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Article: Deep brain imaging of three participants across 1 year: The Bergen breakfast scanning club project.

Wang, Meng-Yun / Korbmacher, Max / Eikeland, Rune / Specht, Karsten

2022 Volume 16, Page(s) 1021503

Abstract: Our understanding of the cognitive functions of the human brain has tremendously benefited from the population functional Magnetic Resonance Imaging (fMRI) studies in the last three decades. The reliability and replicability of the fMRI results, however, ...

Abstract	Our understanding of the cognitive functions of the human brain has tremendously benefited from the population functional Magnetic Resonance Imaging (fMRI) studies in the last three decades. The reliability and replicability of the fMRI results, however, have been recently questioned, which has been named the replication crisis. Sufficient statistical power is fundamental to alleviate the crisis, by either "going big," leveraging big datasets, or by "going small," densely scanning several participants. Here we reported a "going small" project implemented in our department, the Bergen breakfast scanning club (BBSC) project, in which three participants were intensively scanned across a year. It is expected this kind of new data collection method can provide novel insights into the variability of brain networks, facilitate research designs and inference, and ultimately lead to the improvement of the reliability of the fMRI results.
Language	English
Publishing date	2022-10-17
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2425477-0
ISSN	1662-5161
ISSN	1662-5161
DOI	10.3389/fnhum.2022.1021503
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Article ; Online: The intra-individual reliability of

Wang, Meng-Yun / Korbmacher, Max / Eikeland, Rune / Craven, Alexander R / Specht, Karsten

Human brain mapping

2023 Volume 45, Issue 1, Page(s) e26531

Abstract: Magnetic resonance spectroscopy (MRS) is the primary method that can measure the levels of metabolites in the brain in vivo. To achieve its potential in clinical usage, the reliability of the measurement requires further articulation. Although there are ... ...

Abstract	Magnetic resonance spectroscopy (MRS) is the primary method that can measure the levels of metabolites in the brain in vivo. To achieve its potential in clinical usage, the reliability of the measurement requires further articulation. Although there are many studies that investigate the reliability of gamma-aminobutyric acid (GABA), comparatively few studies have investigated the reliability of other brain metabolites, such as glutamate (Glu), N-acetyl-aspartate (NAA), creatine (Cr), phosphocreatine (PCr), or myo-inositol (mI), which all play a significant role in brain development and functions. In addition, previous studies which predominately used only two measurements (two data points) failed to provide the details of the time effect (e.g., time-of-day) on MRS measurement within subjects. Therefore, in this study, MRS data located in the anterior cingulate cortex (ACC) were repeatedly recorded across 1 year leading to at least 25 sessions for each subject with the aim of exploring the variability of other metabolites by using the index coefficient of variability (CV); the smaller the CV, the more reliable the measurements. We found that the metabolites of NAA, tNAA, and tCr showed the smallest CVs (between 1.43% and 4.90%), and the metabolites of Glu, Glx, mI, and tCho showed modest CVs (between 4.26% and 7.89%). Furthermore, we found that the concentration reference of the ratio to water results in smaller CVs compared to the ratio to tCr. In addition, we did not find any time-of-day effect on the MRS measurements. Collectively, the results of this study indicate that the MRS measurement is reasonably reliable in quantifying the levels of metabolites.
MeSH term(s)	Humans ; Gyrus Cinguli/diagnostic imaging ; Gyrus Cinguli/metabolism ; Reproducibility of Results ; Magnetic Resonance Spectroscopy/methods ; Brain/diagnostic imaging ; Brain/metabolism ; Glutamic Acid/metabolism ; Creatine/metabolism ; Inositol/metabolism ; Receptors, Antigen, T-Cell/metabolism ; Aspartic Acid/metabolism ; Proton Magnetic Resonance Spectroscopy ; Choline/metabolism
Chemical Substances	Glutamic Acid (3KX376GY7L) ; Creatine (MU72812GK0) ; Inositol (4L6452S749) ; Receptors, Antigen, T-Cell ; Aspartic Acid (30KYC7MIAI) ; Choline (N91BDP6H0X)
Language	English
Publishing date	2023-11-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	1197207-5
ISSN	1097-0193 ; 1065-9471
ISSN (online)	1097-0193
ISSN	1065-9471
DOI	10.1002/hbm.26531
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Article ; Online: Brain asymmetries from mid- to late life and hemispheric brain age.

