-
The present cross-sectional study obtained ethical approval by the ethical committee of China (NCAIDS) and was conducted in Guangzhou and Harbin in September 2015. These particular two cities were selected as study sites because of the yearly increase of HIV-infection rates in college students, and the fact that they are an example of a typical city in Northern and Southern China. Guangzhou, the provincial capital of Guangdong province in south China, has a total of over 100 universities. In 2012, the proportion of new cases among the college student in Guangzhou was five times that of 2002[35]. Similarly, AIDS has rapidly spread among college students in Harbin, the provincial capital of Heilongjiang. In Harbin, the new cases of young students in 2015 were almost three times higher than 2013[36]. In the present survey, a total of 3, 081 students, aged 17-21 years, were recruited from seven universities and the response rate was 96.5%.
-
Two-stage cluster sample design was used in the current study. In the first stage, seven universities were randomly sampled from Guangzhou and Harbin. In China, the major subjects of the first-grade students are the public basic courses; thus, the HIV awareness would not be affected by the specialized knowledge among freshmen. We randomly selected three classes in the first grade within each university and obtained informed consent from all students before the survey. All students were informed regarding the voluntary nature of participation, and those who did not complete the questionnaires for various reasons were excluded. Students who were willing to participate in this survey completed an anonymous questionnaire written in Chinese at an appointed classroom.
-
On the basis of the construct of the integrated model, we developed a structured self-administered questionnaire. The original items pool was compiled by performing a literature review and consulting experts from health education, psychology, communications, and epidemiology. The final version of the questionnaire was created following numerous rounds of amendments. It consisted of seven aspects, including information on demographics, severity of and susceptibility to HIV, attitude to HIV health education, intent-to-premarital-sex, response efficacy, and condom-use self-efficacy. The levels of perceived severity of and perceived susceptibility to HIV were evaluated by five items according to the Perceived Risk of HIV Scale (PRHS)[37], and their Cronbach's α coefficients were 0.67 and 0.79, respectively. Condom-use self-efficacy was assessed by three items in accordance with the Condom-Use Self-Efficacy Scale (CUSES)[38] and the Cronbach's α coefficient was 0.67. As no maturity scales existed for reference, the items of response efficacy, attitude toward HIV education and intent-to-premarital-sex were formulated according to the related studies and experts' advice. The Cronbach's α coefficients were 0.55, 0.64, and 0.60, respectively. The details of the questionnaire are presented in Table 1. The answers of the questionnaire were in a scoring system: Students were asked to rate their agreement on a scale from 1 (strongly disagree) to 10 (strongly agree).
Table 1. Demographic Characteristics of Students (n=2, 973)
Characteristic N % Age < 20 2, 249 75.3 ≥20 699 23.5 Gender Male 1, 387 46.7 Female 1, 586 53.3 Survey city Guangzhou 2, 107 70.9 Harbin 866 29.1 -
SPSS 13.0 (IBM Corp, Armonk, NY, USA) was used for data process and analysis, including interpolation of missing values, description of statistics of demographic characteristics and measurements of variables, internal reliability, construct validity and Mann-Whitney U-test. IBM SPSS AMOS 17.0 (IBM Corp, Armonk, NY, USA) was used for structure equation modeling (SEM). SEM is a multi-statistics method, which fits theoretical models with sample data in two steps, as follows[39]: (ⅰ) confirmatory factor analysis (CFA) tests the fitting degree between the sample data and hypothetical construct, thus determining the structural validity; (ⅱ) path analysis, which follows a reasonable result of CFA, aims to verify the rationality of structure model and illustrate the causal link among the major latent variables. Through SEM, we could estimate coefficients of variables as well as direct, indirect, and total effects among latent variables in the regression model. Indices, including chi-square goodness-of-fit test (χ2/df), the goodness-of-fit index (GFI), the comparative fit index (CFI), and the root mean square error of approximation (RMSEA) were used to evaluate the model fitness. In general, the criteria to assess the model were: χ2/df < 5[40], GFI > 0.9, CFI > 0.9[41], and RMSEA < 0.05[42].
