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ORIGINAL ARTICLE |
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Year : 2014 | Volume
: 3
| Issue : 2 | Page : 84-90 |
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Socio-economic status may suppress the effect of knowledge on sexual risk among female sex workers
Shervin Assari1, Majid Rezazade2, Khodabakhsh Ahmadi3, Mahmood Sehat4
1 Department of Health Behavior and Health Education; Center for Research on Ethnicity, Culture and Health, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA; Department of Social Welfare, Social Determinants Research Center, University of Social Welfare and Rehabilitation, Tehran, Iran 2 AIDS Prevention and Control Committee, Welfare Organization State, Tehran, Iran 3 Behavioral Sciences Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran 4 Medicine and Health Promotion Institute; Universal Network for Health Information Dissemination and Exchange, Tehran, Iran
Date of Web Publication | 19-May-2014 |
Correspondence Address: Shervin Assari 1415 Washington Heights, Ann Arbor, Michigan 48109 2029, USA
Source of Support: None, Conflict of Interest: None | Check |
DOI: 10.4103/2278-344X.132691
Background: Socio-economic status (SES), human immunodeficiency virus (HIV) knowledge and self-efficacy influence risky behaviors and female sex workers (FSWs) are not exception. Aims: This study was aimed to investigate if SES, HIV knowledge and self-efficacy predict frequency of unprotected sex with injecting drug users (IDUs) among a sample of FSWs in Iran. Setting and Design: Universal Network for Health Information Dissemination and Exchange HIV Risk Study was a survey of IDUs and FSWs, conducted in eight different provinces of Iran, 2009. Materials and Methods: A total of 55 FSWs were entered in this study. Frequency of unprotected sex with IDUs during the past 6 months was the dependent variable. Number of sexual partners during the past 6 month, SES, HIV Knowledge, self-efficacy, perceived HIV risk and intention for change were predictors. Statistical Analysis: We used hierarchical regression for data analysis. In each step, a block of predictors were added to the model. SES block composed of education level, owning a house and living alone. Results: In the absence of SES in the model, HIV knowledge and self-efficacy were not significantly associated with the frequency of unprotected sex with IDUs during the past 6 months, However, with adding SES block to the model, HIV knowledge became significant predictor of the outcome. Thus, among our sample of Iranian FSWs, SES has a suppressor effect for the effect of HIV knowledge on frequency of unprotected sex with IDUs during the past 6 months. Conclusion: Studies which wish to understand the role of theory-based psychological constructs such as HIV knowledge on high risk behaviors need to include SES an essential contextual factor. This finding may also explain why literature is mixed on the effect of HIV knowledge on HIV risk behaviors. Keywords: Female sex workers, human immunodeficiency virus knowledge, human immunodeficiency virus risk, Iran, self-efficacy, socio-economic status
How to cite this article: Assari S, Rezazade M, Ahmadi K, Sehat M. Socio-economic status may suppress the effect of knowledge on sexual risk among female sex workers. Int J Health Allied Sci 2014;3:84-90 |
How to cite this URL: Assari S, Rezazade M, Ahmadi K, Sehat M. Socio-economic status may suppress the effect of knowledge on sexual risk among female sex workers. Int J Health Allied Sci [serial online] 2014 [cited 2024 Mar 29];3:84-90. Available from: https://www.ijhas.in/text.asp?2014/3/2/84/132691 |
Introduction | | |
Self-efficacy is the degree of confidence in the own capacity to execute a certain health behavior. Self-efficacy beliefs have strong effect on behavior and behavior change. Many theories such as social cognitive theory [1] and health belief model [2] suggest that self-efficacy influences human behavior. Empirical data has supported these theories, as links have been shown between self-efficacy and a wide range of behaviors [1],[2],[3] such as condom use. [4] Self-efficacy has been frequently used to explain safe sex practice among individuals who are high risk for human immunodeficiency virus (HIV) infection. [5],[6],[7],[8],[9],[10],[11],[12],[13] However, there are also studies that have reported no association between self-efficacy and behaviors. [14],[15],[16]
