The influence of sexually-oriented music on minority adolescent's sexual initiation.
Answers as to whether sexually-oriented music lyrics influence
adolescent sexual initiation are unclear.
The purpose of this study was to develop a reliable and valid instrument based on the Theory of Reasoned Action to enable researchers to predict the influence of sexually-oriented music lyrics on early sexual initiation among African-American adolescents (AAas).
Participants (n =185) resided in rural and urban areas in the southeastern U.S.
The final instrument had a Cronbach's alpha of .846. While further development work is needed, the survey is in a promising state. Additional psychometric work will prove the predictive ability and worth of the instrument.
Youth (Sexual behavior)
Gordon, Brian C.
Perko, Mike A.
Turner, Lori W.
Leeper, James D.
Usdan, Stuart L.
Pruitt, Samory T.
|Publication:||Name: American Journal of Health Studies Publisher: American Journal of Health Studies Audience: Professional Format: Magazine/Journal Subject: Health Copyright: COPYRIGHT 2012 American Journal of Health Studies ISSN: 1090-0500|
|Issue:||Date: Spring, 2012 Source Volume: 27 Source Issue: 2|
|Topic:||Canadian Subject Form: Teenage sexual behaviour|
|Product:||Product Code: E121930 Youth|
|Organization:||Organization: The University of Alabama|
|Geographic:||Geographic Scope: California Geographic Code: 1U9CA California|
Factors such as gender, race and ethnicity, environment, age, and attitudes contribute to sexual behaviors of adolescents (Manlove, Terry-Humen, Papillo, Franzetta, Williams, & Ryan, 2002). Males are more likely to initiate sex early and have multiple partners; minorities are more likely to engage in behavior that lead to early pregnancy and STIs; and older adolescents are more sexually experienced than younger adolescents (Abma, Driscoll, & Moore, 1998; Miller, Norton, Curtis, Hill, Schvaneveldt, & Young, 1997; Raine, et al., 1999; Santelli, Lowry, Brener, & Robin, 2000; Shrier, 2004). Furthermore, studies show adolescents from disadvantaged communities with high poverty rates are more likely to have sex, become pregnant, and give birth in relation to adolescents from advantaged communities who are less likely to engage in risky behaviors (Brewster, Billy, & Grady, 1993; Hogan, & Kitagawa, 1985; Manlove, Terry-Humen, Papillo, Franzetta, Williams, & Ryan, 2002; Sucoff & Upchurch, 1998).
One largely unexplored factor that may cut cross all areas and influence sexual initiation and sexual behavior among adolescents is through music media, specifically sexually-oriented music lyrics.
A relationship among music media exposure and influence on adolescents' sexual perceptions, attitudes, and intentions has been demonstrated (Brown, L'Engle, Pardun, Guang, Kenneavy, & Jackson, 2006; L'Engle, Brown, and Kenneavy, 2006; Martino, Collins, Elliott, Strachman, Kanouse, & Berry, 2006); however, answers as to whether sexually-oriented music lyrics influence adolescent sexual initiation are unclear. According to Social Learning Theory (SLT), adolescents' attitudes, beliefs, and behaviors are influenced by modeling and other vicarious experiences (Bandura, 1962).
While research on the influence of sexual media is lacking, SLT is the one of the premises for the argument of a causal relationship as it relates to exposure to sexually-oriented lyrics (Allen, Herrett-Skjellum, Jorgenson, Ryan, Kramer, & Timmerman, 2007; Escobar-Chaves, Tortolero, Markham, Low, Eitel, & Thickstun, 2005; Martino, Collins, Elliott, Strachman, Kanouse, & Berry, 2006). Allen and colleagues (2007) commented that in relation to SLT adolescents might be listening to crude song lyrics and mimicking or acting out scenarios that they hear. What is not known is whether exposure to sexually-oriented music lyrics influences early sexual behavior and if so, can it be predicted? Various social science theories exist that have contributed to understanding adolescent behavior. One such theory, the Theory of Reasoned Action (TRA), has been used to determine the predictive weight of attitudes and subjective norms of adolescents on the intentions to perform behaviors such as drinking, dietary supplement use, and sun protection behaviors. Research using the TRA has shown that behavior can be accurately predicted from intentions when there are no issues of control (Ajzen, 1988; Sheppard, Hartwick, & Warshaw, 1988). Application of the TRA to predict early initiation of sexual activity from exposure to sexually-oriented music lyrics by African-American adolescents (AAas) has not been done.
MUSIC AND ADOLESCENTS
Music plays an important role in the socialization process of adolescents (Roberts & Christenson, 2001). Adolescents spend significant amounts of time listening to music with more than half (65%) of 8-18 year old adolescents reporting carrying portable music devices when away from home (Rideout, Roberts, & Foehr, 2005). In relation to gender and race, females listen more than males (Greenberg, Ku, & Li, 1989; Roberts & Henriksen, 1990), and African-American adolescents listen more than White adolescents (Brown, Childers, Bauman, & Koch, 1990). Moreover, Hall (1998) noted that African-American adolescents 10-12 years of age not only recognize lyrical content, but are able to describe lyrical messages.
Adolescents are saturated with mass media, spending an average of 6 hours and 30 minutes a day utilizing media; media use increases to 8 hours and 30 minutes when considering the multiple mediums adolescents use simultaneously (Rideout, Roberts, & Foehr, 2005). Media is defined as television, radio, newspapers and magazines, records, computers, video, and films (Feldman, & Elliott, 1990). Given the wide array of media devices and technological advances such as Ipods, MP3 players, as well as Internet availability, music persists as the dominant media chosen by adolescents (Rideout, Roberts, & Foehr, 2005). Adolescents spend an average of 1 hour and 45 minutes daily listening to music (Rideout, Roberts, & Foehr, 2005). Adolescents spend roughly 1 hour using the computer, 50 minutes playing video games, and 45 minutes reading on a daily basis (Rideout, Roberts, & Foehr, 2005).
The fact that sexual references readily occur in music lyrics is alarming (Wartella, Heintz, Aidman, & Mazzarella, 1990). Researchers suggest that song lyrics have become more sexually explicit as society has become more accepting of overt sexuality (Hirsch, 1971; Prinsky & Rosenbaum, 1987; Rice, 1980). Content analysis of selected media showed that music contained 40% more sexual content than any other medium, with 15% of music's sexual content focusing solely on intercourse, compared to a 3% and 4% focus in television and movies, respectively (Pardun, L'Engle, & Brown, 2005).