-
Table 1 describes the participants' demographic characteristics. Among 2, 973 valid participants, 46.7% were male and 53.3% were female. An approximate of 75.3% students were aged < 20 years, and the average age was 18.6 years (s=0.8). Finally, an approximate of seven out of 10 students were surveyed from Guangzhou.
-
Results of confirmatory factor analysis are demonstrated in Figure 2. The goodness-of-fit statistics suggested that the structural equation model could be accepted and was appropriate for the data. The standardized regression weights (factor loading) and median scores for all items are listed in Table 2. All factor loadings were above 0.45 (0.47-0.81) and statistically significant (P < 0.05), except for the response efficacy. Because the internal consistency of response efficacy was also below the conservative limitation, this variable was excluded from the subsequent analysis.
Figure 2. Confirmatory factor analysis on the integrated model (n=2, 973). Coefficients are shown above and the goodness-of-fit statistics is: χ2/df=335.4/85=3.95, P < 0.001; CFI=0.91; GFI=0.98; RMSEA=0.03. **P < 0.001, *P < 0.05.
Table 2. Factor Loadings and Median Scores
Item Factor Loading M Perceived severity 8 If you encounter a HIV-infection-risk event, you will feel fear 0.71 9 If HIV cases was detected in your school, you will feel fear 0.55 6 You regard AIDS as a terrible disease 0.70 8 Perceived susceptibility 2 Your friends may be infected with the HIV virus 0.74 3 Your friend may be a HIV carrier 0.81 2 Response efficacy 6 Using condom properly will decrease the HIV-infection risk 0.72 6 Having one sexual partner is an effective way to prevent HIV 0.53 9 Avoiding premarital sex is an effective way to prevent HIV 0.37 9 Attitude of HIV health education 8 HIV education is an effective way to prevent HIV 0.50 8 You would like to study HIV knowledge for HIV prevention 0.57 8 HIV health education is necessary for college students 0.78 10 Intent-to-premarital-sex 6 The possibility of you have sex during university 0.70 2 You approve of premarital sex 0.65 5 Condom-use self-efficacy 7 You have confidence to use a condom during sex 0.65 9 If you didn't use condom during sex, you would regret 0.70 7 If you didn't use condom during sex, you feel fear 0.47 8 -
To generate a parsimonious model, the statistically insignificant paths were removed and the final model is depicted in Figure 3. The fit indices suggested that the model was satisfied with the conservative criteria, explaining 50.6% of the variance of condom-use self-efficacy.
Figure 3. The final integrated model. The fit indexes were: χ2/df=243.3/53=4.59, P < 0.001; CFI=0.91; GFI=0.98; RMSEA=0.04. **P < 0.001, *P < 0.05.
Table 3 displays the direct, indirect, and total effect of variables on self-efficacy. Apart from the direct effect (r=0.23), perceived severity had two indirect effects on condom-use self-efficacy; i.e., through the attitude to HIV education (r=0.40) and premarital sex (r=-0.16), respectively. Consequently, the total effect of perceived severity on self-efficacy was positive and strong (0.47). However, perceived susceptibility mediated by intent-to-premarital-sex (r=0.29) had an indirect and weak impact on self-efficacy (-0.06). Furthermore, the attitude toward HIV education (r=0.49) and intent-to-premarital-sex (r=-0.31) had a strong direct effect on condom-use self-efficacy.
Table 3. Effects on Condom-use Self-efficacy
Variable Direct Effects Indirect Effects Total Effects Perceived severity 0.23 0.24 0.47 Perceived susceptibility 0 -0.06 -0.06 Attitude to HIV education 0.49 0 0.49 Intent-to-premarital-sex -0.31 0 -0.31 -
The results of the rank-sum test demonstrated that male students perceived higher susceptibility, stronger intent-to-premarital-sex and lower condom-use self-efficacy compared with the female students. The mean ranks, median and P values are presented in Table 4.
