Prediction of stage transitions in fruit and vegetable intake

Department of Health Psychology, Freie Universität Berlin, Habelschwerdter Allee 45, 14195 Berlin, Germany.
Health Education Research (Impact Factor: 1.66). 12/2008; 24(4):596-607. DOI: 10.1093/her/cyn061
Source: PubMed


Stage theories propose that individuals pass through different stages on their way toward behavior change. The present study examines stage-specific prediction patterns of social-cognitive variables (risk perception, outcome expectancies, perceived self-efficacy, action planning and social support) regarding transitions between the three stages of the Health Action Process Approach (HAPA; preintention, intention and action stage). In an online study (n = 494) on fruit and vegetable intake, social-cognitive variables and stages were assessed at baseline and stage transitions 4 weeks later. Transitions between the preintention, intention and action stage were predicted by social-cognitive variables using binary and multinomial logistic regression analyses. Stage-specific prediction patterns emerged for stage progression and stage regression. Outcome expectancies predicted progression from the preintention stage, whereas social support predicted progression to the action stage. Low levels of planning were associated with relapse to the preintention and the intention stage. Self-efficacy emerged as a universal predictor of stage transitions. Findings support not only the usefulness of the stage construct for describing health behavior change but also the validity of the HAPA variables as predictors of stage transitions. Stage-matched interventions targeting the variables identified as stage-specific predictors might support stage progression toward the goal behavior.

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Available from: Amelie U. Wiedemann, Oct 03, 2015
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    • "Subsequent text messages sent during the remaining 11 weeks of the intensive phase are tailored to the processes-of-change evident to be used in transitioning to action or maintenance from the participants’ baseline stage-of-change; that is, pre-contemplation (not thinking about change), intention (contemplation/preparation) or action (action/maintenance) [33-37]. For example, a greater proportion of text messages sent to participants in preparation for changing their fruit and vegetable intake are framed on self-reevaluation and helping relationships (that is, obtaining social support), as these processes are identified in the literature as assisting transition from intention to action for fruit and vegetable intake [34,36]. Fruit and vegetable messages coupled with replacing energy-dense foods, such as confectionery, crisps and energy-dense take-away foods with fruit or vegetables to promote a reduction in total energy intake for weight management [38]. "
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    ABSTRACT: Despite international efforts to arrest increasing rates of overweight and obesity, many population strategies have neglected young adults as a target group. Young adults are at high risk for unhealthy weight gain which tends to persist throughout adulthood with associated chronic disease health risks. Methods/design: TXT2BFiT is a nine month two-arm parallel-group randomized controlled trial aimed at improving weight management and weight-related dietary and physical activity behaviors among young adults. Participants are recruited via general practice (primary medical care) clinics in Sydney, New South Wales, Australia. All participants receive a mailed resource outlining national physical activity and dietary guidelines and access to the study website. Additional resources accessible to the intervention arm via the study website include Smartphone mobile applications, printable handouts, an interactive healthy weight tracker chart, and a community blog. The study consists of two phases: (1) Intensive phase (weeks 1 to 12): the control arm receives four short message service (SMS) text messages; the intervention arm receives eight SMS messages/week tailored to their baseline stage-of-change, one Email/week, and personalized coaching calls during weeks 0, 2, 5, 8, and 11; and (2) Maintenance phase (weeks 14 to 36): the intervention arm receives one SMS message/month, one Email/month and booster coaching calls during months 5 and 8. A sample of N = 354 (177 per arm) is required to detect differences in primary outcomes: body weight (kg) and body mass index (kg/m2), and secondary outcomes: physical activity, sitting time, intake of specific foods, beverages and nutrients, stage-of-change, self-efficacy and participant well-being, at three and nine months. Program reach, costs, implementation and participant engagement will also be assessed. DISCUSSION: This mobile phone based program addresses an important gap in obesity prevention efforts to date. The method of intervention delivery is via platforms that are highly accessible and appropriate for this population group. If effective, further translational research will be required to assess how this program might operate in the broader community.Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12612000924853
    Trials 03/2013; 14(1):75. DOI:10.1186/1745-6215-14-75 · 1.73 Impact Factor
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    • "One possible explanation is that the items used in this as well as some other studies with the HAPA framework (e.g. Wiedemann et al., 2009) tap mostly healthrelated expectancies. A recent critique has pointed out that by focusing on measuring only few distal outcome expectancies, the importance of the concept of outcome expectations is undermined (Williams, 2010). "
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    ABSTRACT: Background: Measurement of social cognitive variables is often restricted to long-term and health-related outcomes. A more comprehensive measurement of cognitive determinants would enable evidence-based design of health behavior interventions with a focus on the most relevant targets. The purpose of this study was to examine the relative impact of different social cognitive determinants on fruit and vegetable (FV) and fast food consumption. Methods: Finnish male conscripts (N = 855, age M = 20) filled in questionnaires on social cognitive factors when entering the military service, and on food consumption frequency after two months. The data were analysed using structural equation modeling. Results: Physical well-being expectation and bad taste expectation were most strongly related to both FV and fat avoidance intentions. Perceived weight gain risk predicted fat avoidance intention, whereas perceived risk for other health problems predicted FV intention. Social self-efficacy was associated with FV intention only. Consumption of both FV and fast food was predicted by action planning and intention. Conclusions: A more careful evaluation of subtypes of social cognitions sheds light on the specific content behind motivation. Such understanding might help in designing more effective intervention messages.
    Applied Psychology Health and Well-Being 03/2013; 5(1):118-35. DOI:10.1111/j.1758-0854.2012.01081.x · 1.75 Impact Factor
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    • "Our data are not representative for the German general population, as our study sample overrepresented women and individuals with higher education. It appeared, however, roughly representative in comparison to other online studies (see Wiedemann et al., 2009). Moreover, as the primary aim of this study is to provide evidence on the feasibility and practicability of implementing stage-specific interventions, the validation of these interventions in a general population is a challenge for further studies. "
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    ABSTRACT: Health education interventions can be tailored toward stages of change. This strategy is based on theories that predict at which stage which variables are indicative of subsequent behavior change processes. For example, planning is regarded as being effective in intenders. However, rather few studies have tested whether matched interventions are more successful for stage transitions than mismatched ones. Also very few previous studies have identified specific variables as targets of stage-matched interventions. A 2 (condition) x 2 (stages) experimental study tested the effects of stage-matched interventions for 226 participants. The stage-matched intervention moved significantly more individuals forward to action than did the control condition. Stage-specific effects were found to corroborate 78% of the assumptions. Multiple mediator analyses revealed stage-specific mechanisms, indicating that intention and planning facilitated behavior change in intenders. Thus, health behavior interventions should take stages of change into account.
    Health Education & Behavior 08/2010; 37(4):533-46. DOI:10.1177/1090198109359386 · 2.23 Impact Factor
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