Sebire and Standage are with the Motivation for Exercise, Sport, The past 20 years has seen the emergence of a compelling and consistent body .. of the GCEQ items in relation to intrinsic and extrinsic goal content. .. version is recommended for use in scale development research (DeVellis, ) and. Development and Validation of the Exercise Appearance Motivations Scale by Keywords: fitness, health, psychometrics, body image, disordered eating online survey designed to assess the EAMS' psychometric properties. may illuminate and clarify the relationships between exercise and body image and eating. THE OBJECTIFIED BODY CONSCIOUSNESS SCALE Development and Validation The relationship of OBC to women's body experience is discussed.
For example, every German household containing young people aged between 12 and 19 years is equipped with a computer or laptop [ 5 ]. In addition, personal computers are no longer the most common way of accessing the Internet in Europe. There has been unequivocal growth in access to the Internet via handheld or portable devices eg, touchpads and smartphonesshowing that the Internet is now accessible to everyone [ 35 ].
Therefore, we can assume the existence of a generation that has grown up with the latest technologies from a very young age [ 12 ] and that Internet use is an extremely widespread phenomenon. This situation can be clearly explained by the fact that the Internet is a convenient source of information, social contacts, education, shopping, and recreational activities [ 6 - 10 ] that simplifies everyday life.
The Internet also has a negative side. Furthermore, different studies in several countries show that for 1. Initial results from longitudinal studies even give rise to the suspicion that the disorder is highly stable [ 18 ].
Regarding the relationship between the Internet and all areas of life [ 5 - 7 ] and the suggested DSM-5 criteria for Internet addiction [ 11 ], the duration someone spends online does not appear to be a valid criterion. Thus, getting to know the motives behind adolescent Internet consumption is important. Concerning motives for media use in general, McQuail [ 1920 ] assumes 4 basic motives: Recent research regarding the motivations of Internet use in particular found the existence of instrumental motives, such as information seeking and social interaction, as well as a relationship between personality types and Internet use [ 621 - 28 ].
There are, however, a number of gaps in current research. First, not much is known about affectivity, which plays an important role in understanding problematic Internet use. In fact, there are instruments for measuring Internet addiction and instrumental motives for using the Internet.
Infor example, Young [ 29 ] developed the first instrument for measuring Internet addiction, the Internet Addiction Test IATwhich was translated into various languages and validated in different samples [ 30 - 33 ].
Also, the previously mentioned Internet Motives Questionnaire assesses motives that are more instrumental as they target the affective function the Internet serves for adolescents.
According to the motivation model of McClelland [ 34 ], affective change is assumed to be the driving force behind human behavior. Hence, striving for positive affect and escaping or relieving a dysphoric mood is seen as the basis of motivational Internet behavior and thus, according to the DSM-5, a criterion for Internet use disorder [ 11 ]. Second, none of the studies were based on a theoretical framework defining the dimensionality of motives for Internet use a priori.
The MOGQ is based on a theoretical approach, although this model was developed by observing online players. This is particularly important given that many online incidents begin with problems offline. The OVS adapts these responses to the victimization experiences and rather than dichotomous responses, it determines whether the experience never happened, happened once, a few times a year, a few times a month, a few times a week or occurs on a daily basis.
Race related items were developed based on theory e. Harrell,previous studies of race on the Internet e. Following the theoretical arguments outlined previously as well as extant literature on online victimization, we posit that victimization will be associated with the most salient aspects of the physical body offline in the following domains: The sexual-gender domain includes stereotyping based on gender, sexual solicitation, and risk factors commonly associated with this form of victimization.
The racial domain includes racial epithets, images and stereotyping based on race or ethnicity directed at the individual and vicarious experiences by same and cross race peers.
Fifty-four items were originally created in the OVS-Preliminary version of the scale. Four focus groups were then conducted to determine the age-appropriateness of the items and whether content adequately represented online experiences of teens. A total of 20 adolescents ages participated in the 4 focus group groups. Upon completion of a pencil and paper version of the scale, participants were then asked to review the items and discuss any that should be removed or modified.
Twenty eight items assessed victimization experiences and risk factors for sexual victimization, 12 stress associated with victimization, 3 location of experiences, 4 their worst internet experience and their responses and 4 internet safety.
Measures In addition to the OVS, a demographic questionnaire was used. Procedure Participants were recruited from 3 Midwestern US high schools. Researchers introduced the study at high school faculty meetings explaining that little is known about how the Internet may impact academic and mental health outcomes."Relationship Status: Online" (Short Film)
Teachers were given a script to read verbatim and fliers to hand out to students in their classes. The teachers read the script to their students describing the study as students read the flier.