Table 4. The Mann-Whitney U-test between Male and Female Students
Variable Mean Rank Median P Male Female Male Female Perceived susceptibility 1562.6 1420.9 3 2 < 0.001 Intent-to-premarital-sex 1854.8 1165.4 6 6 < 0.001 Condom-use self-efficacy 1122.6 1805.7 7 8 < 0.001
doi: 10.3967/bes2017.013
Correlates of Condom-use Self-efficacy on the EPPM-based Integrated Model among Chinese College Students
-
Abstract:
Objective To explore the predictors of condom-use self-efficacy in Chinese college students according to the extended parallel process model (EPPM)-based integrated model. Methods A total of 3, 081 college students were anonymously surveyed through self-administered questionnaires in Guangzhou and Harbin, China. A structural equation model was applied to assess the integrated model. Results Among the participants, 1, 387 (46.7%) were male, 1, 586 (53.3%) were female, and the average age was 18.6 years. The final integrated model was acceptable. Apart from the direct effect (r=0.23), perceived severity had two indirect effects on condom-use self-efficacy through the attitude to HIV education (r=0.40) and intention to engage in premarital sex (r=-0.16), respectively. However, the perceived susceptibility mediated through the intention to engage in premarital sex (intent-to-premarital-sex) had a poor indirect impact on condom-use self-efficacy (total effect was-0.06). Furthermore, attitude toward HIV health education (r=0.49) and intent-to-premarital-sex (r=-0.31) had a strong direct effect on condom-use self-efficacy. In addition, male students perceived higher susceptibility, stronger intent-to-premarital-sex, and lower condom-use self-efficacy than female students. Conclusion The integrated model may be used to assess the determinants of condom-use self-efficacy among Chinese college students. Future research should focus on raising the severity perception, HIV-risk-reduction motivation, and the premarital abstinence intention among college students. Furthermore, considering the gender differences observed in the present survey, single-sex HIV education is required in school-based HIV/sex intervention. -
Key words:
- HIV infection /
- Condom-use self-efficacy /
- Chinese college students
-
Table 1. Demographic Characteristics of Students (n=2, 973)
Characteristic N % Age < 20 2, 249 75.3 ≥20 699 23.5 Gender Male 1, 387 46.7 Female 1, 586 53.3 Survey city Guangzhou 2, 107 70.9 Harbin 866 29.1 Table 2. Factor Loadings and Median Scores
Item Factor Loading M Perceived severity 8 If you encounter a HIV-infection-risk event, you will feel fear 0.71 9 If HIV cases was detected in your school, you will feel fear 0.55 6 You regard AIDS as a terrible disease 0.70 8 Perceived susceptibility 2 Your friends may be infected with the HIV virus 0.74 3 Your friend may be a HIV carrier 0.81 2 Response efficacy 6 Using condom properly will decrease the HIV-infection risk 0.72 6 Having one sexual partner is an effective way to prevent HIV 0.53 9 Avoiding premarital sex is an effective way to prevent HIV 0.37 9 Attitude of HIV health education 8 HIV education is an effective way to prevent HIV 0.50 8 You would like to study HIV knowledge for HIV prevention 0.57 8 HIV health education is necessary for college students 0.78 10 Intent-to-premarital-sex 6 The possibility of you have sex during university 0.70 2 You approve of premarital sex 0.65 5 Condom-use self-efficacy 7 You have confidence to use a condom during sex 0.65 9 If you didn't use condom during sex, you would regret 0.70 7 If you didn't use condom during sex, you feel fear 0.47 8 Table 3. Effects on Condom-use Self-efficacy
