WHO DO YOU KNOW: IMPROVING AND EXPLORING THE NETWORK SCALE-UP METHOD

The purpose of this dissertation was to examine ways to improve and explore the network scale-up method (NSUM). This dissertation improved the NSUM by proposing a new mean of sums (MoS) estimation process, improving recursive back-estimation techniques, exploring how NSUM design changes effected estimates of personal network size, what predicts having larger personal networks, and the cognitive process used by participants taking a NSUM survey. Data was collected from an address-based survey (n=617) of Nebraskans conducted in 2014 and a series of cognitive interviews (n=19) conducted in 2016. The MoS estimator better predicted the size of a target group than the traditional estimator. Further, recursive back-estimation was shown to retain more scaling variables when used with the MoS than the traditional estimator. However, the MoS estimator did produce larger average estimates of personal network size. The application of recursive back-estimation reduced the average of both the MoS and traditional estimates of personal network size to comparable levels. Differences in the treatment of item nonresponse among NSUM scaling questions had little to no impact on the average estimate of personal network size. Eighteen different estimates of personal network size were calculated based upon different assumptions and methodological choices for regression models. In all eighteen models rural Nebraskans had larger networks than their urban counterparts, and those who made less than $25,000 had smaller networks than those who made between$50,000 and $99,999. In some models education, religious attendance, and age were associated with expected network size, but these associations were erratic. This shows that NSUM methodological decisions NSUM can have effects on both estimates of network size and statistical inference. Finally, cognitive interviews revealed a series of issues around participants’ ability to accurately answer NSUM questions including memory search, definition retention, and differences between the known-population technique and the summation method. A series of suggestions for practical implementation and further testing of these issues are discussed. This dissertation demonstrates new ways to adapt the NSUM without having to use the generalized NSUM and explores how participants’ process NSUM style questions when developing their answers. Advisors: Kirk Dombrowski and Lisa Kort-Butle

Chapter 10: Unintended Interviewer Bias in a Community-based Participatory Research Randomized Control Trial among American Indian Youth Appendix 10

Appendix 10A Analysis of Internalizing and Externalizing Subscales Table A10A.1: Linear Mixed-Effects Models Predicting Subscales of Internalizing Behavior Table A10A.2: Linear Mixed-Effects Models Predicting Subscales of Externalizing Behavio

Migration to the US among rural Puerto Ricans who inject drugs: influential factors, sources of support, and challenges for harm reduction interventions

Background: While PWID of Puerto Rican origin have been migrating to the US for decades, the range of factors influencing their migration to the US and the resources they draw on to do so are not well understood. This is particularly true for rural Puerto Rican PWID, and the present study is the first empirical research to document migration patterns among this population. The specificities of their migration raise important challenges that need to be documented in order to implement more effective harm reduction policies at home (Puerto Rico) and abroad (US). Methods: This paper draws from data obtained employing a modified NHBS survey which was administered to (N =296) PWID in four rural municipalities of Puerto Rico with participants 18 years or older. The primary dependent variables for this paper are the number of times a person has lived in the continental US, and if they are planning on moving to the continental US in the future. Results: Findings suggest that 65% of the sample reported ever lived in the US and that 49% are planning on moving in the future. The number of times living in the US is associated with higher education and older age, but not with self-reported positive HIV or HCV statuses. Planning to move to the US is associated with knowing PWID who have moved or plan to move, negatively associated with age, and is not associated with HIV or HCV status. Around one-third of those that lived in the US reported having some sort of support, with the majority receiving support from family sources. No participant received help to enter HIV/HCV treatment. Conclusions: A multi-region approach to prevention is required to make a dent in curbing HIV/HCV transmission in this population. Understanding PWID migration patterns, risk behaviors, and health care needs in the US is now more important than ever as natural disasters prompted by human-made climate change will only increase in the future, raising demands not only for service providers but also harm reduction policies to cope with an increasing influx of “climate refugees” as PWID move across national borders

Unintended Interviewer Bias in a Community-based Participatory Research Randomized Control Trial among American Indian Youth

