scholarly journals Copeptin response to acute physical stress during hypohydration: An exploratory secondary analysis

2021 ◽  
Author(s):  
Harriet Amy Carroll ◽  
Olle Melander

Purpose: Plasma copeptin (a surrogate marker of arginine vasopressin) is increasingly being used as a marker of stress in several research and clinical contexts. However, the response to an acute physical stressor in healthy adults has not yet been tested meaning it is unclear whether copeptin reflects dynamic changes in stress or whether this is moderated by different basal copeptin concentrations and how this relates to other stress hormones. Methods: Secondary data analysis in a subsample of participants (n = 7; n = 1 woman) who opted-in for muscle biopsies in a randomised crossover study investigating the effects of acute hypohydration (HYPO) versus rehydration (RE) on metabolism. Results: Plasma copeptin responded to the muscle biopsy stress stimulus, with a similar magnitude of difference according to basal concentrations during HYPO and RE; however, the peak was higher and concentrations typically took longer to return to baseline during HYPO. Despite large differences in copeptin concentrations, adrenocorticotropin hormone (ACTH) and cortisol showed a similar trends in response to the biopsies, regardless of hydration status. Conclusion: Copeptin responded dynamically to an acute physical stressor (muscle biopsy). HYPO induced higher basal copeptin concentrations compared to RE, and resulted in a higher and prolonged copeptin response. Further research should investigate the mechanisms underlying the lack of differences in ACTH and cortisol according to hydration status.

2018 ◽  
Vol 50 (3) ◽  
pp. 322-331 ◽  
Author(s):  
Leanne Bowler ◽  
Heidi Julien ◽  
Leslie Haddon

This paper examines issues associated with secondary analysis of qualitative data and their implications for information behaviour scholarship. Secondary data analysis poses a range of potential challenges for data creators, but also opportunities, including the ability to expand theory to a wider context, strengthen the reliability and validity of existing theory, gain access to populations that may be difficult to access, and to promote data archiving. The paper uses as a case study of secondary data analysis the results from our re-examination of data gathered previously in the European Union project Net Children Go Mobile, drawing from the interview transcripts from the 34 children in the UK data set. Our approach to secondary analysis was reanalysis, applying a new interpretive lens to the data that necessitated new questions in order to reveal hidden layers in the data. The data was analysed for evidence of information behaviour in order to understand how mobile technologies may be changing the way that young people seek and use information. The reanalysis of the data set supported existing models of information behaviour but revealed new ways of information seeking based on the affordances of screen size and data plans.


2020 ◽  
pp. 1357633X2097200
Author(s):  
Hsiu-Hsin Tsai ◽  
Ching-Yu Cheng ◽  
Wann-Yun Shieh

Introduction The worldwide coronavirus disease 2019 pandemic re-emphasises the importance of Internet videoconferencing in supporting interactions between nursing home residents and their family and friends. However, there is a scarcity of comparative studies on how modalities of conferencing programs impact health outcomes. The purpose of this study was to compare laptop-based with smartphone-based videoconferencing programs on nursing home residents’ perceptions of loneliness, depressive symptoms and social support. Methods This retrospective secondary analysis used data from two previous studies on the effectiveness of videoconferencing programs (laptop-based and smartphone-based) to improve outcomes of loneliness, depressive symptoms and social support (type and source) among nursing home residents. Generalised estimating equations compared differences from baseline measures with measures at 1 and 3 months between the two groups with and without adjusting for the effects of confounding variables. Results With the exception of age, there were no differences in demographics between participants in the laptop and smartphone groups. Neither changes from baseline in mean scores for loneliness nor depressive symptoms differed between groups. However, changes in mean scores from baseline between groups were significantly greater in the smartphone-based group compared with the laptop-based group for three types of social support: informational and appraisal at 1 and 3 months; and emotional at 3 months. Changes from baseline in mean scores for social support from friends (at 1 and 3 months) and other sources (at 3 months) were also significantly greater for the smartphone group compared with the laptop group. Discussion The two modalities of videoconferencing did not differ in effects on depressive symptoms or loneliness. However, smartphones had a greater effect on the type and source of social support compared with laptops. Whether the small screen of a smartphone reduces users’ anxiety and allows them to talk more on screen is worth studying.


2017 ◽  
Vol 18 (1) ◽  
pp. 81-97 ◽  
Author(s):  
Nicole Ruggiano ◽  
Tam E Perry

While secondary data analysis of quantitative data has become commonplace and encouraged across disciplines, the practice of secondary data analysis with qualitative data has met more criticism and concerns regarding potential methodological and ethical problems. Though commentary about qualitative secondary data analysis has increased, little is known about the current state of qualitative secondary data analysis or how researchers are conducting secondary data analysis with qualitative data. This critical interpretive synthesis examined research articles (n = 71) published between 2006 and 2016 that involved qualitative secondary data analysis and assessed the context, purpose, and methodologies that were reported. Implications of findings are discussed, with particular focus on recommended guidelines and best practices of conducting qualitative secondary data analysis.


2021 ◽  
Author(s):  
Ayush Raman

Secondary data analysis refers to re-analyzing publicly available datasets to investigate the questions that original scientists had not posited. This helps in scientific progress by paving the path to more reliable and robust analyses and new research directions without any considerable expense. However, these datasets are anything but perfect, and researchers must investigate and assess the signal to noise ratio robustly to extract meaningful information. These efforts of rigorous secondary analysis are further recognized and supported by the Research Parasite Awards. As the 2020 Junior Research Parasite Award recipient, I share my journey and perspective of a research parasite in this commentary article.


