In a microbicide safety and effectiveness trial (HPTN 035) in Malawi, 585 women completed the same questionnaire through a face-to-face interview (FTFI) and an audio computer-assisted self-interview (ACASI). Concordance between FTFI and ACASI responses ranged from 72.0 % for frequency of sex in the past week to 95.2 % for anal intercourse (AI) in the past 3 months. Reported gel and condom use at last sex act were marginally lower with ACASI than FTFI (73.5 % vs. 77.2 %, p = 0.11 and 60.9 % vs. 65.5 %, p = 0.05, respectively). More women reported AI with ACASI than FTFI (5.0 % vs. 0.2 %, p < 0.001). Analyses of consistency of responses within ACASI revealed that 15.0 % of participants in the condom-only arm and 28.7 % in the gel arm provided at least one discrepant answer regarding total sex acts and sex acts where condom and gel were used (19.2 % reported one inconsistent answer, 8.1 % reported two inconsistent answers, and 1.4 % reported three inconsistent answers). While ACASI may provide more accurate assessments of sensitive behaviors in HIV prevention trials, it also results in a high level of internally inconsistent responses.

Misreporting of adherence undermines detection of an association between product use and HIV infection in microbicide trials. This study investigates whether, in a placebo trial, audio computer-assisted self-interviewing (ACASI) produces more accurate reporting of adherence and sexual behavior than a face-to-face interview (FTFI). At three South African clinics, 849 women were enrolled and instructed to use applicators filled with placebo gel; participants were randomly assigned to FTFI or ACASI. Behavioral reports were validated through two biomarkers that detect product usage and unprotected sex. For most behaviors, ACASI generated significantly higher reporting, although differences by interview mode appeared to diminish over time. ACASI participants were more likely to report having had sex without gel, but reported and tested applicators did not indicate greater honesty about gel insertion with ACASI. While comparisons of reported unprotected sex with the validated biomarker revealed more agreement with ACASI than with FTFI, differences were small.

BackgroundAudio-Computer Assisted Self- Interview (ACASI) is a method of data collection in which participants listen to pre-recorded questions through headphones and respond to questions by selecting their answers on a touch screen or keypad, and is seen as advantageous for gathering data on sensitive topics such as experiences of violence. This paper seeks to explore the feasibility and acceptability of using ACASI with adolescent girls and to document the implementation of such an approach in two humanitarian settings: conflict-affected communities in eastern Democratic Republic of Congo (DRC) and refugee camps along the Sudan-Ethiopia border.MethodsThis paper evaluates the feasibility and acceptability of implementing ACASI, based on the experiences of using this tool in baseline data collections for COMPASS (Creating Opportunities through Mentorship, Parental involvement, and Safe Spaces) impact evaluations in DRC (N = 868) and Ethiopia (N = 919) among adolescent girls. Descriptive statistics and logistic regression models were generated to examine associations between understanding of the survey and selected demographics in both countries.ResultsOverall, nearly 90 % of girls in the DRC felt that the questions were easy to understand as compared to approximately 75 % in Ethiopia. Level of education, but not age, was associated with understanding of the survey in both countries.ConclusionsFinancial and time investment to ready ACASI was substantial in order to properly contextualize the approach to these specific humanitarian settings, including piloting of images, language assessments, and checking both written translations and corresponding verbal recordings. Despite challenges, we conclude that ACASI proved feasible and acceptable to participants and to data collection teams in two diverse humanitarian settings.Electronic supplementary materialThe online version of this article (doi:10.1186/s13031-016-0098-1) contains supplementary material, which is available to authorized users.

Young men who have sex with men (YMSM) face a disproportionately high burden of HIV. Oral pre-exposure prophylaxis (PrEP) is effective in preventing HIV acquisition, but adherence to PrEP among YMSM may be inadequate. Medication adherence may be assessed via biomarkers, which are expensive and invasive, or via self-report through Audio Computer Assisted Self-Interview (ACASI), which may result in over-reporting of adherence. In this paper we assess the potential of a new method of self-report, the Interactive Questionnaire System (iQS), in validly estimating true adherence rates. PrEP adherence among 167 YMSM aged 15-23 was measured via dried blood spot (DBS), ACASI, and iQS twice over a 24-week study period. Both ACASI- and iQS-reported data revealed that over 40% of individuals self-reporting adequate PrEP adherence had DBS-estimated drug levels indicating inadequate adherence. Adjusted logistic repeated measures random intercept regression analyses indicated that younger YMSM had higher odds of over-reporting adherence than older YMSM-each 1 year increase in age was associated with 0.79 times the odds of over-reporting adherence (95% CI 0.63, 0.98; p value = 0.031), and being African American was associated with 3.22 times greater odds of over-reporting than non-African Americans (95% CI 1.51, 6.90; p-value = 0.0003). These results suggest that ACASI and iQS methods of self-report significantly overestimate true PrEP adherence rates among YMSM, and that the odds of over-reporting adherence may be affected by both age and race.

This paper will discuss whether bots, particularly chat bots, can be useful in public health research and health or pharmacy systems operations.  Bots have been discussed for many years; particularly when coupled with artificial intelligence, they offer the opportunity of automating mundane or error-ridden processes and tasks by replacing human involvement with bots. This paper will discuss areas where there are greater advances in the use of bots, as well as areas that may benefit from the use of bots, and will offer practical ways to get started with bot technology.  Several popular bot applications and bot development tools along with practical security considerations will be discussed, and a toolbox that one can begin to use to implement bots will be presented.