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Competing Interests: Declaration of competing interest The authors declare no conflict of interests.

Academic Abstract: In the wake of the replication crisis, social and personality psychologists have increased attention to power analysis and the adequacy of sample sizes. In this article, we analyze current controversies in this area, including choosing effect sizes, why and whether power analyses should be conducted on already-collected data, how to mitigate the negative effects of sample size criteria on specific kinds of research, and which power criterion to use. For novel research questions, we advocate that researchers base sample sizes on effects that are likely to be cost-effective for other people to implement (in applied settings) or to study (in basic research settings), given the limitations of interest-based minimums or field-wide effect sizes. We discuss two alternatives to power analysis, precision analysis and sequential analysis, and end with recommendations for improving the practices of researchers, reviewers, and journal editors in social-personality psychology., Public Abstract: Recently, social-personality psychology has been criticized for basing some of its conclusions on studies with low numbers of participants. As a result, power analysis, a mathematical way to ensure that a study has enough participants to reliably "detect" a given size of psychological effect, has become popular. This article describes power analysis and discusses some controversies about it, including how researchers should derive assumptions about effect size, and how the requirements of power analysis can be applied without harming research on hard-to-reach and marginalized communities. For novel research questions, we advocate that researchers base sample sizes on effects that are likely to be cost-effective for other people to implement (in applied settings) or to study (in basic research settings). We discuss two alternatives to power analysis, precision analysis and sequential analysis, and end with recommendations for improving the practices of researchers, reviewers, and journal editors in social-personality psychology., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

NHLBI funded seven projects as part of the Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Risk (DECIPHeR) Initiative. They were expected to collaborate with community partners to (1) employ validated theoretical or conceptual implementation research frameworks, (2) include implementation research study designs, (3) include implementation measures as primary outcomes, and (4) inform our understanding of mediators and mechanisms of action of the implementation strategy. Several projects focused on late-stage implementation strategies that optimally and sustainably delivered two or more evidence-based multilevel interventions to reduce or eliminate cardiovascular and/or pulmonary health disparities and to improve population health in high-burden communities. Projects that were successful in the three-year planning phase transitioned to a 4-year execution phase. NHLBI formed a Technical Assistance Workgroup during the planning phase to help awardees refine study aims, strengthen research designs, detail analytic plans, and to use valid sample size methods. This paper highlights methodological and study design challenges encountered during this process. Important lessons learned included (1) the need for greater emphasis on implementation outcomes, (2) the need to clearly distinguish between intervention and implementation strategies in the protocol, (3) the need to address clustering due to randomization of groups or clusters, (4) the need to address the cross-classification that results when intervention agents work across multiple units of randomization in the same arm, (5) the need to accommodate time-varying intervention effects in stepped-wedge designs, and (6) the need for data-based estimates of the parameters required for sample size estimation.

Our Issue: Researchers often design interventions or experiences to meet the needs of a specific user. However, the user's perspective is often excluded in the process, which can minimize effectiveness due to a lack of understanding about the user, their perspective, and/or their needs. User experience (UX) research methods offer an opportunity to capture additional information about the user that can inform the design of these solutions., Methodological Literature Review: UX research became prominent during the 1990s to describe the complexity of human interactions with technological solutions. UX research methods emerged in other disciplines as strategies for describing user perspectives, needs, challenges, and potential impact of proposed solutions-these may be useful in health professions education research., Our Recommendations and Their Applications: Those interested in UX research methods should define the user, establish focused research questions, and select applicable strategies cognizant of time and resource constraints. UX research often requires a clear outline of research activities, how they address the questions, and techniques to engage representative users for data collection. Researchers can optimize data collection by creating inclusive spaces that emphasize active listening. Researchers should compile insights regularly and remember UX research emphasizes an iterative approach to design., Potential Impact: UX research can support deeper insights into users, their perspectives, their needs, and offers opportunities to co-construct solutions with their experiences in mind. These methods may help educators design impactful experiences that better achieve targeted outcomes in collaboration with their users (e.g., learners, faculty, teams)., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Aims: To propose a decision tree for identifying appropriate integration procedures and joint displays for  achieving integration in mixed methods studies., Design: A methodological discussion., Data Sources: Methodological literature including mixed methods textbooks, methodological reviews and studies published in the last 10 years (2012-2022)., Implications for Nursing: Mixed methods are instrumental to study complex nursing care processes and health-human phenomena. Nurse researchers can use this decision tree to choose the most appropriate integration procedures to overcome the integration challenge when designing and conducting mixed methods nursing studies., Conclusion: Integration procedures and joint displays are the most widely used methods for tackling the integration challenge in mixed methods research (MMR). The multifaceted and contingent nature of these methods are beneficial for their tailored and adapted use at the data collection, analysis, interpretation and reporting levels. The use of the most pertinent integration procedures and joint displays is critical for ensuring quality in MMR., Impact: A growing methodological literature on MMR offers a wide range of integration procedures and techniques. Therefore, choosing appropriate integration procedures and analysis methods can be challenging for nurse researchers interested in conducting mixed methods studies. A decision tree is developed outlining 14 integration procedures and their corresponding mixed methods designs, purposes and joint displays. Examples of mixed methods studies in the discipline of nursing are presented to illustrate the implementation of the integration procedures. The decision tree can serve as a straightforward methodological tool for decision making in MMR. Nurse researchers can effectively use this decision tree for research and teaching purposes., Patient or Public Contribution: No direct patient or public contribution., (© 2022 The Authors. Journal of Advanced Nursing published by John Wiley & Sons Ltd.)