2020 ◽  
Author(s):  
Sally Y Xie ◽  
Eric Hehman

This preregistration is part of the PSA secondary analysis challenge. We investigate how the facial 'trait space' shifts across countries and world regions, using the PSA_001 dataset shared by the Psychological Science Accelerator. The facial trait space refers to the interrelationships between many of the trait impressions that people infer from faces. Here, we examine whether this trait space is more homogeneous (or less differentiated) in some cultures than others.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tara Rava Zolnikov ◽  
Michael Hammel ◽  
Frances Furio ◽  
Brandon Eggleston

Purpose Dual diagnosis is a term that describes the co-occurrence of mental health disorders or illness and substance use or abuse disorders. Because this co-occurrence results in multiple diseases, layers of treatment are often needed to successfully create positive change in the individual. The purpose of this study is to explore factors of treatment that could facilitate improvements in functionality and quality of life for those with a dual diagnosis. Design/methodology/approach A secondary data analysis, using both quantitative and qualitative data, was completed. Secondary analysis is an empirical exercise that applies the same basic research principles as studies using primary data and has steps to be followed, including the evaluative and procedural steps commonly associated with secondary data analysis. Documentation data from the intensive mobile psychosocial assertive community treatment program was gathered for this analysis; this program was used because of the intensive and community-based services provided to patients with a dual diagnosis. Findings The major findings from this secondary analysis suggested that significant barriers included “denial” (e.g. evasion, suspension or avoidance of internal awareness) of diagnoses, complicated treatment and other barriers related to housing. Ultimately, these findings provided greater insight into potential effective treatment interventions for people living with a dual diagnosis. Originality/value This study adds to the growing body of literature showing that patient-centered care allows for more effective treatment and ultimately, improved health outcomes.


2020 ◽  
pp. 174239532094961
Author(s):  
Haley Feller ◽  
Nancy Baker

Objectives The purpose of this study is to describe the prevalence of leisure activities in adults ages 50 and over and to examine if pain changes that prevalence. Methods We completed a secondary analysis using data from the 2014 Health and Retirement Study Leave-Behind Questionnaire (n = 7,541) to analyze frequency and 95% confidence intervals of leisure participation and its relationship to pain. Results The majority of respondents reported regular participation in half of the 10 leisure activities analyzed. Watching television (98.0%) and using the computer (64.5%) had the highest reported regular participation, while volunteering and attending a club or meeting warranted less than 10% regular participation. Of the 7,541 respondents, 39.1% reported pain. For those with pain, regular participation was significantly lower than those without pain in five leisure activities, with exercise having the greatest difference. Discussion The results of our secondary data analysis indicate that older adults may not be regularly participating in different types of leisure activities and that they more regularly participate in passive activities, such as watching television. Older adults with pain have significantly lower reported rates of participation in leisure activities than those without pain, especially in relation to exercise.


2020 ◽  
Vol 29 (5) ◽  
pp. 279-284
Author(s):  
Siobhan O’Connor

This editorial provides an overview of secondary data analysis in nursing science and its application in a range of contemporary research. The practice of undertaking secondary analysis of qualitative and quantitative data is also discussed, along with the benefits, risks and limitations of this analytical method.


2009 ◽  
Vol 23 (3) ◽  
pp. 203-215 ◽  
Author(s):  
Daniel M. Doolan ◽  
Erika S. Froelicher

The vast majority of the research methods literature assumes that the researcher designs the study subsequent to determining research questions. This assumption is not met for the many researchers involved in secondary data analysis. Researchers doing secondary data analysis need not only understand research concepts related to designing a new study, but additionally must be aware of challenges specific to conducting research using an existing data set. Techniques are discussed to determine if secondary data analysis is appropriate. Suggestions are offered on how to best identify, obtain, and evaluate a data set; refine research questions; manage data; calculate power; and report results. Examples from nursing research are provided. If an existing data set is suitable for answering a new research question, then a secondary analysis is preferable since it can be completed in less time, for less money, and with far lower risks to subjects. The researcher must carefully consider if the existing data set’s available power and data quality are adequate to answer the proposed research questions.


2018 ◽  
Vol 16 (1) ◽  
pp. 1
Author(s):  
Ria Manurung

Research conducted to obtain empirical evidence how the influence of independent variables of intellectual intelligence to accounting with moderating variables of emotional and spiritual intelligence. The research method used is descriptive quantitative with explanatory descriptive or explanatory research. This method is an explanatory research that proves the existence of causal relationship of independent variable (independent variable) that is intellectual intelligence; moderating variable (emotional and spiritual intelligence); and dependent variable (accounted dependent variable). Research begins by conducting library search, followed by primary data collection conducted by using questionnaires and secondary data through data analysis. And for the use of data analysis consists of descriptive analysis, classical assumption test and verification analysis with the method of Moderated Regression Analysis (MRA). This study is a census study with homogeneous and limited population of 92 students, all students of Accounting Graduate Program at UNSOED. Conclusion of research result that is: (1) Intellectual intelligence have influence either positively or signifikan to accountancy. Thus intellectual intelligence can lead students to more easily understand accounting, (2) Intellectual intelligence can be strengthened by emotional intelligence on accounting both positively and significantly. (3) Spiritual intelligence can strengthen the influence of intellectual intelligence on accounting both positively and significantly.


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