Development and Validation of the Tinder Motives Scale (TMS) A recent trend in online dating is the use of “Proximity Dating solely based on the other user's picture, a short bio, mutual Facebook friends and interests, as the recursive relationship between user expectations and practices by drawing a. In this article, we develop and validate a comprehensive self-report scale of why people In Study 1, we administered an initial pool of 54 items to a general adult sample online. Relationship between empathy and the Big Five personality traits in a sample of . A very brief measure of the Big-Five personality domains. Published online Jun doi: /a In the current study, we report on the development and validation of the Hookup Motives . suggested that the social dimension be divided into sexual motives and relationship motives . The short-form version of the Depression Anxiety Stress Scales (DASS–21): .
Another aim was to identify the motivational differences between high-risk and low-risk Internet users. Methods A sample of German adolescents female: A reliability analysis revealed good internal consistencies of the subscales.
Moreover, regression analyses confirmed that the enhancement and coping motive groups significantly predicted high-risk Internet consumption and the OSVK-S sum score. A mixed-model ANOVA confirmed that adolescents mainly access the Internet for social motives, followed by enhancement and coping motives, and that high-risk users access the Internet more frequently for coping and enhancement motives than low-risk users.
Low-risk users were primarily motivated socially. Conclusions The IMQ-A enables the assessment of motives related to adolescent Internet use and thus the identification of populations at risk.
The questionnaire enables the development of preventive measures or early intervention programs, especially dealing with internal motives of Internet consumption. 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.
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. As the boundary between online and offline is becoming increasingly blurred and more youth are reporting being victimized because of offline experiences, Internet safety programs should be designed to better equip youth to manage being personally victimized because of their behavior, race or gender.
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