A dramatic increase in the volume of research literature referencing social determinants of health (SDH) since the report of the World Health Organization Commission on the topic in 2008 has not been matched by expansion of policies and interventions to reduce health inequalities by way of SDH. This article argues that familiar hierarchies of evidence that privilege clinical epidemiology as used in evidence-based medicine are inappropriate to address SDH. They misunderstand both the range of relevant evidence and the value-based nature of standards of proof. A richer conceptual armamentarium is available; it includes several applications of the concepts of epidemiological worlds and the lifecourse, which are explained in the article. A more appropriate evidentiary approach to SDH and health inequalities requires "downing the master's tools," to adapt Audre Lorde's phrase, and instead applying a multidisciplinary approach to assessing the evidence that adequately reflects the complexity of the relevant causal pathways. Doing so is made more difficult by the power structures that shape research priorities, yet it is essential.

As mixed methods research approaches become increasingly more common, it is imperative they are conducted in a thoughtful and rigorous manner to yield useful results. While researchers have begun to explore the use of various qualitative research methodologies in mixed methods research, there is a gap in literature discussing the philosophical congruence of using interpretive description in mixed method studies, and how to ensure rigor while integrating interpretive description results. Our purpose in writing this article is to discuss the issues of fit, purpose, process, context, and design when using interpretive description in mixed methods research approaches by drawing on examples from the literature. Further, we explore the contributions that interpretive description can make in a mixed methods inquiry. This article offers a first step in using a purposeful approach to mixed methods interpretive description studies to increase transparency and rigor in this relatively new methodology., (© 2022 John Wiley & Sons Ltd.)

Qualitative research methods, while rising in popularity, are still a relatively underutilized tool in public health research. Usually reserved for small samples, qualitative research techniques have the potential to enhance insights gained from large questionnaires and cohort studies, both deepening the interpretation of quantitative data and generating novel hypotheses that might otherwise be missed by standard approaches; this is especially true where exposures and outcomes are new, understudied, or rapidly changing, as in a pandemic. However, methods for the conduct of qualitative research within large samples are underdeveloped. Here, we describe a novel method of applying qualitative research methods to free-text comments collected in a large epidemiologic questionnaire. Specifically, this method includes: 1) a hierarchical system of coding through content analysis; 2) a qualitative data management application; and 3) an adaptation of Cohen's κ and percent agreement statistics for use by a team of coders, applying multiple codes per record from a large codebook. The methods outlined in this paper may help direct future applications of qualitative and mixed methods within large cohort studies., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

There is a compelling need to evaluate the real-world health effects of medical products outside of tightly controlled preapproval clinical trials. This is done through pharmacoepidemiology, which is the study of the health effects of medical products (including drugs, biologicals, and medical devices and diagnostics) in populations, often using nonrandomized designs. Recent developments in pharmacoepidemiology span changes in the focus of research questions, research designs, data used, and statistical analysis methods. Developments in these areas are thought to improve the value of the evidence produced by such studies, and are prompting greater use of real-world evidence to inform clinical, regulatory, and reimbursement decisions., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: This study aims to analyze research methodologies from 157 research articles published in this journal in the last five years (2016-2020)., Background: Health environments research is comprised of research covering many topics and from various disciplines worldwide. No systematic study exists to uncover themes in evidence-based design (EBD) research concerning the types of research published, people engaged in research, and the research methods employed. Understanding the nature of health environment research performed can help researchers, practitioners, and students situate their work within an EBD research structure., Methods: Case study research was used to analyze 157 articles published in the Health Environments Research & Design Journal devoted to EBD and research. Secondary data were extracted to capture research methods from health environments studies and then analyzed to identify themes. The design and outcome categories were structured around and the Center for Health Design's (CHD) Knowledge Repository with origins to Ulrich et al.'s Evidence-Based Design Framework., Results: Findings are reported on categories commonly found in empirical research articles: (i) key words, (ii) disciplines from authors, (iii) settings studied, (iv) populations studied or sampled, (v) research approach and study design, (vi) research strategies, (vii) data collection methods, (viii) data analysis procedures, (ix) design categories and variables, and (x) outcome categories and variables., Conclusions: The analyses highlighted the research methods most frequently used in health environments research. Findings revealed several inconsistencies across articles on key words and the framing of research methodologies. Results suggest that there should be a consistent and overarching research taxonomy with a set of acceptable terms for effective literature searches.

Reducing research waste and protecting research participants from unnecessary harm should be top priorities for researchers studying interventions. However, the traditional use of fixed sample sizes exposes trials to risks of under- and overrecruitment by requiring that effect sizes be determined a priori. One mitigating approach is to adopt a Bayesian sequential design, which enables evaluation of the available evidence continuously over the trial period to decide when to stop recruitment. Target criteria are defined, which encode researchers' intentions for what is considered findings of interest, and the trial is stopped once the scientific question is sufficiently addressed. In this tutorial, we revisit a trial of a digital alcohol intervention that used a fixed sample size of 2129 participants. We show that had a Bayesian sequential design been used, the trial could have ended after collecting data from approximately 300 participants. This would have meant exposing far fewer individuals to trial procedures, including being allocated to the waiting list control condition, and the evidence from the trial could have been made public sooner., (©Marcus Bendtsen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 16.12.2022.)

Nursing and health researchers may be presented with uncertainty regarding the utilization or legitimacy of methodological or analytic decisions. Sensitivity analyses are purposed to gain insight and certainty about the validity of research findings reported. Reporting guidelines and health research methodologists have emphasized the importance of utilizing and reporting sensitivity analyses in clinical research. However, sensitivity analyses are underreported in nursing and health research. The aim of this methodological overview is to provide an introduction to the purpose, conduct, interpretation, and reporting of sensitivity analyses, using a series of simulated and contemporary case examples.