Knowledge can be defined as the recall recognition of elements around a subject area. HIV knowledge implies to ability to recall risks related to causes, transmission and prevention of HIV and acquired immunodeficiency syndrome (AIDS). Knowledge about correct routes for HIV transmission may play a role in condom use frequency. [17] Among female sex workers (FSWs), an increase in knowledge of HIV and AIDS may be associated with an increase in condom use. [18] However, high level of knowledge does not always translate to practice of preventive strategies. For instance, we know that despite of high levels of HIV knowledge, preventive practices such as condom use are not widely conformed to. [19],[20]
Although sexual HIV risk behaviors are a main rout of HIV infection in countries such as Iran, [21] our knowledge is very limited on sexual risk behaviors of FSWs in Iran. McFarland et al. have discussed the challenges associated with studying sexual risk behaviors among HIV risk groups, such as FSWs in Middle Eastern countries. They argue that socio-cultural sensitivities and political restrictions have resulted in lack of information in such countries. [22]
In one of the very few available reports, Ahmadi et al., showed that up to 20% of Iranian FSWs may have unprotected sex with injecting drug users (IDUs) in the last month. [23] This is extremely important because about 5% of Iranian FSWs and 20% of Iranian IDUs may be HIV positive. [24],[25],[26] Ahmadi et al., entered socio-economic status (SES), HIV knowledge and HIV attitude into a logistic regression and showed that unprotected sex with IDU (s) during the past month was associated with educational level (odds ratio [OR] = –0.653), perceived HIV risk (OR = –1.047) and perceived family intimacy during childhood (OR = –1.104). The study failed to show any association between HIV knowledge and self-efficacy on having sex with IDUs. [23]
We conducted this study to investigate the effect of SES, HIV knowledge and self-efficacy on frequency of unprotected sex with IDUs among FSWs. We hoped that current study will help us explore why Ahmadi et al., reported no effect of HIV knowledge and self-efficacy on HIV risk behaviors among Iranian FSWs. [23]
Materials and methods | | |
The current study used data of FSWs who had participated in the Universal Network for Health Information Dissemination and Exchange (UNHIDE) HIV-risk study. UNHIDE HIV-risk study was a cross-sectional survey of IDUs, FSWs, and men who have sex with men conducted in eight different provinces of Iran, 2009. We used respondent driven sampling (RDS), in the following provinces: Tehran, Fars, Isfahan, Markazi, Khuzestan, Guilan, Khorasan and Azerbaijan. Using a non-random strategy, these provinces were selected based on their locations and size. These provinces were within the largest provinces in North (Guilan), Northeast (Khorasan), Northwest (Azerbaijan), South (Fars, Khuzestan) and Middle (Tehran, Isfahan, Markazi) of Iran.
RDS, akin to snowball sampling, is a non-random sampling method that facilitates recruitment of hidden populations through a chain-referral procedure. In this technique, participants recruit other participants. [27],[28],[29] RDS is widely used in public health research and has been recently applied in more than 100 studies in more than 20 countries. [30] RDS is also used by the Centers for Disease Control and Prevention in United States. [31],[32] In this technique, a number of initial participants ("seeds") are selected. These participants will be asked to recruit their contacts in the population. [27] This process continues until the desired sample size is reached. [33]
The study was conducted by the Behavioral Sciences Research Center at Baqiyatallah University of Medical Sciences. The Ethical Review Committee of the Baqiyatallah University of Medical Sciences approved the study. We received informed consent from all participants. Data was kept confidential and anonymous. Participants did not receive any monetary incentives, however they received HIV education and free condoms.
