Survey of the perceptions of key stakeholders on the attributes of the South African Notifiable Diseases Surveillance System: data documentation

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dc.contributor.author Benson, Frew
dc.contributor.other Supervisor: Rispel LC
dc.contributor.other Project over sight Blumberg L,
dc.date.accessioned 2016-08-01T09:29:08Z
dc.date.available 2016-08-01T09:29:08Z
dc.date.available 2016-10-29
dc.date.issued 2016-10-25
dc.date.submitted 2016-06-07
dc.identifier.citation Data set documentation: Survey of the perceptions of key stakeholders on the attributes of the South African Notifiable Diseases Surveillance Benson FG, Corresponding Author, Email bensonf@health.gov.za
dc.identifier.citation Cite this article as: Benson, F.G., Musekiwa, A., Blumberg, L. et al. BMC Public Health (2016) 16: 1120. doi:10.1186/s12889-016-3781-7 312
dc.identifier.uri http://hdl.handle.net/10539/20795
dc.identifier.uri https://redcap.core.wits.ac.za/redcap/
dc.identifier.uri http://link.springer.com/article/10.1186/s12889-016-3781-7
dc.description Availability of data and materials in this project: The supporting documentation explains the context in which the data was collected and analysed. It is essential for understanding the data. The researcher's results can only be replicated using the same process, techniques and conceptual models . This dataset is available to any scientist wishing to use them for non-commercial purposes after the author's periods of embargoed usage expires in 2026 , without breaching participant confidentiality. The data is part of an ongoing research project is on the South African National Notifiable Disease Surveillance System. The data set are being merged in the final study. To preserve this confidentiality these data is being held under access control in the Redcap secure severs. The datasets on which the conclusions of the paper rely is available but data access is restricted for ethical reason. Those wishing to access the read only , anonymised data for peer review purposes strictly are requested to request a copy of the data from the administrator by clicking on a file icon padlock: please state your reasons and credentials.
dc.description.abstract An original and uniquely created electronic semi-structured questionnaire was piloted and then sent out using the secure, web-based Research Electronic Data Capture (REDCap), programme hosted at the University of Witwatersrand. In addition to socio- demographic information, the questionnaire elicited information on participants’ perceptions of the NDSS( Notifiable Diseases Surveillance System) attributes of acceptability (the willingness of providers to participate in the NDSS), flexibility (adaptability to changing circumstances and needs), simplicity (ease of understanding of NDSS forms and processes), timeliness (the speed at which the provider takes the appropriate steps after an event came to her/his attention) and usefulness (whether the data contributes to outbreak response, or the prevention and control of communicable diseases or improved public health knowledge). en_ZA
dc.description.sponsorship National Department of Health, South Africa en_ZA
dc.description.uri https://redcap.core.wits.ac.za/redcap/
dc.subject.mesh Epidemiology
dc.subject.mesh Dataset
dc.subject.mesh Evaluation
dc.subject.mesh Surveys and Questionnaires
dc.subject.mesh Notifiable Diseases Surveillance System
dc.title Survey of the perceptions of key stakeholders on the attributes of the South African Notifiable Diseases Surveillance System: data documentation en_ZA
dc.type Dataset en_ZA
dc.journal.title BMC Public Health
ddi.analysisunit Knowledge , Skills training and experience of the Notifiable Diseases Surveillance System as self reported by Key Stakeholders
ddi.cleanops Frew Benson and Statistician Alfred Musekiwa cleaning for Logistical regression analysis.