Teachers instructed the students to complete the surveys on their own and without consultation from peers. The fliers included a website address for the study and were complete with instructions on how to log on.
Students completed the surveys either on school computers during lunch time or afterschool, logging on to the website listed on the flier. The online survey settings ensured that the participants completed the survey only once. Online assent was obtained from participants prior to participation. Per university Institutional Review Board approval, parent consent was waived to allow participants to freely respond to sensitive questions related to Internet experiences. Participants were assured that they could discontinue the study at any time if they felt discomfort.
These four domains were used to construct the theoretical four-factor online victimization model, which was investigated through a confirmatory factor analytic procedure. However, our preliminary theoretical investigation led to the dismissal of seven of the 28 items because they did not directly relate to the investigated construct. Specifically, items were dismissed from consideration for the sexual victimization construct because they were determined to assess risk factors, not necessarily direct online sexual victimization.
Overall, the theoretical four-factor model examined direct general online victimization 8 itemsdirect sexual online harassment 6 itemsdirect racial discrimination 4 items and vicarious racial discrimination 3 items.
See Table 2 Table 2. The General Online Victimization factor is comprised of an 8-item experiential dimension of general victimization the respondent experienced online. Items addressed personal victimization experienced by the respondent online e. People have said negative things like rumors or name calling about how I look, act, or dress online. Items also tap into the repeated nature of online victimization e.
I have been bullied online. Factor loadings from the subsequent confirmatory factor analytic procedure ranged from. The Online Sexual Victimization factor is comprised of a 6-item experiential dimension of sexual victimization the respondent experienced online.
Items addressed individual sexual victimization directly experienced by the respondent online e. The Individual Online Racial Discrimination factor is comprised of a 4-tiem experiential dimension of racial discrimination the respondent experienced online. Items addressed individual racial discrimination directly experienced by the respondent online e.
Vicarious Online Racial Discrimination. The Vicarious Online Racial Discrimination factor is comprised of a 3-item vicarious experiential dimension of racial discrimination the respondent experienced online. Items addressed vicarious experiences directed at same race and cross race peers witnessed online by the respondent e. Confirmatory Factor Analysis To examine the fit of the theoretical four-factor model, we conducted a maximum-likelihood estimation confirmatory factor analysis in LISREL 8.
The competing three-factor model was theory driven, and was comprised of the Online Victimization factor, Online Sexual Victimization factor, and an aggregate Racial Discrimination factor i.
First, we examined the chi-square statistic divided by the degrees of freedom to assess overall model fit. Based on the 21 items from the OVS, we examined the theoretical four-factor model against the competing three-factor model, independence model, and unideminsional model, and it was determined that the hypothesized four-factor model demonstrated more acceptable model fit when compared to all other models see Table 3.
Fit Statistics for Theoretical four-factor model and model comparisons for Study 1 Figure 1. Confirmatory Factor Analysis for theoretical four- factor model investigated in Study 1. Factor Correlations, Skewness and Kurtosis As hypothesized, and due to the experiential nature of the victimization experienced by the respondent, all four factors were significantly correlated. Additionally, it is conceivable to believe that a majority of the respondents would score on the lower end of the scales due to the nature of the experiential items.
Demographic Differences To assess demographic differences, a multivariate analysis of variance MANOVA was conducted across the four online victimization factors as the dependent variables and gender, ethnicity, and age as the independent variables.
Tukey Post Hoc tests revealed that Asian Americans 1. Additionally, Asian Americans 3. Interestingly, the Tukey Post Hoc test only revealed a significant difference between 17 and 18 year olds on individual online racial discrimination, where 17 year olds 1.
The self-reported ethnicity of participants was Measures The Online Victimization Scale is a item measure that assesses online victimization in four domains: I have been bullied online and People have said negative things -like rumors or name calling- about how I look, act, or dress onlinesexual e. People have continued to have sexual discussions with me even after I told them to stop and individual racial discrimination e.
People have said mean or rude things about me because of my race or ethnic group online and vicarious online racial discrimination e. People have cracked jokes about people of my race or ethnic group online. The measure is designed to be used on adolescents ages in research, clinical and educational settings. To validate the Online Victimization Scale the following measures that have been associated with victimization in offline settings were used.
This item self-report measure assesses cognitive, affective, and behavioral signs of depression in school-age children and adolescents ages Each item is composed of three choices e. This scale is a shortened version of the POMS, a item measure used on adults.
It is a item measure of six mood states of adolescents: Items range from those that would only be endorsed by those with low self-esteem to those endorsed solely by those with high self-esteem e. I feel that I am a person of worth, at least on an equal plane with others. Respondents indicate the frequency with which they experience each item. Scores range from 5 to 35; higher scores indicate greater life satisfaction.
