Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis

Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Khani Jeihooni, Ali [verfasserIn] Jafari, Fatemeh Shiraly, Ramin Rakhshani, Tayebeh Asadollahi, Abdolrahim Karami, Hamed

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	COVID-19 Physical activity Structural equation modeling (SEM) Theory of planned behavior (TPB)

Anmerkung:	© The Author(s) 2022

Übergeordnetes Werk:	Enthalten in: BMC public health - London : BioMed Central, 2001, 22(2022), 1 vom: 22. Juli
Übergeordnetes Werk:	volume:22 ; year:2022 ; number:1 ; day:22 ; month:07

Links:	Volltext

DOI / URN:	10.1186/s12889-022-13797-3

Katalog-ID:	SPR050872532

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100	1		\|a Khani Jeihooni, Ali \|e verfasserin \|4 aut
245	1	0	\|a Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis
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520			\|a Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions.
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allfields	10.1186/s12889-022-13797-3 doi (DE-627)SPR050872532 (SPR)s12889-022-13797-3-e DE-627 ger DE-627 rakwb eng Khani Jeihooni, Ali verfasserin aut Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. COVID-19 (dpeaa)DE-He213 Physical activity (dpeaa)DE-He213 Structural equation modeling (SEM) (dpeaa)DE-He213 Theory of planned behavior (TPB) (dpeaa)DE-He213 Jafari, Fatemeh aut Shiraly, Ramin aut Rakhshani, Tayebeh aut Asadollahi, Abdolrahim aut Karami, Hamed aut Enthalten in BMC public health London : BioMed Central, 2001 22(2022), 1 vom: 22. Juli (DE-627)326643583 (DE-600)2041338-5 1471-2458 nnns volume:22 year:2022 number:1 day:22 month:07 https://dx.doi.org/10.1186/s12889-022-13797-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 22 07
spelling	10.1186/s12889-022-13797-3 doi (DE-627)SPR050872532 (SPR)s12889-022-13797-3-e DE-627 ger DE-627 rakwb eng Khani Jeihooni, Ali verfasserin aut Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. COVID-19 (dpeaa)DE-He213 Physical activity (dpeaa)DE-He213 Structural equation modeling (SEM) (dpeaa)DE-He213 Theory of planned behavior (TPB) (dpeaa)DE-He213 Jafari, Fatemeh aut Shiraly, Ramin aut Rakhshani, Tayebeh aut Asadollahi, Abdolrahim aut Karami, Hamed aut Enthalten in BMC public health London : BioMed Central, 2001 22(2022), 1 vom: 22. Juli (DE-627)326643583 (DE-600)2041338-5 1471-2458 nnns volume:22 year:2022 number:1 day:22 month:07 https://dx.doi.org/10.1186/s12889-022-13797-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 22 07
allfields_unstemmed	10.1186/s12889-022-13797-3 doi (DE-627)SPR050872532 (SPR)s12889-022-13797-3-e DE-627 ger DE-627 rakwb eng Khani Jeihooni, Ali verfasserin aut Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. COVID-19 (dpeaa)DE-He213 Physical activity (dpeaa)DE-He213 Structural equation modeling (SEM) (dpeaa)DE-He213 Theory of planned behavior (TPB) (dpeaa)DE-He213 Jafari, Fatemeh aut Shiraly, Ramin aut Rakhshani, Tayebeh aut Asadollahi, Abdolrahim aut Karami, Hamed aut Enthalten in BMC public health London : BioMed Central, 2001 22(2022), 1 vom: 22. Juli (DE-627)326643583 (DE-600)2041338-5 1471-2458 nnns volume:22 year:2022 number:1 day:22 month:07 https://dx.doi.org/10.1186/s12889-022-13797-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 22 07
allfieldsGer	10.1186/s12889-022-13797-3 doi (DE-627)SPR050872532 (SPR)s12889-022-13797-3-e DE-627 ger DE-627 rakwb eng Khani Jeihooni, Ali verfasserin aut Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. COVID-19 (dpeaa)DE-He213 Physical activity (dpeaa)DE-He213 Structural equation modeling (SEM) (dpeaa)DE-He213 Theory of planned behavior (TPB) (dpeaa)DE-He213 Jafari, Fatemeh aut Shiraly, Ramin aut Rakhshani, Tayebeh aut Asadollahi, Abdolrahim aut Karami, Hamed aut Enthalten in BMC public health London : BioMed Central, 2001 22(2022), 1 vom: 22. Juli (DE-627)326643583 (DE-600)2041338-5 1471-2458 nnns volume:22 year:2022 number:1 day:22 month:07 https://dx.doi.org/10.1186/s12889-022-13797-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 22 07
allfieldsSound	10.1186/s12889-022-13797-3 doi (DE-627)SPR050872532 (SPR)s12889-022-13797-3-e DE-627 ger DE-627 rakwb eng Khani Jeihooni, Ali verfasserin aut Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. COVID-19 (dpeaa)DE-He213 Physical activity (dpeaa)DE-He213 Structural equation modeling (SEM) (dpeaa)DE-He213 Theory of planned behavior (TPB) (dpeaa)DE-He213 Jafari, Fatemeh aut Shiraly, Ramin aut Rakhshani, Tayebeh aut Asadollahi, Abdolrahim aut Karami, Hamed aut Enthalten in BMC public health London : BioMed Central, 2001 22(2022), 1 vom: 22. Juli (DE-627)326643583 (DE-600)2041338-5 1471-2458 nnns volume:22 year:2022 number:1 day:22 month:07 https://dx.doi.org/10.1186/s12889-022-13797-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 22 07
language	English
source	Enthalten in BMC public health 22(2022), 1 vom: 22. Juli volume:22 year:2022 number:1 day:22 month:07
sourceStr	Enthalten in BMC public health 22(2022), 1 vom: 22. Juli volume:22 year:2022 number:1 day:22 month:07
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	COVID-19 Physical activity Structural equation modeling (SEM) Theory of planned behavior (TPB)
isfreeaccess_bool	true
container_title	BMC public health
