title: Generating and predicting high quality action plans to facilitate physical activity and fruit and vegetable consumption: results from an experimental arm of a randomised controlled trial.
abstract: BACKGROUND
  In order to improve the transition from an intention to a change in health behaviour, action planning is a frequently used behavioural change method. The quality of action plans in terms of instrumentality and specificity is important in terms of supporting a successful change in health behaviour. Until now, little has been known about the predictors of action plan generation and the predictors of high quality action plans and, therefore, the current study investigates these predictors.
  
  
  METHODS
  A randomised controlled trial was conducted to improve physical activity (PA) and fruit and vegetable (FV) consumption using a web-based computer tailored intervention. During the 8-week intervention period, participants in the intervention arm (n = 346) were guided (step-by-step) to generate their own action plans to improve their health behaviours. Demographic characteristics, social cognitions, and health behaviour were assessed at baseline by means of self-reporting. Whether participants generated action plans was tracked by means of server registrations within two modules of the intervention.
  
  
  RESULTS
  The action planning component of the intervention regarding physical activity and fruit and vegetable consumption was used by 40.9 and 20.7 % of the participants, respectively. We found that participants who were physically active at baseline were less likely to generate action plans concerning physical activity. With regards to generating fruit and vegetable action plans, participants with a high risk perception and a strong intention to eat fruit and vegetables on a daily basis made more use of the action planning component for this behaviour. Finally, the large majority of the action plans for physical activity (96.6 %) and fruit and vegetable consumption (100 %) were instrumental and about half of the action plans were found to be highly specific (PA = 69.6 %/FV = 59.7 %). The specificity of the action plans is associated with having a relationship and low levels of negative outcome expectancies.
  
  
  CONCLUSIONS
  Risk perception and intention are predictors of using the application of action planning. Increasing the motivation to change behaviour should be prioritised in interventions concerning changes in health behaviour before participants are asked to generate action plans. This would also make the intervention suitable for unmotivated people. For those participants who already perform the desired health behaviour prior to the intervention, action plans might be less relevant. Nevertheless, using a guided step-by-step approach to generate action plans resulted in highly instrumental and specific action plans and might be integrated into other interventions concerning changes in health behaviour.
  
  
  BACKGROUND
  Netherlands Trial Register: NTR 3706, ClinicalTrials.gov: NCT01909349 .
authors.affiliation: Department of Psychology and Methods, Jacobs University Bremen, Campus Ring 1, Bremen, 28759, Germany. d.reinwand@jacobs-university.de.|CAPHRI, Department of Health Promotion, Maastricht University, P. O. Box 616, Maastricht, 6200, MD, The Netherlands. d.reinwand@jacobs-university.de.
authors.forename: Dominique Alexandra
authors.initials: DA
authors.lastname: Reinwand
authors.affiliation: CAPHRI, Department of Health Promotion, Maastricht University, P. O. Box 616, Maastricht, 6200, MD, The Netherlands.
authors.forename: Rik
authors.initials: R
authors.lastname: Crutzen
authors.affiliation: Department of Psychology and Methods, Jacobs University Bremen, Campus Ring 1, Bremen, 28759, Germany.
authors.forename: Vera
authors.initials: V
authors.lastname: Storm
authors.affiliation: Institute for Social Medicine and Epidemiology, University of Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.
authors.forename: Julian
authors.initials: J
authors.lastname: Wienert
authors.affiliation: Department of Psychology, University of Konstanz, 78457, Konstanz, Germany.
authors.forename: Tim
authors.initials: T
authors.lastname: Kuhlmann
authors.affiliation: CAPHRI, Department of Health Promotion, Maastricht University, P. O. Box 616, Maastricht, 6200, MD, The Netherlands.
authors.forename: Hein
authors.initials: H
authors.lastname: de Vries
authors.affiliation: Department of Psychology and Methods, Jacobs University Bremen, Campus Ring 1, Bremen, 28759, Germany.
authors.forename: Sonia
authors.initials: S
authors.lastname: Lippke
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003194:Computer-Assisted Instruction; D000072001:Diet, Healthy / Q000523:psychology* / Q000706:statistics & numerical data; D005260:Female; D005638:Fruit; D015438:Health Behavior; D006801:Humans; D033182:Intention; D020407:Internet; D008297:Male; D008875:Middle Aged; D009042:Motivation; D009043:Motor Activity; D009426:Netherlands; D018570:Risk Assessment; D014675:Vegetables; D055815:Young Adult
keywords: Action plan; Fruit and vegetable consumption; Instrumentality; Physical activity; Plan quality; Specificity