Methodological considerations in using the Network Scale Up (NSU) for the estimation of risky behaviors of particular age-gender groups: An example in the case of intentional abortion

Validity and Reliability of the Human Immunodeficiency Virus-Related Stigma Questionnaire in Persian

Background: It was aimed to adapt a 12-item questionnaire into Persian among people living with human immunodeficiency virus (PLHIV) in Markazi province. Material and Methods: Content validity was evaluated based on the opinions of the relevant experts, and by calculating the scale-level content validity index (S-CVI) and the item-level content validity index (I-CVI). Reliability was assessed via test-retest, intraclass correlation coefficient (ICC), and Cronbach's alpha. Results: The obtained scores on clarity and relevancy (I-CVI) ranged from 0.9 to 1. The S-CVI also had an acceptable validity of 0.99. The Cronbach's alpha index of the whole questionnaire was 0.84 and ranged from 0.69 to 0.82 for subscales. The ICC in test-retest for all questionnaires was 0.88 and for subscales ranged from 0.77 to 0.88. Conclusion: The Persian version of the 12-item human immunodeficiency virus-related stigma questionnaire was found to be, in addition to being short and comprehensive, acceptable reliability and high validity to use in order to determine the stigma related to Persian-speaker PLHIV.

Estimating the prevalence of high-risk behaviors using network scale-up method in medical university students

BACKGROUND

There is not much information about high-risk behaviors in young groups, especially students. This study was conducted to estimate the prevalence of high-risk behaviors in students of universities of medical sciences in West Azerbaijan Province, Iran, by network scale-up (NSU) method.

MATERIALS AND METHODS

This cross-sectional study was performed on 450 students from the universities of medical sciences. A researcher-developed checklist was used to collect the data. We considered number 16 for the social network size of students according to a previous study. Based on the response of individuals to each of the high-risk behaviors (including cigarette smoking, hookah use, opium consumption, alcohol drinking, tramadol/ecstasy taking, and extramarital sex) in their social network, the prevalence of these behaviors was estimated. The required calculations were performed using the NSU method. Furthermore, 95% uncertainty interval (UI) was calculated using the bootstrap method.

RESULTS

Totally, 196 (44%) participants were male. The mean age (standard deviation) of the participants was 22 ± 2 years. Results showed that hookah use (20% 95% UI [18.9-21.1]) and opium consumption (0.4% 95% UI [0.24-0.6]) had the highest and lowest frequencies, respectively. Cigarette smoking (17% 95% UI [15.8-18]), alcohol use (8.3% 95% UI [7.5-9.1]), extramarital sex (8.2% 95% UI [7.4-9]), and tramadol/ecstasy taking (4% 95% UI [6.4-4.6]) were the next most common high-risk behaviors, respectively.

CONCLUSIONS

Given that hookah use and cigarette smoking are the most common high-risk behaviors in students, especially males, appropriate cultural activities and educational programs should be employed by relevant authorities to reduce these behaviors.

Measure of Personal Network Size Using the Known Population Method: A Methodological Guide

The network scale-up method (NSUM) has shown promise in measuring the prevalence of hidden public health problems and at-risk populations. The technique involves asking survey respondents how many people they know with the health problem or characteristic of interest and extrapolating this information to the population level. An important component of the NSUM estimate is the size of each respondent's network, which is determined by asking respondents about the number of people they know who belong to populations of known size. There is little systematic discussion, however, to guide selection of these questions. Furthermore, many of the most commonly used known population questions are appropriate only in countries with a robust data infrastructure. Here, we draw from the NSUM literature to present a set of best practices in the selection of NSUM known population questions. Throughout, we address the unique situations that many researchers face in collecting prevalence data in the developing world, where innovative prevalence estimation techniques, such as NSUM, are most needed. (Am J Public Health. 2022;112(5):747-753. https://doi.org/10.2105/AJPH.2022.306731).

Population Size Estimation of Drug Users in Isfahan City (Iran) Using Network Scale-up Method in 2018

BACKGROUND

To provide prevention programs and educate drug users (DUs), the estimation of their population is necessary. This study aimed to estimate the population size of this hidden group in Isfahan city as a metropolitan in Iran using the network scale-up ýmethod (NSUM).

METHODS

This cross-sectional study was performed in summer 2018 on 1000 people selected through a multistage sampling method based on 14 region of the municipality of Isfahan. The data collection tool was a questionnaire that was previously used in Dr. Banshi's national plan without any changes. The Cronbach's alpha value of the questionnaire was 0.826. Using correction factors such as transparency of response and the ratio of social network size used in previous national studies, the number of people with high-risk behaviors was estimated. The results were analyzed through NSUM based on survey analysis.

FINDINGS

Among all kinds of DUs, men were the largest consumers. The prevalence of use of opium, cannabis, heroin/crack, stimulants, ecstasy, hallucinogens, tramadol, zolpidem, tobacco, and drug injection was 2983, 2342, 613, 766, 86, 268, 1185, 213, 5869, 135 in 100000 people, among individuals of over 18 years of age. In both sexes, the prevalence of using opium and its nectar and illegal treatment with methadone and buprenorphine was higher in people of over 30 years of age, while the prevalence of consuming cannabis, ecstasy, tramadol, tobacco products, and stimulants was higher in the age group of 18 to 30 years.

CONCLUSION

The results indicated that the prevalence of different DUs in Isfahan city, especially among men was higher than the reported average (especially in young men of 18-30 years of age). Since the prevalence of drug use varies based on the type of substance used among age groups, targeted preventive planning based on the type of drug used and age group is recommended.

HIV-Related Stigma Among People Living With HIV in Iran: A Cross-Sectional Study

ABSTRACT

HIV is perceived as a taboo topic in Iranian culture. This study examined HIV-related stigma among Iranian people living with HIV (PLWH). This cross-sectional study was conducted among 123 PLWH in 2019. HIV-related stigma was assessed by a standardized questionnaire adapted into Persian for this study. The range of the stigma scores for each of the subscales (personalized stigma, negative self-image, disclosure concerns, and concerns about public attitudes) was 3-12, whereas the range for the total stigma score was 12-48. The highest and lowest mean scores were observed in concerns about public attitudes (10.07) and negative self-image (7.39). The total mean stigma score was 37.03, indicating a high level of stigma. The most important factors determining HIV-related stigma were socioeconomic status, transmission method, duration of disease, and education level. This study suggests the need for more effective interventions to reduce HIV-related stigma among Iranian PLWH.

Using Social Networks to Estimate the Number of COVID-19 Cases: The Incident (Hidden COVID-19 Cases Network Estimation) Study Protocol

Recent literature has reported a high percentage of asymptomatic or paucisymptomatic cases in subjects with COVID-19 infection. This proportion can be difficult to quantify; therefore, it constitutes a hidden population. This study aims to develop a proof-of-concept method for estimating the number of undocumented infections of COVID-19. This is the protocol for the INCIDENT (Hidden COVID-19 Cases Network Estimation) study, an online, cross-sectional survey with snowball sampling based on the network scale-up method (NSUM). The original personal network size estimation method was based on a fixed-effects maximum likelihood estimator. We propose an extension of previous Bayesian estimation methods to estimate the unknown network size using the Markov chain Monte Carlo algorithm. On 6 May 2020, 1963 questionnaires were collected, 1703 were completed except for the random questions, and 1652 were completed in all three sections. The algorithm was initialized at the first iteration and applied to the whole dataset. Knowing the number of asymptomatic COVID-19 cases is extremely important for reducing the spread of the virus. Our approach reduces the number of questions posed. This allows us to speed up the completion of the questionnaire with a subsequent reduction in the nonresponse rate.