Peer Review #1 of "The use and evaluation of self-regulation techniques can predict health goal attainment in adults: an explorative study (v0.1)" [peer_review]

2016 unpublished
Background. Self-regulation tools are not always used optimally, and implementation intention plans often lack quality. Therefore, this study explored participants' use and evaluation of self-regulation techniques and their impact on goal attainment. Methods. Data were obtained from 452 adults in a proof of concept (POC) intervention of 'MyPlan', an eHealth intervention using self-regulation techniques to promote three healthy behaviours (physical activity(PA), fruit intake, or vegetable
more » ... or vegetable intake). Participants applied self-regulation techniques to a self-selected health behaviour, and evaluated the self-regulation techniques. The quality of implementation intentions was rated by the authors as a function of instrumentality (instrumental and non-instrumental) and specificity (non-specific and medium to highly specific). Logistic regression analyses were conducted to predict goal attainment. Results. Goal attainment was significantly predicted by the motivational value of the personal advice (OR:1.86), by the specificity of the implementation intentions (OR:3.5), by the motivational value of the action plan (OR:1.86), and by making a new action plan at follow-up (OR:4.10). Interaction-effects with behaviour showed that the specificity score of the implementation intention plans (OR:4.59), the motivational value of the personal advice (OR:2.38), selecting hindering factors and solutions(OR:2.00) and making a new action plan at follow-up (OR:7.54) were predictive of goal attainment only for fruit or vegetable intake. Also, when participants in the fruit and vegetable group made more than three plans, they were more likely to attain their goal (OR:1.73), whereas the reverse was the case in the PA group (OR:0.34). Discussion. The chance that adults reach fruit and vegetable goals can be increased by including motivating personal advice, self-formulated action plans, and instructions/strategies to make specific implementation intentions into eHealth interventions. To increase the chance that adults reach short-term PA goals, it is suggested to keep eHealth PA interventions simple and focus only on developing a few implementation intentions. However, more research is needed to identify behaviour change techniques that can increase health goal attainment at long-term. PeerJ reviewing PDF | (Abstract 14 Background. Self-regulation tools are not always used optimally, and implementation intention 15 plans often lack quality. Therefore, this study explored participants' use and evaluation of self-16 regulation techniques and their impact on goal attainment. 17 Methods. Data were obtained from 452 adults in a proof of concept (POC) intervention of 18 'MyPlan', an eHealth intervention using self-regulation techniques to promote three healthy 19 behaviours (physical activity(PA), fruit intake, or vegetable intake). Participants applied self-20 regulation techniques to a self-selected health behaviour, and evaluated the self-regulation 21 techniques. The quality of implementation intentions was rated by the authors as a function of 22 instrumentality (instrumental and non-instrumental) and specificity (non-specific and medium to 23 highly specific). Logistic regression analyses were conducted to predict goal attainment. 24 Results. Goal attainment was significantly predicted by the motivational value of the personal 25 advice (OR:1.86), by the specificity of the implementation intentions (OR:3.5), by the 26 motivational value of the action plan (OR:1.86), and by making a new action plan at follow-up 27 (OR:4.10). Interaction-effects with behaviour showed that the specificity score of the 28 implementation intention plans (OR:4.59), the motivational value of the personal advice 29 (OR:2.38), selecting hindering factors and solutions(OR:2.00) and making a new action plan at 30 follow-up (OR:7.54) were predictive of goal attainment only for fruit or vegetable intake. Also, 31 when participants in the fruit and vegetable group made more than three plans, they were more 32 likely to attain their goal (OR:1.73), whereas the reverse was the case in the PA group (OR:0.34). 33 Discussion. The chance that adults reach fruit and vegetable goals can be increased by including 34 motivating personal advice, self-formulated action plans, and instructions/strategies to make 35 specific implementation intentions into eHealth interventions. To increase the chance that adults 36 reach short-term PA goals, it is suggested to keep eHealth PA interventions simple and focus PeerJ reviewing PDF | (2015:11:7534:1:0:REVIEW 15 Jan 2016) Manuscript to be reviewed 37 only on developing a few implementation intentions. However, more research is needed to 38 identify behaviour change techniques that can increase health goal attainment at long-term. 39 40 41 Introduction 42 Physical activity (PA) and a varied diet with fruits and vegetables are associated with decreased 43 risk of cardiovascular diseases and cancer(Lock et al. 2005; WHO 2009; WHO 2010). 44 Therefore, adults are recommended to perform at least 30 minutes of PA at moderate to vigorous 45 intensity on most, preferably all days of the week, and to consume at least 400 g of fruit and 46 vegetable per day(Haskell et al. 2007). However, many adults do not meet these 47 recommendations(WHO 2003). Despite the efforts to promote these health behaviours in adults, 48 fruit and vegetable intake have been decreasing, and PA levels have remained the same since 49 2008 in Belgium. A recent meta-analysis focusing on these health behaviours indeed stated that 50 changing unhealthy lifestyle is difficult, and there is room for improvement(Hallal et al. 2012). 