiable individual-level licensing and crash data for use in non-governmental research.

RESULTS

Thirty-six states and D.C. explicitly authorize release of identifiable individual-level licensing data to researchers. Only five states and D.C. authorize release of identifiable individual-level crash records. No states explicitly prohibit the release of individual-level data about licensing records and only three states prohibit release of individual-level crash record data, meaning that in many states it is ambiguous whether and when releasing such data to researchers is permitted.

CONCLUSIONS

It is important to understand why licensing data are not used more frequently in transportation safety research given that many state laws permit access for non-governmental researchers. Reforming state laws to clarify and increase access to identifiable individual-level crash report data is an important priority for transportation safety advocates and researchers.

Predictors of Research Assessment Completion in a Latino Sample with Dual Disorders

Latinos are underrepresented in clinical trials, where they encounter challenges in participation and a lack of effective recruitment and retention strategies. For Latino migrants with mental health and substance use problems, these challenges are even greater. Analyzing results from a multicenter randomized clinical trial for Latino migrants with mental health and substance use problems in Boston, Massachusetts, USA as well as Madrid and Barcelona, Spain, we describe six retention strategies used to facilitate participant engagement in follow-up assessments, and report the sociodemographic, clinical, and educational factors associated with research assessment completion. Among 341 randomized participants, 77% completed the 12-month follow-up and 75% completed at least 3 of the 4 follow-up assessments. Having a high school diploma, being recruited at community centers versus other sites, and having a less severe mental health condition were significantly associated with completing more follow-up interviews. Rigorous and customized methods reflecting participant's individual context can bolster research assessment completion for diverse Latino populations with behavioral health concerns.

The use of three-dimensional model construction of virtual technology in orthopedic treatment

Objective

The objective of this study is to explore the construction of a digital three-dimensional model of virtual technology that plays an auxiliary role in orthopedic treatment.

Methods

Three fracture patients were selected, with no abnormality was observed in bone examination, no musculoskeletal disease in the past; and spiral CT scan of the spine and pelvis, upper limbs, and lower limbs was performed. The virtual technology was used to build a digital 3D model, mainly using the editing software Mimics10.0 software. In addition, the virtual three-dimensional model was verified by virtual surgery, data storage security, work efficiency of the model, model validity, three-dimensional characteristics of the model, the interaction mode of the model, and the data accuracy of the model were studied.

Results

The digital 3D model was successfully established by Mimics10.0 software. The data fitting efficiency was very high. The data storage security of the 3D model was greatly improved compared with the 2D model, and the work efficiency was improved by at least 50%. There was also a significant change in the accuracy and interaction of data acquisition. Therefore, the detection of digital 3D model work through virtual surgery simulation fully demonstrated the positive auxiliary role of 3D model in orthopedic treatment.

Conclusion

The digital 3D model based on Mimics10.0 software is efficient and accurate in obtaining data. It is very effective for subsequent adjuvant therapy in the field of orthopedics, reducing the probability of misdiagnosis by doctors, saving time and improving efficiency, reducing patient's physical pain and unnecessary economic expenses.

Impacts of mandated data collection on syringe distribution programs in the United States

OBJECTIVES

Syringe Distribution Programs (SDPs) are a well-proven public health response to the spread of HIV and other blood borne illnesses among people who inject drugs. Many SDPs in the United States are required to collect data from service users as a condition of either legal authorization to operate or as a condition of funding. We sought to describe the prevalence of such externally mandated data collection and impact on service delivery at syringe distribution programs (SDPs) in the United States via an online survey.

METHODS

Online survey of SDPs in the US.

RESULTS

63 SDPs participated. 95•2% collected data about individual service users, with 76•7% being mandated to do so by an external entity as a condition of legal authorization, and/or as a condition of funding. Only 21•7% of mandated respondents received any report back on how data was used. 60•0% reported that data collection acted as a barrier to providing syringes to people who use drugs due to service user fears about loss of anonymity and/or law enforcement. 33•3% reported that the computer literacy and language skills required to collect data meant otherwise appropriate members of the community could not he hired as staff or volunteers.

CONCLUSIONS

Data collection at SDPs may act as a barrier to service provision to populations at high risk for HIV and other blood born viruses, and place considerable logistic burdens on often under-resourced public health programs. Further, it is often unclear to SDPs what purpose their data is being put to. We argue that to be ethical, the purpose of data collection should be carefully considered and regularly reviewed to ensure data is being put to meaningful purpose which is commensurate with impacts on service delivery.

Template for documenting and reporting data in physician-staffed pre-hospital services: a consensus-based update

BACKGROUND

Physician-staffed emergency medical services (p-EMS) are resource demanding, and research is needed to evaluate any potential effects of p-EMS. Templates, designed through expert agreement, are valuable and feasible, but they need to be updated on a regular basis due to developments in available equipment and treatment options. In 2011, a consensus-based template documenting and reporting data in p-EMS was published. We aimed to revise and update the template for documenting and reporting in p-EMS.

METHODS

A Delphi method was applied to achieve a consensus from a panel of selected European experts. The experts were blinded to each other until a consensus was reached, and all responses were anonymized. The experts were asked to propose variables within five predefined sections. There was also an optional sixth section for variables that did not fit into the pre-defined sections. Experts were asked to review and rate all variables from 1 (totally disagree) to 5 (totally agree) based on relevance, and consensus was defined as variables rated ≥4 by more than 70% of the experts.