In this paper, we take a closer look at Danish psychology students' Master's thesis projects. We do this by analysing 4,100 descriptions of all Master's theses in Danish psychology study programs between 2014 and 2019. Via a sentiment analysis of the data material, we identify and categorize the different theses and attempt to identify their methodological focus. Initially, we describe the characteristics of the Danish Master's thesis and discuss why an analysis of different theoretical and methodological orientations within the theses is relevant. The results we draw out in this article point to what we term a methodological discrepancy between psychological research published in journals and Danish psychology students' Master's thesis projects. The sentiment analysis also shows that Danish Master's theses in many cases refer to one or more specific (meta)theoretical orientations in their problem statements. The paper discusses whether students' (meta)theoretical orientation(s) can be interpreted as a sign of sound theoretical literacy among students or, conversely, if theory rather is applied in a routine-like manner in Master's thesis projects. It is further discussed whether the methodological discrepancy is seen because of the more intuitive nature of qualitative methods, or if it caused by what could be termed a dustbowl (qualitative) empiricism. The article is concluded with a discussion on the social normativity of psychological research., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objectives: To develop a web-based decision support tool that guides users through a series of simple questions for recommending knowledge synthesis methods suitable for their research question., Study Design and Setting: We used findings from previous work to structure a set of questions along key dimensions of different knowledge synthesis methods. We developed the tool using four steps: (1) designing the tool, (2) conducting usability testing, (3) disseminating the tool, and (4) evaluating its real-world use. Steps 1-3 were conducted iteratively, and the tool was evaluated using the RE-AIM framework., Results: The "Right Review" tool separates quantitative reviews and qualitative evidence synthesis (QES). Five questions are asked to select from among 26 methods for quantitative reviews, and 10 questions to select methods from among 15 QES. Conduct/reporting guidance and open-access examples are provided for each recommended method. The tool was disseminated to >4,600 users worldwide within 12 months. Evaluation results showed that the tool was fit-for-purpose and easy to use., Conclusion: The proliferation of knowledge synthesis methods makes it challenging for reviewers to select the "right" method. "Right Review" is a free, practical decision support tool that helps reviewers choose an appropriate method from 41 alternatives., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Interpreting research is an important skill to ensure one can maintain their practise with current evidence. The technicalities of statistics can be daunting and thus, this article aims to provide a clear overview of key statistical tests that a surgeon will encounter. It highlights the various study designs, summary statistics and comparative tests that are used in clinical research. Furthermore, it provides a guide to determine which statistical method is most appropriate for various study designs. Overall, it aims to act as an introductory text to supplement further reading into the more advanced statistical methodologies. Level of Evidence: Level V.

Infertility randomized controlled trials (RCTs) are often too small to detect realistic treatment effects. Large observational studies have been proposed as a solution. However, this strategy threatens to weaken the evidence base further, because non-random assignment to treatments makes it impossible to distinguish effects of treatment from confounding factors. Alternative solutions are required. Power in an RCT can be increased by adjusting for prespecified, prognostic covariates when performing statistical analysis, and if stratified randomization or minimization has been used, it is essential to adjust in order to get the correct answer. We present data showing that this simple, free and frequently necessary strategy for increasing power is seldom employed, even in trials appearing in leading journals. We use this article to motivate a pedagogical discussion and provide a worked example. While covariate adjustment cannot solve the problem of underpowered trials outright, there is an imperative to use sound methodology to maximize the information each trial yields., (© The Author(s) 2022. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology.)

Aims: A discussion of the challenges of recruiting participants from harder-to-reach populations for quantitative survey studies and potential avenues for tailored strategies to address these challenges., Design: Discussion paper., Data Sources: The search was conducted on August 2, 2021, in the CINAHL and PubMed databases, and in Google scholar. The initial search identified 5880 articles, and the final analysis included 44 articles that met the inclusion criteria. Articles were retained if they addressed methodological challenges or strategies for recruitment and concerned research with harder-to-reach populations., Implications for Nursing: This article draws on the literature regarding the challenges of recruiting research participants from harder-to-reach populations and known strategies for overcoming them. These strategies include, for example, establishing a trusting relationship between the researcher and the participant community and gaining in-depth knowledge of the target population. These challenges and strategies for recruiting participants from these populations are discussed specifically in the context of quantitative survey research., Conclusion: Nurse researchers conducting quantitative survey studies with participants from harder-to-reach populations must tailor their recruitment strategies to the target population and, most importantly, be flexible and creative in their recruitment methods., Impact: The article discusses the challenges of recruiting participants from harder-to-reach populations and strategies to overcome them in quantitative survey studies. Successful recruitment requires researchers to develop a thorough understanding of the harder-to-reach population, develop partnerships to locate and access potential participants, build trust with the community, tailor their language, minimize participation risk and resource constraints, recognize the cognitive and physical demands required, and be flexible and creative in developing recruitment strategies. This knowledge can enable the inclusion of more people from harder-to-reach populations in survey studies and provide evidence that can inform research and practice to provide healthcare tailored to their needs and ultimately help improve their health and well-being., (© 2022 John Wiley & Sons Ltd.)

