Understanding acceptability in the context of text messages to encourage medication adherence in people with type 2 diabetes.

backgroundAcceptability is recognised as a key concept in the development of health interventions, but there has been a lack of consensus about how acceptability should be conceptualised. The theoretical framework of acceptability (TFA) provides a potential tool for understanding acceptability. It has been proposed that acceptability measured before use of an intervention (anticipated acceptability) may differ from measures taken during and after use (experienced acceptability), but thus far this distinction has not been tested for a specific intervention. This paper 1) directly compares ratings of anticipated and experienced acceptability of a text message-based intervention, 2) explores the applicability of the TFA in a technology-based intervention, and 3) uses these findings to inform suggestions for measuring acceptability over the lifespan of technology-based health interventions.

methodsData were obtained from a quantitative online survey assessing anticipated acceptability of the proposed text messages (n = 59) and a 12-week proof-of-concept mixed methods study assessing experienced acceptability while receiving the text messages (n = 48). Both quantitative ratings by return text message, and qualitative data from participant interviews were collected during the proof-of-concept study.

resultsThe quantitative analysis showed anticipated and experienced acceptability were significantly positively correlated (r

conclusionsThe high correlation between anticipated and experienced acceptability was a surprising finding and could indicate that, in some cases, acceptability of an intervention can be gauged adequately from an anticipated acceptability study, prior to an expensive pilot or feasibility study. Directly exploring perceptions of appropriateness and understanding whether the acceptability described by participants is related to the intervention or the research - and is for themselves or others - is important in interpreting the results and using them to further develop interventions and predict future use.