Variable Direct Effects Indirect Effects Total Effects Perceived severity 0.23 0.24 0.47 Perceived susceptibility 0 -0.06 -0.06 Attitude to HIV education 0.49 0 0.49 Intent-to-premarital-sex -0.31 0 -0.31 Table 4. The Mann-Whitney U-test between Male and Female Students
Variable Mean Rank Median P Male Female Male Female Perceived susceptibility 1562.6 1420.9 3 2 < 0.001 Intent-to-premarital-sex 1854.8 1165.4 6 6 < 0.001 Condom-use self-efficacy 1122.6 1805.7 7 8 < 0.001 -
[1] NCAIDS NCC. Update on the AIDS/STD epidemic in China and main response in control and prevention in December, 2015, China. J AIDS STD, 2016; 21, 2015. (In Chinese) [2] NHFPC. http://www.nhfpc.gov.cn/xcs/s3574/201504/bee34823e1343d9b6822366ac.shtml.[2015-4-10]. (In Chinese) [3] Wu Z. strategy and situation of AIDS prevention and control in school of China. Chinese Journal of School Health, 2015; 36, 1604-5. (In Chinese) [4] Dick B, Ferguson J, Ross DA. Preventing HIV/AIDS in young people. A systematic review of the evidence from developing countries. Introduction and rationale. World Health Organ Tech Rep Ser, 2006; 938, 1-13, 317-41. [5] Lin GE, Cui Y, Dong-Min LI. Cross-sectional study on AIDS/HIV related sexual behavior among students from 2010-2015. Chinese Journal of School Health, 2015; 36, 1611-3. (In Chinese) [6] Xiao YK, Wei B, Guo Ping JI, et al. Survey on the knowledge and behavior of AIDS and serological analysis among young students in Anhui Province. Chinese Journal of Disease Control & Prevention, 2013; 36, 837-40. (In Chinese) [7] Tang SK, Liu Y, Huang XM, et al. Investigation of Knowledge about STD and AIDS, Sex Attitude and Sex Behavior among Students from Several Colleges in Guangzhou. Journal of Diagnosis and Therapy on Dermato-venereology, 2014; 21, 328-32. (In Chinese) [8] Li X, Stanton B, Wang B, et al. Cultural adaptation of the focus on kids program for college students in China. Aids Educ Prev, 2008; 20, 1-14. doi: 10.1521/aeap.2008.20.1.1 [9] Cheng Y, Lou CH, Mueller LM, et al. Effectiveness of a school-based AIDS education program among rural students in HIV high epidemic area of China. J Adolesc Health, 2008; 42, 184-91. doi: 10.1016/j.jadohealth.2007.07.016 [10] Xiao Z, Noar SM, Zeng L. Systematic review of HIV prevention interventions in China: a health communication perspective. Int J Public Health, 2014; 59, 123-42. doi: 10.1007/s00038-013-0467-0 [11] Rogers RW, Cacioppo JT, Petty R. Cognitive and physiological processes in fear appeals and attitude change: A revised theory of protection motivation. Social Psychophysiology: A Sourcebook, 1983. [12] Witte KR. Preventing AIDS through persuasive communications: fear appeals and preventive-action efficacy. Ann Arbor Michigan University Microfilms International. [13] Witte K, Allen M. A Meta-Analysis of Fear Appeals: Implications for Effective Public Health Campaigns. Health Edu Behav, 2000; 27, 591-615. doi: 10.1177/109019810002700506 [14] Tannenbaum MB, Hepler J, Zimmerman RS, et al. Appealing to fear: A meta-analysis of fear appeal effectiveness and theories. Psychol Bull, 2015; 141, 178-1204. http://psycnet.apa.org/journals/bul/141/6/1178/ [15] Amsalu S. Response to HIV/AIDS prevention message: based on the extended parallel process model, BAHIR DAR university students, northwest Ethiopia. 