title: Individual characteristics associated with physical activity intervention delivery mode preferences among adults.
abstract: BACKGROUND
  People have different preferences on how health behaviour change interventions are delivered to them; intervention implementation, retention and effectiveness may be improved if preferences can be matched.
  
  
  OBJECTIVE
  This study aims to explore factors related to preference of face-to-face, and group-, print- or web-based physical activity intervention delivery modes among adults recruited from the general population.
  
  
  METHODS
  A question relating to physical activity intervention preference was included in the telephone administered 2010 Queensland Social Survey. Multinomial regression models were used to explore socio-demographic (e.g., age, marital status, location), health (e.g., BMI, chronic disease status) and behavioral factors (e.g., internet use, physical activity, diet, social networking) related to intervention preferences, using 'a face-to-face intervention' as the reference category.
  
  
  RESULTS
  35.2% of those approached took part in the telephone interviews (n=1,261). Preference for a web-based intervention was positively associated with being in the 35-44 age group (compared to the 18-34 age group; RR=2.71), living in a rural area (RR=2.01), and high internet use (RR=1.03); and negatively associated with female gender (RR=0.52), obesity (RR=0.42), and higher physical activity participation (RR=0.99). Preference for a print-based intervention was positively associated with older age (RR=5.50); and negatively associated with female gender (RR=0.48) and obesity (RR=0.47). Preference for a group-based program was positively associated with living in a regional town (RR=1.48) and negatively associated with being separated (RR=0.45) and obesity (RR =0.56).
  
  
  CONCLUSIONS
  Findings from this study help to delineate what physical activity intervention delivery modes are likely to be appealing for specific target groups, especially in relation to people of different weight status, age, gender and living environment. As such, this information will be useful in the development of interventions targeted at these groups.
authors.affiliation: School of Human, Health and Social Sciences, Centre for Physical activity studies, Central Queensland University, Rockhampton, Australia. c.short@cqu.edu.au.
authors.forename: Camille E
authors.initials: CE
authors.lastname: Short
authors.forename: Corneel
authors.initials: C
authors.lastname: Vandelanotte
authors.forename: Mitch J
authors.initials: MJ
authors.lastname: Duncan
mesh_terms: D000328:Adult; D000368:Aged; D015992:Body Mass Index; D001835:Body Weight; D003258:Consumer Behavior; D003430:Cross-Sectional Studies; D004032:Diet; D005260:Female; D015438:Health Behavior; D006293:Health Promotion / Q000379:methods*; D006801:Humans; D020407:Internet; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D011793:Queensland