We enrolled all female Iranian FSWs who had not injected drugs in their lifetime and had data on SES, HIV knowledge, perceived risk, intention for change, self-efficacy and sexual behaviors. The study included 55 FSWs. Other reports have been published from this study. [34],[35],[36],[37],[38],[39],[40],[41]
Data collection was carried out during a 7-month period in 2009. Interviews took up to 60 min. Interviews were conducted by university-trained research assistants. The study questionnaire measured socio-demographic data
(age, gender, educational level, housing and occupational situation, living condition), HIV knowledge (knowledge about safe and unsafe sex, as well as other HIV transmission routes), self-efficacy, perceived HIV risk, perceived need for HIV education, intention for change and HIV risk behaviors. [23]
Outcome was measured using the following question: "During the past 6 months, how many times did you have condom-less sex with someone who was a drug injector?". Response categories included (1) never, (2) a few times,
(3) 1-3 times a month, (4) 1-5 times a week, (5) almost every day, (6) don't know. [40]
We used Statistical Package for the Social Sciences 14 (SPSS Inc., IL, USA) for data analysis. Hierarchical linear regression model was used. Frequency of unprotected sex with IDUs during the past 6 months was the dependent variable. We entered three blocks of predictors to this model. In the first block, we entered intention for change, perceived risk and number of sexual partners during the past 6 months. We entered HIV Knowledge and self-efficacy as our second block. In the last block, we entered three SES indicators (i.e. education level, owning a house and living alone). Frequency of unprotected sex with IDUs during the past 6 months, perceived HIV risk, intention for change, number of sexual partners during the past 6 month HIV Knowledge, self-efficacy and education level were considered as continuous variables. Owning a house and living alone were dichotomous variables. Beta coefficients and 95% confidence intervals are reported. Significance level was set at 0.05.
Although suppression is not frequently described in the context of HIV research, it is a well-known concept in the fields of education and psychology. [42],[43],[44],[45] In this study, we used one of the most generally accepted definitions of the suppressor variable provided by Conger. [46],[47] Suppressor was defined as a third variable which increases the predictive validity of an independent variable (or set of variables) on a dependent variable. Predictive validity was assessed by the magnitude of the regression coefficient. Thus, a situation in which the magnitude of the relationship between an independent variable and a dependent variable becomes larger when a third variable is included indicates suppression. More detailed discussions about the suppressor effect are available. [48],[49]
Results | | |
Age of FSWs ranged between 16 and 70 years, with a mean (standard deviation) of 30 ± 10 years. From participants, 20% reported no, 12.7% reported one and others reported two or more sexual partners in the past 6 months. From all, 3.6% did not report number of sexual partner in the past 6 months. During the past 6 months, 45.5% reported never having unprotected sex with IDUs, 25.5% a few times, 12.7% 1-3 times/month and 12.7% did not report frequency of unprotected sex with IDUs during past 6 months [Table 1]. | Table 1: Frequency of unprotected sex with IDUs during past 6 months among 55 FSWs in Iran
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Based on our bivariate analysis, frequency of unprotected sex with IDUs during the past 6 months was significantly correlated with the number of sex partners during the past 6 months. The frequency of unprotected sex with IDUs during the past 6 months was not correlated with age, SES measures, total HIV knowledge, self-efficacy, intention for change or perceived risk [Table 2]. | Table 2: Bivariate associates of frequency of unprotected sex with IDUs during past 6 months
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In the first model, perceived risk and intention for behavior change and number of sexual partners during the past 6 months were significant predictors of frequency of unprotected sex with IDU (s) during the past 6 months. HIV knowledge and self-efficacy were not associated with the outcome in the next model, however. When we added SES block to the final model, HIV knowledge became a significant predictor of frequency of unprotected sex with IDU (s) during the past 6 months [Table 3]. | Table 3: Results of hierarchical linear modeling applied to frequency of unprotected sex with IDUs during past 6 months among Iranian FSWs
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Discussion | | |
In the absence of SES factors, HIV knowledge did not show an association with frequency of unprotected sex with IDU(s) during the past 6 months among Iranian FSWs. When SES position of FSWs was taken into account, HIV knowledge showed an association with frequency of unprotected sex with IDU(s) during the past 6 months. Based on our finding, SES acts as a suppressor for the association between HIV knowledge and the outcome.
