Publications

Abstract

Background and objectives: Promoted globally as an evidence-based intervention in the prevention of HIV and treatment of heroin addiction among people who inject drugs (PWID), opioid substitution treatment (OST) can help control emerging HIV epidemics among PWID. With implementation in December 2014, Kenya is the third Sub-Saharan African country to have introduced OST. We combine dynamic mathematical modelling with qualitative sociological research to examine the 'promise of methadone' to Kenya. Methods, setting and participants: We model the HIV prevention impact of OST in Nairobi, Kenya, at different levels of intervention coverage. We draw on thematic analyses of 109 qualitative interviews with PWID, and 43 with stakeholders, to chart their narratives of expectation in relation to the promise of methadone. Results: The modelled impact of OST shows relatively slight reductions in HIV incidence (5-10%) and prevalence (2-4%) over 5 years at coverage levels (around 10%) anticipated in the planned roll-out of OST. However, there is a higher impact with increased coverage, with 40% coverage producing a 20% reduction in HIV incidence, even when accounting for relatively high sexual transmissions. Qualitative findings emphasise a culture of 'rationed expectation' in relation to access to care and a 'poverty of drug treatment opportunity'. In this context, the promise of methadone may be narrated as a symbol of hope - both for individuals and community - in relation to addiction recovery. Conclusions: Methadone offers HIV prevention potential, but there is a need to better model the effects of sexual HIV transmission in mediating the impact of OST among PWID in settings characterised by a combination of generalised and concentrated epidemics. We find that individual and community narratives of methadone as hope for recovery coexist with policy narratives positioning methadone primarily in relation to HIV prevention. Our analyses show the value of mixed methods approaches to investigating newly-introduced interventions.

Abstract

Background: Physical inactivity continues to be amajor risk factor for cardiovascular disease, and only one half of adults in the United States meet physical activity (PA) goals. PA data are often collected for surveillance or for measuring change after an intervention. One of the challenges in PA research is quantifying exactly how much and what type of PA is taking place-especially because self-report instruments have inconsistent validity. Objective: The purpose is to review the elements to consider when collecting PA data via motion sensors, including the difference between PA and exercise, type of data to collect, choosing the device, length of time to monitor PA, instructions to the participants, and interpretation of the data. Methods: The current literature on motion sensor research was reviewed and synthesized to summarize relevant considerations when using a motion sensor to collect PA data. Results: Exercise is a division of PA that is structured, planned, and repetitive. Pedometer data include steps taken and calculated distance and energy expenditure. Accelerometer data include activity counts and intensity. The device chosen depends on desired data, cost, validity, and ease of use. Reactivity to the device may influence the duration of data collection. Instructions to participantsmay vary depending on the purpose of the study. Experts suggest pedometer data be reported as steps-because that is the direct output-and distance traveled and energy expenditure are estimated values. Accelerometer count data may be analyzed to provide information on time spent in moderate or vigorous activity. Discussion: Thoughtful decision making about PA data collection using motion sensor devices is needed to advance nursing science.