A recent review of missing data in pharmacy literature has highlighted that a low proportion of studies reported how missing data was handled. In this paper we discuss the concept of missing data in survey research, how missing data is classified, common techniques to account for missingness and how to report on missing data. The paper provides guidance to mitigate the occurrence of missing data through planning. Considerations include estimating expected missing data, intended vs unintended missing data, survey length, working with electronic surveys, choosing between standard and filtered form questions, forced responses and straight-lining, as well as responses that can generate missingness like "I don't know" and "Not Applicable". We introduce methods for analysing data with missing values, such as deletion, imputation and likelihood methods. The manuscript provides a framework and flow chart for choosing the appropriate analysis method based on how much missing data is observed and the type of missingness. Special circumstances involving missing data have been discussed, such as in studies with repeated or cohort measures, factor analysis or as part of data integration. Finally, a checklist of questions are provided for researchers to guide the reporting of the missing data when conducting future research., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Replication-an important, uncommon, and misunderstood practice-is gaining appreciation in psychology. Achieving replicability is important for making research progress. If findings are not replicable, then prediction and theory development are stifled. If findings are replicable, then interrogation of their meaning and validity can advance knowledge. Assessing replicability can be productive for generating and testing hypotheses by actively confronting current understandings to identify weaknesses and spur innovation. For psychology, the 2010s might be characterized as a decade of active confrontation. Systematic and multi-site replication projects assessed current understandings and observed surprising failures to replicate many published findings. Replication efforts highlighted sociocultural challenges such as disincentives to conduct replications and a tendency to frame replication as a personal attack rather than a healthy scientific practice, and they raised awareness that replication contributes to self-correction. Nevertheless, innovation in doing and understanding replication and its cousins, reproducibility and robustness, has positioned psychology to improve research practices and accelerate progress.

Background: The appreciative inquiry (AI) interview follows a specific format and needs to be planned and developed before implementation. AI questions are designed to draw on the interviewee's experiences, commencing with general questioning and progressing to more focused questioning., Aim: To explain how to plan and undertake AI interviews, and to discuss issues that nurse researchers might encounter., Discussion: This article is based on the first author's experience of undertaking an AI doctoral study. The primary method of collecting data for the study was AI interviews. The more focused questioning related to participants' experiences of positive actions or behaviours. Although questioning was positive in nature and participant-centric, conducting the interviews was more problematic than the first author anticipated. Some participants struggled to recall positive memories to share., Conclusion: The unexpected response to the interview questions required the first author to examine her practices, as well as beliefs and judgements relating to AI. This reflexivity assisted in implementing changes to the study's process, resulting in a more positive experience for her and the participants., Implications for Practice: Researchers using the AI interview require the capacity to be self-critical and change the process if necessary to enrich the outcome., Competing Interests: None declared, (©2021 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)

Background: In recent years, the value of patient and public involvement (PPI) in developing research has become apparent. Patients and service users have insights that are essential to successfully developing and completing research. PPI collaborations may improve the scope, quality, relevance and impact of research. Nevertheless, there are challenges for nurse researchers in ensuring effective PPI is embedded in research proposals and practice., Aim: To discuss the practical aspects of developing a PPI group, including one approach to convening a PPI group, and provide examples of where a PPI group has refined and improved the design of research., Discussion: Directly inviting patients and members of the public to collaborate in the research resulted in successful working relationships and tangible improvements to a study's methodology. None of the patients approached had considered collaborating in research before and so would not have been reached by any other means., Conclusion: There are several approaches nurse researchers can take to convene a PPI group, including open forums and relevant charity groups. The authors' experience was broadly successful, although future research would involve collaboration with other teams to recruit more diverse groups., Implications for Practice: Nurse researchers are ideally placed to collaborate with patients and members of the public in designing and delivering research., Competing Interests: JF receives funding from the National Institute for Health Research (NIHR), MH reports personal fees from Internis, SC reports educational sponsorship from Takeda, Fresenius-Kabi and honoraria from Novartis and Baxter. AS reports no conflicts of interest., (©2021 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)

This article is concerned with the processes of doing research with people who use drugs, as someone who has a history of using drugs. It offers a brief introductory review to autoethnographic research methods and how they might be used to enhance the practice of drugs research. Through illustrative examples from the author's own experiences of researching heroin use, the article cautiously makes the case for an increased focus upon our drug-using experiences in drugs research. The positive and negative implications of this for research methods in drug studies are discussed, as well as their potential intersections with drug policy debates., Competing Interests: Declarations of Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Photo elicitation offers novel opportunities to augment the qualitative research toolbox. The use of photographs can enrich connections with participants, and empower them to be creative and engaged to communicate their insights, priorities, and perspectives. There is growing evidence of the effective use of photo elicitation in health research, with emerging interest in the cardiovascular community. Careful study planning, including attention to equipment, participant training, photograph selection, data collection, and ethical consideration, is essential. Detailed reporting of the study design and rationale for use of photographs, conceptual thinking underpinnings, elicitation process, and analytical plan contribute to strengthening the methodological approach., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2021. For permissions, please email: journals.permissions@oup.com.)

Objective: The fragility index is a clinically interpretable metric increasingly used to interpret the robustness of clinical trials results that is generally not incorporated in sample size calculation and applied post-hoc. In this manuscript, we propose to base the sample size calculation on the fragility index in a way that supplements the classical prefixed alpha and power cutoffs and we provide a dedicated R software package for the design and analysis tools., Study Design and Setting: This approach follows from a novel hypothesis testing framework that is based on the fragility index and builds on the classical testing approach. As case studies, we re-analyse the design of two important trials in cardiovascular medicine, the FAME and FAMOUS-NSTEMI trials., Results: The analyses show that approach returns sample sizes which results in a higher power for the P value based test and most importantly a lower and context dependent Type I error rate for the fragility index based test compared to standard tests., Conclusion: Our method allows clinicians to control for the fragility index during clinical trial design., (Copyright © 2021. Published by Elsevier Inc.)