RESULTS

Eleven experts participated. The experts generated 194 unique variables in the first round. After five rounds, a consensus was reached. The updated dataset was an expanded version of the original dataset and the template was expanded from 45 to 73 main variables. The experts approved the final version of the template.

CONCLUSIONS

Using a Delphi method, we have updated the template for documenting and reporting in p-EMS. We recommend implementing the dataset for standard reporting in p-EMS.

Evaluation of Manualized Instruction to Train Staff to Implement a Token Economy

All components of behavioral skills training may not be necessary to effectively train staff to implement behavior-analytic technologies with children with disabilities. This study evaluated manualized instruction to train inexperienced staff to implement a token economy with a confederate and collect data on learner responding. A nonconcurrent multiple-baseline design across staff trainees was used to evaluate the effectiveness of manualized instruction to increase the staff trainees' accurate implementation of a token economy. Additionally, a modified general case analysis was conducted to identify potential child behaviors. Multiple-exemplar training of these behaviors was presented in random order during sessions. Following the use of the manualized instruction, staff trainees' accurate implementation of a token economy and data collection on confederate responding increased, the skills generalized from a confederate to a child with autism spectrum disorder, and the skills maintained 1 month following training.

Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development

Human preverbal development refers to the period of steadily increasing vocal capacities until the emergence of a child's first meaningful words. Over the last decades, research has intensively focused on preverbal behavior in typical development. Preverbal vocal patterns have been phonetically classified and acoustically characterized. More recently, specific preverbal phenomena were discussed to play a role as early indicators of atypical development. Recent advancements in audio signal processing and machine learning have allowed for novel approaches in preverbal behavior analysis including automatic vocalization-based differentiation of typically and atypically developing individuals. In this paper, we give a methodological overview of current strategies for collecting and acoustically representing preverbal data for intelligent audio analysis paradigms. Efficiency in the context of data collection and data representation is discussed. Following current research trends, we set a special focus on challenges that arise when dealing with preverbal data of individuals with late detected developmental disorders, such as autism spectrum disorder or Rett syndrome.

Standardization of Data Collection to Document Adverse Events Associated with Euthanasia

Data collection and research about adverse effects associated with euthanasia are lacking in the veterinary profession. The goal of this article is to review current research about euthanasia and propose concepts to collect and document euthanasia data to support future studies. A better understanding of the side effects witnessed near perimortem should provide benefits to pet owners, veterinarians, and staff, especially if methods are uncovered to minimize or mitigate the adverse events witnessed. Such data can provide valuable insight and guidance in improving the quality of death and furthering education about the dying process.

Design and implementation of a mobile health electronic data capture platform that functions in fully-disconnected settings: a pilot study in rural Liberia

Background

Mobile phones and personal digital assistants have been used for data collection in developing world settings for over three decades, and have become increasingly common. However, the use of electronic data capture (EDC) through mobile phones is limited in many areas by inconsistent network connectivity and poor access to electricity, which thwart data transmission and device usage. This is the case in rural Liberia, where many health workers live and work in areas without any access to cellular connectivity or reliable power. Many existing EDC mobile software tools are built for occasionally-disconnected settings, allowing a user to collect data while out of range of a cell tower and transmit data to a central server when he/she regains a network connection. However, few tools exist that can be used indefinitely in fully-disconnected settings, where a user will never have access to the internet or a cell network. This led us to create and implement an EDC software tool that allows for completely offline data transfer and application updating.

Results

We designed, pilot-tested, and scaled an open-source fork of Open Data Kit Collect (an Android application that can be used to create EDC systems) that allows for offline Bluetooth-based bidirectional data transfer, enabling a system in which permanently-offline users can collect data and receive application updates. We implemented this platform among a cohort of 317 community health workers and 28 supervisors in a remote area of rural Liberia with incomplete cellular connectivity and low access to power sources.

Conclusions

Running a fully-offline EDC program that completely bypasses the cellular network was found to be feasible; the system is still running, over 4 years after the initial pilot program. The users of this program can theoretically collect data offline for months or years, assuming they receive hardware support when needed. Fully-offline EDC has applications in settings where cellular network coverage is poor, as well as in disaster relief settings in which portions of the communications infrastructure may be temporarily nonfunctional.

Gathering data for decisions: best practice use of primary care electronic records for research

In Australia, there is limited use of primary health care data for research and for data linkage between health care settings. This puts Australia behind many developed countries. In addition, without use of primary health care data for research, knowledge about patients’ journeys through the health care system is limited.

There is growing momentum to establish “big data” repositories of primary care clinical data to enable data linkage, primary care and population health research, and quality assurance activities. However, little research has been conducted on the general public's and practitioners’ concerns about secondary use of electronic health records in Australia.

International studies have identified barriers to use of general practice patient records for research. These include legal, technical, ethical, social and resource‐related issues. Examples include concerns about privacy protection, data security, data custodians and the motives for collecting data, as well as a lack of incentives for general practitioners to share data.

Addressing barriers may help define good practices for appropriate use of health data for research. Any model for general practice data sharing for research should be underpinned by transparency and a strong legal, ethical, governance and data security framework.

Mechanisms to collect electronic medical records in ethical, secure and privacy‐controlled ways are available.

Before the potential benefits of health‐related data research can be realised, Australians should be well informed of the risks and benefits so that the necessary social licence can be generated to support such endeavours.