The Fitness, Game Bike Adherence, Motivation and Exercise Study

Physical Activity Clinical Trial

— FitGAME  

Official title:

Interactive Videogame Bikes and Their Effect on Exercise Adherence and Health Related Fitness Among Families

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT01373762
• Other study ID #: CCS-21041
• Status: Completed
• Phase: N/A
• First received: June 1, 2011
• Last updated: December 11, 2014
• Start date: January 2011
• Est. completion date: May 2014

Study information

• Verified date: December 2014
• Source: University of Victoria
• Contact: n/a
• Is FDA regulated: No
• Health authority: Canada: Ethics Review Committee
• Study type: Interventional

Clinical Trial Summary

The purpose of this study is to determine whether an interactive exercise videogame bike is effective in improving physical activity adherence, motivations to do physical activity, and physical fitness among families. Families receive either an interactive videogame bike and gaming console, or a traditional stationary bike which is placed in front of the television, to keep in their home for six months. It is expected that families within the videogame bike condition will show greater exercise adherence. It is also expected that these families will have higher self-reported physical activity levels, greater motivation to do physical activity, and improved cardiovascular fitness at the end of the three month period compared to the families in the stationary bike condition.

Description:

Short title: Fit Game: Fitness & Game Bike Adherence, Motivation and Exercise Study

Study period: 3 years Clinical phase: Phase III trial

Background:

Cancer is a significant economic burden in Canada, through direct costs to the health-care system (e.g., care and rehabilitation related to disease) and indirectly through lost economic output (e.g., missed work due to illness, premature death). At least half of all new cancer cases and deaths worldwide can be prevented, thus it is imperative that primary prevention become a focus of research. Recent research suggests a strong relationship between physical activity and many of the most prevalent forms of cancer including breast, lung, and colon cancer (i.e., the more an individual exercises the less likely they are to develop cancer). Despite these findings, over half of the Canadian population fails to meet levels of physical activity recommended as a preventative measure. Additionally, it has been found that the largest declines in physical activity occur early in life; thus, promotion efforts targeting critical transitions to physical inactivity early in life are paramount. Findings from a Canadian Community Health Survey note that only 21% of Canadian youth are accumulating enough daily activity to meet international guidelines for optimal growth and development. As well, national cross-sectional and cohort studies on physical inactivity/overweight prevalence demonstrate that the most prominent deflection point is between ages 25 to 35, and this has been linked convincingly to the demands of parenthood. Thus, two important target groups for disease prevention are parents and their children through family-based physical activity initiatives. Unfortunately, interventions of this type are limited and have resulted in little changes in physical activity. Previous studies have focused heavily on education about the benefits/barriers of physical activity, followed by a self-monitoring and self-regulatory (e.g., goal-setting) component. One area that has been overlooked when trying to increase physical activity participation among youth, despite its reliable and robust association with physical activity, is the modification of affective expectations or judgements (expected pleasure or enjoyment).

The introduction of new, enjoyable, and engaging exercise activities may present a novel approach to increase physical activity. One group of activities with this potential is interactive exercise video gaming including games such as the Game Bike system, Sony PlayStation EyeToy, and Nintendo Wii. These games allow players to interact physically (using leg, arm, or whole-body movement) in response to some on-screen virtual activity and provide a controlled opportunity for physical activity and exercise in a family environment.

Emerging evidence suggests that these games can significantly increase energy expenditure similar to moderate to vigorous intensity physical activities that can translate into health-related fitness improvements. Our systematic review of existing active video game interventions highlight the potential of this approach to increase physical activity in children and young people. Additionally, our previous research with these games has also demonstrated the health-related fitness gains even when compared to standard cycling conditions.

Despite these positive effects, there is very little information present to understand adherence to exercise videogames (EV). Our own research with university-aged males showed that an intervention group using an interactive Game bike attended 30% more sessions than a control group using traditional stationary exercise bikes. Even fewer studies on EV have evaluated the motivational properties of these games and the potential reasons for this improved adherence over control physical activity conditions. Only two studies have measured psychological constructs to examine effects of EV on motivation. Results of our previous work suggests that EV can effectively change affective judgments about physical activity and subsequent behaviour unlike most prior intervention efforts.