It has been theorized that behavioral change and maintenance of behavior are a function of expectations about one's ability to perform a certain behavior (self-efficacy). Based on social cognitive theory, self-efficacy plays a unique role in the adoption of health behaviors, the modification of unhealthy habits and the maintenance of change. [50] As explained by Bandura, an individual's persistence and efforts toward a particular behavior is closely related to his or her level of self-efficacy. Self-efficacy determines the type of activities chosen, the effort to be expended and the degree of persistence in the effort. [1] People with high self-efficacy are more likely to initiate and persist the behavior, while those with lower level of self-efficacy have a greater tendency to abandon their attempts in carrying out the target behavior. [51]
Based on our finding, SES has a suppressor effect for the association between HIV knowledge and frequency of unprotected sex with IDU (s). Different suppressor phenomenons have been described in the literature. [52] For instance, smoking has shown a supressive effect on the link between depressive symptoms and obesity. [53]
Inclusion of a suppressor to a regression equation removes the unwanted variance from the predictor variable, thus enhancing the relationship between the other independent and dependent variables. [54] In our case, controlling for SES may have removed the unwanted variance from HIV knowledge and enables this construct to show an association with the outcome, frequency of unprotected sex with IDU(s) during the past 6 months.
Our finding may explain why many studies fail to show an association between HIV knowledge and HIV risk behaviors. We argue that failure to control for the suppressor variable may be a reason why some studies have reported no effect of HIV knowledge on risky behaviors. Most of the studies have shown no link between HIV Knowledge and risky behaviors. [23],[55],[56],[57],[58],[59],[60],[61],[62]
Similarly, lack of association between self-efficacy and HIV risk behaviors reported by some studies may be explained by our finding. Literature review shows several studies which have failed to show an effect for self-efficacy on safe sex practices. [14],[15],[16] For instance, self-efficacy was not correlated with condom use or intention of use among young adults in one study. [63] Halpern-Felsher et al. reported that peer communication self-efficacy was not related to condom use among youth. [64] Similar results have been reported among FSWs. [65]
The suppressor phenomenon has been the subject of debate for several decades, using a comprehensive review of suppressor variables. [52],[66] In 1941, Horst coined the term. [55] In 1972 and 1974, Conger defined a suppressor variable as a variable that increases the predictive validity of another variable (or set of variables) in a regression equation. [67],[68] The same concept was called a suppressant by McNemar. [66]
Using McNemar's definition of suppressant, HIV knowledge may have several elements in common with risky behaviors but also have irrelevant elements. SES, the suppressant, partials out the irrelevant elements from HIV Knowledge and "purifies" the HIV knowledge and improves its prediction strength. [47],[69] Based on MacKinnon et al., we can argue that HIV knowledge has both direct and indirect effects on risky behaviors and that these direct and indirect effects are of fairly similar magnitudes and opposite directions. [66] Without having SES in our model, we fail to observe the effect of HIV knowledge on our outcome.
Statistical adjustment for SES did not reduce the effect of HIV knowledge on frequency of unprotected sex with IDU(s) during the past 6 months among Iranian FSWs. MacKinnon argued that the traditional assumption on reduction of the magnitude of the relationship between the independent and dependent variables following statistical adjustment for a third variable is not always the case. He argues that in the meditational or confounding context, the magnitude of the association becomes reduced only because the mediator/confounder explains part or all of the relationship between the independent and dependent variables. There are, however, instances that the statistical removal of a meditational or confounding factor could increase the magnitude of the relationship between two variables of interest. [66]
MacKinnon believes that suppression is mediation when in a bivariate analysis, a relationship fails to be significant. He argues that the first listed criterion for mediation is not necessary for inconsistent mediation phenomen. [66] As we know, the first criterion for consistent mediation is a significant relationship between the independent variable and the dependent variable. [70],[71] MacKinnon believes that suppression is inconsistent mediation. [66] Thus he proposes possibility of mediation even if there is no significant relationship between the independent and dependent variable. This is not similar to the mostly accepted definition of mediation. [72]
Our results suggest that theory-based psychological constructs that predict behavior and behavior change should not be used in modeling HIV risk behaviors without taking into account contextual factors such as SES. Our findings also show a complex interplay between SES, knowledge and HIV risk behaviors. Research on the effect of HIV knowledge on risky behaviors needs to control for SES factors. We recommend that harm reduction and public health programmers who want to change HIV risk behaviors of FSWs should tailor their interventions for SES characteristics with their target population.