Furthermore, Primack and colleagues (2008) conducted a content analysis of music lyrics to determine the prevalence of sexual content. Popular songs were identified and analyzed for degrading and non-degrading sexual music lyrics. Thirty-seven percent (37%) of lyrics contained sexual content. Degrading lyrics were more common (65%) than non-degrading (35%) music lyrics. Rap (64%) and R&B/ Hip-Hop (22%) were the genres that contained the highest amounts of degrading lyrics, while Country (45%) and R&B/Hip-Hop (28%) contained the highest percentages of non-degrading sexual lyrics. Researchers in this area conclude that investigation into the influence of sexual music lyrics on adolescents' sexual behavior, including initiation be done using social science theory.
Adolescence is a time of increasing independence and exploring new boundaries; music exposure is bound to increase as adolescents seek new ways to express themselves. Older adolescents listen to more music than younger adolescents. Listening patterns differ significantly, with 8-10 year olds listening for 59 minutes, 11-14 year olds listening for 1 hour and 42 minutes, and 15-18 year olds listening to music an average of 2 hours and 24 minutes daily (Rideout, Roberts, & Foehr, 2005). This increase in exposure is likely to exert some influence on adolescents' sexual attitudes, beliefs, and behaviors. Walsh-Childers and Brown (1993) noted that regardless of gender, adolescents with higher levels of exposure to music are more likely to consider lyrical messages more realistic than those with low levels of exposure.
To date, one longitudinal study has attempted to examine the relationship of degrading vs. non-degrading music lyrics on the attitudes and behaviors of adolescents. Martino and colleagues (2006) conducted national telephone surveys of 1,242 adolescents 12-17 years of age. The sample was 43% female and consisted of 68%, 14%, 12%, and 6% White, African-American, Hispanic, and other adolescents respectively. The researchers concluded that exposure to degrading music lyrics is related to advancement in sexual activities, i.e., intercourse and noncoital behaviors. However, exposure to lyrics was not related to advances in sexual behavior when music lyrics were not degrading. Additionally, adolescents who listened to increased amounts of music were more likely to advance in noncoital sexual behavior and initiate sex even after controlling for sexual content in the music. Researchers recommended future studies examine how male and female adolescents make sense of sexually explicit lyrics and how it relates to sexual behavior. Up until this time, no such instrument existed.
PURPOSE OF STUDY
The purpose of this study was to develop a reliable and valid instrument based on the Theory of Reasoned Action to predict the influence of sexually-oriented music lyrics on sexual initiation of African-American adolescents. The majority of research in this emerging area suggests adolescents with greater exposure to sexually-oriented music lyrics are more sexually active, have greater intentions to have sex, and are more likely to initiate sexual activity (L'Engle, Brown, Kenneavy, 2006; Martino, Collins, Elliott, Strachman, Kanouse, & Berry, 2006). However, of the available research examining the influence of sexual media exposure on the attitudes and behaviors of adolescents, African-American adolescents have rarely been included in research efforts (EscobarChaves et al., 2005). Furthermore, the development of a theory-based instrument to predict the influence of sexually-oriented music lyrics on the attitudes, beliefs, and intentions of African-American adolescents is the first of its kind.
The survey was developed based on an adapted version of Mueller's (1986) procedures for the development of an attitude and belief instrument. More specifically, procedures employed replicated those of Perko (1996) who utilized a 9 step model in survey development. The study was conducted in the Southeastern United States from spring 2009 to spring 2010.
The steps used to develop the Survey to Predict the Influence of Sexually-Oriented Music Lyrics on African-American Adolescents (SPISOML-AAA) are listed below.
1. Identify the attitudinal object.
2. Collect a pool of opinion items.
3. Submit pool of items to expert panel for review.
4. Pilot test draft of SPISOM-AAA.
5. Administer item pool to a group of respondents.
6. Score each item for each respondent.
7. Sum respondents' item scores.
8. Correlate item scores with total scale scores for all respondents.
9. Apply statistical criteria for elimination of test items.
Due to length requirements, specific strategies will not be discussed. Please contact the lead author for specific procedures conducted at each step. Parental consent and student assent were received before students were allowed to participate in the study. Approval for the study's protocol was secured from The University of Alabama's Institutional Review Board (IRB).
STEP 1: IDENTIFY THE ATTITUDINAL OBJECT
Three strategies were used to determine the influence sexually-oriented music lyrics have on the attitudes and beliefs of AAas. The strategies used were a review of the literature, focus group interviews with AAas, and input from an expert panel. Focus group interviews (n=12) were conducted with 36 AAas in 6th-8th grades. Twenty (n=20) students resided in a rural county and 16 students resided in an urban county. Nineteen (n=19) students were female and 17 were male. Focus groups were conducted during school hours in private rooms designated by the school counselors. Interviews took place during designated exploratory periods for 6th, 7th, and 8th grades. No school officials were present during the focus group interviews. Focus groups were separated according to gender with corresponding moderators of the same gender and ethnic background. Each session last approximately 30 minutes. Focus group participants received a meal equal to $6 as an incentive for participation. The expert panel was asked to provide existing instruments and/or items, and information for construction of attitudinal items by authors of the items. No existing instruments were submitted by the expert panel.
STEP 2: DEVELOP POOL OF TEST ITEMS
Utilizing information gathered in step 1, 95 items were constructed for use in the initial pool of items. These items were divided into 4 areas; demographics (1-14), behavioral beliefs (15-40), subjective norms (41-85), and behavioral intention (86-95).
STEP 3: POOL OF ITEMS REVIEWED BY PANEL OF EXPERTS
A total of 5 experts reviewed the initial pool of items. The expert panel review resulted in the deletion of 22 items. Items were omitted based on clarity of questions, relevance, and lack of conformity to the tenets of a TRA questionnaire. The panel recommended that some questions be reworded. After initial feedback was received, the pool of items was refined until a consensus was reached that the items used were representative of a TRA survey. This consensus was reached with this researcher and the experts in the area of health behavior theory. Twenty-seven (n = 27) additional items were deleted.