Korbmacher, Max / van der Meer, Dennis / Beck, Dani / de Lange, Ann-Marie G / Eikefjord, Eli / Lundervold, Arvid / Andreassen, Ole A / Westlye, Lars T / Maximov, Ivan I

Nature communications

2024 Volume 15, Issue 1, Page(s) 956

Abstract: The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI ... ...

Abstract	The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI data in N=48,040 UK Biobank participants to evaluate age-related differences in brain asymmetry. Most regional grey and white matter metrics presented asymmetry, which were higher later in life. Informed by these results, we conducted hemispheric brain age (HBA) predictions from left/right multimodal MRI metrics. HBA was concordant to conventional brain age predictions, using metrics from both hemispheres, but offers a supplemental general marker of brain asymmetry when setting left/right HBA into relationship with each other. In contrast to WM brain asymmetries, left/right discrepancies in HBA are lower at higher ages. Our findings outline various sex-specific differences, particularly important for brain age estimates, and the value of further investigating the role of brain asymmetries in brain ageing and disease development.
MeSH term(s)	Male ; Female ; Humans ; Functional Laterality ; Brain/diagnostic imaging ; Brain/pathology ; Magnetic Resonance Imaging/methods ; Diffusion Magnetic Resonance Imaging ; White Matter/diagnostic imaging ; White Matter/pathology
Language	English
Publishing date	2024-02-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-024-45282-3
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Article: Bio-psycho-social factors' associations with brain age: a large-scale UK Biobank diffusion study of 35,749 participants.

Korbmacher, Max / Gurholt, Tiril P / de Lange, Ann-Marie G / van der Meer, Dennis / Beck, Dani / Eikefjord, Eli / Lundervold, Arvid / Andreassen, Ole A / Westlye, Lars T / Maximov, Ivan I

Frontiers in psychology

2023 Volume 14, Page(s) 1117732

Abstract: Brain age refers to age predicted by brain features. Brain age has previously been associated with various health and disease outcomes and suggested as a potential biomarker of general health. Few previous studies have systematically assessed brain age ... ...

Abstract	Brain age refers to age predicted by brain features. Brain age has previously been associated with various health and disease outcomes and suggested as a potential biomarker of general health. Few previous studies have systematically assessed brain age variability derived from single and multi-shell diffusion magnetic resonance imaging data. Here, we present multivariate models of brain age derived from various diffusion approaches and how they relate to bio-psycho-social variables within the domains of sociodemographic, cognitive, life-satisfaction, as well as health and lifestyle factors in midlife to old age (
Language	English
Publishing date	2023-06-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2563826-9
ISSN	1664-1078
ISSN	1664-1078
DOI	10.3389/fpsyg.2023.1117732
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Article ; Online: Brain-wide associations between white matter and age highlight the role of fornix microstructure in brain ageing.

Korbmacher, Max / de Lange, Ann Marie / van der Meer, Dennis / Beck, Dani / Eikefjord, Eli / Lundervold, Arvid / Andreassen, Ole A / Westlye, Lars T / Maximov, Ivan I

Human brain mapping

2023 Volume 44, Issue 10, Page(s) 4101–4119

Abstract: Unveiling the details of white matter (WM) maturation throughout ageing is a fundamental question for understanding the ageing brain. In an extensive comparison of brain age predictions and age-associations of WM features from different diffusion ... ...

