Abstract

Round 1 of the Afrobarometer survey was conducted from July 1999 through June 2001 in 12 African countries, to solicit public opinion on democracy, governance, markets, and national identity. The full 12 country dataset released was pieced together out of different projects, Round 1 of the Afrobarometer survey,the old Southern African Democracy Barometer, and similar surveys done in West and East Africa.

The 7 country dataset is a subset of the Round 1 survey dataset, and consists of a combined dataset for the 7 Southern African countries surveyed with other African countries in Round 1, 1999-2000 (Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe). It is a useful dataset because, in contrast to the full 12 country Round 1 dataset, all countries in this dataset were surveyed with the identical questionnaire

Geographic coverage

Botswana Lesotho Malawi Namibia South Africa Zambia Zimbabwe

Analysis unit

Basic units of analysis that the study investigates include: individuals and groups

Kind of data

Sample survey data [ssd]

Sampling procedure

A new sample has to be drawn for each round of Afrobarometer surveys. Whereas the standard sample size for Round 3 surveys will be 1200 cases, a larger sample size will be required in societies that are extremely heterogeneous (such as South Africa and Nigeria), where the sample size will be increased to 2400. Other adaptations may be necessary within some countries to account for the varying quality of the census data or the availability of census maps.

The sample is designed as a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of selection for interview. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible. A randomly selected sample of 1200 cases allows inferences to national adult populations with a margin of sampling error of no more than plus or minus 2.5 percent with a confidence level of 95 percent. If the sample size is increased to 2400, the confidence interval shrinks to plus or minus 2 percent.

Sample Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

Sample Design

The sample design is a clustered, stratified, multi-stage, area probability sample.

To repeat the main sampling principle, the objective of the design is to give every sample element (i.e. adult citizen) an equal and known chance of being chosen for inclusion in the sample. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible.

In a series of stages, geographically defined sampling units of decreasing size are selected. To ensure that the sample is representative, the probability of selection at various stages is adjusted as follows:

The sample is stratified by key social characteristics in the population such as sub-national area (e.g. region/province) and residential locality (urban or rural). The area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. And the urban/rural stratification is a means to make sure that these localities are represented in their correct proportions. Wherever possible, and always in the first stage of sampling, random sampling is conducted with probability proportionate to population size (PPPS). The purpose is to guarantee that larger (i.e., more populated) geographical units have a proportionally greater probability of being chosen into the sample. The sampling design has four stages

A first-stage to stratify and randomly select primary sampling units;

A second-stage to randomly select sampling start-points;

A third stage to randomly choose households;

A final-stage involving the random selection of individual respondents

We shall deal with each of these stages in turn.

STAGE ONE: Selection of Primary Sampling Units (PSUs)

The primary sampling units (PSU's) are the smallest, well-defined geographic units for which reliable population data are available. In most countries, these will be Census Enumeration Areas (or EAs). Most national census data and maps are broken down to the EA level. In the text that follows we will use the acronyms PSU and EA interchangeably because, when census data are employed, they refer to the same unit.

We strongly recommend that NIs use official national census data as the sampling frame for Afrobarometer surveys. Where recent or reliable census data are not available, NIs are asked to inform the relevant Core Partner before they substitute any other demographic data. Where the census is out of date, NIs should consult a demographer to obtain the best possible estimates of population growth rates. These should be applied to the outdated census data in order to make projections of population figures for the year of the survey. It is important to bear in mind that population growth rates vary by area (region) and (especially) between rural and urban localities. Therefore, any projected census data should include adjustments to take such variations into account.

Indeed, we urge NIs to establish collegial working relationships within professionals in the national census bureau, not only to obtain the most recent census data, projections, and maps, but to gain access to sampling expertise. NIs may even commission a census statistician to draw the sample to Afrobarometer specifications, provided that provision for this service has been made in the survey budget.

Regardless of who draws the sample, the NIs should thoroughly acquaint themselves with the strengths and weaknesses of the available census data and the availability and quality of EA maps. The country and methodology reports should cite the exact census data used, its known shortcomings, if any, and any projections made from the data. At minimum, the NI must know the size of the population and the urban/rural population divide in each region in order to specify how to distribute population and PSU's in the first stage of sampling. National investigators should obtain this written data before they attempt to stratify the sample.

