Good Research Practice Research Articles

Building reliable evidence from real-world data: methods, cautiousness and recommendations

Routinely stored information on healthcare utilisation in everyday clinical practice has proliferated over the past several decades. There is, however, some reluctance on the part of many health professionals to use observational data to support healthcare decisions, especially when data are derived from large databases. Challenges in conducting observational studies based on electronic databases include concern about the adequacy of study design and methods to minimise the effect of both misclassifications (in the absence of direct assessments of exposure and outcome validity) and confounding (in the absence of randomisation). This paper points out issues that may compromise the validity of such studies, and approaches to managing analytic challenges. First, strategies of sampling within a large cohort, as an alternative to analysing the full cohort, will be presented. Second, methods for controlling outcome and exposure misclassifications will be described. Third, several techniques that take into account both measured and unmeasured confounders will also be presented. Fourth, some considerations regarding random uncertainty in the framework of observational studies using healthcare utilisation data will be discussed. Finally, some recommendations for good research practice are listed in this paper. The aim is to provide researchers with a methodological framework, while commenting on the value of new techniques for more advanced users.

Last Word on Viewpoint: Using V̇o2max as a marker of training status in athletes-can we do better?

Last Word on Viewpoint: Using V̇o2max as a marker of training status in athletes-can we do better?

Research integrity requires to be aware of good and questionable research practices

Research integrity requires to be aware of good and questionable research practices

A step-by-step guide to perform x-ray photoelectron spectroscopy

There is a growing concern within the surface science community that the massive increase in the number of XPS articles over the last few decades is accompanied by a decrease in work quality including in many cases meaningless chemical bond assignment. Should this trend continue, it would have disastrous consequences for scientific research. While there are many factors responsible for this situation, the lack of insight of physical principles combined with seeming ease of XPS operation and insufficient training are certainly the major ones. To counter that, we offer a comprehensive tutorial written in the form of a step-by-step guide starting from experimental planning, through sample selection and handling, instrument setup, data acquisition, spectra analysis, and results presentation. Six application examples highlight the broad range of research questions that can be answered by XPS. The topic selection and the discussion level are intended to be accessible for novices yet challenging possible preconceptions of experienced practitioners. The analyses of thin film samples are chosen for model cases as this is from where the bulk of XPS reports presently emanate and also where the author's key expertise lies. At the same time, the majority of discussed topics is applicable to surface science in general and is, thus, of relevance for the analyses of any type of sample and material class. The tutorial contains ca. 160 original spectra and over 290 references for further reading. Particular attention is paid to the correct workflow, development of good research practices, and solid knowledge of factors that impact the quality and reliability of the obtained information. What matters in the end is that the conclusions from the analysis can be trusted. Our aspiration is that after reading this tutorial each practitioner will be able to perform error-free data analysis and draw meaningful insights from the rich well of XPS.

A scoping review of good methodological practices in research involving transgender, non-binary, and two-spirit youth

Transgender, non-binary, two-spirit, and other gender non-conforming (GNC) youth have been the focus of increasing scholarly attention over the past decade. A scoping review method was applied to this growing body of literature to identify good practices and important themes in conducting research with GNC youth. A body of non-clinical, English-language scholarship was identified utilizing keywords relating to GNC youth, methods, and methodologies via searches in 33 databases, 3 specific journals, and other online sources. These works were then analyzed for good practices, with themes emerging related to institutional review boards (IRBs) and assent/consent, advisory boards and community involvement, recruitment, identity descriptions, adultism, youth agency and voice, intersectionality, knowledge mobilization, and researcher reflexivity.

The COLO-COHORT (Colorectal Cancer Cohort) study: Protocol for a multi-centre, observational research study and development of a consent-for-contact research platform.