authorswithroles_txt_mv	Khani Jeihooni, Ali @@aut@@ Jafari, Fatemeh @@aut@@ Shiraly, Ramin @@aut@@ Rakhshani, Tayebeh @@aut@@ Asadollahi, Abdolrahim @@aut@@ Karami, Hamed @@aut@@
publishDateDaySort_date	2022-07-22T00:00:00Z
hierarchy_top_id	326643583
id	SPR050872532
language_de	englisch
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The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). 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author	Khani Jeihooni, Ali
spellingShingle	Khani Jeihooni, Ali misc COVID-19 misc Physical activity misc Structural equation modeling (SEM) misc Theory of planned behavior (TPB) Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis
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topic_title	Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis COVID-19 (dpeaa)DE-He213 Physical activity (dpeaa)DE-He213 Structural equation modeling (SEM) (dpeaa)DE-He213 Theory of planned behavior (TPB) (dpeaa)DE-He213
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title	Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis
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title_full	Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis
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author_browse	Khani Jeihooni, Ali Jafari, Fatemeh Shiraly, Ramin Rakhshani, Tayebeh Asadollahi, Abdolrahim Karami, Hamed
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title_sort	physical activity behavior during covid 19 pandemic among iranian dwellers in southern iran based on planned behavior theory: a sem analysis
title_auth	Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis
abstract	Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. © The Author(s) 2022
abstractGer	Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. © The Author(s) 2022
abstract_unstemmed	Background The COVID-19 pandemic restrictions curtailed physical activity. The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions. © The Author(s) 2022
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title_short	Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis
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author2	Jafari, Fatemeh Shiraly, Ramin Rakhshani, Tayebeh Asadollahi, Abdolrahim Karami, Hamed
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The current study applied an integrated Theory of Planned Behavior to identify the determinants of physical activity behavior and the processes involved in the COVID-19 pandemic. Methods A cross-sectional study was conducted in Shiraz city, Southern Iran, among 2500 people who met the inclusion criteria were included in the study. Data were collected using the demographic information questions and questionnaire based on the Theory of Planned Behavior (TPB) constructs. The Questionnaire via WhatsApp, emails, and SMS was shared. Data analysis was performed using SPSS26 and Amos version 24. Mean and standard deviation was used to describe the data. Also, one-way ANOVA and structural equation analysis were used to analyze the data. The significance level in all the tests was considered to be 0.05. Results One thousand one hundred sixty-nine samples (46.8%) said they had been exercising less than 3 days a week, and 47.6% of them did not have any exercise or physical activities (n = 1191). The mean score of attitudes, SN, PBC, and intention were 9.38 ± 2.07, 9.27 ± 2.03, 9.32 ± 2.05, and 12.29 ± 2.35, respectively. The effect size values demonstrate the independent variables’ high coefficient of influence on explaining the theoretical model. According to the results, the factors play an important role in samples’ intention ($ η^{2} $ ≥ 0.2, p ≤ 0.05). The effect size of intention on doing physical activities and exercise during the SARS-CoV-2 pandemic is Eta square = 0.777, which means the measure was high. The obtained model was good based on the main goodness of fit indices (Chi2 = 108.6, df = 25, n = 2500, Chi2/df = 4.344, RMSEA = 0.036, AGFI = 0.92, CFI = 0.95, GFI = 0.90, Fornell-Larcker criterion = 0.87, HTMT = 0.89). Conclusion The TPB provides a useful framework to explore psychosocial determinants of physical activity behavior during the pandemic and identify key strategies for program planning aimed at improving exercise among people who were already influenced by quarantine and lockdown restrictions.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">COVID-19</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Physical activity</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Structural equation modeling (SEM)</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Theory of planned behavior (TPB)</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jafari, Fatemeh</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shiraly, Ramin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rakhshani, Tayebeh</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Asadollahi, Abdolrahim</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Karami, Hamed</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">BMC public health</subfield><subfield code="d">London : BioMed Central, 2001</subfield><subfield code="g">22(2022), 1 vom: 22. 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Physical activity behavior during Covid 19 pandemic among Iranian dwellers in Southern Iran based on planned behavior theory: a SEM analysis

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