Measuring psychological constructs in computer-tailored interventions: novel possibilities to reduce participant burden and increase engagement

Abstract

Within the field of health psychology, there has been an enormous increase in behaviour change interventions that use digital technology. Answering questions and providing tailored feedback based on the answers provided by participants is the key working mechanism when using computer-tailoring in behaviour change interventions. This behaviour change method has proven to be (cost-)effective and results in participants being exposed to material that is tailored to their social-cognitive profile. At the same time, answering questions to assess this profile increases participant burden and might contribute to low levels of engagement - key challenges in digital health. This article provides insight into whether and how routinely collected data and novel self-assessment methods can be used in computer-tailoring to measure psychological constructs and address these key challenges. The examples presented suggest that the development of novel proxy measures for measuring psychological constructs relevant to computer-tailoring is indeed possible. However, the extent to which measures are valid and actually do reduce participant burden, increase engagement and have other potential benefits is speculative and needs further investigation. The recommendations provided for future research and practice are hoped to serve as a stimulance for driving further momentum in this area.

Effects of an Explicit Value Clarification Method With Computer-Tailored Advice on the Effectiveness of a Web-Based Smoking Cessation Decision Aid: Findings From a Randomized Controlled Trial

“…Although demographic variables seem to be the more obvious choice based on our data, the 1-item scale used to assess the stage of decision-making has the major advantage of being easy to use and not requiring participants to complete lengthy questionnaires. By tailoring DAs to the stage of decision-making (as opposed to other constructs or demographic characteristics), it would be possible to alleviate one of the core problems of most contemporary approaches to computer tailoring—that they often impose a significant burden on participants [ 68 ]. The fact that participants’ stage of decision-making had the most consistent effect on the outcomes among the included predictors only adds to this.…”

When informed decision making meets health promotion

“…Motorny et al [298] recently presented a framework that can be used to individualize DAs based on multiple components, such as one's information needs. While promising, their approach could potentially lead to the same problem recently described in the scientific literature in relation to computer-tailored interventions: that computer-tailoring based on multi-item questionnaires can increase participant burden and thereby non-usage attrition as well [284]. Based on the findings from the RCT, a feasible way to offer computer-tailored DAs without increasing participant burden (much) could be to employ the one-item stage of decision making scale as the scale is much shorter than the scales traditionally used within computer-tailored interventions (e.g., [46,71,299,300]).…”

“…While demographic variables seem like the more obvious choice based on our data, the one-item scale used to assess stage of decision making has the major advantage of being easy to use and not requiring participants to complete lengthy questionnaires. By tailoring DAs to the stage of decision making (as opposed to other constructs or demographic characteristics), it would be possible to alleviate one of the core problems of most contemporary approaches to computer-tailoring, namely that they often impose a significant burden on participants [284]. That participants' stage of decision making had the most consistent effect on the outcomes among the included predictors, only adds to that.…”

Optimizing digital smoking cessation interventions

“…In terms of computer-tailoring, although this is the usual procedure, studies have shown that participants can be burdened by answering (lengthy) questionnaires for the tailoring process (Alley et al, 2016;Vandelanotte & de Bourdeaudhuij, 2003;Vandelanotte et al, 2004). Therefore, Short et al (2022) discussed new approaches in computer tailoring to increase user engagement and reduce participant burden by reducing or avoiding answering (lengthy) questionnaires, such as by assessing online behavior or sensor data. While data for the tailoring process has generally been collected purposively (e.g., disseminating a questionnaire at baseline), novel ways to use routinely collected data are emerging (Short et al, 2022).…”

“…Therefore, Short et al (2022) discussed new approaches in computer tailoring to increase user engagement and reduce participant burden by reducing or avoiding answering (lengthy) questionnaires, such as by assessing online behavior or sensor data. While data for the tailoring process has generally been collected purposively (e.g., disseminating a questionnaire at baseline), novel ways to use routinely collected data are emerging (Short et al, 2022). For instance, psychological constructs such as attitude could be inferred based on routinely collected data on online behavior, such as browsing history (Short et al, 2022).…”