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Where are our pathways to change? eHealth weight management in young adults

By Emma Norris, on 1 August 2019

By Taylor Willmott – Griffith University, Australia

The magnitude of the obesity epidemic has led to a shift in focus from the clinical treatment of obesity to the development of prevention strategies that address the economic, environmental, sociocultural, and lifestyle-related causes of weight gain. Targeting high-risk groups with prevention interventions is assumed to have the greatest impact on the ever-rising prevalence of overweight and obesity. We are most likely to gain weight in our early twenties to mid-thirties, with incident obesity at a younger age associated with an increased risk of chronic disease and mortality in later adult life. The good news? If we adopt healthy lifestyle behaviours in young adulthood, we lower our future risk of developing obesity and associated chronic disease(s).

Current state-of-play

Our previously published review sought to evaluate the current state of evidence on eHealth weight management interventions targeting young adults (aged 18-35 years), with findings highlighting the limited evidence base for successful interventions. Of the 24 studies identified, eight reported positive weight-related outcomes, four reported mixed outcomes, and 12 did not report any significant changes in weight-related outcomes. To obtain a more nuanced understanding of this apparent lack of effectiveness, we assessed the extent of reported theory use in included interventions using the Theory Coding Scheme (TCS). Note: previously published review findings are available (open access) and our recent Digi-Hub blog post offers a summary of key findings.


Why assess theory use?

Previous reviews of interventions in this context have focused primarily on pooling primary outcome results to obtain one overall estimate of effectiveness. These reviews provide limited insight into how interventions are (or are not) achieving the desired outcomes. To obtain a more nuanced understanding, we must unpack the ‘black box’ and deconstruct these seemingly complex eHealth weight management interventions. Theory is a critical aspect of being able to deconstruct interventions—with theory we can identify the underlying mechanisms of action (and their associated behaviour change techniques) driving (or not) intervention outcomes. These theoretical links represent our pathways to change! For further discussions on the role and importance of theory, refer to this scoping review and/or our previously published agenda outlining ten theory development goals.


Improving the current state-of-play

In our latest review paper published in Health Psychology Review, we assessed the extent of reported theory use in eHealth weight management interventions targeting young adults according to the TCS. We then calculated an overall use of theory score based on total TCS item scores (1 = present, 0 = not present). Each study was categorised as having either weak, moderate, or strong levels of theory use based on total TCS scores (weak = 0-7; moderate = 8-15; and strong = 16-23). Overall, the mean total use of theory score was 6/23 (SD = 5; Min. = 0, Max. = 17); 17 studies were classified as having weak application of theory, five as moderate, and two as strong (see Table 1).

Mention of theory

The majority (N = 18) of studies mentioned theory (see Table 2); however, only nine studies referred to the referenced theory as a predictor of behaviour and presented evidence of the relationship between the theoretical constructs in the theory cited and the target behaviour(s). Of those studies referencing a theory, 50% (N = 9) were reportedly based on a single theory such as Social Cognitive Theory (SCT) or Self-Determination Theory (SDT), while the other 50% (N = 9) were reportedly based on a combination of predictors from multiple theories.

Application of theory

Most (N = 17) studies used theoretical predictors to select and/or develop intervention techniques (see Table 3). No study used theory to select intervention recipients, with only four tailoring intervention techniques to different sub-groups of the target population that varied on a theoretical construct at baseline. For example, in the TXT2BFiT intervention data collected from participants at baseline were used to create a staging algorithm based on the TTM to generate a personalised set of text messages tailored to each participants’ stage of change. In terms of linking intervention techniques with theoretical constructs, only four studies explicitly linked all intervention techniques to at least one theory-relevant construct. A further 12 explicitly linked at least one, but not all. Similarly, only four studies explicitly linked all theory-relevant constructs to at least one intervention technique, with a further 11 explicitly linking at least one, but not all. Nine studies linked a group or cluster of intervention techniques to a group or cluster of theoretical constructs.

Testing, building, and refining of theory

Only six studies measured theory-relevant constructs pre and postintervention; and only three reported the reliability and/or validity of the psychometric scales used to measure theory-relevant constructs (see Table 4). Of the six studies measuring theory pre and postintervention, four reported that the intervention led to a significant change in at least one theory-relevant construct in favour of the intervention. Five studies discussed intervention outcomes in relation to the theory mentioned, and one provided appropriate support for the stated theory. No study reported using intervention results to build and/or refine the theory upon which the intervention was based, or formulate suggestions for future refinement.

Where to from here?

While some interventions incorporated elements from a referenced theory, it was rare that all theoretical constructs within a particular theory were targeted in the intervention; and that valid measures of theoretical constructs were measured and tested pre and postintervention. The lack of studies linking theoretical constructs to intervention techniques, and testing theory in evaluations may be limiting effectiveness. Indeed, post-hoc analyses indicate that weight-related outcomes may be enhanced when at least one or more theoretical constructs are explicitly linked to an intervention technique, and when theoretical constructs are included in evaluations. Increases in theory application and reporting are therefore needed to assist the scientific research community in systematically identifying which theories work, for whom, how, why, and when; thereby delivering an advanced understanding of how best to apply theory to enhance intervention outcomes.

Read the full paper here.



Taylor Willmott is a final year PhD candidate at Social Marketing @ Griffith, Griffith University. Taylor has held various research and teaching roles across leading higher education institutions in Australia including Queensland University of Technology, Griffith University, and the University of Queensland. The broad focus of Taylor’s research lies in applying marketing principles and techniques, combined with other evidence-based approaches, to create innovative behaviour change programs that benefit both individuals and society. Taylor’s research is multi-award winning, has been presented at world-renowned conferences, and published in top-tier academic journals such as the Journal of Marketing Management, International Journal of Consumer Studies, Health Education & Behavior, Health Psychology Review, and the Journal of Medical Internet Research.

Connect with Taylor:

LinkedIn: https://www.linkedin.com/in/taylorwillmott/

Twitter: https://twitter.com/TaylorWillmott

Email: t.willmott@griffith.edu.au




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