Despite early positive findings, EV research has notable limitations. First, the populations employed in EV research have been limited to convenience samples of male undergraduate students. Research needs to expand to other samples in order to examine the reach of EV. Second, EV research has almost been exclusively conducted in a laboratory setting. While helpful for initial pilot/efficacy phase research, EV research needs to be conducted in ecologically valid locations. The family home seems an excellent test for whether EVs can still affect psychological, behavioural, and fitness outcomes when situated in a naturalistic location with other leisure-time stimuli. Finally, the length of EV trials has been limited to six-week longitudinal tests or single exposure examinations. Trials of longer duration would be very helpful to examine continuing interest in EV and subsequent adherence. It may be that EV provides a powerful novel experience in the short term but wanes similar to other exercise initiatives across time. Our proposed study will overcome these past limitations and advance the current knowledge of EV.

Objectives:

The primary objective of this study is to evaluate the effect of an interactive exercise video bike (i.e., Active Cycle) in comparison to a stationary bike (Active Cycle without the videogame controllers) in front of a TV on physical fitness, use of the bikes, and perceptions of the bikes. We will also explore whether season (winter/summer), age (parents/kids) and gender (males/females) affect the use of the various bikes.

Study population:

The targeted population will be inactive families within the Greater Victoria Area, British Columbia and the Greater Halifax Area, Nova Scotia, Canada.

Number of subjects:

A total of 160 families will be recruited (n=80 per group). 120 families will be recruited at the Greater Victoria site. The remainder will be recruited from Greater Halifax.

Each family in the EV-interactive condition will receive a videogame bike (Hogan Health Industries, West Jordan, Utah) that will be linked into the family's Sony Playstation 2 or 3® (Sony Computer Entertainment America Inc, Foster City, California). If the family does not own a Sony Playstation 2 or 3® it will be provided to them for the duration of the intervention. Families will choose five videogames from a variety of Sony Playstation 2 or 3® videogames. At 3 months, families will be given the opportunity to select five new videogames, if they wish. Each family in the control group will receive a traditional stationary bike (i.e., an Active Cycle without the videogame controllers) which will be placed in front of their television.

Statistical methods:

Study power:

A sample size of 160 families (80 per group) will be recruited to detect a small-medium effect size (f2 = .10) in adherence to physical activity (primary outcome) with a type one error of .05, an average correlation of .75 across time for our dependent variable (DV) of interest, and a power of .80. Our sample size also considers the main 2 (group) x 2 (parent/child) x 4 (time)repeated measures design and a potential 15% attrition rate. The prediction-based research will be examined by group condition as well as via the collapsed sample for mediation analyses. Considering an average of 5 predictor independent variables (Theory of Planned Behavior (TPB) or Self-Determination Theory (SDT) models), and using a small-medium effect size (f2 = .10) we will have sufficient power (.80) to evaluate these predictors at an alpha of .05.

Statistical analysis:

Intention to treat analysis will be used to evaluate the main treatment effect. Missing data in the primary outcome measures will be imputed using a pre-specified approach. Research question 1 will be analyzed using a 2 (condition) x 4 (time) repeated measures factorial ANOVA on the primary outcome of child adherence to the bikes. A child (i.e., the target child) from each household in the eligibility range will serve for this analysis (chosen through randomization procedures). Post hoc examinations using Tukey follow-up procedures will be utilized if necessary.

Our secondary objectives (parent; parent/child; gender; season; fitness variables, etc.), will also be analyzed using a variant of this design with the addition of factors. Cluster analysis/Hierarchical Linear Modelling will be used for parent/child collinearity. Our pilot study (r = .21) and prior research suggests limited collinearity but it is appropriate to explore findings with these approaches given these are naturally clustered environments (i.e., family home). Prediction using our models (TPB, SDT) and questions of mediation will be achieved via multiple regression analyses following standard procedures for these types of tests.