Community-based participatory research (CBPR) projects often employ members of the host partner community to engage and assist with research projects. However, CBPR may also introduce bias to survey statistics when community partners work as interviewers for projects within their own communities. Here, the advantage of employing interviewers from the local community and region may lead to unintended bias when participants and interviewers know each other outside of the research project. In situations where a preexisting social relationship exists, there is a greater possibility of social desirability bias. This may be particularly true for sensitive issues where they may not wish for members of their community to learn something about themselves which would otherwise remain hidden or private. This paper examines three sources of potential interviewer effects upon measures of mental health and cultural engagement. Both are key outcomes of a random control trial intervention underway with American Indian youth living on or near reservations. Mental health is measured using the Achenbach System of Empirically Based Assessment (ASEBA) with a 107 item tool which gauges levels of externalizing and internalizing behavior among minors, as well as three subscales for internalizing behavior and two subscales for externalizing behavior. Cultural engagement is measured with an inventory of common local/regional cultural activities. Three interview/interviewer characteristics are assessed in this paper. The first is whether an interviewer reports knowing the participant very well or somewhat well compared to not knowing them at all. We find that participants who were known by the interviewer scored lower on the aggregate internalizing scale and in all three subscales than participants who were unknown to the interviewer. However, there was no effect upon either externalizing scores or reported cultural participation when the interviewer knew the participant. The second factor tested is whether the interviewer reported a third party present during the interview who was listening or taking part. Here we found that having a third party present was associated with lower scores on the somatic complaints subscale of the internalizing scale, but no other subscale or aggregate measures. The third interview factor tested is the interviewer’s assessment of whether the participant was open with their responses or not. Here we find participants who were rated as open, reported higher levels of cultural participation and lower values on the internalizing subscale that assess withdrawn characteristics. We found no difference in the externalizing scales or the aggregate internalizing scale. The effects of these associations upon study outcomes and their potential to shift the diagnostic criteria of the ASEBA are discussed in the full paper

Unintended Interviewer Bias in a Community-based Participatory Research Randomized Control Trial among American Indian Youth

Community-based participatory research (CBPR) projects often employ members of the host partner community to engage and assist with research projects. However, CBPR may also introduce bias to survey statistics when community partners work as interviewers for projects within their own communities. Here, the advantage of employing interviewers from the local community and region may lead to unintended bias when participants and interviewers know each other outside of the research project. In situations where a preexisting social relationship exists, there is a greater possibility of social desirability bias. This may be particularly true for sensitive issues where they may not wish for members of their community to learn something about themselves which would otherwise remain hidden or private. This paper examines three sources of potential interviewer effects upon measures of mental health and cultural engagement. Both are key outcomes of a random control trial intervention underway with American Indian youth living on or near reservations. Mental health is measured using the Achenbach System of Empirically Based Assessment (ASEBA) with a 107 item tool which gauges levels of externalizing and internalizing behavior among minors, as well as three subscales for internalizing behavior and two subscales for externalizing behavior. Cultural engagement is measured with an inventory of common local/regional cultural activities. Three interview/interviewer characteristics are assessed in this paper. The first is whether an interviewer reports knowing the participant very well or somewhat well compared to not knowing them at all. We find that participants who were known by the interviewer scored lower on the aggregate internalizing scale and in all three subscales than participants who were unknown to the interviewer. However, there was no effect upon either externalizing scores or reported cultural participation when the interviewer knew the participant. The second factor tested is whether the interviewer reported a third party present during the interview who was listening or taking part. Here we found that having a third party present was associated with lower scores on the somatic complaints subscale of the internalizing scale, but no other subscale or aggregate measures. The third interview factor tested is the interviewer’s assessment of whether the participant was open with their responses or not. Here we find participants who were rated as open, reported higher levels of cultural participation and lower values on the internalizing subscale that assess withdrawn characteristics. We found no difference in the externalizing scales or the aggregate internalizing scale. The effects of these associations upon study outcomes and their potential to shift the diagnostic criteria of the ASEBA are discussed in the full paper

Framing and Cultivating the Story of Crime: The Effects of Media Use, Victimization, and Social Networks on Attitudes About Crime

The current study extended prior research by considering the effects of media, victimization, and network experiences on attitudes about crime and justice, drawing on the problem frame, cultivation, real-word, and interpersonal diffusion theses. Data were from a survey of Nebraska adults (n = 550) who were asked about their social networks; beliefs about media reliability; use of newspaper and news on TV, radio, and the Internet; and exposure to violence on TV, movies, and the Internet. Results indicated that viewing TV violence predicted worry and anger about crime. Believing the media are a reliable source of information about crime predicted more anger and more support for the justice system. Personal and network members’ victimization was also linked to attitudes. Other network contacts, including knowing police or correctional officers or knowing someone who had been arrested or incarcerated, had limited effects. The results support the problem frame and cultivation theses in that media framing and media consumption influence attitudes about crime, as do certain real-world experiences