Abstract	Unveiling the details of white matter (WM) maturation throughout ageing is a fundamental question for understanding the ageing brain. In an extensive comparison of brain age predictions and age-associations of WM features from different diffusion approaches, we analyzed UK Biobank diffusion magnetic resonance imaging (dMRI) data across midlife and older age (N = 35,749, 44.6-82.8 years of age). Conventional and advanced dMRI approaches were consistent in predicting brain age. WM-age associations indicate a steady microstructure degeneration with increasing age from midlife to older ages. Brain age was estimated best when combining diffusion approaches, showing different aspects of WM contributing to brain age. Fornix was found as the central region for brain age predictions across diffusion approaches in complement to forceps minor as another important region. These regions exhibited a general pattern of positive associations with age for intra axonal water fractions, axial, radial diffusivities, and negative relationships with age for mean diffusivities, fractional anisotropy, kurtosis. We encourage the application of multiple dMRI approaches for detailed insights into WM, and the further investigation of fornix and forceps as potential biomarkers of brain age and ageing.
MeSH term(s)	Humans ; White Matter/diagnostic imaging ; White Matter/pathology ; Brain/diagnostic imaging ; Brain/pathology ; Diffusion Magnetic Resonance Imaging/methods ; Aging ; Corpus Callosum
Language	English
Publishing date	2023-05-17
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1197207-5
ISSN	1097-0193 ; 1065-9471
ISSN (online)	1097-0193
ISSN	1065-9471
DOI	10.1002/hbm.26333
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Article ; Online: Considerations on brain age predictions from repeatedly sampled data across time.

Korbmacher, Max / Wang, Meng-Yun / Eikeland, Rune / Buchert, Ralph / Andreassen, Ole A / Espeseth, Thomas / Leonardsen, Esten / Westlye, Lars T / Maximov, Ivan I / Specht, Karsten

Brain and behavior

2023 Volume 13, Issue 10, Page(s) e3219

Abstract: Introduction: Brain age, the estimation of a person's age from magnetic resonance imaging (MRI) parameters, has been used as a general indicator of health. The marker requires however further validation for application in clinical contexts. Here, we ... ...

Abstract	Introduction: Brain age, the estimation of a person's age from magnetic resonance imaging (MRI) parameters, has been used as a general indicator of health. The marker requires however further validation for application in clinical contexts. Here, we show how brain age predictions perform for the same individual at various time points and validate our findings with age-matched healthy controls. Methods: We used densely sampled T1-weighted MRI data from four individuals (from two densely sampled datasets) to observe how brain age corresponds to age and is influenced by acquisition and quality parameters. For validation, we used two cross-sectional datasets. Brain age was predicted by a pretrained deep learning model. Results: We found small within-subject correlations between age and brain age. We also found evidence for the influence of field strength on brain age which replicated in the cross-sectional validation data and inconclusive effects of scan quality. Conclusion: The absence of maturation effects for the age range in the presented sample, brain age model bias (including training age distribution and field strength), and model error are potential reasons for small relationships between age and brain age in densely sampled longitudinal data. Clinical applications of brain age models should consider of the possibility of apparent biases caused by variation in the data acquisition process.
Language	English
Publishing date	2023-08-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	2623587-0
ISSN	2162-3279 ; 2162-3279
ISSN (online)	2162-3279
ISSN	2162-3279
DOI	10.1002/brb3.3219
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Article ; Online: Dissecting unique and common variance across body and brain health indicators using age prediction.

Beck, Dani / de Lange, Ann-Marie G / Gurholt, Tiril P / Voldsbekk, Irene / Maximov, Ivan I / Subramaniapillai, Sivaniya / Schindler, Louise / Hindley, Guy / Leonardsen, Esten H / Rahman, Zillur / van der Meer, Dennis / Korbmacher, Max / Linge, Jennifer / Leinhard, Olof D / Kalleberg, Karl T / Engvig, Andreas / Sønderby, Ida / Andreassen, Ole A / Westlye, Lars T

Human brain mapping

2024 Volume 45, Issue 6, Page(s) e26685

Abstract: Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter- ... ...