2008. [16] Doyore F, Birhanu Z, Kebede Y, et al. Are people controlling the danger or fear for condom use as HIV/AIDS preventive message? An evaluative type of study based on extended parallel process model. Journal of AIDS Clin Res, 2013; 4. https://www.cabdirect.org/cabdirect/abstract/20143106694 [17] Doyore DJF. Evaluating Effectiveness of Abstinence Message Response for HIV/Aids Prevention and Associated Factors among Hadiya Zone College Students using Extended Parallel Process Model. South Ethiopia, 2014; 05, 3. http://search.proquest.com/openview/52cf93b9c40c10f64ccd31fa68d391fd/1.pdf?pq-origsite=gscholar&cbl=2027386 [18] Witte K. Putting the fear back into fear appeals: The extended parallel process model. Health Commun, 1992; 59, 329-49. doi: 10.1080/03637759209376276 [19] Witte K. Chapter 16-Fear as motivator, fear as inhibitor: Using the extended parallel process model to explain fear appeal successes and failures. Handbook of Communication & Emotion, 1997; 423-50. http://psycnet.apa.org/psycinfo/1997-36344-015 [20] Bandura A. Social foundations of thought and action: A social cognitive theory. Pearson Schweiz Ag, 1986. [21] Leventhal H, Watts JC, Pagano F. Effects of fear and instructions on how to cope with danger. J Per Soc Psychol, 1967; 6, 313-21. doi: 10.1037/h0021222 [22] Maddux JE, Rogers RW. Protection motivation and self-efficacy: A revised theory of fear appeals and attitude change. J Exp Soc Psychol, 1983; 19, 469-79. doi: 10.1016/0022-1031(83)90023-9 [23] Fisher JD, Fisher WA, Williams SS, et al. Empirical tests of an information-motivation-behavioral skills model of AIDS-preventive behavior with gay men and heterosexual university students. Health Psychol, 1994; 13, 238-50. doi: 10.1037/0278-6133.13.3.238 [24] Rosenstock IM. Historical Origins of the Health Belief Model. Health Educ Monogr, 1974; 2, 328-35. doi: 10.1177/109019817400200403 [25] Ajzen I, Fishbein M. Understanding attitudes and predicting social behavior. PRENTICE-HALL, 1980. [26] Cai Y, Ye X, Shi R, et al. Predictors of consistent condom use based on the Information-Motivation-Behavior Skill (IMB) model among senior high school students in three coastal cities in China. BMC Infect Dis, 2013; 13, 1-8. doi: 10.1186/1471-2334-13-1 [27] Zhihao Liu PWMH. Determinants of Consistent Condom Use among College Students in China: Application of the Information-Motivation-Behavior Skills (IMB) Model. PLoS One, 2014; 9, e108976. doi: 10.1371/journal.pone.0108976 [28] Floyd DL, Prentice-Dunn S, Rogers RW. A Meta-Analysis of Research on Protection Motivation Theory. J Appl Soc Psychol, 2000; 30, 407-29. doi: 10.1111/jasp.2000.30.issue-2 [29] Kaiyan H, Hua T. Survey on the Actuality and the Changes of Sexual Behaviors among the College Students. Journal of Neijiang Normal University, 2016; 31, 111-5. (In Chinese) [30] Gelibo T, Belachew T, Tilahun T. Predictors of sexual abstinence among Wolaita Sodo University Students, South Ethiopia. Reprod Health, 2013; 10, 1-6. doi: 10.1186/1742-4755-10-1 [31] Iriyama S, Nakahara S, Jimba M, et al. AIDS health beliefs and intention for sexual abstinence among male adolescent students in Kathmandu, Nepal: A test of perceived severity and susceptibility. Public Health, 2007; 121, 64-72. doi: 10.1016/j.puhe.2006.08.016 [32] Zhang P, Lou C, Szabin L. Analysis on Factors Influencing Adolescent Sex-related Behaviors in Shanghai City under the Structural Equation Model. Chinese Journal of Health Statistics, 2011; 28, 139-41. (In Chinese) [33] Dilorio C, Dudley WN, Soet J, et al. A social cognitive-based model for condom use among college students. Nur Res, 2000; 49, 208-14. doi: 10.1097/00006199-200007000-00004 [34] Mahoney CA. The role of cues, self-efficacy, level of worry, and high-risk behaviors in college student condom use. J Sex Edu Ther, 2015; 21, 103-16. doi: 10.1080/01614576.1995.11074141 [35] Fan LR, Li BU, Qin FJ. Epidemiological features of students living with HIV/AIDS in Guangzhou city during 2002-2012. Chinese Journal of Aids & Std, 2015; 21, 194-6. (In Chinese) [36] Yi