Once this data is obtained, the sample population (either 1200 or 2400) should be stratified, first by area (region/province) and then by residential locality (urban or rural). In each case, the proportion of the sample in each locality in each region should be the same as its proportion in the national population as indicated by the updated census figures.

Having stratified the sample, it is then possible to determine how many PSU's should be selected for the country as a whole, for each region, and for each urban or rural locality.

The total number of PSU's to be selected for the whole country is determined by calculating the maximum degree of clustering of interviews one can accept in any PSU. Because PSUs (which are usually geographically small EAs) tend to be socially homogenous we do not want to select too many people in any one place. Thus, the Afrobarometer has established a standard of no more than 8 interviews per PSU. For a sample size of 1200, the sample must therefore contain 150 PSUs/EAs (1200 divided by 8). For a sample size of 2400, there must be 300 PSUs/EAs.

These PSUs should then be allocated proportionally to the urban and rural localities within each regional stratum of the sample. Let's take a couple of examples from a country with a sample size of 1200. If the urban locality of Region X in this country constitutes 10 percent of the current national population, then the sample for this stratum should be 15 PSUs (calculated as 10 percent of 150 PSUs). If the rural population of Region Y constitutes 4 percent of the current national population, then the sample for this stratum should be 6 PSU's.

The next step is to select particular PSUs/EAs using random methods. Using the above example of the rural localities in Region Y, let us say that you need to pick 6 sample EAs out of a census list that contains a total of 240 rural EAs in Region Y. But which 6? If the EAs created by the national census bureau are of equal or roughly equal population size, then selection is relatively straightforward. Just number all EAs consecutively, then make six selections using a table of random numbers. This procedure, known as simple random sampling (SRS), will

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics.

The 12 country datasetis a combined dataset for the 12 African countries surveyed during round 1 of the survey, conducted between 1999-2000 (Botswana, Ghana, Lesotho, Mali, Malawi, Namibia, Nigeria South Africa, Tanzania, Uganda, Zambia and Zimbabwe), plus data from the old Southern African Democracy Barometer, and similar surveys done in West and East Africa.

Geographic coverage

The Round 1 Afrobarometer surveys have national coverage for the following countries: Botswana, Ghana, Lesotho, Malawi, Mali, Namibia, Nigeria, South Africa, Tanzania, Uganda, Zambia, Zimbabwe.

Analysis unit

Individuals

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Data weights For some national surveys, data are weighted to correct for over or under-sampling or for household size. "Withinwt" should be turned on for all national -level descriptive statistics in countries that contain this weighting variable. It is included as the last variable in the data set, with details described in the codebook. For merged data sets, "Combinwt" should be turned on for cross-national comparisons of descriptive statistics. Note: this weighting variable standardizes each national sample as if it were equal in size.

Further information on sampling protocols, including full details of the methodologies used for each stage of sample selection, can be found at https://afrobarometer.org/surveys-and-methods/sampling-principles

Mode of data collection

Face-to-face [f2f]

Research instrument

Because Afrobarometer Round 1 emerged out of several different survey research efforts, survey instruments were not standardized across all countries, there are a number of features of the questionnaires that should be noted, as follows: • In most cases, the data set only includes those questions/variables that were asked in nine or more countries. Complete Round 1 data sets for each individual country have already been released, and are available from ICPSR or from the Afrobarometer website at www.afrobarometer.org. • In the seven countries that originally formed the Southern Africa Barometer (SAB) - Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe - a standardized questionnaire was used, so question wording and response categories are the generally the same for all of these countries. The questionnaires in Mali and Tanzania were also essentially identical (in the original English version). Ghana, Uganda and Nigeria each had distinct questionnaires. • This merged dataset combines, into a single variable, responses from across these different countries where either identical or very similar questions were used, or where conceptually equivalent questions can be found in at least nine of the different countries. For each variable, the exact question text from each of the countries or groups of countries ("SAB" refers to the Southern Africa Barometer countries) is listed. • Response options also varied on some questions, and where applicable, these differences are also noted.