ddi.colldate 04/28/2015 12:34pm 06/02/2015 12:13pm
ddi.collmode REDcap electronic survey: Semi-structured questionnaire The questionnaire consisted of two to four questions per attribute for each of the five system attributes. The questions were designed on a 7-point Likert-scale ranging from 1 (strongly disagree) to 7 (strongly agree). The questions were phrased in a manner that attempted to minimise an unreflective response by participants, for instance questions requiring a positive response were alternated with questions requiring negative responses so that respondents would not be tempted to continue answering all the questions using the same response. Cronbach’s alpha coefficients were calculated to determine reliability and coherence between items and ranged from 0.82 to 0.97, indicating high reliability and inter-item correlation. We piloted the questionnaire prior to implementation, and no changes were deemed necessary. The questionnaire was in English as this is the main official language used for business communication in South Africa. We electronically sent invitations for participation in the survey to all identified key stakeholders via REDCap on 7 April 2015. The first page of the questionnaire consisted of an information sheet and we asked participants to consent before completing the survey electronically. Those not consenting were allowed to opt out. We sent four reminders to participants who did not respond after two weeks and we closed the survey after 54 days from the enrolment date Frew Benson Surveys: electronic tabular Perception of services survey Division of Global Health Protection, United States Centers for Diseases Control and Prevention (CDC), PO Box 9536, Pretoria, 0001, South Africa not for research but for clinical purposes Country During April and May 2015, all communicable diseases coordinators, epidemiologists and surveillance officers at the National Department of Health (NDoH) and all nine provincial health departments, as well as members of the National Surveillance Forum, the South African Malaria Elimination Committee, the South African Expanded Programme on Immunisations Committee and the National and Provincial Outbreak Response Teams (NORT and PORT respectively), to participate in a cross-sectional survey. As experience is an important determinant of the perspectives of the stakeholders, we excluded those not working in a health related field and those with less than one year experience of the NDSS from the study. The South African NDSS The NDSS in South Africa is a paper-based system that tracks 33 medical conditions. In terms of existing legislation, all health care providers are obliged to notify these 33 conditions to their local authority, which in turn reports it to the district, district to province, and province to the NDOH (Figure 1).[25] Over the years, parallel surveillance systems have been developed for tuberculosis (TB), malaria and vaccine-preventable notifiable diseases. Measurement and data collection We developed an electronic semi-structured questionnaire using the secure, web-based Research Electronic Data Capture (REDCap), programme hosted at the University of Witwatersrand.[26] In addition to socio- demographic information, the questionnaire elicited information on participants’ perceptions of the NDSS attributes[13] of acceptability (the willingness of providers to participate in the NDSS), flexibility (adaptability to changing circumstances and needs), simplicity (ease of understanding of NDSS forms and processes), timeliness (the speed at which the provider takes the appropriate steps after an event came to her/his attention) and usefulness (whether the data contributes to outbreak response, or the prevention and control of communicable diseases or improved public health knowledge). The questionnaire consisted of two to four questions per attribute for each of the five system attributes. The questions were designed on a 7-point Likert-scale ranging from 1 (strongly disagree) to 7 (strongly agree). The questions were phrased in a manner that attempted to minimise an unreflective response by participants, for instance questions requiring a positive response were alternated with questions requiring negative responses so that respondents would not be tempted to continue answering all the questions using the same response. Cronbach’s alpha coefficients were calculated to determine reliability and coherence between items and ranged from 0.82 to 0.97, indicating high reliability and inter-item correlation. We piloted the questionnaire prior to implementation, and no changes were deemed necessary. The questionnaire was in English as this is the main official language used for business communication in South Africa. We electronically sent invitations for participation in the survey to all identified key stakeholders via REDCap on 7 April 2015. The first page of the questionnaire consisted of an information sheet and we asked participants to consent before completing the survey electronically. Those not consenting were allowed to opt out. We sent four reminders to participants who did not respond after two weeks and we closed the survey after 54 days from the enrolment date. Data Analysis We captured data entered by participants in REDCap and exported the data into STATA® 14 for cleaning and analysis. We computed frequency and summary tables to describe participants’ age, position, experience, training and roles on committees. We summarized categorical variables in tables showing frequency and percentage of each category. We also summarized numerical/ measured variables using means (standard deviations) or medians (ranges) depending on whether they could be assumed to be normally distributed or skewed. We analysed responses from 7-point Likert scale attribute questions by describing the frequency distribution for each point on the scale. In order to simplify the interpretation of the results, we then categorized the responses to each question on attributes as agree or disagree; the ‘neither agree nor disagree’ response was categorized as disagree. We then computed the percentage of respondents who agreed with a particular attribute. We determined whether participants’ experience, training and roles with regards to the NDSS were associated with each of the attributes using logistic regression. The outcome variable was whether the participant agreed with the attribute or not. We calculated odds ratios (OR), 95% confidence intervals (95% CI) and p-values. P-values of less than 0.05 were considered to be statistically significant.