Abstract	Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals.
MeSH term(s)	Humans ; Middle Aged ; Aged ; Adult ; Male ; Aging/physiology ; Female ; Aged, 80 and over ; Magnetic Resonance Imaging ; Machine Learning ; Brain/diagnostic imaging ; Brain/physiology ; Body Composition/physiology ; Gray Matter/diagnostic imaging ; Gray Matter/anatomy & histology ; White Matter/diagnostic imaging ; White Matter/anatomy & histology ; Bayes Theorem
Language	English
Publishing date	2024-05-01
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1197207-5
ISSN	1097-0193 ; 1065-9471
ISSN (online)	1097-0193
ISSN	1065-9471
DOI	10.1002/hbm.26685
Database	MEDical Literature Analysis and Retrieval System OnLINE

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ab Jg. 2022: Lesesaal (EG)

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Article ; Online: National income inequality predicts cultural variation in mouth to mouth kissing.

Watkins, Christopher D / Leongómez, Juan David / Bovet, Jeanne / Żelaźniewicz, Agnieszka / Korbmacher, Max / Varella, Marco Antônio Corrêa / Fernandez, Ana Maria / Wagstaff, Danielle / Bolgan, Samuela

Scientific reports

2019 Volume 9, Issue 1, Page(s) 6698

Abstract: Romantic mouth-to-mouth kissing is culturally widespread, although not a human universal, and may play a functional role in assessing partner health and maintaining long-term pair bonds. Use and appreciation of kissing may therefore vary according to ... ...

Abstract	Romantic mouth-to-mouth kissing is culturally widespread, although not a human universal, and may play a functional role in assessing partner health and maintaining long-term pair bonds. Use and appreciation of kissing may therefore vary according to whether the environment places a premium on good health and partner investment. Here, we test for cultural variation (13 countries from six continents) in these behaviours/attitudes according to national health (historical pathogen prevalence) and both absolute (GDP) and relative wealth (GINI). Our data reveal that kissing is valued more in established relationships than it is valued during courtship. Also, consistent with the pair bonding hypothesis of the function of romantic kissing, relative poverty (income inequality) predicts frequency of kissing across romantic relationships. When aggregated, the predicted relationship between income inequality and kissing frequency (r = 0.67, BCa 95% CI[0.32,0.89]) was over five times the size of the null correlations between income inequality and frequency of hugging/cuddling and sex. As social complexity requires monitoring resource competition among large groups and predicts kissing prevalence in remote societies, this gesture may be important in the maintenance of long-term pair bonds in specific environments.
MeSH term(s)	Cultural Characteristics ; Female ; Humans ; Income/statistics & numerical data ; Male ; Poverty ; Sexual Behavior/psychology ; Sexual Behavior/statistics & numerical data ; Sexual Partners/psychology ; Socioeconomic Factors
Language	English
Publishing date	2019-04-30
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-019-43267-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: The Psychological Science Accelerator's COVID-19 rapid-response dataset

Buchanan, Erin M. / Lewis, Savannah C. / Paris, Bastien / Forscher, Patrick S. / Pavlacic, Jeffrey M. / Beshears, Julie E. / Drexler, Shira Meir / Gourdon-Kanhukamwe, Amelie / Mallik, Peter R. / Silan, Miguel Alejandro A. / Miller, Jeremy K. / IJzerman, Hans / Moshontz, Hannah / Beaudry, Jennifer L. / Suchow, Jordan W. / Chartier, Christopher R. / Coles, Nicholas A. / Sharifian, MohammadHasan / Todsen, Anna Louise /