The knowledge, attitudes and behaviour of South Africans with respect to NCDs and tuberculosis; The nutritional status of South Africans as it relates to food security, dietary intake/ behaviour including alcohol consumption, body image and weight management; The perceptions of general and mental health (stress and trauma) and healthcare services; The health status of children under the age of five years; The health status of children aged 2–9 years with respect to physical and/or mental disabilities; The behavioural (smoking, diet, physical inactivity) and social determinants of health and nutrition (demographic, socio-economic status and locality) and relate these to the health and nutritional status of the population. Clinical measurements Face-to-face interview Physical measurements Psychological measurements All persons living in occupied households (HHs) were eligible to participate. The survey applied a multi-stage disproportionate, stratified cluster sampling approach. A total of 1 000 census enumeration areas (EAs) from the 2001 population census were selected from a database of 86 000 EAs and mapped in 2007 using aerial photography to create the 2007 HSRC master sample to use as a basis for sampling of households. The selection of EAs was stratified by province and locality type. In the formal urban areas, race was also used as a third stratification variable (based on the predominant race group in the selected EA at the time of the 2001 census). The allocation of EAs to different stratification categories was disproportionate, in other words, over-sampling or over-allocation of EAs occurred in areas that were dominated by Indian, Coloured or White race groups to ensure that the minimum required sample size in those smaller race groups were obtained. Based on the HSRC 2007 Master Sample, 500 EAs representative of the socio-demographic profile of South Africa were identified and a random sample of 20 visiting points (VPs) were randomly selected from each EA, yielding an overall sample of 10 000. EAs were sampled with probability proportional to the size of the EA using the 2001 census estimate of the number of VPs in the EA database as a Measure of Size (MOS). 1 An enumeration area (EA) is the spatial area that is used by Statistics South Africa (Stats SA) to collect census information on the South African population. An enumeration area consists of approximately 180 households in urban areas, and 80 to 120 households in rural areas. The response rate is as follows: Households: Of the 10 000 households (VPs) sampled, 8 166 were valid, occupied households. Therefore, 1 834 VPs were invalid or clearly abandoned VPs/households. In addition, 573 VPs were not realised for either being empty after repeated visits or other reasons.

District Municipalities 2018 is a shapefile and attributes information of all the district municipalities in South Africa. In the hierarchy of local government structure, the District Municipalities are contained within Provinces, then District Municipalities contain Local Municipalities. District Municipalities 2018 was published in the Year 2018 after the municipal boundaries had minor technical adjustments. The district (Category C) municipalities are municipalities that are comprised of local (Category B) municipalities. The Metropolitan (Category A) Municipalities are municipalities with the major cities as the core (e.g. City of Johannesburg) and they are outside the District Municipalities. When the boundaries of local municipalities change and affect the boundary of district municipalities, the new district municipal boundary is generated. In the District Municipalities 2018 shapefile there are 44 District Municipalities and 8 Metropolitan Municipalities. Note that Metropolitan Municipalities are included in the District Municipalities shapefile to ensure that the layer is continuous throughout the country. If the Metropolitan Municipalities were left out, there will be void spaces in the layer.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countires and was later extended to 12 countries (1999-2001). The 12 country dataset was pieced together out of different projects including the intial Round 1 Afrobarometer 7 country survey, the old Southern African Democracy Barometer and similar surveys done in West and East Africa. The 12 country dataset consists of a combined dataset of the following countries:

Botswana, Ghana, Lesotho, Mali, Malawi, Namibia, Nigeria, South Africa, Tanzania, Uganda, Zambia and Zimbabwe

Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, and Round 4 (2008) 20 countries. The survey covered 34 countries in Round 5 (2011-2013) and 36 countries in Round 6 (2014-2015). Round 6 (2014-2015) covers 34 countries and Round 7 (2016-2018) coveres 36 countries.

Geographic coverage

The survey has national coverage in the following 12 African countrires: Botswana, Ghana, Lesotho, Malawi, Mali, Namibia, Nigeria, South Africa,Tanzania, Uganda, Zambia and Zimbabwe.