ddi.datacollector Frew Benson
ddi.datakind tabular survey : quantitative
ddi.datatype Perception of services survey
ddi.fundag Division of Global Health Protection, United States Centers for Diseases Control and Prevention (CDC), PO Box 9536, Pretoria, 0001, South Africa not for research but for clinical purposes
ddi.geogcover Country
ddi.method During April and May 2015, all communicable diseases coordinators, epidemiologists and surveillance officers at the National Department of Health (NDoH) and all nine provincial health departments, as well as members of the National Surveillance Forum, the South African Malaria Elimination Committee, the South African Expanded Programme on Immunisations Committee and the National and Provincial Outbreak Response Teams (NORT and PORT respectively), to participate in a cross-sectional survey. As experience is an important determinant of the perspectives of the stakeholders, we excluded those not working in a health related field and those with less than one year experience of the NDSS from the study. The South African NDSS The NDSS in South Africa is a paper-based system that tracks 33 medical conditions. In terms of existing legislation, all health care providers are obliged to notify these 33 conditions to their local authority, which in turn reports it to the district, district to province, and province to the NDOH (Figure 1).[25] Over the years, parallel surveillance systems have been developed for tuberculosis (TB), malaria and vaccine-preventable notifiable diseases. Measurement and data collection We developed an electronic semi-structured questionnaire using the secure, web-based Research Electronic Data Capture (REDCap), programme hosted at the University of Witwatersrand.[26] In addition to socio- demographic information, the questionnaire elicited information on participants’ perceptions of the NDSS attributes[13] of acceptability (the willingness of providers to participate in the NDSS), flexibility (adaptability to changing circumstances and needs), simplicity (ease of understanding of NDSS forms and processes), timeliness (the speed at which the provider takes the appropriate steps after an event came to her/his attention) and usefulness (whether the data contributes to outbreak response, or the prevention and control of communicable diseases or improved public health knowledge). The questionnaire consisted of two to four questions per attribute for each of the five system attributes. The questions were designed on a 7-point Likert-scale ranging from 1 (strongly disagree) to 7 (strongly agree). The questions were phrased in a manner that attempted to minimise an unreflective response by participants, for instance questions requiring a positive response were alternated with questions requiring negative responses so that respondents would not be tempted to continue answering all the questions using the same response. Cronbach’s alpha coefficients were calculated to determine reliability and coherence between items and ranged from 0.82 to 0.97, indicating high reliability and inter-item correlation. We piloted the questionnaire prior to implementation, and no changes were deemed necessary. The questionnaire was in English as this is the main official language used for business communication in South Africa. We electronically sent invitations for participation in the survey to all identified key stakeholders via REDCap on 7 April 2015. The first page of the questionnaire consisted of an information sheet and we asked participants to consent before completing the survey electronically. Those not consenting were allowed to opt out. We sent four reminders to participants who did not respond after two weeks and we closed the survey after 54 days from the enrolment date. Data Analysis We captured data entered by participants in REDCap and exported the data into STATA® 14 for cleaning and analysis. We computed frequency and summary tables to describe participants’ age, position, experience, training and roles on committees. We summarized categorical variables in tables showing frequency and percentage of each category. We also summarized numerical/ measured variables using means (standard deviations) or medians (ranges) depending on whether they could be assumed to be normally distributed or skewed. We analysed responses from 7-point Likert scale attribute questions by describing the frequency distribution for each point on the scale. In order to simplify the interpretation of the results, we then categorized the responses to each question on attributes as agree or disagree; the ‘neither agree nor disagree’ response was categorized as disagree. We then computed the percentage of respondents who agreed with a particular attribute. We determined whether participants’ experience, training and roles with regards to the NDSS were associated with each of the attributes using logistic regression. The outcome variable was whether the participant agreed with the attribute or not. We calculated odds ratios (OR), 95% confidence intervals (95% CI) and p-values. P-values of less than 0.05 were considered to be statistically significant.
ddi.sampproc The study population consists of all stakeholders involved with analysing, interpreting, responding, reporting and providing feedback on data collected; as well as those involved with monitoring and evaluation of the system at a national level
ddi.sources REDcap database
ddi.timemeth cross-sectional
ddi.universe Staff and associated professionals operating within the South African National Notifiable Diseases Surveillance System specifically epidemiologists and surveillance officers at the National Department of Health (NDoH) and all nine provincial health departments, as well as members of the National Surveillance Forum, the South African Malaria Elimination Committee, the South African Expanded Programme on Immunisations Committee and the National and Provincial Outbreak Response Teams (NORT and PORT respectively)
z.orcid 0000-0001-5648-6466
ddi.diststmt Limited distribution only for peer review and only anonymised data
ddi.geogunit district
ddi.timeprd 2015
dc.citation.doi 10.1186/s12889-016-3781-7
dc.citation.epage 1-9
dc.description.url https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-016-3781-7.


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