Our study had several limitations. Design was cross-sectional and findings are associations not causations. Sample size was very low. This was because the main study was mostly composed of IDUs and FSWs only composed a small proportion of participants. This study was also limited to participants who had never injected drugs and had data on SES, HIV knowledge, perceived risk, intention for change, self-efficacy and sexual behaviors. Finally, the study had only collected SES data on education, owning a house and living alone. The study did not have data on wealth index, or standard of living index. Education has been widely used as a measure of SES. [73],[74] Our outcome was a single item. The study is also prone to desirability bias. Thus, misclassification cannot be ruled out, as sexual behaviors may be under reported. Finally, we could not determine type of suppressor role of SES in our study.
Our study may add to the current knowledge about the unique role of SES in studies focusing on sexual risk behaviors among FSWs. [75],[76],[77],78 Although HIV knowledge is considered a promising modifiable factor which can be target of harm reduction purposes, analysis of its association with risk behaviors should be done by taking SES factors of the target population into account. Data presented here invites policy makers and program developers to build their interventions with attention to SES as the context of the intervention.
Conclusion | | |
Based on the above study, it can be concluded that among Iranian FSWs, SES characteristics act as suppressor for the association of HIV knowledge with unprotected sex with IDUs. Studies that wish to understand the association between theory-based psychological constructs and high risk behaviors should also consider the context in which the participant is living in.
References | | |
1. | Bandura A. Self-efficacy: Toward a unifying theory of behavioral change. Psychol Rev 1977;84:191-215. [PUBMED] |
2. | Rosenstock IM, Strecher VJ, Becker MH. Social learning theory and the health belief model. Health Educ Q 1988;15:175-83. |
3. | AbuSabha R, Achterberg C. Review of self-efficacy and locus of control for nutrition- and health-related behavior. J Am Diet Assoc 1997;97:1122-32. |
4. | Brafford LJ, Beck KH. Development and validation of a condom self-efficacy scale for college students. J Am Coll Health 1991;39:219-25. |
5. | Mahoney CA, Thombs DL, Ford OJ. Health belief and self-efficacy models: Their utility in explaining college student condom use. AIDS Educ Prev 1995;7:32-49. |
6. | Forsyth AD, Carey MP. Measuring self-efficacy in the context of HIV risk reduction: Research challenges and recommendations. Health Psychol 1998;17:559-68. |
7. | Hanna KM. An adolescent and young adult condom perception scale. West J Nurs Res 1999;21:621-31. [PUBMED] |
8. | Brien TM, Thombs DL, Mahoney CA, Wallnau L. Dimensions of self-efficacy among three distinct groups of condom users. J Am Coll Health 1994;42:167-74. |
9. | Cecil H, Pinkerton SD. Reliability and validity of a self-efficacy instrument for protective sexual behaviors. J Am Coll Health 1998;47:113-21. |
10. | Polacsek M, Celentano DD, O›Campo P, Santelli J. Correlates of condom use stage of change: Implications for intervention. AIDS Educ Prev 1999;11:38-52. |
11. | Sands T, Archer J, Puleo S. Prevention of health-risk behaviors in college students: Evaluating seven variables. J Coll Stud Dev 1998;39:331-42. |
12. | Wulfert E, Wan CK. Condom use: A self-efficacy model. Health Psychol 1993;12:346-53. |
13. | DiIorio C, Maibach E, O›Leary A, Sanderson CA, Celentano D. Measurement of condom use self-efficacy and outcome expectancies in a geographically diverse group of STD patients. AIDS Educ Prev 1997;9:1-13. |
