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<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Sport Management Journal</JournalTitle>
				<Issn>2008-9341</Issn>
				<Volume>10</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2018</Year>
					<Month>06</Month>
					<Day>22</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Model of Relationship of Sources of Power and Coaches’ Misconduct with Progressive Motivation in Elite Female Athletes</ArticleTitle>
<VernacularTitle>The Model of Relationship of Sources of Power and Coaches’ Misconduct with Progressive Motivation in Elite Female Athletes</VernacularTitle>
			<FirstPage>414</FirstPage>
			<LastPage>401</LastPage>
			<ELocationID EIdType="pii">70350</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jsm.2019.238096.1897</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Lila</FirstName>
					<LastName>Saffari</LastName>
<Affiliation>Faculty</Affiliation>

</Author>
<Author>
					<FirstName>Afsar</FirstName>
					<LastName>Jafari</LastName>
<Affiliation>faculty</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2017</Year>
					<Month>08</Month>
					<Day>09</Day>
				</PubDate>
			</History>
		<Abstract>The aim of this study was to provide the model of the relationship of the sources of power and coaches’ misconduct with progressive motivation in elite female athletes. The research method was factor analysis and field. The statistical population consisted of all elite female athletes in 2 team sports and 2 individual sports including cycling and rowing who were invited to the camps of national teams in 2016. 190 athletes were selected as the sample. To collect data, Power in Sport Questionnaire by Wann et al. (2000), Blurizadeh (2015) Misconduct Experience Questionnaire, Long and Fries Progressive Motivation Questionnaire (2006) were used. Pearson correlation coefficient and regression analysis were used to predict changes and factor analysis and t test were applied to examine the fit of the model and to determine the effect by SPSS, Excel and SMART-PLS. The results showed a multiplicity relationship between sources of power and progressive motivation in elite female athletes and the sources of power explained progressive motivation. There was a multiplicity relationship between the components of misconduct and progressive motivation in elite female athletes and these components explained progressive motivation. The goodness of fit indicators of NFI and SRMR along with their interpretations showed that the model does not have a good fit. And in PLS-SMART, indicators should be interpreted with caution.</Abstract>
			<OtherAbstract Language="FA">The aim of this study was to provide the model of the relationship of the sources of power and coaches’ misconduct with progressive motivation in elite female athletes. The research method was factor analysis and field. The statistical population consisted of all elite female athletes in 2 team sports and 2 individual sports including cycling and rowing who were invited to the camps of national teams in 2016. 190 athletes were selected as the sample. To collect data, Power in Sport Questionnaire by Wann et al. (2000), Blurizadeh (2015) Misconduct Experience Questionnaire, Long and Fries Progressive Motivation Questionnaire (2006) were used. Pearson correlation coefficient and regression analysis were used to predict changes and factor analysis and t test were applied to examine the fit of the model and to determine the effect by SPSS, Excel and SMART-PLS. The results showed a multiplicity relationship between sources of power and progressive motivation in elite female athletes and the sources of power explained progressive motivation. There was a multiplicity relationship between the components of misconduct and progressive motivation in elite female athletes and these components explained progressive motivation. The goodness of fit indicators of NFI and SRMR along with their interpretations showed that the model does not have a good fit. And in PLS-SMART, indicators should be interpreted with caution.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">elite athletes</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">female athlete</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">misconduct</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">progressive motivation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">sources of power</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jsm.ut.ac.ir/article_70350_7c3abb9b54b16db1db8d3dc17f424f5d.pdf</ArchiveCopySource>
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