Background: Choosing how to answer a research question requires an understanding of philosophical and theoretical assumptions and how these inform a study's methodology and methods. This can be a challenge for all researchers, but for novice researchers, such as doctoral candidates, this can feel like an overwhelming task. Ensuring there is clear alignment between philosophy, theory, methodology and methods is an essential part of the research process, that enables research to be undertaken with clarity and integrity. This alignment must be a good fit for the research aim, and to ensure the researcher's intrinsic values and beliefs do not affect the analysis undertaken., Aim: To describe the alignment between qualitative description and naturalistic inquiry and how it was applied to a doctoral candidate's exploration of the meaning of safety for people with experience of admission to an acute mental health unit., Discussion: Understanding the alignment between qualitative descriptive methodology and naturalistic inquiry provided a clear pathway for the doctoral candidate., Conclusion: The assumptions that underpin a methodological approach need to be unpacked to understand how to answer a research question effectively., Implications for Practice: Qualitative description, informed by naturalistic inquiry, offers a practical way to explore and answer research questions., Competing Interests: None declared, (©2021 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)

Although systematic reviews are the method of choice to synthesize scientific evidence, they can take years to complete and publish. Clinicians, managers, and policy-makers often need input from scientific evidence in a more timely and resource-efficient manner. For this purpose, rapid reviews are conducted. Rapid reviews are performed using an accelerated process. However, they should not be less systematic than standard systematic reviews, and the introduction of bias must be avoided. In this article, we describe what rapid reviews are, present their characteristics, give some examples, highlight potential pitfalls, and draw attention to the importance of evidence summaries in order to facilitate adoption in clinical decision-making., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Traditional non-participatory research methodologies have struggled to address the needs of multicultural populations in the United States (U.S.). Community-based participatory research (CBPR) is a research paradigm offering a unique opportunity for culturally appropriate research and improving health equity. CBPR is an equitable, strength-based approach involving all stakeholders throughout the research process. We investigate the field of psychology's utilization of CBPR as an approach for working with multicultural populations to collaboratively address relevant and impactful research questions. A total of 1912 CBPR-related articles, from 2004 to 2014, were identified using PsycINFO, PubMed, and CINAHL Complete databases. Of these, approximately 16% (n = 311) met our criteria for psychology-related CBPR articles accounting for a negligible amount (<1%) of peer-reviewed publications in mainstream psychological journals during the same time period. Among U.S. psychology-related CBPR articles, 86% focused on multicultural and marginalized populations. Prominent topics of investigation included physical health, mental and behavioral health, and theoretical or methodological articles. Features of publications, including authors' training, types of journals, study populations, and topics under investigation, were explored for all 1912 publications. Findings highlight an opportunity for further utilization of CBPR within psychology, with key implications for health equity. Recommendations for increasing CBPR uptake within the discipline are also offered., (© 2020 Society for Community Research and Action.)

Background: Truly patient-centred care needs to be aligned with what patients consider important, and is highly desirable in the first 24 h of an acute admission, as many decisions are made during this period. However, there is limited knowledge on what matters most to patients in this phase of their hospital stay. The objective of this study was to identify what mattered most to patients in acute care and to assess the patient perspective as to whether their treating doctors were aware of this., Methods: This was a large-scale, qualitative, flash mob study, conducted simultaneously in sixty-six hospitals in seven countries, starting November 14th 2018, ending 50 h later. One thousand eight hundred fifty adults in the first 24 h of an acute medical admission were interviewed on what mattered most to them, why this mattered and whether they felt the treating doctor was aware of this., Results: The most reported answers to "what matters most (and why)?" were 'getting better or being in good health' (why: to be with family/friends or pick-up life again), 'getting home' (why: more comfortable at home or to take care of someone) and 'having a diagnosis' (why: to feel less anxious or insecure). Of all patients, 51.9% felt the treating doctor did not know what mattered most to them., Conclusions: The priorities for acutely admitted patients were ostensibly disease- and care-oriented and thus in line with the hospitals' own priorities. However, answers to why these were important were diverse, more personal, and often related to psychological well-being and relations. A large group of patients felt their treating doctor did not know what mattered most to them. Explicitly asking patients what is important and why, could help healthcare professionals to get to know the person behind the patient, which is essential in delivering patient-centred care., Trial Registration: NTR (Netherlands Trial Register) NTR7538 .

Because the time between study conception and dissemination of findings generally takes long, efforts to reduce this lag are important. A solution to accelerate the research process can be found in flash mob research. This is a method to study clinically relevant questions on a large scale in a very short course of time. The research question and the set-up of the study should be exciting. Doing so, it attracts a large 'mob' of people who collect the data. Consequently, the generalizability of flash mob studies may be higher than that of traditional research studies., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: A study aimed at reducing the time spent on the phone obtaining insurance preauthorisation in a neurosurgical clinic was successfully completed. However, the researchers were unable to reject the null hypothesis because of a combination of chronological bias and the Hawthorne effect., Aim: To increase nurse researchers' awareness of the potential to introduce a chronological bias as a confounder in clinical research and suggest potential alternative approaches to study design., Discussion: The researcher shared the study's purpose, design and outcome measure with the participants before collecting the baseline data. This enabled the participants to alter their practice before the intervention was implemented (a chronological bias) and change their behaviour surrounding the outcome (the Hawthorne effect)., Conclusion: The use of the Delphi method became a catalyst for change before the collection of baseline data, the combination of chronological bias and the Hawthorne effect affecting the study's results., Implications for Practice: Nurse researchers seeking to improve practice should collect baseline data before informing participants and consider the risks and benefits of blinding (concealment) surrounding the outcome., Competing Interests: None declared, (©2021 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)