Results To further examine the structure of the theoretical four-factor model from Study 1, the confirmatory factor analytic procedure was repeated for Study 2. Factor loadings and alpha coefficients mirrored the results of Study 1, where loadings for Online Victimization ranged from. The competing three-factor model maintained theoretical integrity, and was comprised of the Online Victimization factor, Online Sexual Victimization factor, and an aggregate Racial Discrimination factor i.
As in Study 1, it was determined that the hypothesized four-factor model demonstrated more acceptable model fit when compared to the independence, unidimensional, and competing three-factor models see Table 4. Fit Statistics for Theoretical four-factor model and model comparisons for Study 2 Figure 2.
Confirmatory Factor Analysis for theoretical four- factor model investigated in Study 2. Demographic Differences Similar to Study 1, we assessed demographic differences using a MANOVA across the four online victimization factors as the dependent variables and gender, race, and age as the independent variables.
Due to the sample size discrepancy between racial groupings, post hoc analyses i. To extend Study 1 and determine the convergent validity of the theoretical four-factor model, Pearson correlations were performed on the CFA factors from Study 2 and measures of adjustment. Four distinct subscales were found: Results showed a good model fit for the data for the four factors that make up the Online Victimization Scale. In addition, to validate the OVS, each of the subscales were compared to measures that have been traditionally associated with victimization in offline and online settings.
As expected online victimization subscales were associated with depressive symptomatology, anxiety, perceived stress and decreased self esteem and satisfaction with life. Although the measurement of online victimization has gotten increasingly more sophisticated through the years Cassidy, et.
For example, just among adolescents in the US, rates of victimization may range from 9. The OVS provides a psychometrically sound measure that can be used across studies. Ultimately, the burgeoning field of new media studies may be able to more systematically study online victimization with the OVS. In addition, the OVS moves beyond assessment of whether online victimization has occurred and assesses reasons why the experiences occurred, including physical appearance, social status as evidenced in dress and writing styleand experiences that extend from the school settings.
Measures that do provide this level of detail may provide respondents with responses that mask the true frequency of victimization. Moreover, they still may not include varying types of sexual or racial victimization. The most important contribution the OVS makes to the literature is its focus on racial discrimination in online contexts.
Though these racially discriminatory experiences are common online Tynes et al,to date, this aspect of online victimization has largely been neglected. When it is assessed it is with items that ascertain if respondent has been called a name because of race or ethnicity. This does not account for racist images, cloaked websites, racist jokes and vicarious online racial discrimination.
Considering the growing amount of online hate activity since the nomination and election of President Barack Obama in the US Chen, ; Daniels, ; Hanna, and the fact that online racial discrimination is associated with increased anxiety and depressive symptoms Tynes, et.
For example, using the Adolescent Discrimination Distress Index Fisher,the authors measured the level of perceived discrimination in 3 contexts: Because the developmental literature indicates that risk associated with negative adjustment outcomes is compounded as youth experience stressors across differing environments Compas, ; Rutter, a measure that assesses online experiences will help to capture unique experiences and impact of online interaction.
This study is also consistent with questionnaires and measures of online victimization that have found associations with distress and depressive symptoms. The OVS builds on previous questionnaires and measures however, in that it accounts for direct and vicarious race-related victimization experiences.
With the creation of the OVS, research at the intersection of Internet Studies, developmental psychology and public health may now use a psychometrically sound measure across studies. Although recent research has shown differences in victimization based on age and gender, results revealed no differences in this study Wolak, et.
Females and older adolescents have been noted to experience more sexual victimization than their male and younger counterparts. This departure in the literature is attributable to the fact that this sample is generally older than those in other studies. We, for example, did not include any youth below age 14 and the average age of the sample was approximately 16 years of age. This is about the time when victimization is at its height.
Study1 found that Asian American and biracial students experienced significantly more individual online racial discrimination than African Americans and Whites. It should be noted, however, that the sample of Asians and Biracial participants was particularly small however, so findings may not be generalizable to youth across the United States.
A limitation of the measure is that the items do not differentiate between strangers and known peers that commit victimization. A final limitation is that sexual victimization items should distinguish between whether an adult is asking to meet the person online or a peer and should also determine whether showing the sexual images, etc were unwanted. Future research should address these limitations. Following the theoretical framework of re-embodiment, this study showed that victimization does occur along the most salient aspects of the offline physical body, including physical appearance and or ability, and the sexual and racial domains.
And just as in face-to-face settings victimization has consequences for mental health. Future studies should assess whether online victimization impacts other domains offline including academic performance.
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