Analysis unit

Households and individuals

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

Kind of data

Sample survey data

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalised settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design: Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages: Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewers alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Further information on sampling protocols, including full details of the methodologies used for each stage of sample selection, can be found in Section 5 of the Afrobarometer Round 5 Survey Manual

Mode of data collection

Face-to-face [f2f]

Research instrument

Because Afrobarometer Round 1 emerged out of several different survey research efforts, survey instruments were not standardized across all countries, there are a number of features of the questionnaires that should be noted, as follows:

• In most cases, the data set only includes those questions/variables that were asked in nine or more countries. Complete Round 1 data sets for each individual country have already been released, and are available from ICPSR or from the Afrobarometer website at www.afrobarometer.org.

• In the seven countries that originally formed the Southern Africa Barometer (SAB) - Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe - a standardized questionnaire was used, so question wording and response categories are the generally the same for all of these countries. The questionnaires in Mali and Tanzania were also essentially identical (in the original English version). Ghana, Uganda and Nigeria each had distinct questionnaires.

• This merged dataset combines, into a single variable, responses from across these different countries where either identical or very similar questions were used, or where conceptually equivalent questions can be found in at least nine of the different countries. For each variable, the exact question text from each of the countries or groups of countries ("SAB" refers to the Southern Africa Barometer countries) is listed.

• Response options also varied on some questions, and where applicable, these differences are also noted.

The HIV/AIDS pandemic cut a swathe through young-adult and middle-aged South African generations, leaving behind millions of orphans and vulnerable children. Traditional gendered demands, and high mortality rates among older men, mean that caregiving for those children frequently falls to grandmothers, producing significant strain, increased vulnerability to psychpathology, but also expression of resilience. Extant literature has not measured subjective caregiver burden or distinguished between predictors of that burden quantitatively. We used a mixed methods design to collect quantitative and qualitative data from 57 urban-dwelling grandmothers. Each headed an HIV-affected household and served as primary caregiver for at least one grandchild. Regression modeling identified number of children for whom the participant served as primary caregiver; number of chronically ill household residents; and whether or not the participant received caregiving assistance as predictors of subjective caregiver burden. Open-ended questions revealed trends consistent with that model and suggested that, despite severe resource shortages, grandmothers displayed resilience in, and expressed pride at, fulfilling caregiving responsibilities. This is the first study to measure, using a standardized, well-validated instrument, the subjective burden of caregiving experienced by South African grandmothers heading HIV-affected households. The descriptive data we present support formulation of grounded hypotheses (e.g., how dynamics of household composition affect caregiving experiences; how such experiences might be a source of pride and resilience) that might guide future research.

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

The Afrobarometer project assesses attitudes and public opinion on democracy, markets, and civil society in several sub-Saharan African.This dataset was compiled from the studies in Round 2 of the Afrobarometer, conducted from 2002-2004 in 16 countries, including Botswana, Cape Verde, Ghana, Kenya, Lesotho, Malawi, Mali, Mozambique, Namibia, Nigeria, Senegal, South Africa, Tanzania, Uganda, Zambia, and Zimbabwe

Geographic coverage

The Round 2 Afrobarometer surveys have national coverage for the following countries: Botswana, Ghana, Kenya, Lesotho, Malawi, Mali, Mozambique, Namibia, Nigeria, Republic of Cabo Verde, Senegal, South Africa, Tanzania, Uganda, Zambia, Zimbabwe.

Analysis unit

Individuals

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Data weights For some national surveys, data are weighted to correct for over or under-sampling or for household size. "Withinwt" should be turned on for all national -level descriptive statistics in countries that contain this weighting variable. It is included as the last variable in the data set, with details described in the codebook. For merged data sets, "Combinwt" should be turned on for cross-national comparisons of descriptive statistics. Note: this weighting variable standardizes each national sample as if it were equal in size.

