東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ null ]

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Potential Vulnerability to Mental Health Consequences Related to Income Loss from Any Cause among Older Populations in New Jersey (NJ) and Pennsylvania (PA): Outlook on COVID-19-Related Income Loss.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Potential Vulnerability to Mental Health Consequences Related to Income Loss from Any Cause among Older Populations in New Jersey (NJ) and Pennsylvania (PA): Outlook on COVID-19-Related Income Loss./
作者:	Ezenwafor, Edward, II.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	50 p.
附註:	Source: Masters Abstracts International, Volume: 82-12.
Contained By:	Masters Abstracts International82-12.
標題:	Mental health. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28543124
ISBN:	9798516069604

Potential Vulnerability to Mental Health Consequences Related to Income Loss from Any Cause among Older Populations in New Jersey (NJ) and Pennsylvania (PA): Outlook on COVID-19-Related Income Loss.
Ezenwafor, Edward, II.

Potential Vulnerability to Mental Health Consequences Related to Income Loss from Any Cause among Older Populations in New Jersey (NJ) and Pennsylvania (PA): Outlook on COVID-19-Related Income Loss. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 50 p.

Source: Masters Abstracts International, Volume: 82-12.

Thesis (M.S.)--Icahn School of Medicine at Mount Sinai, 2021.

This item must not be sold to any third party vendors.

Background: Sub-optimal mental health prevalence may worsen in the United States (US) during major adverse social and economic events due to intersection of underlying factors. Methods: The study was a cross-sectional quantitative analysis of 2018 BRFSS data with complex sampling procedures for weighted analyses to account for potential bias from varying probabilities of selection, non-independence and noncoverage among segments of the population. Results: The study identified a statistically significant association of demographic factors with suboptimal mental health in two states in the US and equally statistically significant impact of their intersection. Conclusions: This project provided empirical evidence for the need to pay higher attention to intersection of factors that impact mental health, especially during major adverse events.

ISBN: 9798516069604Subjects--Topical Terms:

534751
Mental health.
Subjects--Index Terms:

COVID-19

Potential Vulnerability to Mental Health Consequences Related to Income Loss from Any Cause among Older Populations in New Jersey (NJ) and Pennsylvania (PA): Outlook on COVID-19-Related Income Loss.
LDR:02142nmm a2200385 4500 001 2344726
005 20220531065742.5
008 241004s2021 ||||||||||||||||| ||eng d
020 $a 9798516069604
035 $a (MiAaPQ)AAI28543124
035 $a AAI28543124
040 $a MiAaPQ $c MiAaPQ
100 1 $a Ezenwafor, Edward, II. $0 (orcid)0000-0001-6872-1443 $3 3683529
245 1 0 $a Potential Vulnerability to Mental Health Consequences Related to Income Loss from Any Cause among Older Populations in New Jersey (NJ) and Pennsylvania (PA): Outlook on COVID-19-Related Income Loss.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 50 p.
500 $a Source: Masters Abstracts International, Volume: 82-12.
500 $a Advisor: Sacks, Henry.
502 $a Thesis (M.S.)--Icahn School of Medicine at Mount Sinai, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a Background: Sub-optimal mental health prevalence may worsen in the United States (US) during major adverse social and economic events due to intersection of underlying factors. Methods: The study was a cross-sectional quantitative analysis of 2018 BRFSS data with complex sampling procedures for weighted analyses to account for potential bias from varying probabilities of selection, non-independence and noncoverage among segments of the population. Results: The study identified a statistically significant association of demographic factors with suboptimal mental health in two states in the US and equally statistically significant impact of their intersection. Conclusions: This project provided empirical evidence for the need to pay higher attention to intersection of factors that impact mental health, especially during major adverse events.
590 $a School code: 1734.
650 4 $a Mental health. $3 534751
650 4 $a Public health. $3 534748
650 4 $a Biostatistics. $3 1002712
650 4 $a COVID-19. $3 3554449
653 $a COVID-19
653 $a Income loss
653 $a Intersectionality
653 $a Major adverse events
653 $a Mental health
653 $a Social support
690 $a 0347
690 $a 0573
690 $a 0308
710 2 $a Icahn School of Medicine at Mount Sinai. $b Clinical Research. $3 3181218
773 0 $t Masters Abstracts International $g 82-12.
790 $a 1734
791 $a M.S.
792 $a 2021
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28543124