STEP 4: PILOT TEST DRAFT OF THE SURVEY
The pilot draft of the Survey consisted of the refined pool of items (n = 46) developed in step 3. A total of 12 AAas in grades 6-8 answered survey items of the pilot test draft of the survey. As a result of the information gathered from administration of the pilot test draft, the survey was refined. In general, definitions of terms were clarified, time intervals were changed, and students suggested additional questions be added.
STEP 5: ADMINISTER THE ITEM POOL TO A GROUP OF RESPONDENTS
The refined draft of the survey from step 4 resulted in the final item pool (n = 48). After a presentation to a school board, several meetings with superintendents, principals, and assistant principals; researchers were approved to administer the survey in predominantly minority serving middle schools (grades 6-8). The entire student populations at each school were invited to participate. Please contact the lead author for detailed recruitment strategies. The final draft of the survey was administered to a total of 185 AAas. Four surveys were omitted from data analysis due to biased responses. The total sample for analysis was 181 AAas. Table 1 provides the demographic profile of the pilot study population. Once the study's protocol was approved by school administrators, all students in grades 6-8 were asked to participate in the study.
STEP 6: SCORE EACH ITEM FOR EACH RESPONDENT
Each item was scaled as having a positive or negative weight. Five answer choices were provided: "strongly agree," "agree," "neither disagree nor agree," "disagree," and "strongly disagree." Items received a score of 1-5, with 3 representing "neither agree nor disagree." "Strongly agree" and "agree" received a score of 5 and 4, respectively, for each positively scored item. For negatively scored items "strongly disagree" or "disagree" received a 1 and 2, respectively.
STEP 7: SUM RESPONDENTS' ITEM SCORES
Table 2 shows the mean score, standard deviation, and the minimum and maximum scores for respondents in each construct. The behavioral beliefs construct measured the positive or negative value students placed on listening to sexually-oriented music lyrics for advice about sexual activities. The subjective norms construct measured the social pressure students perceived for participating in sexual activities. The behavioral intention construct measured students' intention to participate in sexual activities or to have sexual intercourse. Positive responses toward the attitudinal object received a high score, and negative responses toward the attitudinal object received a low score.
STEP 8: CORRELATE ITEMS WITH TOTAL SCALE
SCORES FOR ALL RESPONDENTS
Item scores were correlated with total scores one at a time. Item scores with total correlation and the alpha if each item is deleted can be attained by contacting the lead author.
Results of the initial factor analysis identified items that loaded on 4 components. According to Ajzen and Fishbein (1980), correlations of .30-.50 are acceptable; however, correlations of .50 or higher indicate a strong relationship among variables. Therefore, items not loading at .40 or higher were deleted from the scale. One (n = 1) behavioral belief item was deleted as a result of the initial factor analysis. Item scores were correlated with total scores for each of the identified subscales. No items were deleted from subscale 1 as the minimum correlation among items in the scale was .40. No items were deleted from subscale 2 as the minimum correlation among items in the scale was .78. One (n = 1) item was deleted from subscale 3 due to a weak correlation among the other items. Remaining items in subscale 3 had a minimum correlation among items of .46. Two (n = 2) items were deleted from subscale 4 due to a weak correlation among the other items. Remaining items in subscale 4 had a minimum correlation among items of .54. Contact the lead author for item scores with total correlation and the alpha if each item is deleted for the subscales.
Item discrimination analyzed the data for frequencies of responses on each item. Mainly items were observed for clustering of responses. Items where responses were clustered on either end of the scale with little range in responses were deleted. No items were deleted using this method.
STEP 9: APPLY STATISTICAL CRITERIA FOR ELIMINATION OF TEST ITEMS
Data analysis consisted of factor analysis, descriptive statistics, item response discrimination, and Cronbach's alpha to determine internal consistency. Factor analysis was used to examine the pilot data for patterns, and to eliminate insignificant variables. The initial factor analysis resulted in the deletion of 1 item. Reliability tests were performed on the identified subscales from the initial factor analysis. As indicated above, 1 item was deleted from subscale 3, and 2 items were deleted from subscale 4. Therefore, a total of 4 items were deleted from the scale. As a follow up measure, factor analysis and reliability tests were performed a second time. Factor analysis was set to extract 4 components. Table 3 depicts the results of the factor loadings of items included in the final scale and the corresponding alpha. All items loaded at .49 or higher on a minimum of 1 of the identified subscales.
The survey consists of 27 total items and explains 63.3% of the variance. Cronbach's [alpha] after all items were deleted was .846. Items in subscale 1 and 2 explained 40.7% of the variance. Subscale 1 had an a of .930, and subscale 2 had a corresponding [alpha] of .946. Subscale 3 accounted for 15.3%, and subscale 4 accounted for 7.3% of the variance. Reliability statistics were performed on subscales 3 and 4 after items were deleted. Cronbach's a for subscale 3 was .831, and the [alpha] for subscale 4 was .722. Sub-analysis showed the survey is a reliable measure among adolescents in the study. Reliability statistics reported an alpha of [greater than or equal to].70 for participants by grade, gender, and study site.
The survey is currently the only such instrument developed specifically to predict the influence of sexually-oriented music lyrics on the sexual attitudes, beliefs, and intentions of African-American adolescents. This is timely, given that research has identified factors such as gender, race and ethnicity, environment, age, and attitudes as contributors to sexual behaviors of adolescents (Manlove, Terry-Humen, Papillo, Franzetta, Williams, & Ryan, 2002). One specific factor that led to the development of the survey is the largely unexplored and rapidly growing area of media and its inluence on the sexual attitudes and behavior of AAas, specifically through exposure to sexually-oriented music lyrics. The survey was developed to address several of the limitations in this area and is a response to calls to action from the literature. The following will highlight the survey development in light of gaps in the literature, and how it offers contributions to the literature.
1. The survey was developed based on a theoretical framework (TRA) and following specific protocol set forth by TRA developers Fishbein and Ajzen in a survey utilizing his theory.
2. The survey was developed for those in early adolescence. Survey development completed in stages 1, 4, and 5 of this study ensured that the survey was sensitive to and representative of the attitudes and beliefs of AAas who were demographically in the 6th, 7th, and 8th grades. Stanton and colleagues (1995) completed similar processes in efforts to develop and validate a culturally appropriate instrument to measure the impact of an AIDs intervention for early AAas.
3. Third, the survey was developed for an at-risk adolescent population. The survey was developed specifically for at risk AAas from a rural and urban background. Special attention was given in the developmental processes to ensure the instrument was culturally appropriate.