Improving the Network Scale-Up Estimator: Incorporating Means of Sums, Recursive Back Estimation, and Sampling Weights

Researchers interested in studying populations that are difficult to reach through traditional survey methods can now draw on a range of methods to access these populations. Yet many of these methods are more expensive and difficult to implement than studies using conventional sampling frames and trusted sampling methods. The network scale-up method (NSUM) provides a middle ground for researchers who wish to estimate the size of a hidden population, but lack the resources to conduct a more specialized hidden population study. Through this method it is possible to generate population estimates for a wide variety of groups that are perhaps unwilling to self-identify as such (for example, users of illegal drugs or other stigmatized populations) via traditional survey tools such as telephone or mail surveys—by asking a representative sample to estimate the number of people they know who are members of such a “hidden” subpopulation. The original estimator is formulated to minimize the weight a single scaling variable can exert upon the estimates. We argue that this introduces hidden and difficult to predict biases, and instead propose a series of methodological advances on the traditional scale-up estimation procedure, including a new estimator. Additionally, we formalize the incorporation of sample weights into the network scale-up estimation process, and propose a recursive process of back estimation “trimming” to identify and remove poorly performing predictors from the estimation process. To demonstrate these suggestions we use data from a network scale-up mail survey conducted in Nebraska during 2014. We find that using the new estimator and recursive trimming process provides more accurate estimates, especially when used in conjunction with sampling weights

Improving the Network Scale-Up Estimator: Incorporating Means of Sums, Recursive Back Estimation, and Sampling Weights

Researchers interested in studying populations that are difficult to reach through traditional survey methods can now draw on a range of methods to access these populations. Yet many of these methods are more expensive and difficult to implement than studies using conventional sampling frames and trusted sampling methods. The network scale-up method (NSUM) provides a middle ground for researchers who wish to estimate the size of a hidden population, but lack the resources to conduct a more specialized hidden population study. Through this method it is possible to generate population estimates for a wide variety of groups that are perhaps unwilling to self-identify as such (for example, users of illegal drugs or other stigmatized populations) via traditional survey tools such as telephone or mail surveys—by asking a representative sample to estimate the number of people they know who are members of such a “hidden” subpopulation. The original estimator is formulated to minimize the weight a single scaling variable can exert upon the estimates. We argue that this introduces hidden and difficult to predict biases, and instead propose a series of methodological advances on the traditional scale-up estimation procedure, including a new estimator. Additionally, we formalize the incorporation of sample weights into the network scale-up estimation process, and propose a recursive process of back estimation “trimming” to identify and remove poorly performing predictors from the estimation process. To demonstrate these suggestions we use data from a network scale-up mail survey conducted in Nebraska during 2014. We find that using the new estimator and recursive trimming process provides more accurate estimates, especially when used in conjunction with sampling weights

Harm reduction in the Heartland: public knowledge and beliefs about naloxone in Nebraska, USA

Background: Opioid-related overdose deaths have been increasing in the United States (U.S.) in the last twenty years, creating a public health challenge. Take-home naloxone is an effective strategy for preventing opioid-related overdose death, but its widespread use is particularly challenging in smaller cities, towns, and rural areas where it may be stigmatized and/or poorly understood. Methods: We analyzed data on knowledge and beliefs about drug use and naloxone among the general public in Nebraska, a largely rural state in the Great Plains region of the U.S., drawing on the 2020 Nebraska Annual Social Indicators Survey. Results: Respondents reported negative beliefs about people who use drugs (PWUD) and little knowledge of naloxone. Over half reported that members of their community view PWUD as blameworthy, untrustworthy, and dangerous. Approximately 31% reported being unaware of naloxone. Only 15% reported knowing where to obtain naloxone and less than a quarter reported knowing how to use it. Knowing where to obtain naloxone is associated with access to opioids and knowing someone who has recently overdosed, but having ever used opioids or being close to someone who uses opioids is not associated with naloxone knowledge. Finally, almost a quarter of respondents endorsed the belief that people who use opioids will use more if they have access to naloxone. Conclusion: Our findings highlight stigmatizing beliefs about PWUD and underscore the need for further education on naloxone as an effective strategy to reduce opioid-related overdose death. We highlight the implications of these findings for public education efforts tailored to non-urban communities