Further information on sampling protocols, including full details of the methodologies used for each stage of sample selection, can be found at https://afrobarometer.org/surveys-and-methods/sampling-principles

Mode of data collection

Face-to-face [f2f]

Research instrument

Certain questions in the questionnaires for the Afrobarometer 2 survey addressed country-specific issues, but many of the same questions were asked across surveys. Citizens of the 16 countries were asked questions about their economic and social situations, and their opinions were elicited on recent political and economic changes within their country.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countires and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, and Round 4 (2008) 20 countries.The survey covered 34 countries in Round 5 (2011-2013), 36 countries in Round 6 (2014-2015), 34 countries in Round 7 (2016-2018), and 34 countries in Round 8 (2019-2021). Round 9 covered 39 African countries. The 39 countries covered in Round 9 (2021-2023) are: Angola, Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Congo-Brazaville, Côte d'Ivoire, eSwatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Sao Tome & Principe, Senegal, Seychelles, Sierra Leone, South Africa, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia and Zimbabwe.

Geographic coverage

The survey has national coverage in the following 39 African countries: Angola, Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Congo-Brazaville, Côte d'Ivoire, eSwatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Sao Tome & Principe, Seychelles, Senegal, Sierra Leone, South Africa, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia and Zimbabwe.

Analysis unit

Households and individuals

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

Kind of data

Survey data

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalised settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewers alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Data weights For some national surveys, data are weighted to correct for over or under-sampling or for household size. "Withinwt" should be turned on for all national -level descriptive statistics in countries that contain this weighting variable. It is included as the last variable in the data set, with details described in the codebook. For merged data sets, "Combinwt" should be turned on for cross-national comparisons of descriptive statistics. Note: this weighting variable standardizes each national sample as if it were equal in size.

Further information on sampling protocols, including full details of the methodologies used for each stage of sample selection, can be found in Section 5 of the Afrobarometer Round 5 Survey Manual

Mode of data collection

Face-to-face

Research instrument

The questionnaire for Round 3 addressed country-specific issues, but many of the same questions were asked across surveys. The survey instruments were not standardized across all countries and the following features should be noted:

• In the seven countries that originally formed the Southern Africa Barometer (SAB) - Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe - a standardized questionnaire was used, so question wording and response categories are the generally the same for all of these countries. The questionnaires in Mali and Tanzania were also essentially identical (in the original English version). Ghana, Uganda and Nigeria each had distinct questionnaires.

• This merged dataset combines, into a single variable, responses from across these different countries where either identical or very similar questions were used, or where conceptually equivalent questions can be found in at least nine of the different countries. For each variable, the exact question text from each of the countries or groups of countries ("SAB" refers to the Southern Africa Barometer countries) is listed.

• Response options also varied on some questions, and where applicable, these differences are also noted.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, and Round 6 (2014-2015) 36 countries. The survey covered 34 countries in Round 7 (2016-2018).

Geographic coverage

The survey has national coverage in the following 34 African countries: Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Côte d'Ivoire, eSwatini, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, São Tomé and Príncipe, Senegal, Sierra Leone, South Africa, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia and Zimbabwe.

Analysis unit

Individuals

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Data weights For some national surveys, data are weighted to correct for over or under-sampling or for household size. "Withinwt" should be turned on for all national -level descriptive statistics in countries that contain this weighting variable. It is included as the last variable in the data set, with details described in the codebook. For merged data sets, "Combinwt" should be turned on for cross-national comparisons of descriptive statistics. Note: this weighting variable standardizes each national sample as if it were equal in size.

Further information on sampling protocols, including full details of the methodologies used for each stage of sample selection, can be found at https://afrobarometer.org/surveys-and-methods/sampling-principles

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for Round 7 addressed country-specific issues, but many of the same questions were asked across surveys. The survey instruments were not standardized across all countries and the following features should be noted:

• In the seven countries that originally formed the Southern Africa Barometer (SAB) - Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe - a standardized questionnaire was used, so question wording and response categories are the generally the same for all of these countries. The questionnaires in Mali and Tanzania were also essentially identical (in the original English version). Ghana, Uganda and Nigeria each had distinct questionnaires.

• This merged dataset combines, into a single variable, responses from across these different countries where either identical or very similar questions were used, or where conceptually equivalent questions can be found in at least nine of the different countries. For each variable, the exact question text from each of the countries or groups of countries ("SAB" refers to the Southern Africa Barometer countries) is listed.

• Response options also varied on some questions, and where applicable, these differences are also noted.