L, Shan H, Lan Y, et al. Survey on variation trend of epidemic situation and relevant knowledge andbehavior about HIV/AIDS among Youth/Students in Heilongjiang Province. Chinese Journal of Public Health Management, 2013; 5, 562-4. (In Chinese) [37] Napper LE, Fisher DG, Reynolds GL. Development of the Perceived Risk of HIV Scale. AIDS Behav, 2012; 16, 1075-83. doi: 10.1007/s10461-011-0003-2 [38] MA LJB, PhD KHB. Development and validation of a condom self-efficacy scale for college students. J Am Coll Health, 1991; 39, 219-25. doi: 10.1080/07448481.1991.9936238 [39] Anderson JC, Gerbing DW. Structural equation modeling in practice: A review and recommended two-step approach. Psychol Bull, 1988; 103, 411-23. doi: 10.1037/0033-2909.103.3.411 [40] Fox J. Structural Equation Modeling with LISREL: Essentials and Advances by Leslie A. Hayduk: Johns Hopkins University Press. Am J Sociol, 1989; 95, 257. https://academic.oup.com/sf/article-pdf/69/1/338/6516734/69-1-338.pdf?frame=sidebar [41] Hu LT, Bentler PM. Cutoff Criteria for Fit Indexes in Covariance Structure Anaysis: Conventional Criteria versus New Alternatives. Struct Equ Modeling, 1999; 6, 1-55. doi: 10.1080/10705519909540118 [42] Mcdonald RP, Ho MH. Principles and practice in reporting structural equation analyses. Psychol Methods, 2002; 7, 64-82. doi: 10.1037/1082-989X.7.1.64 [43] Meekers D, Klein M. Determinants of condom use among unmarried youth in Yaounde and Douala Cameroon. Washington D. 2001. [44] Ndabarora E, Mchunu G. Factors that influence utilisation of HIV/AIDS prevention methods among university students residing at a selected university campus. SAHARA J, 2014; 11, 202-10. doi: 10.1080/17290376.2014.986517 [45] Bengel J, Belzmerk M, Farin E. The role of risk perception and efficacy cognitions in the prediction of HIV-related preventive behavior and condom use. Psychol Health, 1996; 11, 505-25. doi: 10.1080/08870449608401986 [46] Reed YM. Predictors of Condom Use among Middle-Income, African American Women. Dissertations & Theses-Gradworks, 2015. [47] Zang C, Guida J, Sun Y, et al. Collectivism culture, HIV stigma and social network support in Anhui, China: a path analytic model. AIDS Patient Care STDS, 2014; 28, 452-8. doi: 10.1089/apc.2014.0015 [48] Hofstede G. Cultures and organizations: software of the mind. Intercultural cooperation and its importance for survival. Adm Sci, 1991; 23, 113-9. http://www.worldcat.org/title/cultures-and-organizations-software-of-the-mind-intercultural-cooperation-and-its-importance-for-survival/oclc/558675706 [49] Jansen C, Verstappen R. Fear Appeals in Health Communication: Should the Receivers' Nationality or Cultural Orientation be taken into Account? J Intercult Commun Res, 2014; 43, 346-68. doi: 10.1080/17475759.2014.981675 [50] Setegn T, Tulu B, Takele a, et al. Correlates of Risk Perception to HIV Infection, Abstinence and Condom use among Madawalabu University Students, Southeast Ethiopia: Using Health Belief Model (HBM). Global Journal of Medical Research, 2013; 13, 24-32. https://www.researchgate.net/publication/267514987_Correlates_of_Risk_Perception_to_Hiv_Infection_Abstinence_and_Condom_use_among_Madawalabu_University_Students_Southeast_Ethiopia_Using_Health_Belief_Model_HBM [51] Eileen SAED, Wagstaff DA, Heckman TG, et al. Information-Motivation-Behavioral Skills (IMB) Model: Testing direct and mediated treatment effects on condom use among women in low-income housing. Ann Behav Med, 2006; 31, 70-9. doi: 10.1207/s15324796abm3101_11 [52] Huy NV, Dunne MP, Debattista J. Predictors of condom use behaviour among male street labourers in urban Vietnam using a modified Information-Motivation-Behavioral