DESCRIPTIONThis repository contains analysis scripts (with outputs), figures from the manuscript, and supplementary files the HIV Pain (HIP) Intervention Study. All analysis scripts (and their outputs -- /outputs subdirectory) are found in HIP-study.zip, while PDF copies of the analysis outputs that are cited in the manuscript as supplementary material are found in the relevant supplement-*.pdf file.Note: Participant consent did not provide for the publication of their data, and hence neither the original nor cleaned data have been made available. However, we do not wish to bar access to the data unnecessarily and we will judge requests to access the data on a case-by-case basis. Examples of potential use cases include independent assessments of our analyses, and secondary data analyses. Please contact Peter Kamerman (peter.kamerman@gmail.com), Dr Tory Madden (torymadden@gmail.com, or open an issue on the GitHub repo (https://github.com/kamermanpr/HIP-study/issues).BIBLIOGRAPHIC INFORMATIONRepository citationKamerman PR, Madden VJ, Parker R, Devan D, Cameron S, Jackson K, Reardon C, Wadley A. Analysis scripts and supplementary files: Barriers to implementing clinical trials on non-pharmacological treatments in developing countries – lessons learnt from addressing pain in HIV. DOI: 10.6084/m9.figshare.7654637.Manuscript citationParker R, Madden VJ, Devan D, Cameron S, Jackson K, Kamerman P, Reardon C, Wadley A. Barriers to implementing clinical trials on non-pharmacological treatments in developing countries – lessons learnt from addressing pain in HIV. Pain Reports [submitted 2019-01-31]Manuscript abstractintroduction: Pain affects over half of people living with HIV/AIDS (LWHA) and pharmacological treatment has limited efficacy. Preliminary evidence supports non-pharmacological interventions. We previously piloted a multimodal intervention in amaXhosa women LWHA and chronic pain in South Africa with improvements seen in all outcomes, in both intervention and control groups. Methods: A multicentre, single-blind randomised controlled trial with 160 participants recruited was conducted to determine whether the multimodal peer-led intervention reduced pain in different populations of both male and female South Africans LWHA. Participants were followed up at Weeks 4, 8, 12, 24 and 48 to evaluate effects on the primary outcome of pain, and on depression, self-efficacy and health-related quality of life. Results: We were unable to assess the efficacy of the intervention due to a 58% loss to follow up (LTFU). Secondary analysis of the LTFU found that sociocultural factors were not predictive of LTFU. Depression, however, did associate with LTFU, with greater severity of depressive symptoms predicting LTFU at week 8 (p=0.01). Discussion: We were unable to evaluate the effectiveness of the intervention due to the high LTFU and the risk of retention bias. The different sociocultural context in South Africa may warrant a different approach to interventions for pain in HIV compared to resource-rich countries, including a concurrent strategy to address barriers to health care service delivery. We suggest that assessment of pain and depression need to occur simultaneously in those with pain in HIV. We suggest investigation of the effect of social inclusion on pain and depression. USING DOCKER TO RUN THE HIP-STUDY ANALYSIS SCRIPTSThese instructions are for running the analysis on your local machine.You need to have Docker installed on your computer. To do so, go to docker.com (https://www.docker.com/community-edition#/download) and follow the instructions for downloading and installing Docker for your operating system. Once Docker has been installed, follow the steps below, noting that Docker commands are entered in a terminal window (Linux and OSX/macOS) or command prompt window (Windows). Windows users also may wish to install GNU Make (http://gnuwin32.sourceforge.net/downlinks/make.php) (required for the make method of running the scripts) and Git (https://gitforwindows.org/) version control software (not essential).Download the latest imageEnter: docker pull kamermanpr/docker-hip-study:v2.0.0Run the containerEnter: docker run -d -p 8787:8787 -v :/home/rstudio --name threshold -e USER=hip -e PASSWORD=study kamermanpr/docker-hip-study:v2.0.0Where refers to the path to the HIP-study directory on your computer, which you either cloned from GitHub (https://github.com/kamermanpr/HIP-study.git), git clone https://github.com/kamermanpr/HIP-study, or downloaded and extracted from figshare (https://doi.org/10.6084/m9.figshare.7654637).Login to RStudio Server- Open a web browser window and navigate to: localhost:8787- Use the following login credentials: - Username: hip - Password: study Prepare the HIP-study directoryThe HIP-study directory comes with the outputs for all the analysis scripts in the /outputs directory (html and md formats). However, should you wish to run the scripts yourself, there are several preparatory steps that are required:1. Acquire the data. The data required to run the scripts have not been included in the repo because participants in the studies did not consent to public release of their data. However, the data are available on request from Peter Kamerman (peter.kamerman@gmail.com). Once the data have been obtained, the files should be copied into a subdirectory named /data-original.2. Clean the /outputs directory by entering make clean in the Terminal tab in RStudio.Run the HIP-study analysis scriptsTo run all the scripts (including the data cleaning scripts), enter make all in the Terminal tab in RStudio.To run individual RMarkdown scripts (*.Rmd files)1. Generate the cleaned data using one of the following methods: - Enter make data-cleaned/demographics.rds in the Terminal tab in RStudio. - Enter source('clean-data-script.R') in the Console tab in RStudio. - Open the clean-data-script.R script through the File tab in RStudio, and then click the 'Source' button on the right of the Script console in RStudio for each script. 2. Run the individual script by: - Entering make outputs/.html in the Terminal tab in RStudio, OR - Opening the relevant *.Rmd file through the File tab in RStudio, and then clicking the 'knit' button on the left of the Script console in RStudio. Shutting downOnce done, log out of RStudio Server and enter the following into a terminal to stop the Docker container: docker stop hip. If you then want to remove the container, enter: docker rm threshold. If you also want to remove the Docker image you downloaded, enter: docker rmi kamermanpr/docker-hip-study:v2.0.0