14. | Dorothy Ellis-Hernandez K. Condom self-efficacy, HIV knowledge and understanding, perceived peer sexual behavior, and condom use among sexually active adolescents; 2009. ETD Collection for Fordham University. Paper AAI3361352. Available from: http://fordham.bepress.com/dissertations/AAI3361352. |
15. | Christ MJ, Raszka WV Jr, Dillon CA. Prioritizing education about condom use among sexually active adolescent females. Adolescence 1998;33:735-44. |
16. | DiIorio C, Dudley WN, Kelly M, Soet JE, Mbwara J, Sharpe Potter J. Social cognitive correlates of sexual experience and condom use among 13- through 15-year-old adolescents. J Adolesc Health 2001;29:208-16. |
17. | Osho A, Olayinka BA. Sexual practices conducive to HIV transmission in South West Nigeria. Research on African HIV/AIDS epidemic Yaba: Lagos: St Luku Hospital and Maternity Ltd,1999. |
18. | Ford K, Wirawan DN, Reed BD, Muliawan P, Sutarga M. AIDS and STD knowledge, condom use and HIV/STD infection among female sex workers in Bali, Indonesia. AIDS Care 2000;12:523-34. |
19. | Esu-Williams E. HIV and AIDS: The global inter-connection clients and commercial sex work. Available from: http://www.undp.org. [Last accessed on 2014 Apr 29]. |
20. | Prybylski D, Alto WA. Knowledge, attitudes and practices concerning HIV/AIDS among sex workers in Phnom Penh, Cambodia. AIDS Care 1999;11:459-72. |
21. | McFarland W, Assari S. HIV in developing world. Dev World Epidemiol 2013, p. 1. |
22. | McFarland W, Abu-Raddad LJ, Mahfoud Z, DeJong J, Riedner G, Forsyth A, et al. HIV/AIDS in the Middle East and North Africa: New study methods, results, and implications for prevention and care. AIDS 2010;24 Suppl 2:S1-4. |
23. | Ahmadi K, Rezazade M, Nafarie M, Moazen B, Yarmohmmadi Vasel M, Assari S. Unprotected sex with injecting drug users among Iranian female sex workers: Unhide HIV risk study. AIDS Res Treat 2012;2012:651070. |
24. | Kazerooni PA, Motazedian N, Motamedifar M, Sayadi M, Sabet M, Lari MA, et al. The prevalence of human immunodeficiency virus and sexually transmitted infections among female sex workers in Shiraz, South of Iran: By respondent-driven sampling. Int J STD AIDS 2013;DOI:10.1177/0956462413496227. |
25. | Zamani S, Kihara M, Gouya MM, Vazirian M, Nassirimanesh B, Ono-Kihara M, et al. High prevalence of HIV infection associated with incarceration among community-based injecting drug users in Tehran, Iran. J Acquir Immune Defic Syndr 2006;42:342-6. |
26. | Amin-Esmaeili M, Rahimi-Movaghar A, Haghdoost AA, Mohraz M. Evidence of HIV epidemics among non-injecting drug users in Iran: A systematic review. Addiction 2012;107:1929-38. |
27. | Heckathorn DD. Respondent-driven sampling: A new approach to the study of hidden populations. Soc Probl 1997;44:174-99. |
28. | Heckathorn DD. Respondent-driven sampling II: Deriving valid population estimates from chain-referral samples of hidden populations. Soc Probl 2002;49:11-34. |
29. | Salganik MJ, Heckathorn DD Sampling and estimation in hidden populations using respondent-driven sampling. Sociol Methodol 2004;34:193-239. |
30. | Malekinejad M, Johnston LG, Kendall C, Kerr LR, Rifkin MR, Rutherford GW. Using respondent-driven sampling methodology for HIV biological and behavioral surveillance in international settings: A systematic review. AIDS Behav 2008;12:S105-30. |
31. | Lansky A, Abdul-Quader AS, Cribbin M, Hall T, Finlayson TJ, Garfein RS, et al. Developing an HIV behavioral surveillance system for injecting drug users: The National HIV Behavioral Surveillance System. Public Health Rep 2007;122 Suppl 1:48-55. |
32. | Centers for Disease Control and Prevention (CDC). HIV-associated behaviors among injecting-drug users - 23 Cities, United States, May 2005-February 2006. MMWR Morb Mortal Wkly Rep 2009;58:329-32. [PUBMED] |