Skills (IMB) model. Cult Health Sex, 2015; 18, 1-16. https://www.researchgate.net/publication/282759712_Predictors_of_condom_use_behaviour_among_male_street_labourers_in_urban_Vietnam_using_a_modified_Information-Motivation-Behavioral_Skills_IMB_model [53] Scott-Sheldon LA, Carey MP, Vanable PA, et al. Predicting condom use among STD clinic patients using the Information-Motivation-Behavioral Skills (IMB) model. J Health Psychol, 2010; 15, 1093-02. doi: 10.1177/1359105310364174 [54] Liu Z, Wei P, Huang M, et al. Determinants of consistent condom use among college students in China: application of the information-motivation-behavior skills (IMB) model. PLoS One, 2013; 9, e108976. https://www.researchgate.net/publication/266263752_Determinants_of_Consistent_Condom_Use_among_College_Students_in_China_Application_of_the_Information-Motivation-Behavior_Skills_IMB_Model/fulltext/543f733f0cf2e76f022455b8/266263752_Determinants_of_Consistent_Condom_Use_among_College_Students_in_China_Application_of_the_Information-Motivation-Behavior_Skills_IMB_Model.pdf [55] Cooper M, Loue S, Lloyd LS. Perceived susceptibility to HIV infection among Asian and Pacific Islander women in San Diego. J Health Care Poor Underserved, 2001; 12, 208-23. doi: 10.1353/hpu.2010.0808 [56] Diiorio C, Parsons M, Lehr S, et al. Factors associated with use of safer sex practices among college freshmen. Res Nurs Health, 1993; 16, 343-50. doi: 10.1002/(ISSN)1098-240X [57] Carpenter CJ. A meta-analysis of the effectiveness of health belief model variables in predicting behavior. Health Commun, 2010; 25, 661-9. doi: 10.1080/10410236.2010.521906 [58] Kalichman S, Stein JA, Malow R, et al. Predicting protected sexual behavior using the Information-Motivation-Behaviour skills model among adolescent substance abusers in court-ordered treatment. Psychol Health Med, 2002; 7, 327-38. doi: 10.1080/13548500220139368 [59] White RC. Health Belief Model, condom use and Jamaican adolescents. Social & Economic Studies, 2004; 53, 155-86. [60] Buckingham R, Meister E. Condom Utilization among Female Sex Workers in Thailand: Assessing the Value of the Health Belief Model. California Journal of Health Promotion, 2003. [61] Lammers J, Van Wijnbergen S, Willebrands D. Gender Differences, HIV Risk Perception and Condom Use. Ssrn Electronic Journal, 2011; ti2011-51/2. [62] Zuo X, Lou C, Gao E, et al. Gender Differences in Adolescent Premarital Sexual Permissiveness in Three Asian Cities: Effects of Gender-Role Attitudes. J Adolesc Health, 2012; 50, S18-S25. https://jhu.pure.elsevier.com/en/publications/gender-differences-in-adolescent-premarital-sexual-permissiveness-5 [63] Sprecher S, Treger S, Sakaluk JK. Premarital sexual standards and sociosexuality: gender, ethnicity, and cohort differences. Arch Sex Behav, 2013; 42, 1395-405. doi: 10.1007/s10508-013-0145-6 [64] Graham CA, Crosby R, Yarber WL, et al. Erection loss in association with condom use among young men attending a public STI clinic: potential correlates and implications for risk behavior. Sex Health, 2006; 3, 255-60. doi: 10.1071/SH06026 [65] Traeen B, Hovland A. Games People Play: Sex, Alcohol and Condom Use among Urban Norwegians, Contemp. drug Probs. 1998; 25. doi: 10.1177/009145099802500101 [66] Sun X, Liu X, Shi Y, et al. Determinants of risky sexual behavior and condom use among college students in China. Aids Care, 2013; 25, 775-83. doi: 10.1080/09540121.2012.748875 [67] Kirby D, Short L, Collins J, et al. School-based programs to reduce sexual risk behaviors: a review of effectiveness. Public Health Rep, 1994; 109, 339-60. http://www.crd.york.ac.uk/CRDWeb/ShowRecord.asp?ID=11994000275