The qualitative analyses will incorporate the following processes: 1) Invite participants to review the transcripts of interviews, and summarize their perception of the data, for accuracy, and check for the trustworthiness of the data; 2) Conduct a thematic analysis using a reciprocal coding approach where researchers engage in open dialogue about themes and data interpretation. In doing so, each transcript is first reviewed independently, then through dialogue composite themes and related critical issues are developed; and 3) Manage the data using the NVivo software program. NVivo enables theory building, testing and elaboration. With NVivo, 'free nodes' can be created during the coding process, capturing participants' perspectives and the investigators' critical issues.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 74
• Est. completion date: May 2014
• Est. primary completion date: May 2014
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Both
• Age group: 10 Years and older

Eligibility

Inclusion Criteria:

• Married or common law parents with children between the ages of 10 and 14

• self-report low family physical activity

• At least 1 parent is not meeting Canada's Physical Activity Guidelines

• Target child is not meeting Canada's Physical Activity Guidelines

Exclusion Criteria:

• Participant is unsafe to participate in physical activity as determined by answers to the Physical Activity Readiness Questionnaire (PAR-Q)

Study Design

Allocation: Randomized, Endpoint Classification: Efficacy Study, Intervention Model: Parallel Assignment, Masking: Single Blind (Investigator), Primary Purpose: Prevention

Related Conditions & MeSH terms

• Physical Activity

Intervention

Behavioral:
• Exercise Videogame Bikes
The intervention group will receive an exercise videogame bike that will be linked into their Sony Playstation 2® (Sony Computer Entertainment America Inc, Foster City, California). The Active Cycle® system reads the participant's cycling cadence which, in combination with a handlebar-mounted game controller, allows each participant to play a variety of Sony Playstation 2 and 3® videogames while exercising. The control-distraction group will receive a traditional stationary bike (i.e., same bike as the Active Cycle, but without the videogame controllers), which will be placed in front of their television. The recommended exercise training regime for both conditions will be activity of moderate intensity exercise (i.e., 60 to 75% of heart rate reserve), 3 days/week for 30 minutes/day.

Locations

Country	Name	City	State
Canada	Cardiovascular Research Unit	Halifax	Nova Scotia
Canada	Behavioural Medicine Laboratory	Victoria	British Columbia

Sponsors (5)

Lead Sponsor	Collaborator
University of Victoria	Canadian Cancer Society Research Institute (CCSRI), Dalhousie University, University of Auckland, New Zealand, University of British Columbia

Country where clinical trial is conducted

Canada, 

References & Publications (86)

ACSM. Guidelines for exercise testing and prescription. Baltimore, Maryland: Lippincott, Williams & Wilkins; 2000.

Adami HO, Day NE, Trichopoulos D, Willett WC. Primary and secondary prevention in the reduction of cancer morbidity and mortality. Eur J Cancer. 2001 Oct;37 Suppl 8:S118-27. Review. — View Citation

Aiken LS, West SG. Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage; 1991.

Ajzen I. Construction of a theory of planned behavior intervention. http://www-unix.oit.umass.edu/~aizen/pdf/tpb.intervention.pdf. Accessed April 4, 2007.

Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes 50:179-211, 1991.

Allison PD. Missing Data. Thousand Oaks: Sage Publications; 2002.

Annesi JJ, Mazas J. Effects of virtual reality-enhanced exercise equipment on adherence and exercise-induced feeling states. Percept Mot Skills. 1997 Dec;85(3 Pt 1):835-44. — View Citation

Armitage CJ, Conner M. Efficacy of the Theory of Planned Behaviour: a meta-analytic review. Br J Soc Psychol. 2001 Dec;40(Pt 4):471-99. — View Citation

Azagba S. Trends in adult exposure to secondhand smoke in vehicles: Findings from the 2009-2012 Canadian Tobacco Use Monitoring Survey. Drug Alcohol Depend. 2015 Oct 1;155:141-6. doi: 10.1016/j.drugalcdep.2015.07.680. Epub 2015 Jul 31. — View Citation

Baranowski T, Anderson C, Carmack C. Mediating variable framework in physical activity interventions. How are we doing? How might we do better? Am J Prev Med. 1998 Nov;15(4):266-97. Review. Erratum in: Am J Prev Med 1999 Jul;17(1):98. — View Citation

Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986 Dec;51(6):1173-82. — View Citation

Bellows-Riecken KH, Rhodes RE. A birth of inactivity? A review of physical activity and parenthood. Prev Med. 2008 Feb;46(2):99-110. Epub 2007 Aug 15. Review. — View Citation

Benoit C, Jansson M, Leadbeater B, McCarthy B. The Impact of Stigma on Marginalized Populations' Work, Health and Access to Services. Canadian Institutes of Health Research; 2002-2005.