The COLO-COHORT study aims to produce a multi-factorial risk prediction model for colorectal neoplasia that can be used to target colonoscopy to those at greatest risk of colorectal neoplasia, ensuring that people are not investigated unnecessarily and maximizing the use of limited endoscopy resources. The study will also explore the link between neoplasia and the human gut microbiome. Additionally, the study aims to generate a cohort of colonoscopy patients who are 'research ready' through the development of a consent-for-contact (C4C) platform, to facilitate a range of colorectal cancer prevention studies to be conducted at scale and speed. This is a multi-centre observational study involving sites across the UK. Recruitment is over a 6-year period (2019-2025). Patients recruited to the study are those attending for colonoscopy. Patients are recruited into two groups, namely observational group A (10000 patients) and C4C group B (10000 patients), known as COLO-SPEED (Colorectal Cancer Screening Prevention Endoscopy and Early Diagnosis; https://colospeed.uk). Patients complete a health questionnaire, provide anthropometric measurements and submit biosamples (blood and stool-depending on the part of the study they are recruited into). Patients' colonoscopy and histology findings are also recorded. Models of factors associated with the presence of neoplasia at colonoscopy will be developed using logistic or multinomial regression. For internal validation, model discrimination and calibration will be assessed and bootstrapping and cross-validation approaches used. To enable long-term follow-up for outcomes related to colorectal cancer and polyps, patients are asked to consent to follow-up through data linkage with national databases. In keeping with good research practice, following analysis by the study team the study investigators will make the anonymized dataset available to other researchers. The C4C platform will also be accessible to other researchers. The study findings will be submitted for publication in peer-reviewed journals and lay summaries will be disseminated to participants and the wider public.

The Implementation of an Advanced Care Planning (ACP) Template on Quality of ACP Visits Performed by Advanced Practice Providers

Advanced care planning in the PALTC setting can improve quality of life and decrease use of unwanted medical services. Research of best practices for ACP is ongoing, and there is a need for strategies to improve the quality and uptake of this service. Providers should be prepared to address these issues and properly document their outcomes.

Proving and improving the reliability of infant research with neuroadaptive Bayesian optimization

AbstractThe field of infant research is not immune from the reproducibility crisis in cognitive science and psychology. In their recent methodological article, Byers‐Heinlein et al. (2021) invited infant researchers to commit to produce robust findings by reporting reliability metrics for their variables of interest, improving data quality and quantity, and moving towards more sophisticated paradigms and analyses. We present a novel artificial intelligence‐enriched individualized approach that, in our view, is particularly promising to shed new light on infant and child development and promote good research practice in the field; neuroadaptive Bayesian optimization (NBO). NBO is a transformative method where the collected brain or behavioural data are processed in real time and used to identify the stimuli that maximize the individual's response. Applying NBO to infant research goes in the direction proposed by Byers‐Heinlein et al. (2021) and further, the method requires careful a priori choices that effectively correspond to preregistering the experimental design and analytic pipeline. In this commentary, we examine how the NBO approach embeds the six proposed solutions for more reliable infant research, encouraging transparency of the planned analyses and robustness of findings.

GOOD CLINICAL PRACTICE IN PHARMACOVIGILANCE

Clinical research is a mechanism or a process that provides convincing evidence that the new treatments or therapies suggested are safe and effective. The ultimate aim of clinical research is the identification and discovery of contemporary diagnostic methods as well as the establishment of advanced standards of medicine. Good Clinical Practice (GCP) is an ethical and scientific quality standard for designs, operations and recordings involving the participation of human subjects. Accompanying the Guidelines pledges to the public that the ethics, integrity and welfare of humans participating in the trials are protected. India has experienced distinct opportunities for clinical trials for clinical trials compared to ethical patients, major medical institutions with fewer and more equipped investigators and fewer patient voices than regulated countries, with larger patient counts. However, our Indian guidelines were needed to ensure a uniform standard of clinical research across the country and to provide data for registration for new drugs before use in the human population in India. Junctions guidelines were developed by a complete committee set up by CDSCO with clinical experts. This article explains the importance of good clinical practice from an Indian clinical research perspective, while defining and outlining the goals and objectives of the GCP. It addresses the historical events that led to the emergence of good clinical practices and examines the current scenario with respect to the application of GCPs in clinical trials in India. Finally, the article addresses the challenges to maintaining a best and competitive system and will suggest a way forward to increase the credibility and efficiency of good clinical practice in clinical research.