4. The survey was developed specifically to assess the positive or negative value AAas place on the significance of sexually-oriented music lyrics, and whether attitudes related to sexually-oriented music lyrics inluence their sexual intentions and subsequent behavior.
5. Finally, the survey was developed to examine the influence of sexually-oriented music lyrics. Previous research has focused on the influence of television programming; the SPISOML-AAA is the first to provide a valid and reliable instrument designed to assess the influence of sexually-oriented music lyrics delivered via a media source.
VALIDITY AND RELIABILITY
Analyses conducted to test the reliability and validity replicated methods of previous researchers who had used a similar survey development process (Perko, 1996; Stanton, Black, Feigelman, Ricardo, Galbraith, Li, Kaljee, Keane, and Nesbitt, 1995). Validity of the instrument was assessed through measures of face and construct validity. Identified subscales were developed through discriminate and convergent validity. The survey went through a rigorous review process and was reviewed by a panel of experts in the fields of adolescent sexual health, communication, and health education theory. Questions not deemed a valid measure by the expert panel were deleted. The survey was also tested for construct validity. Construct validity was assessed by examining the item correlations within the instrument. Items correlated highly with one another on the identified scales indicating each item was a validate measure.
Consistent with discriminant validity, the weak items in the subscales did not correlate highly with the other items. Meaning, the lower loading items were not measuring what they were developed to measure as well as the other items. Therefore, the weak items were deleted. After weak items were eliminated from the subscales, the item correlations increased. This was an indication of higher internal consistency among the remaining items. This effect was consistent with convergent validity, in which measures correlate well with items that they are supposed to. Items in the new subscales had higher correlations. It is important that the validity of the survey is established as it would not be beneficial if the instrument was not measuring what it was developed to measure (Windsor, Baranowski, Clark, and Cutter, 1994). Thus, it is concluded that the survey is a valid measure. Equally important was testing the reliability.
Reliability of the instrument was assessed through Item response discrimination, factor analysis, and Cronbach's alpha. Item response discrimination was assessed by examining the frequencies of responses for each item. This procedure compared adolescents scoring high on an item to those scoring low on an item. No items were eliminated through this procedure as an appropriate range of responses was observed for each item.
Factor analysis was used to examine data for patterns, and to eliminate insignificant items from the instrument. Factor analysis indentified items that loaded on 4 subscales. Visual review of the Scree plot distinctly identified 4 scales; however, data became distorted after the 4th component. Although methods were used to prevent cross loadings, some cross loadings were observed. The distortion after the fourth component and cross loadings could be attributed to the small sample size in the study. Items that did not load on 1 of 4 identified subscales were deleted. One (n = 1) attitude item from the behavioral belief construct, "I would listen to sexually-oriented music lyrics to know what sexual activities people do" loaded at .397 and was deleted from the scale. The remaining items loaded at .430-.861, indicating moderate to strong relationships among items. Reliability statistics were conducted after the item was deleted to determine the reliability of the remaining items. The Cronbach's alpha was .846 indicating a highly reliable scale. Subsequent analyses were performed on the identified subscales.
Analyses were completed on the subscales to determine the internal consistency of the identified scales. Cronbach's alpha is also a method of testing the reliability of the subscales. For this method a subscale that did not report a Cronbach's alpha of .70 was not considered a reliable scale. Item correlations of .40 or greater indicates a moderate to strong relationship among the items in the subscale, and can be considered valid measures of the scale. Subscale 1 consisted of items from the social norm construct of the TRA, specifically, all items (n=10) that measured the variable of motivation to comply. One (n=1) item loaded at .405 in subscale 1 indicating a moderate relationship among the other items. All other items loaded at .600-.833 indicating a strong relationship among the items. This indicates subscale 1 is a valid subscale. Furthermore, the Cronbach's alpha for subscale 1 was .930. This indicated that subscale 1 is a highly reliable subscale. Thus, it is concluded that subscale 1 is a valid and reliable measure of social norms.
Likewise, subscale 2 consisted of items from the social norm construct, more specifically, 6 items developed to measure significant others loaded on component 2. Items in subscale 2 loaded at .783 -.896, indicating a strong relationship among the items. Subscale 2 is considered a valid measure. The Cronbach's alpha for subscale 2 was .946. Subscale 2 is also considered a highly reliable subscale. It is concluded that subscale 2 is a valid and reliable measure of social norms.
Subscale 3 consisted of items developed to measure intentions, behavioral beliefs, and social norms. Both of the intention items loaded on component 3 along with the remaining items (n = 5) from social norms, and 3 behavioral belief items. An item developed to measure attitudes, "I would listen to sexually-oriented music lyrics for advice about sexual activities," loaded at .383 and was deleted from the scale. The remaining items loaded between .466 and .627, indicating moderate to strong relationship among the items. The remaining items in subscale 3 are valid measures. It is important to note that due to the cross loading, it is unclear as to what construct these items are measuring. The Cronbach's alpha for subscale 3 was . 831. This indicates subscale 3 is a highly reliable measure. Subscale 3 is considered a valid and reliable subscale, but it is unclear as to which construct the items are measuring.
Subscale 4 consisted of items developed to assess behavioral beliefs. Four (n=4) items developed to measure the outcome evaluation loaded on component 4. Two (n = 2) items, "It is important to know what sexual activities other people do," and "It is important to relax my mind" loaded at .380 and .300, respectively and were deleted from the scale. The remaining items loaded at .546 and .598 indicating a strong relationship among the items. The remaining items in subscale 4 are considered valid items. The Cronbach's alpha for subscale 4 was .722. Thus, subscale 4 is considered a reliable subscale. Subscale 4 is considered a valid and reliable measure of behavioral beliefs.
Factor analysis was rerun using only those items not deleted in the aforementioned analyses. The second factor analysis consisted of 27 items (31 items were in initial factor). This analysis was completed to determine if the reliability would increase with the deletion of the 4 items. All items in the scale loaded at .493-.912, indicating a moderate to strong relationship among the items. The survey is a valid measure. The Cronbach's alpha remained the same at .846. The survey is a valid and highly reliable measure.
