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Rokicki, Slawa

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Rokicki

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Slawa

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Rokicki, Slawa
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    The Impact of Text Message Reminders on Adherence to Antimalarial Treatment in Northern Ghana: A Randomized Trial
    (Public Library of Science, 2014) Raifman, Julia R. G.; Lanthorn, Heather Elisabeth; Rokicki, Slawa; Fink, Gunther
    Background: Low rates of adherence to artemisinin-based combination therapy (ACT) regimens increase the risk of treatment failure and may lead to drug resistance, threatening the sustainability of current anti-malarial efforts. We assessed the impact of text message reminders on adherence to ACT regimens. Methods: Health workers at hospitals, clinics, pharmacies, and other stationary ACT distributors in Tamale, Ghana provided flyers advertising free mobile health information to individuals receiving malaria treatment. The messaging system automatically randomized self-enrolled individuals to the control group or the treatment group with equal probability; those in the treatment group were further randomly assigned to receive a simple text message reminder or the simple reminder plus an additional statement about adherence in 12-hour intervals. The main outcome was self-reported adherence based on follow-up interviews occurring three days after treatment initiation. We estimated the impact of the messages on treatment completion using logistic regression. Results: 1140 individuals enrolled in both the study and the text reminder system. Among individuals in the control group, 61.5% took the full course of treatment. The simple text message reminders increased the odds of adherence (adjusted OR 1.45, 95% CI [1.03 to 2.04], p-value 0.028). Receiving an additional message did not result in a significant change in adherence (adjusted OR 0.77, 95% CI [0.50 to 1.20], p-value 0.252). Conclusion: The results of this study suggest that a simple text message reminder can increase adherence to antimalarial treatment and that additional information included in messages does not have a significant impact on completion of ACT treatment. Further research is needed to develop the most effective text message content and frequency. Trial Registration ClinicalTrials.gov NCT01722734
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    Improving Reproductive Health: Assessing Determinants and Measuring Policy Impacts
    (2016-05-11) Rokicki, Slawa; Salomon, Joshua; Cohen, Jessica; Fink, Gunther; Landrum, Mary Beth
    In this thesis, I investigate policies and programs to improve reproductive health. My thesis makes a substantive contribution to reproductive health policy and a methodological contribution to quasi-experimental research. In chapter 1, I evaluate the impact of a mobile phone intervention for adolescent girls. I design and implement a randomized controlled trial in Ghana to test whether sending information via mobile phones is an effective way to improve girls’ knowledge of sexual health and to ultimately reduce teenage pregnancy. I find that mobile phone programs are effective not only in increasing knowledge, but also in decreasing risk of pregnancy among sexually active adolescents. I discuss the results in the context of sexual education policy in Ghana. In chapter 2, I explore the complex interactions between migration and reproductive health. I reconstruct the complete migration and reproductive health histories of women residing in the urban slums of Accra, Ghana. Using individual fixed effects to reduce selection bias, I find an increased risk of pregnancy, miscarriage, and abortion in the 48 months after migration, with no significant increase in the chance of live birth during this time period. With half of abortions in Ghana classified as unsafe, these results suggest that policies which target the rapidly growing number of urban migrants by providing access to contraception and public hospital services may reduce unsafe abortion and improve maternal health outcomes. In chapter 3, I investigate the bias of standard errors in difference-in-difference estimation, which typically evaluates the effect of a group-level intervention on individual data. Common modeling adjustments for grouped data, such as cluster-robust standard errors, are biased when the number of clusters is small. I run Monte Carlo simulations to investigate both the coverage and power of a wide variety of modeling solutions from the econometric and biostatistics fields, while varying the balance of cluster sizes, the degree of error correlation, and the proportion of treated clusters. I then apply my results to re-evaluate a recently published study on the effect of emergency contraception on adolescent sexual behavior. I find that the study’s results claiming that emergency contraception increases risky sexual behavior may be spurious once proper adjustments for grouped data are applied.