Brown SG, Rhodes RE. Relationships among dog ownership and leisure-time walking in Western Canadian adults. Am J Prev Med. 2006 Feb;30(2):131-6. — View Citation

Canadian Fitness and Lifestyle Research Institute. Increasing physical activity: Trends for planning effective communication. http://www.cflri.ca/cflri/resources/pub.php#2003capacity. Accessed February 24, 2006.

Chuang JH, Hripcsak G, Heitjan DF. Design and analysis of controlled trials in naturally clustered environments: implications for medical informatics. J Am Med Inform Assoc. 2002 May-Jun;9(3):230-8. — View Citation

Cohen J, Cohen P. Applied multiple regression / correlation analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum; 1983.

Cohen J. A power primer. Psychol Bull. 1992 Jul;112(1):155-9. — View Citation

Crabtree BF, Miller WL. Doing Qualitative Research. Newbury Park, CA: Sage; 1992.

Crocker PR, Bailey DA, Faulkner RA, Kowalski KC, McGrath R. Measuring general levels of physical activity: preliminary evidence for the Physical Activity Questionnaire for Older Children. Med Sci Sports Exerc. 1997 Oct;29(10):1344-9. — View Citation

Davison KK, Birch LL. Childhood overweight: a contextual model and recommendations for future research. Obes Rev. 2001 Aug;2(3):159-71. Review. — View Citation

Deci EL, Ryan RM. Intrinsic motivation and self-determination in human behavior. New York: Plenum Press; 1985.

Deci EL, Ryan RM. The "what" and "why" of goal pursuits: Human needs and the self-determination of behaviour. Psychological Inquiry. 2000;11:227-268.

Diener E, Emmons RA, Larsen RJ, Griffin S. The Satisfaction With Life Scale. J Pers Assess. 1985 Feb;49(1):71-5. — View Citation

Dishman RK, Buckworth J. Increasing physical activity: a quantitative synthesis. Med Sci Sports Exerc. 1996 Jun;28(6):706-19. — View Citation

Dumas JE, Lynch AM, Laughlin JE, Phillips Smith E, Prinz RJ. Promoting intervention fidelity. Conceptual issues, methods, and preliminary results from the EARLY ALLIANCE prevention trial. Am J Prev Med. 2001 Jan;20(1 Suppl):38-47. — View Citation

Entertainment Software Association. Industry Facts; 2009.

Fishbein M, Triandis HC, Kanfer FH, Becker M, Middlestadt SE, Eichler A. Factors influencing behavior and behavior change. In: Baum A, Revenson TA, eds. Handbook of health psychology. Mahwah, New Jersey: Lawrence Erlbaum Associates; 2001:3-17.

French DP, Sutton S, Hennings SJ, et al. The importance of affective beliefs and attitudes in the theory of planned behavior: Predicting intention to increase physical activity. Journal of Applied Social Psychology. 2005;35:1824-1848.

Friedenreich CM. Physical activity and cancer prevention: from observational to intervention research. Cancer Epidemiol Biomarkers Prev. 2001 Apr;10(4):287-301. Review. — View Citation

Gadermann AM, Schonert-Reichl KA, Zumbo BD. Investigating Validity evidence of the Satisfaction with Life Scale Adapted for Children. Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement. in press.

Gillison FB, Standage M, Skevington SM. Relationships among adolescents' weight perceptions, exercise goals, exercise motivation, quality of life and leisure-time exercise behaviour: a self-determination theory approach. Health Educ Res. 2006 Dec;21(6):836-47. Epub 2006 Nov 13. — View Citation

Godin G, Jobin J, Bouillon J. Assessment of leisure time exercise behavior by self-report: a concurrent validity study. Can J Public Health. 1986 Sep-Oct;77(5):359-62. — View Citation

Godin G, Kok G. The theory of planned behavior: a review of its applications to health-related behaviors. Am J Health Promot. 1996 Nov-Dec;11(2):87-98. Review. — View Citation

Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci. 1985 Sep;10(3):141-6. — View Citation

GPOWER: A priori, post hoc, and compromise power analyses for MS DOS [computer program]. Version 2.0. Bonn, Germany: Dept. of Psychology; 1992.