Levitan, Carmel A. / Azevedo, Flavio / Legate, Nicole / Heller, Blake / Rothman, Alexander J. / Dorison, Charles A. / Gill, Brian P. / Wang, Ke / Rees, Vaughan W. / Gibbs, Nancy / Goldenberg, Amit / Thi Nguyen, Thuy-vy / Gross, James J. / Kaminski, Gwenael / von Bastian, Claudia C. / Paruzel-Czachura, Mariola / Mosannenzadeh, Farnaz / Azouaghe, Soufian / Bran, Alexandre / Ruiz-Fernandez, Susana / Santos, Anabela Caetano / Reggev, Niv / Zickfeld, Janis H. / Akkas, Handan / Pantazi, Myrto / Ropovik, Ivan / Korbmacher, Max / Arriaga, Patricia / Gjoneska, Biljana / Warmelink, Lara / Alves, Sara G. / de Holanda Coelho, Gabriel Lins / Stieger,

Scientific Data

2023 Volume 10, Issue 1, Page(s) No

Abstract: In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral ... ...

Title translation	Der COVID-19-Schnellreaktionsdatensatz des Psychological Science Accelerator. (DeepL)
Abstract	In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.
Keywords	Bewältigungsverhalten ; COVID-19 ; Cognitive Appraisal ; Community Mitigation ; Coping Behavior ; Emotional Responses ; Emotionale Reaktionen ; Framing Effects ; Framing-Effekte ; Gesundheitsverhalten ; Health Behavior ; Kognitive Bewertung (Emotionspsychologie) ; Körperliche Distanzierung ; Pandemics ; Pandemie ; Physical Distancing ; Risikominderung (Gesundheitswesen) ; Selbstbestimmung ; Self-Determination
Language	English
Document type	Article
DOI	10.1038/s41597-022-01811-7
Database	PSYNDEX

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Article ; Online: The Psychological Science Accelerator's COVID-19 rapid-response dataset.

Buchanan, Erin M / Lewis, Savannah C / Paris, Bastien / Forscher, Patrick S / Pavlacic, Jeffrey M / Beshears, Julie E / Drexler, Shira Meir / Gourdon-Kanhukamwe, Amélie / Mallik, Peter R / Silan, Miguel Alejandro A / Miller, Jeremy K / IJzerman, Hans / Moshontz, Hannah / Beaudry, Jennifer L / Suchow, Jordan W / Chartier, Christopher R / Coles, Nicholas A / Sharifian, MohammadHasan / Todsen, Anna Louise /

