The Dietary Approaches to Stop Hypertension (DASH) eating plan is the most effective dietary intervention for cardiovascular disease (CVD), but it excludes the consideration of culture and cost. The ...Hispanic/Latine population is disproportionately affected by CVD, with risks increasing if persons are accustomed to a Westernized diet. This research aims to understand the cultural dietary practices aligned with a DASH eating plan and the social determinants of health impacting fruit and vegetable (F/V) consumption among immigrant Hispanic/Latine individuals at a community-based clinic in Minnesota. Utilizing community-based participatory research methods, a community survey informed the development of DASH-focused, medically tailored food kits of varying F/V modalities. Qualitative feedback was sought out regarding the kits when presented to 15 individuals during in-depth interview sessions to validate the cultural appropriateness of food kits for clinical use. Box A was the highest rated kit (66.7%) and consisted of fresh F/V. The average F/V consumption per day was 2.6 ± 1.4 servings. The food insecurity questionnaires showed high/marginal (40%), low (53.3%), and very low (6.7%) food security. The barriers to consuming F/V were money, time, and transportation. Understanding cultural dietary practices related to the DASH eating plan is necessary to mitigate CVD risk and provide inclusive medical nutrition therapy for Hispanic/Latine populations.
Background
Parenting programs aim to reduce children's conduct problems through improvement of family dynamics. To date, research on the precise benefits and possible harms of parenting programs on ...family well‐being has been unsystematic and likely to be subject to selective outcome reporting and publication bias. Better understanding of program benefits and harms requires full disclosure by researchers of all included measures, and large enough numbers of participants to be able to detect small effects and estimate them precisely.
Methods
We obtained individual participant data for 14 of 15 randomized controlled trials on the Incredible Years parenting program in Europe (total N = 1,799). We used multilevel modeling to estimate program effects on 13 parent‐reported outcomes, including parenting practices, children's mental health, and parental mental health.
Results
Parental use of praise, corporal punishment, threats, and shouting improved, while parental use of tangible rewards, monitoring, or laxness did not. Children's conduct problems and attention deficit hyperactivity disorder (ADHD) symptoms improved, while emotional problems did not. Parental mental health (depressive symptoms, self‐efficacy, and stress) did not improve. There was no evidence of harmful effects.
Conclusions
The Incredible Years parenting program improves the aspects of family well‐being that it is primarily designed to improve: parenting and children's conduct problems. It also improves parent‐reported ADHD symptoms in children. Wider benefits are limited: the program does not improve children's emotional problems or parental mental health. There are no signs of harm on any of the target outcomes.
The social technologies of the web permit new techniques of research to emerge, often with novel ethical challenges. One such technique is digital ethnography. While there is a robust literature ...associated with digital approaches to ethnography, there is a lack of development in how digital ethnography can be used when researching vulnerable populations. This article seeks to clarify these methodological considerations, addressing the role of the researcher, data representation, and the ethical considerations necessary to research vulnerable consumers. We consider the various roles that digital ethnography can play in understanding emerging forms of social order in vulnerable consumer contexts, in generating social knowledge that is nuanced, participative, holistic, and practically orientated. We highlight a selection of the core issues concerning the use, practice and dissemination of digital ethnographic research available to social researchers, and how the incorporation of such methods can invigorate research on vulnerable consumers with new methodological innovations.
An individual participant data meta-analysis was conducted in the data of 14 673 Japanese participants without a history of cardiovascular disease (CVD) to examine the association of the ...brachial-ankle pulse wave velocity (baPWV) with the risk of development of CVD. During the average 6.4-year follow-up period, 687 participants died and 735 developed cardiovascular events. A higher baPWV was significantly associated with a higher risk of CVD, even after adjustments for conventional risk factors (
for trend <0.001). When the baPWV values were classified into quintiles, the multivariable-adjusted hazard ratio for CVD increased significantly as the baPWV quintile increased. The hazard ratio in the subjects with baPWV values in quintile 5 versus that in those with the values in quintile 1 was 3.50 (2.14-5.74;
<0.001). Every 1 SD increase of the baPWV was associated with a 1.19-fold (1.10-1.29;
<0.001) increase in the risk of CVD. Moreover, addition of baPWV to a model incorporating the Framingham risk score significantly increased the C statistics from 0.8026 to 0.8131 (
<0.001) and also improved the category-free net reclassification (0.247;
<0.001). The present meta-analysis clearly established baPWV as an independent predictor of the risk of development of CVD in Japanese subjects without preexisting CVD. Thus, measurement of the baPWV could enhance the efficacy of prediction of the risk of development of CVD over that of the Framingham risk score, which is based on the traditional cardiovascular risk factors.