Initial factor analysis showed the survey (n = 30) explained 58% of the variance. Subsequent factor analysis showed the survey (n = 27) accounted for 63.3% of the variance. Collectively, subscales 1 (22.7%) and 2 (18%) consisted of social norm items and explained 40.7% of the variance. Subscale 3 consisted of items from all 3 constructs and accounted for 15.3%. Further, subscale 4 consisted of behavioral beliefs and accounted for 7.3% of the variance. It is concluded, based on the methods employed, the survey is both a valid and reliable scale for measuring the influence of sexually-oriented music lyrics on the attitudes, beliefs, and intentions of AAas.
LIMITATIONS OF STUDY
This study had several limitations. The sample size (n = 181) was smaller than had hoped. It was anticipated that a minimum of 300 students of the total available student populations would participate in the study. Other researchers have noted challenges in recruiting meaningful sample sizes when active parental consent was required in school-based studies. However, the response rate for this study (17%) was smaller compared to similar type studies that reported response rates of 50% and 62% (LaGreca & Harrison, 2005; Markham, Peskin, Addy, Baumler, & Tortolero, 2009). The small sample may have prevented all items from distinctively loading on 1 of the identified subscales. Subscale 3 had items from all constructs; this may have been avoided with a larger study sample. Another factor that may have contributed to the low response rate was lack of an incentive for participation in the pilot study.
Another limitation of this study may have been social desirability. According to Gehlbach (1993) participants respond in a way they think is correct as opposed to how they really feel. Although measures were taken to prevent this in the focus group interviews, some participants may have provided inaccurate responses, thus leading to biased data concerning attitudes, beliefs, and influences as related to music lyrics and sexual intention. Further, social desirability could have impacted the way students responded to questions when completing the SPISOML-AAA. This could have resulted in over or under reporting of responses in the survey.
The fact that this was a school-based study, the sensitive nature of the topic presented a limitation. In considering the population studied and sensitive nature of the topic, researchers were cautious when developing the focus group questions. As discussed earlier, the questions that did not load in the scale were behavioral belief questions. This could be attributed to the conservative tone in which the researchers had to adhere to when assessing AAas attitudes and beliefs about the influences on sex. The researchers were limited as to how questions concerning sex were asked. According to Ajzen and Fishbein (1980) if the attitudes of the target are not thoroughly discussed weak measures may result. However, the SPISOML-AAA did prove to be a valid and reliable instrument.
Although the survey was developed according to the purpose of the study, the results of the study are not generalizable to the total adolescent population. Thus, the SPISOML-AAA may not be a valid and reliable measure for majority and other minority adolescent populations from differing backgrounds.
Finally, researchers were unable to physically administer the SPISOML-AAA in 2 of the 5 study sites. Thus, the surveys were administered by the school counselors. Therefore, the data collection methods were not monitored equally at all study sites.
Adolescents spend an average of 5 hours and 30 minutes a day utilizing media. Media use increases to 8 hours and 30 minutes when you consider the multiple mediums adolescents use simultaneously (Rideout, Roberts, & Foehr, 2005). While this study addresses the influence of sexually-oriented music lyrics on early sexual initiation among African-American adolescents, much is left to be done. The influx of new technological devices allows adolescents immediate media access. The influence and use of new technologies must be investigated and understood. Specifically, it was recommended that the influence of mass media should receive increased attention from future researchers seeking to reduce risky sexual behavior among adolescents (L'Engle, Brown, and Kenneavy, 2006).
RECOMMENDATIONS FOR FURTHER RESEARCH
The significance, implications, and recommendations related to the use of this newly-created survey are interrelated and will be examined using research recommendations which have been the basis for national recommendations and polices. The following organizations (AAP, 1996 & 2009; National Adolescent Health Information Center, 1997 & 2000) and leading researchers (Brown, L'Engle, Pardun, Guang, Kenneavy, & Jackson, 2006; Escobar-Chaves, 2005; Kirby, 2001 & 2007) have suggested, among other recommendations, that future research
1. Investigate the effects of music lyrics on adolescents' sexual attitudes and behaviors.
2. Include early and at risk adolescents.
3. Refine data collection methods.
4. Conduct longitudinal studies to determine the influence of sexual media.
5. Include theory in intervention methods. Now that the survey (SPISOML-AAA) has been developed and has shown to be reliable, a longitudinal database can be established. Recommendations for establishing a database are listed below.
Data should be gathered, using the SPISOML-AAA, from AAas in both urban and rural geographic regions. Escobar-Chaves and colleagues (2005) called for the inclusion of at-risk populations in future research seeking to explain the influence media has on the sexual attitudes and behaviors of adolescents.
Studies should be conducted using the SPI-SOML-AAA controlling for a variety of independent variables such as gender, socioeconomic status, music preference, significant others, geographic region, age, and ethnicity. The benefits of these studies may assist in identifying those variables that influence AAas sexual attitudes, beliefs, and behavioral intentions. Currently, the lack of longitudinal studies examining the influence of sexual media on subsequent behavior has resulted in limited knowledge concerning the influence media has on adolescents' sexual behaviors (Brown, 2002; Brown & Witherspoon, 2002; Escobar-Chaves, 2005; Fine, Mortimer, & Roberts, 1990; Gruber & Grube, 2000; Harris & Scott, 2002; Strasburger & Donnerstein, 1999).
The next recommendation includes the design and implementation of intervention methods that influence the two major constructs of the TRA: subjective norms and attitudes toward the behavior. Escobar-Chaves and colleagues (2005) recommended future research examine mediating variables such as peers and family dynamics on the sexual attitudes of adolescents. Studies should be conducted to assess the influence of significant others on subjective norms, and studies should focus on specific attitudinal differences among AAas. Brown and colleagues (2006) concluded that more research is needed to understand the relationship between exposure to sexual media content and adolescents' sexual attitudes and behaviors (Brown, L'Engle, Pardun, Guang, Kenneavy, & Jackson, 2006). For the controlled intervention trials, the SPISOML-AAA serves as the instrument to measure behavioral intentions, attitudes towards the behavior, and subjective norms. The results of the controlled intervention will be to add to a database. Millstein and colleagues (2000) recommended future research should increase diversity of study populations, and conduct theory based longitudinal studies.
Defined population studies include the implementation of successful interventions with identified populations of AAas. Researchers recommend future research should include younger adolescents, and adolescents from low SES (Escobar-Chaves, Tortolero, Markham, Low, Eitel, & Thickstun, 2005; Millstein, Ozer, Ozer, Brindis, Knopf, & Irwin, 2000). Educational intervention activities should be conducted based on the results of SPISOML-AAA administrations. These should be conducted to determine those activities most effective for educators in developing a national agenda to support the various organizations calling for education regarding potential risks of sexually-oriented music lyrics on AAas. Brindis and colleagues (1997) recommended future research should provide intervention that focus on the needs of adolescents.
