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  1. Article: Statewide Survey of Psychological Distress Among People of Tamil Nadu in the COVID-19 Pandemic.

    Ramasubramanian, Vikhram / Mohandoss, Anusa Arunachalam / Rajendhiran, Gopi / Pandian, P Raja Soundara / Ramasubramanian, C

    Indian journal of psychological medicine

    2020  Volume 42, Issue 4, Page(s) 368–373

    Abstract: ... through COVID-19 Peritraumatic Distress Index (CPDI). Binomial regression analysis was used to identify ... Background: COVID-19-driven pandemic has caused panic, fear, and stress among all strata ... in the state of Tamil Nadu (TN)-a state in the southern India where the levels of stress have not been ...

    Abstract Background: COVID-19-driven pandemic has caused panic, fear, and stress among all strata of society. The study aimed to assess stress and the factors that influence it in a representative population in the state of Tamil Nadu (TN)-a state in the southern India where the levels of stress have not been measured yet.
    Methods: From April 13 to April 25, 2020, we conducted an online survey among the TN population using the snowball sampling technique, collecting basic demographic data. COVID-19-perceived stress was collected through COVID-19 Peritraumatic Distress Index (CPDI). Binomial regression analysis was used to identify the extent of the relationship between CPDI and sociodemographic factors by estimating the odds of having significant stress. P ≤ 0.05 was considered significant.
    Results: A total of 2,317 valid responses were received. Of the respondents, 830 (35.82%) were males, 1,084 (46.79%) were below 25 years of age, and 2,297 (99.14%) were native residents of TN. The mean(±SD) CPDI was 20.66±12.03. While 1,830 (77.2%) respondents had low or no stress, 478 (20.2%) had mild to moderate stress, and 63 (2.7%) had severe stress. The bivariate model included marital status, age, nativity, and income. The odds of having significant stress (mild-moderate or severe) for a 25-34 year age group as compared to >55 years group was 2.38 (P < 0.001). As compared to widowed, the married had higher odds ratio (3.41, P = 0.05). Compared to those with >10 lakh annual income, those with 2.5-5 lakhs annual income had odds ratio of 1.65 (95% CI = 1.01 to 2.7, P = 0.05).
    Conclusions: During the lockdown due to COVID-19, every 1 in 5 TN population had some form of stress, as measured by CPDI. Our model identified certain factors driving the stress, which would help policy framers to initiate an appropriate response.
    Language English
    Publishing date 2020-07-06
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2622378-8
    ISSN 0975-1564 ; 0253-7176
    ISSN (online) 0975-1564
    ISSN 0253-7176
    DOI 10.1177/0253717620935581
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Statewide Survey of Psychological Distress Among People of Tamil Nadu in the COVID-19 Pandemic

    Ramasubramanian, Vikhram / Mohandoss, Anusa Arunachalam / Rajendhiran, Gopi / Pandian, P. Raja Soundara / Ramasubramanian, C.

    Indian Journal of Psychological Medicine

    2020  Volume 42, Issue 4, Page(s) 368–373

    Abstract: ... through COVID-19 Peritraumatic Distress Index (CPDI). Binomial regression analysis was used to identify ... Background: COVID-19-driven pandemic has caused panic, fear, and stress among all strata of society ... in the state of Tamil Nadu (TN)—a state in the southern India where the levels of stress have not been measured ...

    Abstract Background: COVID-19-driven pandemic has caused panic, fear, and stress among all strata of society. The study aimed to assess stress and the factors that influence it in a representative population in the state of Tamil Nadu (TN)—a state in the southern India where the levels of stress have not been measured yet. Methods: From April 13 to April 25, 2020, we conducted an online survey among the TN population using the snowball sampling technique, collecting basic demographic data. COVID-19-perceived stress was collected through COVID-19 Peritraumatic Distress Index (CPDI). Binomial regression analysis was used to identify the extent of the relationship between CPDI and sociodemographic factors by estimating the odds of having significant stress. P ≤ 0.05 was considered significant. Results: A total of 2,317 valid responses were received. Of the respondents, 830 (35.82%) were males, 1,084 (46.79%) were below 25 years of age, and 2,297 (99.14%) were native residents of TN. The mean(±SD) CPDI was 20.66±12.03. While 1,830 (77.2%) respondents had low or no stress, 478 (20.2%) had mild to moderate stress, and 63 (2.7%) had severe stress. The bivariate model included marital status, age, nativity, and income. The odds of having significant stress (mild–moderate or severe) for a 25–34 year age group as compared to >55 years group was 2.38 (P < 0.001). As compared to widowed, the married had higher odds ratio (3.41, P = 0.05). Compared to those with >10 lakh annual income, those with 2.5–5 lakhs annual income had odds ratio of 1.65 (95% CI = 1.01 to 2.7, P = 0.05). Conclusions: During the lockdown due to COVID-19, every 1 in 5 TN population had some form of stress, as measured by CPDI. Our model identified certain factors driving the stress, which would help policy framers to initiate an appropriate response.
    Keywords Clinical Psychology ; covid19
    Language English
    Publisher SAGE Publications
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2622378-8
    ISSN 0975-1564 ; 0253-7176
    ISSN (online) 0975-1564
    ISSN 0253-7176
    DOI 10.1177/0253717620935581
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Statewide Survey of Psychological Distress among People of Tamil Nadu in the COVID-19 Pandemic

    Ramasubramanian, Vikhram / Mohandoss, Anusa Arunachalam / Rajendhiran, Gopi / Pandian, P. Raja Soundara / Ramasubramanian, C.

    Indian Journal of Psychological Medicine

    Abstract: ... through COVID-19 Peritraumatic Distress Index (CPDI) Binomial regression analysis was used to identify ... ABSTRACTBackground: COVID-19-driven pandemic has caused panic, fear, and stress among all strata ... in the state of Tamil Nadu (TN)?a state in the southern India where the levels of stress have not been ...

    Abstract ABSTRACTBackground: COVID-19-driven pandemic has caused panic, fear, and stress among all strata of society The study aimed to assess stress and the factors that influence it in a representative population in the state of Tamil Nadu (TN)?a state in the southern India where the levels of stress have not been measured yet Methods: From April 13 to April 25, 2020, we conducted an online survey among the TN population using the snowball sampling technique, collecting basic demographic data COVID-19-perceived stress was collected through COVID-19 Peritraumatic Distress Index (CPDI) Binomial regression analysis was used to identify the extent of the relationship between CPDI and sociodemographic factors by estimating the odds of having significant stress P ≤ 0 05 was considered significant Results: A total of 2,317 valid responses were received Of the respondents, 830 (35 82%) were males, 1,084 (46 79%) were below 25 years of age, and 2,297 (99 14%) were native residents of TN The mean(±SD) CPDI was 20 66±12 03 While 1,830 (77 2%) respondents had low or no stress, 478 (20 2%) had mild to moderate stress, and 63 (2 7%) had severe stress The bivariate model included marital status, age, nativity, and income The odds of having significant stress (mild?moderate or severe) for a 25?34 year age group as compared to >55 years group was 2 38 (P 10 lakh annual income, those with 2 5?5 lakhs annual income had odds ratio of 1 65 (95% CI = 1 01 to 2 7, P = 0 05) Conclusions: During the lockdown due to COVID-19, every 1 in 5 TN population had some form of stress, as measured by CPDI Our model identified certain factors driving the stress, which would help policy framers to initiate an appropriate response
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #633797
    Database COVID19

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