Gustafson SL, Rhodes RE. Parental correlates of physical activity in children and early adolescents. Sports Med. 2006;36(1):79-97. Review. — View Citation

Hagger M, Chatzisarantis NLD, Biddle SJH. A meta-analytic review of the theories of reasoned action and planned behavior in physical activity: Predictive validity and the contribution of additional variables. Journal of Sport and Exercise Psychology. 2002;24:1-12.

Hagger M, Chatzisarantis NLD, eds. Intrinsic Motivation and Self-Determination in Exercise and Sport. Champaign, IL.: Human Kinetics; 2007.

Harriss DJ, Atkinson G, Batterham A, George K, Cable NT, Reilly T, Haboubi N, Renehan AG; Colorectal Cancer, Lifestyle, Exercise And Research Group. Lifestyle factors and colorectal cancer risk (2): a systematic review and meta-analysis of associations with leisure-time physical activity. Colorectal Dis. 2009 Sep;11(7):689-701. doi: 10.1111/j.1463-1318.2009.01767.x. Epub 2009 Jan 17. Review. — View Citation

Harvard Report on Cancer Prevention. Volume 1: Causes of human cancer. Cancer Causes Control. 1996 Nov;7 Suppl 1:S3-59. — View Citation

Hausenblas HA, Carron AV, Mack DE. Application of the theories of reasoned action and planned behavior to exercise behavior: A meta-analysis. Journal of Sport and Exercise Psychology. 1997;19:36-51.

Health Canada. Economic burden of illness in Canada 1998. Ottawa: Health Canada, 2002.

Health Canada. Health Canada's Physical Activity Guide. http://www.hc-sc.gc.ca/english/lifestyles/physical_activity.html. Accessed August, 2004.

Jacobs DR Jr, Ainsworth BE, Hartman TJ, Leon AS. A simultaneous evaluation of 10 commonly used physical activity questionnaires. Med Sci Sports Exerc. 1993 Jan;25(1):81-91. — View Citation

Jedwab J. Actively Canadian: Who's the most active of us all?: Association for Canadian Studies; 2005.

Kahn EB, Ramsey LT, Brownson RC, Heath GW, Howze EH, Powell KE, Stone EJ, Rajab MW, Corso P. The effectiveness of interventions to increase physical activity. A systematic review. Am J Prev Med. 2002 May;22(4 Suppl):73-107. Review. — View Citation

King AC, Stokols D, Talen E, Brassington GS, Killingsworth R. Theoretical approaches to the promotion of physical activity: forging a transdisciplinary paradigm. Am J Prev Med. 2002 Aug;23(2 Suppl):15-25. — View Citation

Kraft P, Rise J, Sutton S, Røysamb E. Perceived difficulty in the theory of planned behaviour: perceived behavioural control or affective attitude? Br J Soc Psychol. 2005 Sep;44(Pt 3):479-96. — View Citation

Kushi LH, Byers T, Doyle C, Bandera EV, McCullough M, McTiernan A, Gansler T, Andrews KS, Thun MJ; American Cancer Society 2006 Nutrition and Physical Activity Guidelines Advisory Committee. American Cancer Society Guidelines on Nutrition and Physical Activity for cancer prevention: reducing the risk of cancer with healthy food choices and physical activity. CA Cancer J Clin. 2006 Sep-Oct;56(5):254-81; quiz 313-4. Erratum in: CA Cancer J Clin. 2007 Jan-Feb;57(1):66. NcTiernan, Anne [added]. — View Citation

Lawton R, Conner M, McEachan R. Desire or reason: predicting health behaviors from affective and cognitive attitudes. Health Psychol. 2009 Jan;28(1):56-65. doi: 10.1037/a0013424. — View Citation