Background: Nominal group technique (NGT) is a highly structured, commonly used way of exploring areas of interest and developing consensus. However, it is sometimes conflated with focus group methods., Aim: To provide a rationale for selecting NGT as a research method and to examine its systematic application in a doctoral Q-methodology study exploring nursing students' perspectives of preserving dignity in care., Discussion: An outline of NGT is provided, and it is distinguished from focus group methods. As well as providing a step-by-step guide to using NGT, each step is illustrated with its practical application in the study, and the lessons learned concerning the limitations and strengths of NGT in the context of one study are shared., Conclusion: When applied systematically, NGT enables nurse researchers to collaborate in a meaningful and engaging way with participants and generate tangible outcomes relatively quickly., Implications for Practice: This paper offers practical insight into the use of NGT to explore perceptions and develop consensus., Competing Interests: None declared, (©2021 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)

Background: Quantitative research designs are broadly classified as being either experimental or quasi-experimental. Factorial designs are a form of experimental design and enable researchers to examine the main effects of two or more independent variables simultaneously. They also enable researchers to detect interactions among variables., Aim: To present the features of factorial designs., Discussion: This article provides an overview of the factorial design in terms of its applications, design features and statistical analysis, as well as its advantages and disadvantages., Conclusion: Factorial designs are highly efficient for simultaneously evaluating multiple interventions and present the opportunity to detect interactions amongst interventions. Such advantages have led researchers to advocate for the greater use of factorial designs in research when participants are scarce and difficult to recruit., Implications for Practice: A factorial design is a cost-effective way to determine the effects of combinations of interventions in clinical research, but it poses challenges that need to be addressed in determining appropriate sample size and statistical analysis., Competing Interests: None declared, (©2021 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)

Engaging patients-defined broadly as individuals with lived experience of a given condition, family members, caregivers, and the organisations that represent them-as partners in research is a priority for policymakers, funders, and the public. Nonetheless, formal efforts to engage patients are absent from most studies, and models to support meaningful patient engagement in clinical anaesthesia research have not been previously described. Here, we review our experience in developing and implementing a multifaceted patient engagement strategy within the Regional Versus General Anesthesia for Promoting Independence After Hip Fracture (REGAIN) surgery trial, an ongoing randomised trial comparing spinal vs general anaesthesia for hip fracture surgery in 1600 older adults across 45 hospitals in the USA and Canada. This strategy engaged patients and their representatives at both the level of overall trial oversight and at the level of individual recruiting sites. Activities spanned a continuum ranging from events designed to elicit patients' input on key decisions to longitudinal collaborations that empowered patients to actively participate in decision-making related to trial design and management. Engagement activities were highly acceptable to participants and led to concrete changes in the design and conduct of the REGAIN trial. The REGAIN experience offers a model for future efforts to engage patients as partners in clinical anaesthesia research, and highlights potential opportunities for investigators to increase the relevance of anaesthesia studies by incorporating patient voices and perspectives into the research process., (Copyright © 2020 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.)

Limited information is available on strategies for managing the large number of survey requests that reach an individual nursing school. This article addresses problems identified in managing survey requests and describes the implementation and evaluation of a solution. Identified problems included the appearance of endorsing studies of varying quality and rigor, overlap and competition between external study requests and internal studies, respondent burden, and level of anonymity and confidentiality. The solution included a school-wide policy for tracking and vetting study requests before they were distributed. Evaluation data show the number of requests received (total, by month and source, by target population), their disposition (withdrawn, approved, not approved for distribution), and quality improvement data on meeting a 30-day target turnaround time. Additional considerations are also discussed.

Objective: The aim of this paper is to review the literature on barriers to conducting replication research and strategies to increase its use and promotion by researchers, editors, and funders., Study Design and Setting: This review was part of a larger meta-narrative review aimed at conducting a concept analysis of replication and developing a replication research framework. A combination of systematic and snowball search strategies was used to identify relevant literature in multiple research fields. Data were coded and analyzed using the Theoretical Domains Framework for barriers to replication and the behavior change wheel for solutions., Results: In total, 153 papers were included in this narrative review. Multiple barriers limit the use of replication research by researchers, editors, and funders. Many of the barriers were related to knowledge and skills of all these actors. Social influences and the research environmental context were also described as not supportive. Multiple strategies were proposed to create positive outcomes expectations, reinforcement, and structural changes in the physical and social context of research., Conclusion: A social change involving advisory groups, research organizations, and institutions is required to establish new norms that will value, promote, support, and reward replication research., (Copyright © 2020. Published by Elsevier Inc.)

Objectives: Methods for pharmacoepidemiologic studies of large-scale data repositories are established. Although clinical cohorts of older adults often contain critical information to advance our understanding of medication risk and benefit, the methods best suited to manage medication data in these samples are sometimes unclear and their degree of validation unknown. We sought to provide researchers, in the context of a clinical cohort study of delirium in older adults, with guidance on the methodological tools to use data from clinical cohorts to better understand medication risk factors and outcomes., Design: Prospective cohort study., Setting: The Successful Aging After Elective Surgery (SAGES) prospective cohort., Participants: A total of 560 older adults (aged ≥70 years) without dementia undergoing elective major surgery., Measurements: Using the SAGES clinical cohort, methods used to characterize medications were identified, reviewed, analyzed, and distinguished by appropriateness and degree of validation for characterizing pharmacoepidemiologic data in smaller clinical data sets., Results: Medication coding is essential; the American Hospital Formulary System, most often used in the United States, is not preferred over others. Use of equivalent dosing scales (e.g., morphine equivalents) for a single medication class (e.g., opioids) is preferred over multiclass analgesic equivalency scales. Medication aggregation from the same class (e.g., benzodiazepines) is well established; the optimal prevalence breakout for aggregation remains unclear. Validated scale(s) to combine structurally dissimilar medications (e.g., anticholinergics) should be used with caution; a lack of consensus exists regarding the optimal scale. Directed acyclic graph(s) are an accepted method to conceptualize causative frameworks when identifying potential confounders. Modeling-based strategies should be used with evidence-based, a priori variable-selection strategies., Conclusion: As highlighted in the SAGES cohort, the methods used to classify and analyze medication data in clinically rich cohort studies vary in the rigor by which they have been developed and validated., (© 2020 The American Geriatrics Society.)