The implementation of controlled intervention trials that focus on the constructs of the TRA would elicit further validation of the SPISOML-AAA. Escobar-Chaves and colleagues (2005) recommended future research should refine methods used to measure exposure to sexual content in the media. Some recommendations for further study would include, but not be limited to assessing the impact of an educational intervention on the influence of sexually-oriented music lyrics on the behavioral intent of AAas. And, assessing the impact of a media campaign related to sexually-oriented music lyrics on attitudes and behavioral intent of AAas.
Lastly, additional applications of the SPISOML-AAA should concentrate on adding weights to the items in each construct as put forth by the TRA to determine the strength of relationships as they lead to behavioral intentions and, ultimately, behavior. Millstein and colleagues (2000) recommended future research should use valid measurement tools.
This valid and reliable instrument (the SPISOML-AAA) is likely to benefit those groups of individuals who are responsible for the well-being of AAas; most specifically, but not limited to the parents/guardians, educators, physicians, music artists, and the community as a whole. Researchers have suggested that interventions addressing risky sexual behaviors among adolescents must include cultural and economic measures, be theoretically grounded, and comprehensive in nature (Escobar-Chaves & Anderson, 2008; Kirby, 2007). Furthermore, future research should be conducted to determine the impact of music lyrics on early adolescents (Committee on Communications, 1996; Council on Communications and Media, 2009).
Trends have changed as adolescents now prefer MP3 players instead of radio and CDs for music consumption (Nielsen, 2009). With the growing array of mobile digital devices, adolescents will have unlimited means for accessing media in an instant. Current research lags behind media innovations in terms of examining the influence of new mediums. It is unlikely that innovations will halt as consumers demand immediate media access from anywhere (Bhatia, 2009). As early adolescents are likely to receive sexual messages from media sources, tailored interventions are crucial for addressing potential in luences of the media on AAas' sexual risk behaviors. The media deserves substantial focus when addressing adolescent risky sexual behaviors (CDC, 2004).
Abma, J., Driscoll, A., & Moore, K., (1998). Young women's degree of control over first intercourse: An explanatory analysis. Family Planning Perspectives, 30, (1), 12-18.
Ajzen, I. (1988). Attitudes, personality, and behavior. Chicago: Dorsey Press.
Ajzen, I. & Fishbein, M. (Eds.) (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ. Prentice-Hall.
Allen, M., Herrett-Skjellum, J., Jorgenson, J., Ryan, D. J., Kramer, M., & Timmerman, L. (2007). Effects of Music. In Preiss, R., Gayle, B., Burrell, N., Allen, N., & Bryant, J.(Eds.). Mass Media Effects Research: Advances Through Meta-Analysis (pp.263-279). Meahwah, NJ: Lawrence Erlbaum Associates, Inc.
Bandura, A. (1962). "Social Learning Through Imitation." In M. R. Jones (Ed.). Nebraska Symposium on Motivation, Vol. 10. Lincoln, Nebraska: University of Nebraska Press.
Bhatia, M. (2009). You can Take It with You: Future Trends in Media. Nielsen. Accessed 2-26-10, Available at http:/blog.nielsen.com/nielsenwire/online_mobile/you-can-take-it-with-you-future-trends-...
Brewster, K. L., Billy, J. O. G., & Grady, W. R. (1993). Social context and adolescent behavior: The impact of community on the transition to sexual activity. Social Forces, 71, (3), 713-740.
Brindis, C. D., Irwin, C. E., Jr., Ozer, E. M., Handley, M., Knopf, D. K., Millstein, S. G. (1997). Improving Adolescent Health: An Analysis and Synthesis of Health Policy Recommendations. San Francisco, CA: University of California, San Francisco. National Adolescent Health Information Center.
Brown, J. D. (2002). Mass media influences on sexuality. The Journal of Sex Research, 39, (1), 42-47.
Brown, J. D., Childers, K., Bauman, K., & Koch, G. (1990). The influence of new media and family structure on young adolescents' television and radio use. Communication Research, 17, 65-82.
Brown, J. D., L'Engle, K. L., Pardun, C. J., Guang, G., Kenneavy, K., & Jackson, C. (2006). Sexy Media Matter: Exposure to Sexual Content in Music, Movies, Television, and Magazines Predicts Black and White Adolescents' Sexual Behavior. Pediatrics, 117, (4), 1018-1027.
Brown, J. D. & Witherspoon, E. M. (2002). The Mass Media and American Adolescents' Health. Journal of Adolescent Health, 31, (6S), 153-170.
Centers for Disease Control and Prevention [CDC]. (2004). National Center for Chronic Disease Prevention and Health Promotion, Division of Adolescent and School Health; Health Resources and Services Administration, Maternal and Child Health Bureau, Office of Adolescent Health; National Adolescent Health Information Center, University of California, San Francisco. Improving the Health of Adolescents & Young Adults: A Guide for States and Communities. Atlanta, GA.
Committee on Communications. (1996). Impact of Music Lyrics and Music Videos on Children and Youth. Pediatrics, 98, 1219-1221.
Council on Communications and Media. (2009). Impact of Music, Music Lyrics, and Music Videos on Children and Youth. Pediatrics, 124, 1488-1494.
Escobar-Chaves, S. L. (2005). Introduction. Pediatrics, 116, (1), 301-302.
Escobar-Chaves, S. L., & Anderson, C. A. (2008). Media and Risky Behaviors. The Future of Children, 18, (1), 147-180.
Escobar-Chaves, S. L., Tortolero, S. R., Markham, C. M., Low, B. J., Eitel, P., & Thickstun, P. (2005). Impact of the Media on Adolescent Sexual Attitudes and Behaviors. Pediatrics, 116, (1), 303-326.
Feldman, S. S., & Elliott, G. R. (Eds.). (1990). At the Threshold: The Developing Adolescent. Cambridge, MA and London, ENG: Harvard University.
Fine, G. A., Mortimer, J. T., & Roberts, D. F. (1990). Leisure, Work, and the Mass Media. In Feldman, S. S. & Elliott, G. R. (Eds.). At the Threshold: The Developing Adolescent (pp. 225-252). Cambridge, MA and London, ENG:Harvard University.