Lee RG, Garvin T. Moving from information transfer to information exchange in health and health care. Soc Sci Med. 2003 Feb;56(3):449-64. Review. — View Citation

Lonsdale C, Sabiston CM, Raedeke TD, Ha AS, Sum RK. Self-determined motivation and students' physical activity during structured physical education lessons and free choice periods. Prev Med. 2009 Jan;48(1):69-73. doi: 10.1016/j.ypmed.2008.09.013. Epub 2008 Oct 19. — View Citation

Lowe R, Eves F, Carroll D. The influence of affective and instrumental beliefs on exercise intentions and behavior: A longitudinal analysis. Journal of Applied Social Psychology. 2002;32:1241-1252.

Maddison R, Mhurchu CN, Jull A, Jiang Y, Prapavessis H, Rodgers A. Energy expended playing video console games: an opportunity to increase children's physical activity? Pediatr Exerc Sci. 2007 Aug;19(3):334-43. — View Citation

Manske SR. Explaining knowledge use among clients of the Program Training & Consultation Centre. Paper presented at: Toronto, 2001; University of Toronto.

Mark R, Rhodes RE, Warburton DER, Bredin SSG. Interactive video games and physical activity: A review of literature and future directions. Health and Fitness Journal of Canada. in press.

Markland D, Tobin V. A modification to the behavioral regulation in exercise questionnaire to include an assessment of amotivation. Journal of Sport & Exercise Psychology. 2004;26:191-196.

Monninkhof EM, Elias SG, Vlems FA, van der Tweel I, Schuit AJ, Voskuil DW, van Leeuwen FE; TFPAC. Physical activity and breast cancer: a systematic review. Epidemiology. 2007 Jan;18(1):137-57. Review. — View Citation

Morales. Nintendo's Wii scores big sales. Tech bytes; 2007.

O'Connor TM, Jago R, Baranowski T. Engaging parents to increase youth physical activity a systematic review. Am J Prev Med. 2009 Aug;37(2):141-9. doi: 10.1016/j.amepre.2009.04.020. Review. — View Citation

Patton MQ. Qualitative Evaluation and Research Methods. second ed. Newbury Park, NJ: Sage; 1990.

Plummer ML, Wight D, Obasi AI, Wamoyi J, Mshana G, Todd J, Mazige BC, Makokha M, Hayes RJ, Ross DA. A process evaluation of a school-based adolescent sexual health intervention in rural Tanzania: the MEMA kwa Vijana programme. Health Educ Res. 2007 Aug;22(4):500-12. Epub 2006 Oct 3. — View Citation

Public Health Agency of Canada. Canada's family guide to physical activity (6-9 years of age); 2002.

Rhodes RE, Blanchard CM, Matheson DH. A multicomponent model of the theory of planned behaviour. Br J Health Psychol. 2006 Feb;11(Pt 1):119-37. — View Citation

Rhodes RE, Courneya KS. Differentiating motivation and control in the theory of planned behavior. Psychology, Health and Medicine. 2004;9:205-215.

Rhodes RE, Courneya KS. Investigating multiple components of attitude, subjective norm, and perceived control: an examination of the theory of planned behaviour in the exercise domain. Br J Soc Psychol. 2003 Mar;42(Pt 1):129-46. — View Citation

Rhodes RE, Courneya KS. Self-efficacy, controllability, and intention in the theory of planned behavior: Measurement redundancy or causal independence? Psychology and Health. 2003;18:79-91.

Rhodes RE, Fiala B, Conner M. A review and meta-analysis of affective judgments and physical activity in adult populations. Ann Behav Med. 2009 Dec;38(3):180-204. doi: 10.1007/s12160-009-9147-y. Review. — View Citation

Rhodes RE, Fiala B, Conner M. Affective expectations of physical activity among adults: A review and meta-analysis. Annals of Behavioral Medicine (abstract). in press.