True causality is impossible to capture with observational studies. Nevertheless, within the boundaries of observational studies, researchers can follow three steps to answer causal questions in the most optimal way possible. Researchers must: (a) repeatedly assess the same constructs over time in a specific sample; (b) consider the temporal sequence of effects between constructs; and (c) use an analytical strategy that distinguishes within from between-person effects. In this context, it is demonstrated how the random intercepts cross-lagged panel model can be a useful statistical technique. A real-life example of the relationship between loneliness and quality of life in adolescents with congenital heart disease is provided to show how the model can be practically implemented.

In recent years, psychology has wrestled with the broader implications of disappointing rates of replication of previously demonstrated effects. This article proposes that many aspects of this pattern of results can be understood within the classic framework of four proposed forms of validity: statistical conclusion validity, internal validity, construct validity, and external validity. The article explains the conceptual logic for how differences in each type of validity across an original study and a subsequent replication attempt can lead to replication "failure." Existing themes in the replication literature related to each type of validity are also highlighted. Furthermore, empirical evidence is considered for the role of each type of validity in non-replication. The article concludes with a discussion of broader implications of this classic validity framework for improving replication rates in psychological research.

Background: In this clinical commentary, we highlight issues related to conceptual foundations and methods used in training load and injury research. We focus on sources of degrees of freedom that can favor questionable research practices such as P hacking and hypothesizing after the results are known, which can undermine the trustworthiness of research findings., Clinical Question: Is the methodological rigor of studies in the training load and injury field sufficient to inform training-related decisions in clinical practice?, Key Results: The absence of a clear conceptual framework, causal structure, and reliable methods can promote questionable research practices, selective reporting, and confirmation bias. The fact that well-accepted training principles (eg, overload progression) are in line with some study findings may simply be a consequence of confirmation bias, resulting from cherry picking and emphasizing results that align with popular beliefs. Identifying evidence-based practical applications, grounded in high-quality research, is not currently possible. The strongest recommendation we can make for the clinician is grounded in common sense: "Do not train too much, too soon"-not because it has been confirmed by studies, but because it reflects accepted generic training principles., Clinical Application: The training load and injury research field has fundamental conceptual and methodological weaknesses. Therefore, making decisions about planning and modifying training programs for injury reduction in clinical practice, based on available studies, is premature. Clinicians should continue to rely on best practice, experience, and well-known training principles, and consider the potential influence of contextual factors when planning and monitoring training loads. J Orthop Sports Phys Ther 2020;50(10):577-584. Epub 1 Aug 2020. doi:10.2519/jospt.2020.9211 .

The number of systematic reviews and meta-analyses submitted to nursing and allied health journals continues to grow. Well-conducted and reported syntheses of research are valuable to advancing science. One of the common critiques identified in these manuscripts involves how the authors addressed heterogeneity among the studies in their meta-analyses. Methodologically inappropriate approaches regarding heterogeneity introduce error and bias into analyses and may lead to incorrect findings and conclusions. This article will discuss some of the approaches to take as well as avoid when addressing heterogeneity in meta-analyses, including suggestions for how to choose a fixed-effect or random-effects meta-analysis model and steps to follow to address heterogeneity in meta-analysis results.

Background: It is important for researchers to be open and transparent about the relationship between themselves and the subjects of their enquiry. Reflexivity enables them to do this, but although there is much guidance in the literature about reflexivity in general, there is little guidance for PhD candidates on including it in their theses., Aim: To provide a practical illustration of how researchers can evidence reflexivity in their theses., Discussion: The author presents the reflexive stance and journey she made when completing a PhD study that used constructivist grounded theory. It predominantly depicts the influences on the choices and decisions she made, so the reader can make sense of the journey she undertook. The author depicts how she began her journey as a novice nurse researcher and concluded it as a fully fledged researcher., Conclusion: There has been much debate about how to integrate reflexivity in the context of a particular study. This article highlights the importance of reflexivity in research and uses excerpts from the author's thesis to illustrate how it can be presented in a thesis., Implications for Practice: The article provides a guide and questions for PhD candidates to consider so they can present and think more deeply about reflexivity in their theses., Competing Interests: None declared, (©2020 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)

Background: Despite the extensive use of mixed methods across health sciences, there has been a limited discussion about the methodological rigour and quality in mixed methods research (MMR). Although the empirical and methodological literature about mixed methods is increasing, there are few practical examples of the implementation of rigour criteria., Aim: To discuss and illustrate the application of 'legitimation criteria' to the design and conduct of a sequential exploratory MMR study of nurse educators' challenges when teaching undergraduate students., Discussion: The legitimation criteria can establish philosophical and methodological validity and rigour in MMR. MMR is complex and daunting, so maintaining rigour is crucial in ensuring the conclusions drawn are plausible and researchers, practitioners and policymakers use them to guide research and practice., Conclusion: The legitimation criteria are specific to MMR and are useful in improving the conduct and execution of studies. They enable researchers to maintain quality throughout their studies, from the development of a research question to the generation of conclusions., Implications for Practice: This illustration of the legitimation criteria for the design and conduct of MMR will guide researchers in establishing rigour and lessen the threats to their studies' validity., Competing Interests: None declared, (©2020 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)

Background: Methodological studies - studies that evaluate the design, analysis or reporting of other research-related reports - play an important role in health research. They help to highlight issues in the conduct of research with the aim of improving health research methodology, and ultimately reducing research waste., Main Body: We provide an overview of some of the key aspects of methodological studies such as what they are, and when, how and why they are done. We adopt a "frequently asked questions" format to facilitate reading this paper and provide multiple examples to help guide researchers interested in conducting methodological studies. Some of the topics addressed include: is it necessary to publish a study protocol? How to select relevant research reports and databases for a methodological study? What approaches to data extraction and statistical analysis should be considered when conducting a methodological study? What are potential threats to validity and is there a way to appraise the quality of methodological studies?, Conclusion: Appropriate reflection and application of basic principles of epidemiology and biostatistics are required in the design and analysis of methodological studies. This paper provides an introduction for further discussion about the conduct of methodological studies.