Toward openness and transparency to better facilitate knowledge creation

AbstractChanges in modes of publication over recent decades and moves to publish material freely and openly have resulted in increased amounts of research and scholarly outputs being available online. These include teaching and other material but consist mostly of research publications. There have been significant UK and European initiatives as part of the Open Agenda that facilitate and indeed mandate the move to open whether that is for educational materials, research output and data, or the mechanisms for ensuring the quality of these materials. A significant issue is that although making research outputs freely available is praiseworthy, without the data on which that research is based, reproducibility and so verification, which are fundamental principles of scholarly methodology, are not possible. When discrete datasets are linked openly and freely, are able to interact by using common standards, they become more powerful with extended possibilities for research questions that cross disciplinary divides and knowledge domains. There are always objections and resistance to new innovations, and open publication is no exception; published research, nevertheless, indicates that publishing material openly is becoming considered to be “good research practice” and that the positives of “new collaborations and higher citation” outweigh any perceived negative effects.

Guidelines for Safeguarding Good Research Practice. Code of Conduct

Guidelines for Safeguarding Good Research Practice. Code of Conduct

Retrospective on the First Passive Brain-Computer Interface Competition on Cross-Session Workload Estimation.

As is the case in several research domains, data sharing is still scarce in the field of Brain-Computer Interfaces (BCI), and particularly in that of passive BCIs-i.e., systems that enable implicit interaction or task adaptation based on a user's mental state(s) estimated from brain measures. Moreover, research in this field is currently hindered by a major challenge, which is tackling brain signal variability such as cross-session variability. Hence, with a view to develop good research practices in this field and to enable the whole community to join forces in working on cross-session estimation, we created the first passive brain-computer interface competition on cross-session workload estimation. This competition was part of the 3rd International Neuroergonomics conference. The data were electroencephalographic recordings acquired from 15 volunteers (6 females; average 25 y.o.) who performed 3 sessions-separated by 7 days-of the Multi-Attribute Task Battery-II (MATB-II) with 3 levels of difficulty per session (pseudo-randomized order). The data -training and testing sets-were made publicly available on Zenodo along with Matlab and Python toy code (https://doi.org/10.5281/zenodo.5055046). To this day, the database was downloaded more than 900 times (unique downloads of all version on the 10th of December 2021: 911). Eleven teams from 3 continents (31 participants) submitted their work. The best achieving processing pipelines included a Riemannian geometry-based method. Although better than the adjusted chance level (38% with an α at 0.05 for a 3-class classification problem), the results still remained under 60% of accuracy. These results clearly underline the real challenge that is cross-session estimation. Moreover, they confirmed once more the robustness and effectiveness of Riemannian methods for BCI. On the contrary, chance level results were obtained by one third of the methods-4 teams- based on Deep Learning. These methods have not demonstrated superior results in this contest compared to traditional methods, which may be due to severe overfitting. Yet this competition is the first step toward a joint effort to tackle BCI variability and to promote good research practices including reproducibility.

A discrete choice experiment to identify patient preferences for the provision of NHS medicines helpline services