33. | Goel S, Salganik MJ. Assessing respondent-driven sampling. Proc Natl Acad Sci U S A 2010;107:6743-7. |
34. | Yarmohammadi Vasel M, Sehat M, Rezazadeh M, Ahmadi K. Protective effect of educational attainment on injecting risk behaviors among injection drug users. Dev World Epidemiol 2013, p. 1. |
35. | Narenjiha H, Rafiey H, Shirinbayan P, Noori R, Samiei M. Nonfatal overdose among intravenous drug users: A national study from Iran. Dev World Epidemiol 2013, p. 1. |
36. | Yarmohammadi Vasel M, Sehat M, Rezazadeh M, Ahmadi K. Co-occurrence of sexual risk behaviors among sexually active Iranian heterosexual male injection drug users. Dev World Epidemiol 2013, p. 1. |
37. | Noroozinejad G, Yarmohmmadi Vasel M, Bazrafkan F, Sehat M, Rezazadeh M, Ahmadi K. Perceived Risk Modifies the Effect of HIV Knowledge on Sexual Risk Behaviors. Front Public Health 2013;30:1-33. |
38. | Mirabi P, Vasel MY, Moazen B, Sehat M, Rezazadeh M, Ahmadi K. Unprotected anal Intercourse among Iranian Intra-Venous Drug Users. Front Public Health 2013;26:1-34. |
39. | Assari S, Rezazadeh M, Ahmadi K. Do injection drug users and sex workers differ in predictors of risk behaviors? Dev World Epidemiol 2013. |
40. | Assari S, Ahmadi K, Rezazadeh M, UNHIDE risk study; rationale and questionnaire. Dev World Epidemiol 2013, p. 1. |
41. | Assari S, Ahmadi K, Rezazadeh M. HIV knowledge, perceived risk, readiness for change: Comparison of injection drug users and sex workers differ in. Dev World Epidemiol 2013, p.1. |
42. | Cohen J, Cohen P. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. 2 nd ed. Hillsdale, NJ: Lawrence Erlbaum; 1983. |
43. | Horst P. The role of predictor variables which are independent of the criterion. Soc Sci Res Counc Bull 1941;48:431-6. |
44. | Lord FM, Novick R. Statistical Theories of Mental Test Scores. Reading, MA: Addison-Wesley: 1968. |
45. | Velicer WF. Suppressor variables and the semipartial correlation coefficient. Educ Psychol Meas 1978;38:953-8. |
46. | Conger AJ. A revised definition for suppressor variables: A guide to their identification and interpretation. Educ Psychol Meas 1974;34:35-46. |
47. | Tzelgov J, Henik A. Suppression situations in psychological research: Definitions, implications, and applications. Psychol Bull 1991;109:524-36. |
48. | Sharpe NR, Roberts RA. The relationship among sums of squares, correlation coefficients, and suppression. Am Stat 1997;51:46-8. |
49. | Hamilton D. Sometimes R2>r2y1+r2y2. Am Stat 1987;41:129-32. |
50. | Bandura A. Self-efficacy mechanism in physiological activation and health-promoting behavior. In: Madden J, editor. Neurobiology of Learning, Emotion and Affect. New York: Raven Press; 1991. p. 229-70. |
51. | Bandura, A. Cervone D. Self-evaluative and self-efficacy mechanisms governing the motivational effects of goal systems. J Pers Soc Psychol 1983;45:1017-82. |
52. | Maassen G, Bakker A. Suppressor variables in path models. Definitions and interpretations. Sociol Methods Res 2001;30:241-70. |
53. | Schulz AJ, House JS, Israel BA, Mentz G, Dvonch JT, Miranda PY, et al. Relational pathways between socioeconomic position and cardiovascular risk in a multiethnic urban sample: Complexities and their implications for improving health in economically disadvantaged populations. J Epidemiol Community Health 2008;62:638-46. |
54. | Randolph ME, Pinkerton SD, Somlai AM, Kelly JA, McAuliffe TL, Gibson RH, et al. Seriously mentally ill women's safer sex behaviors and the theory of reasoned action. Health Educ Behav 2009;36:948-58. |
55. | Roberts K. Suppressor effects in linear models. Available from: http://faculty.smu.edu/kyler/courses/7311/suppress.pdf. |