While electronic adherence monitoring devices (EAMDs) are the preferred and most objective medication adherence measurement strategy for many populations and research questions, there is no comprehensive methodological framework for EAMD use. We synthesize recommendations from experts in adherence science and the scientific literature to create a temporal framework of EAMD research methods. The goal of this framework is to provide a step-by-step guide that will enable researchers to design, prepare, implement, and clean data from rigorous, high-quality studies using EAMDs to assess adherence. Resources including a checklist of methodological considerations and example protocols have been created to assist readers in using this framework.

Research in the field of health promotion generates evidence-based knowledge and has the potential to increase the acceptance, impact and long-term effectiveness of interventions. Typically, a distinction is made between qualitative and quantitative approaches. Yet, with complex and multidimensional re-search questions in the field of health promotion a combination of the two approaches has proven useful. Using mixed-methods designs promises, among other things, to compensate for weaknesses of the individual methods, to improve the scope of the results, and to provide a comprehensive insight into the topic. In this systematic review of two German journals we examine the role of the mixed-methods approach in the field of health promotion and how it can be translated into specific research projects. The review's results show that mixed-methods designs are implemented in various contexts. In most studies, the quantitative research strand plays the central role. The use of the mixed-methods designs in health promotion can be further discussed, especially taking into account technical innovations in the field of data collection or with regard to the interpretative potential of qualitative research. The presentation of the review is based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) by the Equator Network., (Copyright © 2020. Published by Elsevier GmbH.)

Complex interventions of varying degrees of complexity are commonly used and evaluated in cardiovascular nursing and allied professions. Such interventions are increasingly tested using randomized trial designs. However, process evaluations are seldom used to better understand the results of these trials. Process evaluation aims to understand how complex interventions create change by evaluating implementation, mechanisms of impact, and the surrounding context when delivering an intervention. As such, this method can illuminate important mechanisms and clarify variation in results. In this article, process evaluation is described according to the Medical Research Council guidance and its use exemplified through a randomized controlled trial evaluating the effectiveness of a transition program for adolescents with chronic conditions.

Introduction: Text mining to support screening in large-scale systematic reviews has been recommended; however, their suitability for reviews in injury research is not known. We examined the performance of text mining in supporting the second reviewer in a systematic review examining associations between fault attribution and health and work-related outcomes after transport injury., Methods: Citations were independently screened in Abstrackr in full (reviewer 1; 10 559 citations), and until no more citations were predicted to be relevant (reviewer 2; 1809 citations, 17.1%). All potentially relevant full-text articles were assessed by reviewer 1 (555 articles). Reviewer 2 used text mining (Wordstat, QDA Miner) to reduce assessment to full-text articles containing ≥1 fault-related exposure term (367 articles, 66.1%)., Results: Abstrackr offered excellent workload savings: 82.7% of citations did not require screening by reviewer 2, and total screening time was reduced by 36.6% compared with traditional dual screening of all citations. Abstrackr predictions had high specificity (83.7%), and low false negatives (0.3%), but overestimated citation relevance, probably due to the complexity of the review with multiple outcomes and high imbalance of relevant to irrelevant records, giving low sensitivity (29.7%) and precision (14.5%). Text mining of full-text articles reduced the number needing to be screened by 33.9%, and reduced total full-text screening time by 38.7% compared with traditional dual screening., Conclusions: Overall, text mining offered important benefits to systematic review workflow, but should not replace full screening by one reviewer, especially for complex reviews examining multiple health or injury outcomes., Trial Registration Number: CRD42018084123., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Non-randomised study designs are frequently used by researchers in cardiovascular nursing and allied professions. Baseline differences between the groups to be compared may introduce bias in the results. Methods for causal inference address this issue. One such method is propensity weighting, in which two or more treatments/exposure groups are weighted to make the groups as comparable as possible. As such, it mimics a randomised controlled trial design. In this article, the Twang package is presented for propensity weighting, and its use is exemplified in a study on smoking and cannabis consumption in adults with congenital heart disease.

The paramount importance of research design and research methodologies within the shared space of neurology, clinical neurophysiology, and cognitive neuroscience serves as the theme around which a range of topics is presented. After a tour of historical figures of human electrophysiology and electroencephalography (EEG), the discussion turns to event-related potential (ERP). Emphasizing the lengthy history of these manifestations of cognition, the chapter outlines the extensive research literature that has demonstrated the sensitivity of ERPs to a range cognitive functions, including attention, language processing, and memory. There follows a series of examples of ERP applications in the clinical domain, including disorders of consciousness, stroke, autism, coma, and concussion. These examples not merely demonstrate the general utility of these electrophysiological responses but stress that their independence from behavioral responses provides a much needed clinical method to assess individuals who are literally or virtually impossible to assess using traditional behaviorally based clinical tools. The chapter concludes with the suggestion that is time that the incontrovertible utility of ERPs be employed more fully within clinical contexts to assist the clinical community in providing objective assessments of a range of neurologic conditions., (Copyright © 2020 Elsevier B.V. All rights reserved.)