Abstract Introduction Medicines helplines for patients discharged from NHS hospitals can prevent medicines-related harm (1). They are an underused service, which is partly attributed to under-resourcing and consequent inability to meet NHS standards (2). There is no evidence to inform which elements of these standards should be prioritised to increase patient access. Aim To measure patient preferences for different attributes of the provision of medicines helpline services using a discrete choice experiment (DCE). Methods The International Society for Pharmacoeconomics and Outcomes Research good research practices were used to conduct a DCE. Adult members of the NHS ‘Research for the Future’ database who regularly take ≥1 prescribed medicine (or care for someone for does) completed an online survey. The survey presented ten pairs of helplines, each helpline described by seven attributes. Participants chose which helpline from each pair they would prefer to contact with a query following discharge. The attributes of each helpline were defined using standard descriptors (levels) selected with a D-efficient experimental design from two to four options. Twenty helpline pairs were blocked into two survey variants. Participants’ overall preferences for each attribute level were obtained using conditional logit regression and expressed as willingness for the NHS to pay (WTP). Results 460 participants completed a survey (53% female, aged 20-91 years, mean number of regular medicines: 6.0). All attributes significantly affected patient preferences (p<0.001). Participants’ WTP for key characteristics are shown in the table. Conclusion Hospitals providing a medicines helpline should prioritise seven-day opening for extended hours with queries answered on the same day, as these attributes are valued most by potential patients. Other attributes, such as alternative means of contact or a locally based helpline are also valued, but to a lesser extent. Further analysis is required to determine the influence of participant characteristics on their preferences. Use of a DCE with experimental design and a large sample size has enabled patient preferences to be quantified with reasonable precision. However, findings are limited by the method of recruitment, as all participants had internet access and certain groups were over-represented in the sample (e.g. white ethnicity, university educated, higher income). References (1) Williams M, Jordan A, Scott J, Jones MD. A systematic review examining the effectiveness of medicines information services for patients and the general public. Int J Pharm Pract. 2020; 28(1): 26-40. (2) Williams M, Jordan A, Scott J, Jones MD. Operating a patient medicines helpline: A survey study exploring current practice in England using the RE-AIM evaluation framework. BMC Health Serv Res. 2018; 18:868.

Development and content validation of a self-completed, electronic Pediatric Asthma Symptom Diary

BackgroundChildhood asthma is an important unmet need. To date, patient-reported outcome measures (PROMs) for children with asthma have used a combination of caregiver or proxy-reported and self-reported measures. No comprehensive measure is available to assess the severity and impact of daytime and nighttime asthma symptoms and rescue medication use for self-completion by children aged 6–11 years. This study aimed to develop a novel, interactive, electronic Pediatric Asthma Symptom Diary (ePASD) measuring self-reported key symptom severity and proximal impacts of asthma in young children with varying reading ability and disease severity, consistent with US Food and Drug Administration (FDA) PRO guidance and the International Society for Health Economics and Outcomes Research (ISPOR) good research practices.MethodsA targeted literature review and clinician interviews were undertaken to characterize symptoms and impacts experienced by children with mild-to-severe asthma. Concept elicitation interviews (CEIs) were conducted with 44 children and their caregivers (30 US; 14 UK). Following item and digital application development, the ePASD was assessed for relevance, understanding, and interpretability through cognitive debriefing interviews (CDIs) with 21 US children. Face validity/translatability assessments were also performed.ResultsKey measurement concepts included cough, wheeze, difficulty breathing, chest tightness/discomfort, nighttime awakening, and daytime activity limitations. Concept saturation was reached during CEIs for primary asthma-related daytime and nighttime symptoms and core impacts. Most CDI participants found the ePASD items clear, understandable, and comprehensive. Standardized training is anticipated to facilitate reliable child self-report.ConclusionThe ePASD, a novel PROM for children aged 6–11 years with asthma, uses an innovative multimedia approach and has been developed in accordance with FDA PRO guidance and ISPOR good research practices, directly capturing the child’s self-reported asthma symptoms, impacts on daily activities and nighttime awakening, and rescue medication use.

How should evaluation be? Is a good evaluation of research also just? Towards the implementation of good evaluation

In this paper we answer the question of how evaluation should be by proposing a good evaluation of research practices. A good evaluation of research practices, intended as social practices à la MacIntyre, should take into account the stable motivations and the traits of the characters (i.e. the virtues) of researchers. We also show that a good evaluation is also just, beyond the sense of fairness, as working on good research practices implies keep into account a broader sense of justice. After that, we propose the development of a knowledge base for the assessment of “good” evaluations of research practices to implement a questionnaire for the assessment of researchers’ virtues. Although the latter is a challenging task, the use of ontologies and taxonomic knowledge, and the reasoning algorithms that can draw inferences on the basis of such knowledge represents a way for testing the consistency of the information reported in the questionnaire and to analyse correctly and coherently how the data is gathered through it. Finally, we describe the potential application usefulness of our proposal for the reform of current research assessment systems.