Rhodes RE, Macdonald HM, McKay HA. Predicting physical activity intention and behaviour among children in a longitudinal sample. Soc Sci Med. 2006 Jun;62(12):3146-56. Epub 2006 Jan 9. — View Citation

Rhodes RE, Plotnikoff RC. Can current physical activity act as a reasonable proxy measure of future physical activity? Evaluating cross-sectional and passive prospective designs with the use of social cognition models. Prev Med. 2005 May;40(5):547-55. — View Citation

Rhodes RE, Symons Downs D, Bellows Riecken KH. Delivering inactivity: A review of physical activity and the transition to motherhood. In: Allerton LT, Rutherfode GP, eds. Exercise and Women's Health Research. Hauppauge, NY: Earthlink Science Press; 2008:105-127.

Rhodes RE, Warburton DE, Bredin SS. Predicting the effect of interactive video bikes on exercise adherence: An efficacy trial. Psychol Health Med. 2009 Dec;14(6):631-40. doi: 10.1080/13548500903281088. — View Citation

Sell K, Lillie T, Taylor J. Energy expenditure during physically interactive video game playing in male college students with different playing experience. J Am Coll Health. 2008 Mar-Apr;56(5):505-11. doi: 10.3200/JACH.56.5.505-512. — View Citation

Standage M, Duda JL, Ntoumanis N. Students' motivational processes and their relationship to teacher ratings in school physical education: a self-determination theory approach. Res Q Exerc Sport. 2006 Mar;77(1):100-10. — View Citation

Statistics Canada. Canadian Community Health Survey 1994-2003. http://www.acs-aec.ca/Polls/Physical%20Activity%20and%20Obesity.pdf. Accessed April 13, 2005.

Statistics_Canada. Canadian Community Health Survey 1994-2003. http://www.acs-aec.ca/Polls/Physical%20Activity%20and%20Obesity.pdf. Accessed April 13, 2005.

Tardon A, Lee WJ, Delgado-Rodriguez M, Dosemeci M, Albanes D, Hoover R, Blair A. Leisure-time physical activity and lung cancer: a meta-analysis. Cancer Causes Control. 2005 May;16(4):389-97. Review. — View Citation

Travers KD. The social organization of nutritional inequities. Soc Sci Med. 1996 Aug;43(4):543-53. — View Citation

Travers KD. Using qualitative research to understand the socio-cultural origins of diabetes among Cape Breton Mi'kmaq. Chronic Diseases in Canada. 1995;16:140-143.

van Sluijs EM, McMinn AM, Griffin SJ. Effectiveness of interventions to promote physical activity in children and adolescents: systematic review of controlled trials. BMJ. 2007 Oct 6;335(7622):703. Epub 2007 Sep 20. Review. — View Citation

Warburton DE, Bredin SS, Horita LT, Zbogar D, Scott JM, Esch BT, Rhodes RE. The health benefits of interactive video game exercise. Appl Physiol Nutr Metab. 2007 Aug;32(4):655-63. — View Citation

Warburton DE, Sarkany D, Johnson M, Rhodes RE, Whitford W, Esch BT, Scott JM, Wong SC, Bredin SS. Metabolic requirements of interactive video game cycling. Med Sci Sports Exerc. 2009 Apr;41(4):920-6. doi: 10.1249/MSS.0b013e31819012bd. — View Citation

Widman LM, McDonald CM, Abresch RT. Effectiveness of an upper extremity exercise device integrated with computer gaming for aerobic training in adolescents with spinal cord dysfunction. J Spinal Cord Med. 2006;29(4):363-70. — View Citation

Wilson PM, Rodgers WM. The relationship between perceived autonomy support, exercise regulations and behavioral intentions in women. Psychology of Sport & Exercise. 2004;5:229-242.

