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10.1111/aphw.12284 http://scihub22266oqcxt.onion/10.1111/aphw.12284 34032383!8239601!34032383     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Appl+Psychol+Health+Well+Being 2021 ; 13 (4): 968-985 Nephropedia Template TP {{tp|p=34032383|t=2021. Adhering to COVID-19 health guidelines: Examining demographic and psychological predictors of adherence |pdf=|usr=}}{{34032383}} gab.com Text Adhering to COVID-19 health guidelines: Examining demographic and psychological predictors of adherence JO: Appl Psychol Health Well Being http://www.kidney.de/pget.php?&tw=1&pmid=34032383 #FOAvip The effort to limit the spread of the coronavirus (COVID-19) has relied heavily on the general public's compliance with health guidelines limiting social contact and mitigating risk when contact occurs. The aim of this study was to identify latent variables underlying adherence to COVID-19 guidelines and to examine demographic and psychological predictors of adherence. A sample of US adults (N = 1,200) were surveyed in late April to mid-May 2020. The factor structure of adherence was examined using exploratory factor analysis. Machine learning regression models using elastic net regularization were used to examine predictors of adherence. Two factors characterized adherence: avoidance and cleaning. Elastic net models identified differential demographic and psychological predictors of these two forms of adherence. Religious affiliation, denial coping, full-time employment, substance use coping, and being 60 or older predicted lower avoidance adherence. Behavioral and mindfulness emotion regulation skills, agreeableness, and Democrat political affiliation predicted greater avoidance adherence. For cleaning adherence, interpersonal and behavioral emotion regulation skills and conscientiousness emerged as strong predictors of greater cleaning. Efforts to promote compliance with COVID-19 health guidelines may benefit from distinguishing avoidance and cleaning adherence and considering predictors of each of these aspects of adherence. Twit Text FOAVip Adhering to COVID-19 health guidelines: Examining demographic and psychological predictors of adherence ????Appl Psychol Health Well Being http://www.kidney.de/pget.php?&tw=1&pmid=34032383 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34032383 #FOAvip English Wikipedia <ref>{{Cite pmid|34032383}}</ref> Adhering to COVID-19 health guidelines: Examining demographic and psychological predictors of adherence #MMPMID34032383 Bailey B; Whelen ML; Strunk DR Appl Psychol Health Well Being 2021[Nov]; 13 (4): 968-985 PMID34032383show ga The effort to limit the spread of the coronavirus (COVID-19) has relied heavily on the general public's compliance with health guidelines limiting social contact and mitigating risk when contact occurs. The aim of this study was to identify latent variables underlying adherence to COVID-19 guidelines and to examine demographic and psychological predictors of adherence. A sample of US adults (N = 1,200) were surveyed in late April to mid-May 2020. The factor structure of adherence was examined using exploratory factor analysis. Machine learning regression models using elastic net regularization were used to examine predictors of adherence. Two factors characterized adherence: avoidance and cleaning. Elastic net models identified differential demographic and psychological predictors of these two forms of adherence. Religious affiliation, denial coping, full-time employment, substance use coping, and being 60 or older predicted lower avoidance adherence. Behavioral and mindfulness emotion regulation skills, agreeableness, and Democrat political affiliation predicted greater avoidance adherence. For cleaning adherence, interpersonal and behavioral emotion regulation skills and conscientiousness emerged as strong predictors of greater cleaning. Efforts to promote compliance with COVID-19 health guidelines may benefit from distinguishing avoidance and cleaning adherence and considering predictors of each of these aspects of adherence. |*COVID-19[MESH] |Adaptation, Psychological[MESH] |Adult[MESH] |Demography[MESH] |Guideline Adherence[MESH] |Humans[MESH]Adhering to COVID-19 health guidelines: Examining demographic and psyc(epmc).pdf DeepDyve Pubget Overpricing