↓ Skip to main content

Combining survey data, GIS and qualitative interviews in the analysis of health service access for persons with disabilities

Overview of attention for article published in BMC Public Health, June 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

blogs
1 blog
twitter
3 X users

Readers on

mendeley
107 Mendeley
Title
Combining survey data, GIS and qualitative interviews in the analysis of health service access for persons with disabilities
Published in
BMC Public Health, June 2018
DOI 10.1186/s12914-018-0166-2
Pubmed ID
Authors

Arne H. Eide, Karin Dyrstad, Alister Munthali, Gert Van Rooy, Stine H. Braathen, Thomas Halvorsen, Frans Persendt, Peter Mvula, Jan Ketil Rød

Abstract

Equitable access to health services is a key ingredient in reaching health for persons with disabilities and other vulnerable groups. So far, research on access to health services in low- and middle-income countries has largely relied on self-reported survey data. Realizing that there may be substantial discrepancies between perceived and actual access, other methods are needed for more precise knowledge to guide health policy and planning. The objective of this article is to describe and discuss an innovative methodological triangulation where statistical and spatial analysis of perceived distance and objective measures of access is combined with qualitative evidence. The data for the study was drawn from a large household and individual questionnaire based survey carried out in Namibia and Malawi. The survey data was combined with spatial data of respondents and health facilities, key informant interviews and focus group discussions. To analyse access and barriers to access, a model is developed that takes into account both measured and perceived access. The geo-referenced survey data is used to establish four outcome categories of perceived and measured access as either good or poor. Combined with analyses of the terrain and the actual distance from where the respondents live to the health facility they go to, the data allows for categorising areas and respondents according to the four outcome categories. The four groups are subsequently analysed with respect to variation in individual characteristics and vulnerability factors. The qualitative component includes participatory map drawing and is used to gain further insight into the mechanisms behind the different combinations of perceived and actual access. Preliminary results show that there are substantial discrepancies between perceived and actual access to health services and the qualitative study provides insight into mechanisms behind such divergences. The novel combination of survey data, geographical data and qualitative data will generate a model on access to health services in poor contexts that will feed into efforts to improve access for the most vulnerable people in underserved areas.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 107 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 20%
Researcher 19 18%
Student > Ph. D. Student 12 11%
Lecturer 8 7%
Student > Doctoral Student 5 5%
Other 18 17%
Unknown 24 22%
Readers by discipline Count As %
Social Sciences 16 15%
Nursing and Health Professions 15 14%
Medicine and Dentistry 9 8%
Environmental Science 5 5%
Engineering 5 5%
Other 23 21%
Unknown 34 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 November 2018.
All research outputs
#3,711,099
of 25,385,509 outputs
Outputs from BMC Public Health
#4,558
of 17,517 outputs
Outputs of similar age
#70,664
of 342,601 outputs
Outputs of similar age from BMC Public Health
#129
of 333 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,517 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 342,601 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 333 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.