Levitan, Carmel A / Azevedo, Flávio / Legate, Nicole / Heller, Blake / Rothman, Alexander J / Dorison, Charles A / Gill, Brian P / Wang, Ke / Rees, Vaughan W / Gibbs, Nancy / Goldenberg, Amit / Thi Nguyen, Thuy-Vy / Gross, James J / Kaminski, Gwenaêl / von Bastian, Claudia C / Paruzel-Czachura, Mariola / Mosannenzadeh, Farnaz / Azouaghe, Soufian / Bran, Alexandre / Ruiz-Fernandez, Susana / Santos, Anabela Caetano / Reggev, Niv / Zickfeld, Janis H / Akkas, Handan / Pantazi, Myrto / Ropovik, Ivan / Korbmacher, Max / Arriaga, Patrícia / Gjoneska, Biljana / Warmelink, Lara / Alves, Sara G / de Holanda Coelho, Gabriel Lins / Stieger, Stefan / Schei, Vidar / Hanel, Paul H P / Szaszi, Barnabas / Fedotov, Maksim / Antfolk, Jan / Marcu, Gabriela-Mariana / Schrötter, Jana / Kunst, Jonas R / Geiger, Sandra J / Adetula, Adeyemi / Kocalar, Halil Emre / Kielińska, Julita / Kačmár, Pavol / Bokkour, Ahmed / Galindo-Caballero, Oscar J / Djamai, Ikhlas / Pöntinen, Sara Johanna / Agesin, Bamikole Emmanuel / Jernsäther, Teodor / Urooj, Anum / Rachev, Nikolay R / Koptjevskaja-Tamm, Maria / Kurfalı, Murathan / Pit, Ilse L / Li, Ranran / Çoksan, Sami / Dubrov, Dmitrii / Paltrow, Tamar Elise / Baník, Gabriel / Korobova, Tatiana / Studzinska, Anna / Jiang, Xiaoming / Aruta, John Jamir Benzon R / Vintr, Jáchym / Chiu, Faith / Kaliska, Lada / Berkessel, Jana B / Tümer, Murat / Morales-Izquierdo, Sara / Chuan-Peng, Hu / Vezirian, Kevin / Rosa, Anna Dalla / Bialobrzeska, Olga / Vasilev, Martin R / Beitner, Julia / Kácha, Ondřej / Žuro, Barbara / Westerlund, Minja / Nedelcheva-Datsova, Mina / Findor, Andrej / Krupić, Dajana / Kowal, Marta / Askelund, Adrian Dahl / Pourafshari, Razieh / Đorđević, Jasna Milošević / Schmidt, Nadya-Daniela / Baklanova, Ekaterina / Szala, Anna / Zakharov, Ilya / Vranka, Marek A / Ihaya, Keiko / Grano, Caterina / Cellini, Nicola / Białek, Michał / Anton-Boicuk, Lisa / Dalgar, Ilker / Adıgüzel, Arca / Verharen, Jeroen P H / Maturan, Princess Lovella G / Kassianos, Angelos P / Oliveira, Raquel / Čadek, Martin / Adoric, Vera Cubela / Özdoğru, Asil Ali / Sverdrup, Therese E / Aczel, Balazs / Zambrano, Danilo / Ahmed, Afroja / Tamnes, Christian K / Yamada, Yuki / Volz, Leonhard / Sunami, Naoyuki / Suter, Lilian / Vieira, Luc / Groyecka-Bernard, Agata / Kamburidis, Julia Arhondis / Reips, Ulf-Dietrich / Harutyunyan, Mikayel / Adetula, Gabriel Agboola / Allred, Tara Bulut / Barzykowski, Krystian / Antazo, Benedict G / Zsido, Andras N / Šakan, Dušana Dušan / Cyrus-Lai, Wilson / Ahlgren, Lina Pernilla / Hruška, Matej / Vega, Diego / Manunta, Efisio / Mokady, Aviv / Capizzi, Mariagrazia / Martončik, Marcel / Say, Nicolas / Filip, Katarzyna / Vilar, Roosevelt / Staniaszek, Karolina / Vdovic, Milica / Adamkovic, Matus / Johannes, Niklas / Hajdu, Nandor / Cohen, Noga / Overkott, Clara / Krupić, Dino / Hubena, Barbora / Nilsonne, Gustav / Mioni, Giovanna / Solorzano, Claudio Singh / Ishii, Tatsunori / Chen, Zhang / Kushnir, Elizaveta / Karaarslan, Cemre / Ribeiro, Rafael R / Khaoudi, Ahmed / Kossowska, Małgorzata / Bavolar, Jozef / Hoyer, Karlijn / Roczniewska, Marta / Karababa, Alper / Becker, Maja / Monteiro, Renan P / Kunisato, Yoshihiko / Metin-Orta, Irem / Adamus, Sylwia / Kozma, Luca / Czarnek, Gabriela / Domurat, Artur / Štrukelj, Eva / Alvarez, Daniela