56. | Raj A. Identification of social cognitive variables as predictors of safer sex behavior and intent in heterosexual college students. J Sex Marital Ther 1996;22:247-58. [PUBMED] |
57. | Strathdee SA, Mausbach B, Lozada R, Staines-Orozco H, Semple SJ, Abramovitz D, et al. Predictors of sexual risk reduction among Mexican female sex workers enrolled in a behavioral intervention study. J Acquir Immune Defic Syndr 2009;51 Suppl 1:S42-6. |
58. | Rasamimari A, Dancy B, Talashek M, Park CG. Predictors of sexual behaviors among Thai young adults. J Assoc Nurses AIDS Care 2007;18:13-21. |
59. | Colón RM, Wiatrek DE, Evans RI. The relationship between psychosocial factors and condom use among African-American adolescents. Adolescence 2000;35:559-69. |
60. | Stulhofer A, Graham C, Boziceviæ I, Kufrin K, Ajdukoviæ D. HIV/AIDS-related knowledge, attitudes and sexual behaviors as predictors of condom use among young adults in Croatia. Int Fam Plan Perspect 2007;33:58-65. |
61. | Dixon D, Saul J, Peters M. Psychosocial correlates of HIV sexual protective behavior among Puerto Rican women residing in the Bronx, New York. Health Care Women Int 2010;31:274-93. |
62. | Xiao Z, Palmgreen P, Zimmerman R, Noar S. Adapting and applying a multiple domain model of condom use to Chinese college students. AIDS Care 2010;22:332-8. |
63. | Basen-Engquist K. Psychosocial predictors of "safer sex" behaviors in young adults. AIDS Educ Prev 1992;4:120-34. [PUBMED] |
64. | Halpern-Felsher BL, Kropp RY, Boyer CB, Tschann JM, Ellen JM. Adolescents self-efficacy to communicate about sex: Its role in condom attitudes, commitment, and use. Adolescence 2004;39:443-56. |
65. | Zhao R, Wang B, Fang X, Li X, Stanton B. Condom use and self-efficacy among female sex workers with steady partners in China. AIDS Care 2008;20:782-90. |
66. | MacKinnon DP, Krull JL, Lockwood CM. Equivalence of the mediation, confounding and suppression effect. Prev Sci 2000;1:173-81. |
67. | Conger AJ, Jackson DN. Suppressor variables, prediction, and the interpretation of psychological relationships. Educ Psychol Meas 1972;32:579-99. |
68. | McNemar Q. The mode of operation of suppressant variables. Am J Psychol 1945;58:554-5. |
69. | McNemar Q. Psychological Statistics. London: Wiley; 1969. |
70. | Judd CM, Kenny DA. Process analysis: Estimating mediation in treatment evaluations. Eval Rev 1981;5:602-19. |
71. | Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51:1173-82. [PUBMED] |
72. | Judd CM, Kenny DA. Estimating the Effects of Social Interventions. New York: Cambridge University Press; 1981. |
73. | Herndon JE 2 nd , Kornblith AB, Holland JC, Paskett ED. Effect of socioeconomic status as measured by education level on survival in breast cancer clinical trials. Psychooncology 2013;22:315-23. |
74. | Steenland K, Henley J, Calle E, Thun M. Individual- and area-level socioeconomic status variables as predictors of mortality in a cohort of 179,383 persons. Am J Epidemiol 2004;159:1047-56. |
75. | Karimi M, Ghaheri H, Assari S, Ahmadi K, Moghani Lankarani M, Moghani Lankarani R, Narenjiha H, Rafiey H, Tavakoli M, Jafari F. Drug Injection to Sites other than Arm: A Study of Iranian Heroin Injectors. Front Psychiatry 2014;7:5-23. |
76. | Assari S, Yarmohmmadi Vasel M, Tavakoli M, Sehat M, Jafari F, Narenjiha H, Rafiey H, Ahmadi K. Inconsistent Condom Use among Iranian Male Drug Injectors.Front Psychiatry 2014;4:4-181. |
77. | Noroozinejad G, Yarmohmmadi Vasel M, Bazrafkan F, Sehat M, Rezazadeh M, Ahmadi K. Perceived Risk Modifies the Effect of HIV Knowledge on Sexual Risk Behaviors. Front Public Health 2013; 30:1-33. |
[Table 1], [Table 2], [Table 3]
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