The results of the present study indicate that employing a 7-item scale to measure the HIV transmission risk among IDUs may be useful for evaluation of intervention programs in this key group. In many studies, the focus of risk analysis is on discrete behaviors to identify trends in behaviors or to study the determinants of high risk behaviors in this population (
19,
20). For a better understanding of the current status of HIV transmission risks among IDUs, looking simultaneously at multiple factors and conditions may provide better insight for policymakers and researchers into the mixed nature of HIV transmission risks and assist with identifying IDUs with higher risk of HIV acquisition or transmission based on their behaviors. Furthermore, measuring the impact of interventions on multiple discrete outcomes may increase the chance of type I errors by introducing the problem of multiplicity into the analysis (
21).
To prepare this scale; we used principal component analysis, a multivariate technique which simplifies a set of items to their linear combination in a way that they successively have a maximum variance for the data. The measure of internal consistency, the Cronbach α, was satisfactory, which indicates that summation of different items to construct a global scale for measuring HIV transmission risks is proper. This approach may be more statistically powerful and informative in etiologic research as well as program evaluation efforts.
Regarding high risk behaviors related to injection practice, the highest weight pertained to the needle sharing followed by the number of injection partners and sharing of injection equipment. These findings are supported by the literature that suggests the higher likelihood of HIV transmission among those who share needles with multiple partners than those who only share injection equipment such as cookers or rinse water (
22). In addition, the use of a condom during sexual intercourse is of much more significance than the number of sexual partners. Another item that was extracted in the final scale was proportion of IDUs in the personal network of participants. This item has been ignored in available scales while in many situations, the higher proportion of IDUs in personal networks of individuals has been associated with a higher rate of risky behaviors (
12,
13). In addition, out of 11 items that we entered in the initial scale, 4 were dropped from the final model. These items were duration of injection, average number of daily injections, engagement in MMT program, and use of stimulant drugs within the last 6 months. As these items indirectly affect the risk of HIV transmission among IDUs, it is uninformative to retain them in this scale.
We asked about the high risk behaviors of IDUs during the last 6 months to take into account the turnover of their relations that usually exist among IDUs. In addition, we supposed that some questions such as the number of anal intercourse acts during the last month (that was considered by Darke and colleagues in a similar scale) does not necessarily affect the risk of HIV transmission (
17). Instead, the safety of sexual acts (e.g. use of condoms) is the main determinant of HIV transmission during sexual relationship. Therefore, such items dropped from our suggested scale.
In conclusion, applying a 7-item scale can help harm reductionists and clinical practitioners to simply measure the current status of HIV transmission risks among IDUs in a short period of time (3 - 5 minutes). It also provides an opportunity for policymakers to evaluate the impact of intervention programs by measuring the changes in HIV transmission risk by employing a comprehensive scale that captures different factors related to virus transmission. Undoubtedly, an effective rapport between interviewers and participants increase the validity of such self-reported data. Nevertheless, the cross-sectional nature of the data has limited our ability to assess the usefulness of scales in prediction of HIV seroconversion among IDUs. So, prospective cohort studies are needed to assess the predictive validity of scales.