Maintaining data quality on Amazon Mechanical Turk (MTurk) has always been a concern for researchers. These concerns have grown recently due to the bot crisis of 2018 and observations that past ...safeguards of data quality (e.g., approval ratings of 95%) no longer work. To address data quality concerns, CloudResearch, a third-party website that interfaces with MTurk, has assessed ~165,000 MTurkers and categorized them into those that provide high- (~100,000, Approved) and low- (~65,000, Blocked) quality data. Here, we examined the predictive validity of CloudResearch’s vetting. In a pre-registered study, participants (
N
= 900) from the Approved and Blocked groups, along with a Standard MTurk sample (95% HIT acceptance ratio, 100+ completed HITs), completed an array of data-quality measures. Across several indices, Approved participants (i) identified the content of images more accurately, (ii) answered more reading comprehension questions correctly, (iii) responded to reversed coded items more consistently, (iv) passed a greater number of attention checks, (v) self-reported less cheating and actually left the survey window less often on easily Googleable questions, (vi) replicated classic psychology experimental effects more reliably, and (vii) answered AI-stumping questions more accurately than Blocked participants, who performed at chance on multiple outcomes. Data quality of the Standard sample was generally in between the Approved and Blocked groups. We discuss how MTurk’s Approval Rating system is no longer an effective data-quality control, and we discuss the advantages afforded by using the Approved group for scientific studies on MTurk.
This book addresses a key issue in higher learning, university education and scientific research: the widespread difficulty researchers, experts and students from all disciplines face when trying to ...contribute to change in complex social settings characterized by uncertainty and the unknown. More than ever, researchers need flexible means and grounded theory to combine people-based and evidence-based inquiry into challenging situations that keep evolving and do not lend themselves to straightforward technical explanations and solutions.
In this book, the authors propose innovative strategies for engaged inquiry building on insights from many disciplines and lessons from the history of Participatory Action Research (PAR), including French psychosociology. The ongoing evolution of PAR has had a lasting legacy in fields ranging from community development to education, public engagement, natural resource management and problem solving in the workplace. All formulations have in common the idea that research must be done ‘with’ people and not ‘on’ or ‘for’ people. Inquiry of this kind makes sense of the world through efforts to transform it, as opposed to simply observing and studying human behaviour and people’s views about reality, in the hope that meaningful change will happen somewhere down the road.
The book contributes many new tools and conceptual foundations to this longstanding tradition, grounded in real-life examples of collective fact-finding, analysis and decision-making from around the world. It provides a modular textbook on participatory action research and related methods, theory and practice, suitable for a wide range of undergraduate and postgraduate courses, as well as working professionals.
Introduction: Engaging with Participatory Action Research
1. Action Research History 2. Society, Experience, Knowledge
Module One: Grounding and Uncertainty
3. Creating an Action Learning System 4. Managing Complexity 5. Mapping the Process 6. Walking the Talk
Module Two: Fact Finding and Listening
7. Reinventions of the Wheel 8. Seeking Evidence and Consensus
Module Three: Exploring Problems
9. Getting to the Root 10. Factors and Reasons
Module 4: Knowing the Actors
11. Stakeholder Identification 12. Stakeholder Analysis 13. Positions and Values
Module Five: Assessing Options
14. Blue Sky Thinking 15. Into the Future
Module Six: Understanding Systems
16. Contributing to Change 17. System Dynamics 18. Domain Analysis 19. Breaking the Dependency on Tobacco Production
Conclusion: Rethinking Higher Education and the Discovery Process
"This book is a must for anyone seriously committed to research that ensures the authentic participation and empowerment of people from all walks of life, be they from oral or textual traditions, women or men, old or young, articulate or hesitant, outspoken or reserved." – Farida Akhter, Executive Director, UBINIG (Policy Research for Development Alternative), Dhaka, Bangladesh
" This exciting and innovative book shows the patterns and processes that connect people and their social, practical and conceptual worlds in action. Its key themes of interdependence, relationship, and the need for dialogue make it a book today for tomorrow’s world. It should be on all reading lists as a key resource for developing socially-oriented pedagogies for a more peaceful, productive and interconnected world." – Jean McNiff, Professor of Educational Research at York St John University, York, UK and author of 'Action Research: Principles and Practice', now in its third edition (Routledge, 2013)
"...a wonderful compendium, replete with practical tools and techniques that bring rigour and vigour to the international dialogue among action researchers... This is a serious volume worth the time of any action researcher who is curious about how western (including francophone) perspectives on PAR come alive. This volume makes a significant contribution to the collective craft of scholarly-practice among action researchers." – Hilary Bradbury-Huang, Professor in the Division of Management at Oregon Health & Science University, Portland, USA and Editor of the journal Action Research
Jacques M. Chevalier is Chancellor’s Professor Emeritus in the Department of Sociology and Anthropology at Carleton University, Ottawa, Canada.