Serrato / Parzuchowski, Michal / Massoni, Sébastien / Czamanski-Cohen, Johanna / Pronizius, Ekaterina / Muchembled, Fany / van Schie, Kevin / Saçaklı, Aslı / Hristova, Evgeniya / Kuzminska, Anna O / Charyate, Abdelilah / Bijlstra, Gijsbert / Afhami, Reza / Majeed, Nadyanna M / Musser, Erica D / Sirota, Miroslav / Ross, Robert M / Yeung, Siu Kit / Papadatou-Pastou, Marietta / Foroni, Francesco / Almeida, Inês A T / Grigoryev, Dmitry / Lewis, David M G / Holford, Dawn L / Janssen, Steve M J / Tatachari, Srinivasan / Batres, Carlota / Olofsson, Jonas K / Daches, Shimrit / Belaus, Anabel / Pfuhl, Gerit / Corral-Frias, Nadia Sarai / Sousa, Daniela / Röer, Jan Philipp / Isager, Peder Mortvedt / Godbersen, Hendrik / Walczak, Radoslaw B / Van Doren, Natalia / Ren, Dongning / Gill, Tripat / Voracek, Martin / DeBruine, Lisa M / Anne, Michele / Očovaj, Sanja Batić / Thomas, Andrew G / Arvanitis, Alexios / Ostermann, Thomas / Wolfe, Kelly / Arinze, Nwadiogo Chisom / Bundt, Carsten / Lamm, Claus / Calin-Jageman, Robert J / Davis, William E / Karekla, Maria / Zorjan, Saša / Jaremka, Lisa M / Uttley, Jim / Hricova, Monika / Koehn, Monica A / Kiselnikova, Natalia / Bai, Hui / Krafnick, Anthony J / Balci, Busra Bahar / Ballantyne, Tonia / Lins, Samuel / Vally, Zahir / Esteban-Serna, Celia / Schmidt, Kathleen / Macapagal, Paulo Manuel L / Szwed, Paulina / Zdybek, Przemysław Marcin / Moreau, David / Collins, W Matthew / Joy-Gaba, Jennifer A / Vilares, Iris / Tran, Ulrich S / Boudesseul, Jordane / Albayrak-Aydemir, Nihan / Dixson, Barnaby James Wyld / Perillo, Jennifer T / Ferreira, Ana / Westgate, Erin C / Aberson, Christopher L / Arinze, Azuka Ikechukwu / Jaeger, Bastian / Butt, Muhammad Mussaffa / Silva, Jaime R / Storage, Daniel Shafik / Janak, Allison P / Jiménez-Leal, William / Soto, Jose A / Sorokowska, Agnieszka / McCarthy, Randy / Tullett, Alexa M / Frias-Armenta, Martha / Ribeiro, Matheus Fernando Felix / Hartanto, Andree / Forbes, Paul A G / Willis, Megan L / Del Carmen Tejada R, María / Torres, Adriana Julieth Olaya / Stephen, Ian D / Vaidis, David C / de la Rosa-Gómez, Anabel / Yu, Karen / Sutherland, Clare A M / Manavalan, Mathi / Behzadnia, Behzad / Urban, Jan / Baskin, Ernest / McFall, Joseph P / Ogbonnaya, Chisom Esther / Fu, Cynthia H Y / Rahal, Rima-Maria / Ndukaihe, Izuchukwu L G / Hostler, Thomas J / Kappes, Heather Barry / Sorokowski, Piotr / Khosla, Meetu / Lazarevic, Ljiljana B / Eudave, Luis / Vilsmeier, Johannes K / Luis, Elkin O / Muda, Rafał / Agadullina, Elena / Cárcamo, Rodrigo A / Reeck, Crystal / Anjum, Gulnaz / Venegas, Mónica Camila Toro / Misiak, Michal / Ryan, Richard M / Nock, Nora L / Travaglino, Giovanni A / 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Scientific data

2023 Volume 10, Issue 1, Page(s) 87

Abstract	In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.
MeSH term(s)	Humans ; Adaptation, Psychological ; COVID-19 ; Health Behavior ; Pandemics ; Surveys and Questionnaires
Language	English
Publishing date	2023-02-11
Publishing country	England
Document type	Dataset ; Journal Article
ZDB-ID	2775191-0
ISSN	2052-4463 ; 2052-4463
ISSN (online)	2052-4463
ISSN	2052-4463
DOI	10.1038/s41597-022-01811-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

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