Abstract

This is the microdataset used in the paper "SMS nudges as a tool to reduce Tuberculosis treatment delay and pretreatment loss to follow-up. A randomized controlled trial". We fielded two SMS interventions in three Cape Town clinics to see their effects on whether people returned to clinic, and how quickly. One was a simple reminder; the other aimed to overcome “optimism bias” by reminding people TB is curable and many millions die unnecessarily from it. Recruits were randomly assigned at the clinic level to a control group or one of the two SMS groups (1:2:2). In addition to estimating effects on the full sample, we also estimated effects on HIV-positive patients.

Geographic coverage

3 clinics in Greater Cape Town

Analysis unit

Patient

Kind of data

Clinical data [cli]

Sampling procedure

Patients not already being treated for TB arriving in TB waiting rooms of 3 clinics. Aimed to recruit > 90% of new patients over recruitment period. Inclusion criteria: Adult, provided consent, not already on treatment, waiting for a TB test or just had a TB test. Exclusion criteria: Adult, refused consent, already on treatment, not waiting for a TB test or just had a TB test. Recruitment was from 2 October 2017 until 15 December 2017. Fieldworkers continued visiting clinics and phoning patients until mid-February 2018 to collect data on patients’ return-to-clinic date, test results and treatment start date.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

CAPI interview at recruitment was based on a long questionnaire only a few questions from which were used in the present study. The questionnaire is therefore not attached to the current dataset.

Cleaning operations

Data-cleaning was done by staff at Stellenbosch University and the World Bank.

Background: Acid-base disturbances are common issues during continuous veno-venous hemofiltration (CVVH). Especially using regional citrate anticoagulation (RCA) recent studies have shown that control in intracorporal pH and HCO3- concentration may be improved when the replacement fluid is changed to a solution with a lower HCO3- concentration during continuous renal replacement therapy (CRRT). This prospective trail aims to compare acid base balance between a high (HBF) and low (LBF) bicarbonate replacement fluid over a period of 96 hours after CVVH initiation using RCA. Methods/ design: This is a prospective, randomized, controlled, open-label, cross-over, Phase II, single-centre pilot study involving critically ill patients requiring RRT. The two replacement fluids (Phoxilium and Biphozyl) are compared in two groups with 1:1 block randomization and consecutive crossover after 48 hours of CVVH. The primary endpoints are the occurrence of at least one pH (> 7.45) or HCO3- (> 26 mmol/l) excursion within 16-48 hours of each treatment phase using a Generalized Estimating Equation (GEE) approach. Primary objective: The objective is to examine differences of pH and HCO3- between patients who receive LBF and HBF as replacement fluid during CVVH. Hypothesis: We hypothesize that during CVVH with LBF, pH and HCO3- excursion rates are significantly lower compared to HBF. Trial status: Recruitment of 88 study participants is ongoing, with the trial expected to be completed in 2025. Data cleaning, analysis, and publication preparation will follow thereafter. Discussion: Given the broad inclusion and restricted exclusion criteria, we expect the results of the BiPhox-Trial to be broadly applicable to patients in need of CVVH with RCA in the intensive care setting. This trial aims to determine whether the use of LBF results in more stable acid-base parameters compared to HBF during CVVH with RCA in critically ill patients, and may guide therapeutic decisions in clinical practice.

BackgroundResearch conducted in the United States suggests that two primes (citrus smells and pictures of a person's eyes) can increase hand gel dispenser use on the day they are introduced in hospital. The current study, conducted at a hospital in the United Kingdom, evaluated the effectiveness of these primes, both in isolation and in combination, at the entry way to four separate wards, over a longer duration than the previous work.MethodsA crossover randomized controlled trial was conducted. Four wards were allocated for 6 weeks of observation to each of four conditions, including “control,” “olfactory,” “visual,” or “both” (i.e., “olfactory” and “visual” combined). It was hypothesized that hand hygiene compliance would be greater in all priming conditions relative to the control condition. The primary outcome was whether people used the gel dispenser when they entered the wards. After the trial, a follow up survey of staff at the same hospital assessed the barriers to, and facilitators of, hand hygiene compliance. The trial data were analyzed using regression techniques and the survey data were analyzed using descriptive statistics.ResultsThe total number of individuals observed in the trial was 9,811 (female = 61%), with similar numbers across conditions, including “control” N = 2,582, “olfactory” N = 2,700, “visual” N = 2,488, and “both” N = 2,141. None of the priming conditions consistently increased hand hygiene. The lowest percentage compliance was observed in the “both” condition (7.8%), and the highest was observed in the “visual” condition (12.7%). The survey was completed by 97 staff (female = 81%). “Environmental resources” and “social influences” were the greatest barriers to staff cleaning their hands.ConclusionsTaken together, the current findings suggest that the olfactory and visual priming interventions investigated do not influence hand hygiene consistently. To increase the likelihood of such interventions succeeding, future research should focus on prospectively determined mechanisms of action.