Journal Article

IVF patients show three types of online behaviour

W.S. Tuil, C.M. Verhaak, P.F. De Vries Robbé and J.A.M. Kremer

in Human Reproduction

Published on behalf of European Society of Human Reproduction and Embryology

Volume 23, issue 11, pages 2501-2505
Published in print November 2008 | ISSN: 0268-1161
Published online July 2008 | e-ISSN: 1460-2350 | DOI: https://dx.doi.org/10.1093/humrep/den275
IVF patients show three types of online behaviour

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BACKGROUND

The internet introduces new ways to deal with stress. However, it is unclear how its resources are used in everyday life. Using a web-based personal health record (PHR), we observed the patient’s online behaviour and linked this to distress, theories on dealing with stress and demographics.

METHODS

Between 2004 and 2007, all viewed web-pages were logged and categorized into 14 content types. Behavioural styles were elicited using factor analysis. These behavioural styles were subsequently correlated to data on demographics, coping mechanisms and distress from the female partner of the first 53 patient couples that used the PHR.

RESULTS

One thousand and fifty patient couples viewed 588 887 web pages during their first treatment cycle. Factor analysis elicited three online behavioural styles explaining 66.9% of all variance in usage of the website: an ‘individual information style’, a ‘generic information style’ and a ‘communication style’. The ‘individual information style’ correlated negatively to having paid employment (Spearman = −0.364, P = 0.007) and emotional coping mechanisms (Spearman = −0.305, P = 0.028). The ‘communication style’ correlated positively to having paid employment (Spearman = 0.318, P = 0.021) and anxiety (Spearman = 0.381, P = 0.005).

CONCLUSIONS

IVF patients show three types of online behaviour. Only limited correlations exist between these styles and demographics, coping mechanisms or distress. When planning a website or portal for IVF patients, content should be adopted accordingly.

Keywords: IVF; coping; internet; consumer health informatics; factor analysis

Journal Article.  3984 words. 

Subjects: Reproductive Medicine

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