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A Multi-Dimensional Approach to Measure the Use of Social

Media Tools in Accessing Health Information: A Case Study of Griffith University Students,

Queensland, Australia

Presenters:Dr Ori Gudes and Dr Wayne Usher

• To identify the socio-economical profile of a university students who use Mobile Wireless Communication Technology (MWCT) to access health information, and why;

• To explore if the use of MWCT leads to a behavioural change - either positively or negatively;

• To develop new tools that will enable the analysis and visualisation of qualitative data and GIS findings; and

• To explore spatial patterns or spatial structure in the use of MWCT tools to access health information.

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Study Aims

Literature review what does it tell us?

• There is increasing evidence in the literature about the growing use of MWCT among students especially when connecting to health information (Head & Eisenberg ,2011);

• Young adults are closely linked to MWCT as a way of communication (Seeman, 2008);

• Previous research has focused on Australian secondary schools for promoting better mental health, rather than in the universities sector (Higher Education report, 2011); and

• University students demonstrate higher mental health issues when compared to the general population (Stallman, 2010).

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Literature review, previous studies of qualitative and spatial analysis methods

Some previous studies about the use of qualitative analysis and GIS / spatial analysis conducted by the following key authors:

• Jung and Elwood (2010);• Kwan (2010);• Cope and Elwood (2009); and• Kniggeô and Cope (2006, 2009) – the grounded visualization approach

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Source: Kniggeô and Cope (2006)

Geotagged qualitative data:

• Audio notes

• Video clips

• Field notes

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Research problem and gap in the knowledge

• There is a growing evidence about the importance of MWCT. However, there is lack of understanding about the role of it, as a platform for accessing health information;

• There is also lack of studies that use a multi-dimensional approaches to obtain evidence in this field;

• A gap in the knowledge especially when using qualitative analysis and spatial analysis / GIS has been identified

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A Multi-Dimensional Approach to Measure the Use of Social Media

Tools in Accessing Health

Distribution

Quantitative analysis

dimension

Spatial analysisdimension

Qualitative analysisdimension

Most previous studies focused on visualisation using

one “directionality”

Potential to develop cross methods (e.g., analysis tools) and

not just visualisation

solutions

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A gap in the knowledge

especially when using qualitative

analysis and spatial analysis /

GIS has been identified

Methodology

• Quantitative – Survey and quantitative analysis using SPSS;

• Qualitative: Leximancer tool was utilised; some of the text analysis was differentiated by location as result of spatial data quires undertaken on the textual database; and

• Spatial analysis; to identify any patterns that were associated with location, spatial analysis methods such as clustering analysis were utilised using ArcGIS and SatScan tools. All data has been geocoded and used in ArcGIS and SatScan.

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Quantitative Analysis

Dimension

Findings

The number and percentage of students who use MWCT to access health information was:

Frequency Precent

Yes 463 66.5%

No 231 33.2%

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A demographic profile

Of the people who used MWCT to access health information, we found that the typical socio economic profile associated with the following:

• Born in Australia; • live with other partners or kids;• Speak English at home; and• Average age of 30.5

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Quantitative Analysis

Dimension

From the people who used MWCT to access health information:

• 76% reported as being in good, very good excellent or health status;

• 37% were having BMI considered to be overweight, or obese class 1-2; and

• 5% reported as being in poor health status;

• More than 69% have reported about positive change in their health behaviours;

• 67.9% indicated that they used Facebook and Instagram for accessing or sharing health information;

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Quantitative Analysis

Dimension

A demographic profile cont.

Why qualitative analysis?

This type of analysis revealed the themes or concepts that were frequently used by the survey participants. the closer the themes or the concepts the better it interweaves. Furthermore, the brightness of a concept‘s label reflects its frequency in the text. That is, the brighter the concept label, the more often the concept is coded in the text.

Text Input into Leximancer

Text output from Leximancer

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Qualitative Analysis

Dimension

Major themes:

Access to information, remedies, healthy eating, nutrition, diet and symptoms.

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Qualitative Analysis

Dimension

Reasons for using MWCT to

Access information about health?

“It is easy to find information about

symptoms because I think I might have

depression so I like to find people out there with similar problems

and talk to them, it makes me feel less

alone”

Reasons of not using MWCT to access

information about health? your health?

“I think I'm more likely to get

reliable advice from a proper

medical practitioner, rather

than Dr Google.”

Major themes:

• Reliable (information)• Trust• Professional doctor

preference

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Quantitative Analysis

Dimension

Qualitative Analysis

DimensionTop 3 positive

behavioral changes from MWCT usageMajor themes:

• Healthy eating• Diet• Better motivation• More knowledge

about health and physical exercise.

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“Healthier food choices. Better

exercise techniques increased

motivation to maintain healthy

changes.”

Spatial Analysis

Dimension

Location of students based on vehicle travel time

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Spatial Analysis

Dimension

Who used MWCT and did not use, and where?

Essentially, these maps tells the same story that it could be observed that both measures of using MWCT are clustered in the same areas. This was to be expected (due to the nature of our survey sample);

We also used the Bernoulli Model in SatScan, which found no spatial structure irrespective of the survey sample nature.

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A preliminary example of a unique visualisation using the integration of Leximancer and spatial analysis /GIS

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• Thematic regionalisation (clustering of themes)

• We may answer questions such as:

1. whether people are thematically similar or de-similar?

2. Where some specific themes are clustered?

3. Change of themes in a spatio temporal manner etc.

Data collection• Integration of qualitative data with GIS datasets;

Representations / visualisation• Establishing new type of representations and/or visualisation

methods between GIS and the qualitative analysis dimension;

Analysis• Developing new techniques of analysis that are emerging at the link

between qualitative research and GIS / spatial analysis;

• Increasing data exploration capacity; and

• Demonstrating how qualitative GIS can be used to interrogate data.

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Areas of influence / development of qual analysis and spatial analysis

Conclusion

• The information and knowledge generated from this study has opened a window through which we can view and determine how Australian University students use MWCT;

• Evidence from this study could go towards guiding University Student Services as to how to effectively implement e-health initiatives that could contribute to reducing health inequities amongst Australia’s University students.

• Our conceptual framework may be adopted by researchers working across the geographical information discipline and human Geography;

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Conclusion cont.

• A gap in the knowledge especially when using qualitative analysis and spatial analysis / GIS has been identified, but this also provided an opportunity to develop unique, new and innovative methods of analysis and visualisation solutions; and

• Using the analysis, extraction, and interrogation capabilities of multiple dimensions to find evidence, can be valuable for exploring new insights.

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Limitations and recommendations for future

studiesAs this is an ongoing study, which suppose to be extended, some limitations and recommendations for future actions have been suggested:

• Extend the survey to the general public;

• Obtain better location data from participants (e.g., add journeys of participants);

• Expand the analysis to other measures which have not been covered in this study but were included in the survey (e.g., self-efficacy and adoption of technology);

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Limitations and recommendations cont.

• Include data with time stamp, to better understand spatio temporal trends of using MWCT;

• Explore the impact on health outcomes in the long term; and

• Develop new tools that will enable the analysis and visualisation of qualitative data in GIS.

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- Population & Social Health Research Program for their funding of this study;

- Dr Stephen Ball (Telethon Institute for Child Health Research, Centre for Child Health Research, The University of Western Australia) - Dr Simon Moncrif – School of Spatial Sciences, Curtin University, WA, Australia

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Acknowledgments