Greenberg, B., Ku, L., & Li, H. (1989). Young people and their orientation to the mass media: An international study. Study 2: United States. East Lansing: Michigan State University, College of Communication Arts.
Gruber, E. & Grube, J. W. (2000). Adolescent sexuality and the media: A review of current knowledge and implications. West J Med., 172, (3), 210-214.
Hall, P. D. (1998). The Relationship Between Types of Rap Music and Memory in African American Children. Journal of Black Studies, 28, (6), 802-814.
Harris, R. J. & Scott, C. L. (2002). Effects of Sex in the Media. In Bryant, J. & Zillmann, D. (Eds.). Media Effects: Advances Theory and Research (2nd ed., pp. 307-331). Meahwah, NJ: Lawrence Erlbaum Associates, Inc.
Hirsch, P. (1971). Sociological approaches to the popular music phenomenon. American Behavioral Scientist, 14, 371-388.
Hogan, D. P., & Kitagawa, E. M. (1985). The impact of social status, family structure, and neighborhood on the fertility of black adolescents. American Journal of Sociology, 90, 825-855.
Kirby, D. (2001). Emerging Answers: Research Findings on Programs to Reduce Teen Pregnancy (Summary). Washington, DC: National Campaign to Prevent Teen Pregnancy.
Kirby, D. (2007). Emerging Answers: Research Findings on Programs to Reduce Teen Pregnancy and Sexually Transmitted Diseases. Washington, DC: National Campaign to Prevent Teen and Unplanned Pregnancy.
L'Engle, K. L., Brown, J. D., & Kenneavy, K. (2006). The mass media are an important context for adolescents' sexual behavior. Journal of Adolescent Health, 38, 186-192.
Manlove, J., Terry-Humen, E., Papillo, A., Franzetta, K., Williams, S., & Ryan, S. (2002). Preventing Teenage Pregnancy, Childbearing, and Sexually Transmitted Diseases: What the Research Shows. Child Trends, Research Brief, Washington, DC.
Martino, S. C., Collins, R. L., Elliott, M. N., Strachman, A., Kanouse, D. E., & Berry, S. H. (2006). Exposure to Degrading Versus Nondegrading Music Lyrics and Sexual Behavior Among Youth. Pediatrics, 118, 430-441.
Miller, B. C., Norton, M. C., Curtis, T., Hill, E. J., Schvaneveldt, P., & Young, M. H. (1997). The timing of sexual intercourse among adolescents: Family, peer and other antecedents. Youth and Society, 29, (1), 54-83.
Millstein, S. G., Ozer, E. J., Ozer, E. M., Brindis, C. D., Knopf, D. K., & Irwin, C. E. Jr. (2000). Research Priorities in Adolescent Health: An Analysis and Synthesis of Research Recommendations, Executive Summary. San Francisco, CA: University of California, San Francisco. National Adolescent Health Information Center.
Mueller, D. J. (1986). (Ed.). Measuring Social Attitudes: A Handbok for Researchers and Practitioners. New York, NY: Teachers College Press.
Nielsen. (2009). How Teens Use Media: A Nielsen report on the myths and realities of teen media trends. The Neilsen Company.
Pardun, C. J., L'Engle, K. L., & Brown, J. D. (2005). Linking Exposure to Outcomes: Early Adolescents' Consumption of Sexual Content in Six Media, Mass Communication & Society, 8, (2), 75-91.
Perko, M. A. (1996). Development of an instrument to assess intentions, attitudes, and beliefs of adolescent athletes regarding dietary supplements. Ph.D. dissertation, The University of Alabama, United States--Alabama. Retrieved February 5, 2008, from Dissertations & Theses @ University of Alabama database. (Publication No. ATT 9633979).
Primack, B., Gold, M., Schwarz, E., & Dalton, M. (2008). Degrading and Non-Degrading Sex in Popular Music: A Content Analysis. Public Health Reports, 123, 593-600.
Prinsky, L. E. & Rosenbaum, J. L. (1987). "Leer-ics" or Lyrics: Teenage impressions of rock 'n' roll. Youth & Society, 18, (4), 384-397.
Raine, T. R., Jenkins, R., Aarons, S. J., Woodard, K., Fairfax, J. L., El-Khorazaty, M. N., et al. (1999). Sociodemographic correlates of virginity in seventh-grade Black and Latino students. Journal of Adolescent Health, 24, 304-312.
Rice, R. (1980). The content of popular recordings. Popular Music and Society, 7, 140-158.
Rideout, V., Roberts, D., & Foehr, U. (2005). Generation M: Media in the Lives of 8-18 Year-olds, Executive Summary, Kaiser Family Foundation, Menlo Park, CA.
Roberts, D. F., & Christenson, P. G. (2001). Popular Music in Childhood and Adolescence. In Singer, D. G. & Singer, J. L. (Eds.). Handbook of Children and the Media. (pp. 395-413). Thousand Oaks, CA.: Sage Publications, Inc.
Roberts, D. F., & Henriksen, L. (1990). Music listening vs. television viewing among older adolescents. Paper presented at the annual meetings of the International Communication Association, Dublin, Ireland.
Santelli, J. S., Lowry, R., Brener, N. D., & Robin, L. (2000). The association of sexual behaviors with socioeconomic status, family structure, and race/ethnicity among U.S. adolescents. American Journal of Public Health, 90, (10), 1582-1588.
Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325-343.
Shrier, L. (2004). Sexually transmitted diseases in adolescents: Biologic, cognitive, psychologic, behavioral, and social issues. Adolescent Medicine Clinics, 15, (2), 1-15.
Stanton, B., Black, M., Feigelman, S., Ricardo, I., Galbraith, J., Li, X., et al. (1995). Development of a Culturally, Theoretically and Developmentally Based Survey Instrument for Assessing Risk Behaviors among African-American Early Adolescents living in urban low-income neighborhoods. AIDS Education and Prevention, 7, (2), 160-177.
Strasburger, V. C., & Donnerstein, E. (1999). Children, Adolescents, and the Media: Issues and Solutions. Pediatrics, 103, (1), 129-139.
Sucoff, C. A., & Upchurch, D. M. (1998). The neighborhood context and the risk of childbearing among metropolitan-area black adolescents. American Sociological Review, 63, (4), 571-585.