51 In previous computer-tailored interventions grounded in social-cognitive theories (e.g. Theory of 52 Planned Behaviour), tailored feedback was given on motivational determinants such as 53 awareness, knowledge, subjective norm and outcome expectations. Based on the individuals' 54 scores on scales that measure these determinants, participants were provided with feedback that 55 included a number of tips and suggestions for increasing or maintaining health behaviour(De 56 Vries & Brug 1999; Kroeze 2006 ; Vandelanotte 2003). For example, participants who had a 57 positive attitude regarding PA, but who were not aware that they were not sufficiently physically 58 active, mainly received information about PA norms and on how to increase PA levels. Whereas, 59 participants who had negative attitudes, got tailored feedback on advantages of PA. However, 60 interventions grounded in social-cognitive theories often only target determinants that are 61 important during the early stages of behaviour change. They are also often more effective in PeerJ reviewing PDF | (2015:11:7534:1:0:REVIEW 15 Jan 2016) Manuscript to be reviewed 62 changing intentions than in changing behaviour (Hagger et al. 2012; Sheeran et al. 2005), 63 resulting in a so-called intention-behaviour "gap". This gap can be targeted by also adopting self-64 regulation techniques. One useful framework in this context is the Health Action Process 65 Approach model that includes both pre-intentional processes that lead to a behavioural intention 66 and post-intentional processes that lead to the actual health behaviour(Schwarzer 2008). The 67 model states that individuals first have to become conscious of their own health behaviour and 68 have to be become motivated to change their behaviour, whereafter they have to initiate the new 69 health behaviour to bridge the gap between intentions and behaviour. This can be achieved by 70 defining specific action plans about 'when', 'where', and 'how' to perform the health behaviour, 71 and by stating implementation intentions in which strategies to initiate the action are stated (i.e. 72 "If situation Y is encountered, then I will initiate goal-directed behaviour X") (Gollwitzer & 73 Sheeran 2006). People may also make coping plans in which they state how to cope with 74 anticipated barriers and problems that may hinder goal attainment (Bélanger-Gravel et al. 2013; 75 Schwarzer 2008; Sniehotta et al. 2006). Research has shown that interventions that applied self-76 regulation techniques (i.e. specific goal setting, implementation intentions, providing feedback 77 on performance, prompting review of behaviour goals, social support and self-monitoring) were 78 more effective in changing health behaviour than other interventions that only targeted pre-79 intentional determinants in tailored feedback2014 2009(Broekhuizen et al. 2012; Lara et al. 80 2014; Michie et al. 2009; Morrison et al. 2012). 81 Therefore, based on previous intervention studies(Spittaels et al. 2007; Springvloet et al. 2014; 82 van Genugten et al. 2010; Vandelanotte 2003) and the meta-analyses of Michie et al. (2009) and 83 Gollwitzer and Sheeran (2006) we integrated different behaviour change techniques into a novel 84 self-regulation eHealth intervention that targets both pre-intentional and post-intentional PeerJ reviewing PDF | (2015:11:7534:1:0:REVIEW 15 Jan 2016) Manuscript to be reviewed 85 processes. Pre-intentional processes were targeted with tailored feedback. Post-intentional 86 processes were addressed with action planning, implementation intentions, problem solving, 87 sharing action plans with friends/family for social support, stimulating self-monitoring and goal 88 evaluation and adjustment. 89 'MyPlan' provided the opportunity to select one out of three health behaviours (fruit, vegetables 90 and PA), provided tailored feedback to prompt intention formation, helped adults to set personal 91 goals, and guided them to plan their behaviour and anticipate barriers and hindering situations 92 during goal pursuit. Other studies, that integrated planning tools, have shown that many tools 93 (e.g. action planning, implementation intentions) are used suboptimally by 94 participants(Springvloet et al. 2014; van Genugten 2011; van Osch et al. 2010). For example, 95 Michie et al. (2004) found that more than one-third of pregnant women intending to undergo 96 prenatal screening did not formulate implementation intentions for attending or making an 97 appointment despite being prompted to do so (Michie et al. 2004). Furthermore, when self-98 regulation tools were used, participants did not optimally apply them. Van Osch et al. (2010) 99 reported that plans to promote smoking cessation that are relatively broad and non-specific 100 resulted in less successful behavioural change. Ziegelmann, Lippke and Schwarzer (2006) 101 evaluated completeness of fruit and vegetable plans developed by young, middle-aged and older 102 patients in a rehabilitation clinic (Ziegelmann et al. 2006) . They found that plans that were 103 incomplete (lacking action planning or coping planning) were associated with less physical 104 activity during rehabilitation at 6 months post-test. This shows that self-regulation techniques are 105 perhaps not always feasible, or are difficult to apply. Therefore, it is important to test whether 106 behaviour change techniques that are included in new interventions are acceptable and feasible 107 for the intended target population and to examine the quality of action plans2001(Tones & PeerJ reviewing PDF | (
doi:10.7287/peerj.1666v0.1/reviews/1 fatcat:qzpayeejrfejziokbncg6dgn5y