Good scientific practice in EEG and MEG research: Progress and perspectives

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

Historical and Legal Considerations in Development of a For-Credit Internship Program

Background: This research outlines important factors in the development of a for-credit internship program by providing a historical context of internship work dating back to the original case of Walling v. Portland Terminal (1947), which outlined acceptable non-paid work of trainees, to more current applications of these labor laws in Wang v. Hearst (2016) and Glatt v. Foxlight Pictures (2016) then connects those legal precedents with current research in best practices. Purpose: The purpose of this research was to examine legal implications on for-credit internship programs and create recommendations based on United States law. Methodology/Approach: This work uses peer-reviewed research to support recommendation in internship development, implementation, and evaluation. Findings/Conclusions: Recommendations for programmatic implementation are made to avoid potential litigation against higher education institutions, faculty, staff, students, and internship placement organizations. Implications: These legal cases inform higher education and considerations in change to organizational policies and practices as it relates to fair labor, program development, and oversight of experiential education.

Trends in scientific editing and good research practices: what do researchers-nurses know?

To verify researchers-nurses' knowledge about trends in scientific publishing and good research practices. A descriptive study carried out through an online survey with 197 nurses holding master's and/or doctoral degrees from all Brazilian regions. To raise knowledge, a validated, self-administered and anonymous questionnaire with 18 questions on the subject was used. Descriptive and inferential analyzes were performed on researchers' scores (Mann-Whitney test). Among the specific questions, the mean of correct answers was 7.1: 6.4 for master's and 7.4 for doctoral degree holders. There was a significant difference in the mean of correct answers between masters and doctors (p = 0.025), and between productivity scholarship holders and non-scholarship holders (p = 0.021), according to mean difference tests. Questions about predatory editorial practices were those in which researchers had the worst knowledge. We identified that, regardless of the education level (master's or doctoral degree), nurses have little knowledge about the topics studied, which can compromise the quality of production and the scientific vehicles used to disseminate this knowledge.

Virtual Research with Urban Native Young Women: Cautionary Tales in the Time of a Pandemic.

Community-based participatory research is a particularly powerful approach to research with American Indian and Alaska Native (AIAN) communities who have been subject to a history of mistreatment and unethical research. In person meetings, discussion, and engagement with tribal members and the community have become an essential component of community-based participatory research in AIAN communities. With the advent of the coronavirus disease 2019 pandemic, AIAN communities have moved to close or sharply curtail in-person activities, precluding in-person research methods. Current best practices for research with AIAN communities assumes in-person engagement; little guidance exists on engaging AIAN communities in research using virtual technologies. Our study, Native Women, Young, Strong, Empowered Changing High-risk alcohOl use and Increasing Contraception Effectiveness Study (Native WYSE CHOICES), was intentionally designed before the pandemic to be virtual, including recruitment, enrollment, intervention, and assessment with urban AIAN young women. We present our perspectives on virtual research with AIAN communities, including the critical role of our advisory partners to inform the virtual intervention design and recruitment methods in the formative stages of our project. Experiential reflection among research team and community partners. Virtual technologies, such as videoconferencing, social media, and mobile health apps, offer many tools to reach communities, especially in a pandemic. The virtualization of research with AIAN communities requires a significant investment in time, resources and planning to mitigate disadvantages; it cannot fully replace in-person-based community-based participatory research approaches, but may offer many strengths and unique advantages for research, especially in a pandemic.

Como interpretar uma metanálise?

There is an enormous and ever-growing quantity of healthcare information available and practitioners must transform it into knowledge to be able to use it in their clinical practice. Even readers who do not conduct scientific studies themselves need to understand the scientific method in detail to be able to critically evaluate scientific articles. Evidence-based healthcare (EBH) can be defined as the link between good scientific research and clinical practice and systematic reviews constitute one of the forms of research excellence proposed within EBH. Systematic reviews employ rigorous methods that reduce the occurrence of bias. Systematic reviews with meta-analyses generally optimize the results found, because quantitative analysis of the studies included in the review yields additional information. In this paper, we will discuss how to interpret a meta-analysis and how to apply subset and sensitivity analysis strategies and we will also describe possible sources of heterogeneity and common errors that can affect a meta-analysis.