Walsh-Childers, K., & Brown, J. D. (1993). Adolescents' acceptance of sex-role stereotypes and television viewing. In Greenberg, B. S., Brown, J. D., Buerkel-Rothfuss, N. L. (Eds.). Media, sex, and the adolescent. (pp. 117-133). Cresskill, NJ: Hampton Press.
Wartella, E., Heintz, K. E., Aidman, A. J., & Mazzarella, S. R. (1990). Television and beyond: Children's video media in one community. Communication Research, 17, (1), 45-64.
Windsor, R., Baranowski, T., Clark, N., & Cutter, G. (2nd ed.). (1994) Evaluation of Health Promotion Health Education and Disease Prevention Programs. California: Mayfield Publishing Company.
Brian C. Gordon, PhD, MCHES
Mike A. Perko, PhD, MCHES, FAAHE
Lori W Turner, PhD, RD
James D. Leeper, PhD
Stuart L. Usdan, PhD
Samory T. Pruitt, PhD
Brian C. Gordon, PhD, MCHES, is affiliated with the Department of Health Science, The University of Alabama, 206 East Annex, Box 870311, Tuscaloosa, AL 35487-0311, (205) 348-8366, Fax (205)348-7568, Email: email@example.com. Mike A. Perko, PhD, MCHES, FAAHE, is affiliated with the Department of Public Health Education, University of North Carolina, Greensboro. Lori W. Turner, PhD, RD, is affiliated with the Department of Health Science, The University of Alabama. James D. Leeper, PhD, is affiliated with the Rural Medicine, The University of Alabama. Stuart L. Usdan, PhD, Associate Dean for Graduate Studies, Research, & Development, The University of Alabama. Samory T. Pruitt, PhD, is affiliated with the Community Affairs, The University of Alabama.
Table l: Demographics of Survey to Predict the Influence of Sexually-Oriented Music Lyrics on African-American Adolescents Pilot Study Sample Students (n = 181) Where do you live? Number Percent (%) Rura 77 42.8 Urban 103 57.2 How old are you? 11 years old 40 22.1 12 years old 62 34.3 13 years old 54 29.8 14 years old 25 13.8 What is you sex? Male 75 41.9 Female 104 58.1 In what grade are you? 6th grade 68 38.0 7th grade 65 36.3 8th grade 46 25.7 What is your race? Black 174 98.3 Mixed 3 1.7 Are you Hispanic or Latino? Yes 3 1.7 No 172 98.3 Which of the following do you live with? Mother Only 94 53.4 Father Only 2 1.1 Mother and Father 59 33.5 Other(Grandparent/s, Aunt/Uncle, legal Guardian, Foster Parent) 21 11.9 Which of the following relatives do you live with? Older brother and/or 72 41.4 sister Older step/half brother 8 4.6 and/or sister Older cousin 5 2.9 None of the above 89 51.1 How many people do you live with? 1-2 people 37 20.8 3-4 people 82 46.1 5-6 people 45 25.3 7 or more people 13 7.3 Do you take part in the following lunch plans at school? Free lunch 152 85.4 Reduced lunch 12 6.7 Full pay 14 7.9 About how much music do you listen to or watch during the week (Monday-Friday)? 2 or less hours 61 34.9 3-5 hours 46 25.4 6-8 hours 20 11.4 9 or more hours 48 27.4 About how much music do you listen to or watch during the weekend (Saturday-Sunday)? 8 or less hours 121 69.9 9-11 hours 22 12.7 12-14 hours 9 5.2 15 or more hours 21 12.1 Have you ever had sexual intercourse? Yes 28 15.9 No 148 84.1 Note. Total number and percentages may not equal to 181 due to missing responses. Table 2. Mean, Standard Deviation (SD), and Range of scores of the Survey to Predict the Influence of Sexually-Oriented Music Lyrics on African-American Adolescents, by construct. Construct N Mean SD Range Behavioral Beliefs 176 2.8594 .85300 1.00-4.75 (4 items) Social Norms 150 3.1213 .70832 1.00-4.86 (21 items) Intentions 177 1.9040 1.08021 1.00-5.00 (2 Items) Table 3. Final Factor Analysis-Survey to Predict the Influence of Sexually-Oriented Music Lyrics on African-American Adolescents (n = 27 items), Factor Loadings Component Item 1 2 3 4 I would listen to .513 sexually-oriented music lyrics for advice about girl/boyfriend relationships. I would listen to .613 sexually-oriented music lyrics to relax my mind. My close friends .642 think it is okay to listen to sexually-oriented music lyrics for advice about sexual activities. My close friends .577 think it is okay to try sexual activities that are talked about in songs. My older brother .853 or sister would approve of me trying sexual activities talked about in songs. My cousin would .825 approve of me trying sexual activities talked about in songs. My uncle or aunt .697 would approve of me trying sexual activities talked about in songs. I plan to try .594 sexual activities in the next 2-4 weeks. I plan to have .604 sexual intercourse in the next 2-4 weeks. It is important to .686 get advice about sexual activities. It is important .723 to get advice about girl /boyfriend relationships. My mom does not .907 approve of me trying sexual activities talked about in songs. My dad does not .868 approve of me trying sexual activities talked about in songs. My guardian does .912 not approve of me trying sexual activities talked about in songs. My favorite .898 teacher does not approve of me trying sexual activities talked about in songs. My coach does .853 not approve of me trying sexual activities talked about in songs. My school .833 counselor does not approve of me trying sexual activities talked about in songs. Generally .766 speaking, I want to do what my mom wants me to do. Generally .807 speaking, I want to do what my dad wants me to do. Generally .825 speaking, I want to do what my guardian wants me to do. Generally .819 speaking, I want to do what my favorite teacher wants me to do. Generally .813 speaking, I want to do what my coach wants me to do. Generally .829 speaking, I want to do what my school counselor wants me to do. Generally .493 speaking, I want to do what my close friends wants me to do. Generally .757 speaking, I want to do what my older brother or sister wants me to do. Generally .707 speaking, I want to do what my cousin wants me to do. Generally .867 speaking, I want to do what my uncle or aunt wants me to do. Cronbach's [alpha] SPISOML-AAA= .846, Cronbach's [alpha] subscale 1= .930, Cronbach's [alpha] subscale 2= .946, Cronbach's [alpha] subscale 3= .831, Cronbach's [alpha] subscale 4= .722
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