Daniel J. Buckles is Adjunct Research Professor in the Department of Sociology and Anthropology at Carleton University, Ottawa, Canada, and an independent consultant.
This Handbook presents established and innovative perspectives on involving older adults as co-creators in ageing research. It reorients research and policy toward more inclusive and adequate designs ...that capture the voices and needs of older adults. The Handbook: introduces types of participatory approaches in ageing research; highlights key methodological aspects of these approaches; gives insights from projects across different cultural contexts and academic disciplines, showing ways in which older participants can be involved in co-designing different stages of the research cycle; examines key issues to consider when involving older participants at each step of the research process; includes the voices of older adults directly; draws out conclusions and points ways forward for future research. This Handbook will be essential reading for researchers and students interested in the field of ageing and/ or participatory methods, as well as for those policy stakeholders in the fields of ageing and demographic change, social and public policy, or health and wellbeing who are interested in involving older adults in policy processes. It will be useful for third-sector advocacy organizations and international non-governmental and public agencies working either in citizen involvement/participation or the ageing sector.
EEG-based deep learning models have trended toward models that are designed to perform classification on any individual (cross-participant models). However, because EEG varies across participants due ...to non-stationarity and individual differences, certain guidelines must be followed for partitioning data into training, validation, and testing sets, in order for cross-participant models to avoid overestimation of model accuracy. Despite this necessity, the majority of EEG-based cross-participant models have not adopted such guidelines. Furthermore, some data repositories may unwittingly contribute to the problem by providing partitioned test and non-test datasets for reasons such as competition support. In this study, we demonstrate how improper dataset partitioning and the resulting improper training, validation, and testing of a cross-participant model leads to overestimated model accuracy. We demonstrate this mathematically, and empirically, using five publicly available datasets. To build the cross-participant models for these datasets, we replicate published results and demonstrate how the model accuracies are significantly reduced when proper EEG cross-participant model guidelines are followed. Our empirical results show that by not following these guidelines, error rates of cross-participant models can be underestimated between 35% and 3900%. This misrepresentation of model performance for the general population potentially slows scientific progress toward truly high-performing classification models.
Evaluating digital interventions using remote methods enables the recruitment of large numbers of participants relatively conveniently and cheaply compared with in-person methods. However, conducting ...research remotely based on participant self-report with little verification is open to automated “bots” and participant deception. This paper uses a case study of a remotely conducted trial of an alcohol reduction app to highlight and discuss (1) the issues with participant deception affecting remote research trials with financial compensation; and (2) the importance of rigorous data management to detect and address these issues. We recruited participants on the internet from July 2020 to March 2022 for a randomized controlled trial (n=5602) evaluating the effectiveness of an alcohol reduction app, Drink Less. Follow-up occurred at 3 time points, with financial compensation offered (up to £36 US $39.23). Address authentication and telephone verification were used to detect 2 kinds of deception: “bots,” that is, automated responses generated in clusters; and manual participant deception, that is, participants providing false information. Of the 1142 participants who enrolled in the first 2 months of recruitment, 75.6% (n=863) of them were identified as bots during data screening. As a result, a CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) was added, and after this, no more bots were identified. Manual participant deception occurred throughout the study. Of the 5956 participants (excluding bots) who enrolled in the study, 298 (5%) were identified as false participants. The extent of this decreased from 110 in November 2020, to a negligible level by February 2022 including a number of months with 0. The decline occurred after we added further screening questions such as attention checks, removed the prominence of financial compensation from social media advertising, and added an additional requirement to provide a mobile phone number for identity verification. Data management protocols are necessary to detect automated bots and manual participant deception in remotely conducted trials. Bots and manual deception can be minimized by adding a CAPTCHA, attention checks, a requirement to provide a phone number for identity verification, and not prominently advertising financial compensation on social media.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Linear mixed-effects models (LMMs) are increasingly being used for data analysis in cognitive neuroscience and experimental psychology, where within-participant designs are common. The current ...article provides an introductory review of the use of LMMs for within-participant data analysis and describes a free, simple, graphical user interface (LMMgui). LMMgui uses the package lme4 (Bates et al., 2014a,b) in the statistical environment R (R Core Team).
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