E-Health Inequalities: Development of a Measure of ‘e-Health Readiness’ for Use in Intervention Studies
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Abstract
Background
E-health inequalities, namely differences in the opportunity to use the Internet for health, have been addressed by various initiatives. However, there was no comprehensive validated measure that could be used in randomised controlled trials (RCTs) of such interventions to know if they are effective. The term ‘e-health readiness’ can be used for an individual’s opportunity to use the Internet to get information or support for health. E-health inequalities can therefore be assessed by variation in e-health readiness.
Objective
The aim of this study was to develop and validate a self-completed questionnaire and scoring system to assess e-health readiness and, by examining the spread of scores, e-health inequalities. The intended use of this questionnaire and score is in RCTs of interventions aiming to improve e-health readiness and reduce e-health inequalities.
Methods
A model of influences on e-health readiness was developed from review of the literature. A self-completed questionnaire was drafted and piloted in three stages followed by a final survey of 344 people used to refine the scoring system.
Results
The Plymouth E-health Readiness Questionnaire (PERQ) and ‘e-health readiness’ scores include questions used to calculate four sub-scores: (i) patients’ perception of e-health provision, (ii) their personal ability and confidence in using e-health, (iii) their inter-personal support, and (iv) their perception of relative costs. These are combined into an overall ‘readiness’ score (0-9) which could be used in intervention studies. Reduction in standard deviation of the scores represents reduction in e-health inequalities.
Conclusions
PERQ appears acceptable for participants in British studies and should help identify interventions addressing e-health readiness. The scores produced appear valid and will enable assessment of the effectiveness of interventions to improve e-health readiness and reduce e-health inequalities. Such methods need continued evolution. Full documentation and data have been published to allow others to develop the tool further.
E-health inequalities, namely differences in the opportunity to use the Internet for health, have been addressed by various initiatives. However, there was no comprehensive validated measure that could be used in randomised controlled trials (RCTs) of such interventions to know if they are effective. The term ‘e-health readiness’ can be used for an individual’s opportunity to use the Internet to get information or support for health. E-health inequalities can therefore be assessed by variation in e-health readiness.
Objective
The aim of this study was to develop and validate a self-completed questionnaire and scoring system to assess e-health readiness and, by examining the spread of scores, e-health inequalities. The intended use of this questionnaire and score is in RCTs of interventions aiming to improve e-health readiness and reduce e-health inequalities.
Methods
A model of influences on e-health readiness was developed from review of the literature. A self-completed questionnaire was drafted and piloted in three stages followed by a final survey of 344 people used to refine the scoring system.
Results
The Plymouth E-health Readiness Questionnaire (PERQ) and ‘e-health readiness’ scores include questions used to calculate four sub-scores: (i) patients’ perception of e-health provision, (ii) their personal ability and confidence in using e-health, (iii) their inter-personal support, and (iv) their perception of relative costs. These are combined into an overall ‘readiness’ score (0-9) which could be used in intervention studies. Reduction in standard deviation of the scores represents reduction in e-health inequalities.
Conclusions
PERQ appears acceptable for participants in British studies and should help identify interventions addressing e-health readiness. The scores produced appear valid and will enable assessment of the effectiveness of interventions to improve e-health readiness and reduce e-health inequalities. Such methods need continued evolution. Full documentation and data have been published to allow others to develop the tool further.
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