* Note: There are 86 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Children's self-reported adherence	The primary outcome measure will be children's self-report of adherence to physical activity. Adherence will be assessed with an equipment usage log, which will be filled out each time the child uses either the GameBike or stationary bike. Adherence will be measured using raw attendance scores. Proportion achieved based on the amount prescription will also be calculated.	Usage log will be filled in for 3 month duration	No
Secondary	parent's self-reported adherence	Adherence will be assessed with an equipment usage log, which will be filled out each time the child uses either the Active Cycle or stationary bike. Adherence will be measured using raw attendance scores. Proportion achieved based on the amount prescription will also be calculated	Usage log will be filled in for 3 month duration	No
Secondary	Change from baseline in motivation at 6 weeks	Motivations for physical activity will be using the constructs of the TPB and SDT including affective attitude, instrumental attitude, injunctive norm, descriptive norm, perceived control, behavioural, normative, control beliefs, intrinsic motivation, extrinsic motivation, and amotivation. The Behavioural Regulations in Exercise Questionnaire-2 (BREQ-2) will be completed by both parents and the target child. Change in motivation variables will be examined (6 weeks minus baseline).	baseline & 6 weeks	No
Secondary	Change in baseline in self-reported physical activity at 6 weeks	The target child will complete a modified version of the Physical Activity Questionnaire for Children (PAQ-C) to assess habitual moderate to vigorous physical activity. The Godin Leisure-Time Exercise Questionnaire (LSI) will be used to measure self-reported physical activity in parents. The LSI contains three questions, which assess the frequency of mild, moderate, and strenuous activity performed for at least 15 minutes during free time in a typical week. Change in self-reported physical activity will be examined (6 weeks minus baseline).	baseline & 6 weeks	No
Secondary	Change from baseline in health-related quality of life / psychosocial distress at 3 months	Quality of life will be assessed with parents using the Satisfaction with Life Scale and the 12 item Short Form Health Survey. The target child's quality of life will be assessed using the 5-item Satisfaction with Life Scale Adapted for Children (SWLS-C). Change in health-related quality of life/ psychosocial distress from baseline to 3 months (i.e., post-intervention) will be examined.	baseline & 3 months	No
Secondary	Change from baseline in depression and anxiety at 3 months	The presence and severity of symptoms of depression and anxiety in parents will be assessed using two brief measures: the Beck Depression Inventory, Second Edition (BDI-II) and the Beck Anxiety Inventory (BAI). Two scales from the Beck Youth Inventories will be used to measure the presence and severity of symptoms of depression and anxiety in youth. Change in depression and anxiety from baseline to 3 months (post-intervention) will be examined.	baseline & 3 months	No
Secondary	Change from baseline in physical self-perception at 3 months	Physical self-perception will be measured using the global physical self-worth, physical condition, and body attractiveness subscales from the Physical Self-Perception Profile (PSPP) and Children and Youth Physical Self-Perception Profile (CY-PSPP). Change in global physical self-worth, physical condition, and body attractiveness from baseline to 3 months (post-intrevention) will be examined.	baseline & 3 months	No
Secondary	Change from baseline in physical home environment at 3 months	The physical home environment will be assessed using three sections from the Active Where surveys (i.e., Section A. equipment checklist, Section P. Home Environment, & Section R. Sedentary Behavior). The Active Where surveys include items designed to to assess how the physical environment impacts the physical activity and eating behaviors of youth. Change in physical environment will be examined from baseline to 3 months (post-intervention).	baseline & 3 months	No
Secondary	Change from baseline in body composition at 3 months.	Body mass (kg), height (cm), body mass index, and waist circumference will be measured. Percentage body fat will be estimated via skinfolds (triceps, biceps, subscapular, supra iliac, medial calf) using standard anthropometric procedures. Change in body mass index (BMI), waist circumference, and percentage body fat will be examined from baseline to 3 months (post-intervention)	baseline & 3 months	No
Secondary	Change from baseline in cardiovascular fitness at 3 months	A submaximal cycle ergometer test on a calibrated Monark cycle ergometer will be used to assess cardiovascular fitness in both parents and target child. Heart rate, oxyhaemoglobin saturation (pulse oximetery), and blood pressure (sphygmomanometer and a stethoscope) will be monitored at rest and during exercise. Change in cardiovascular fitness from baseline to 3 months (i.e., post-intervention) will be examined.	baseline & 3 months	No
Secondary	Change from baseline in motivation at 3 months	Motivations for physical activity will be using the constructs of the TPB and SDT including affective attitude, instrumental attitude, injunctive norm, descriptive norm, perceived control, behavioural, normative, control beliefs, intrinsic motivation, extrinsic motivation, and amotivation. The BREQ-2 will be completed by both parents and the target child. Change in motivation variables will be examined (3 months minus baseline).	baseline & 3 months	No
Secondary	Change from baseline in self-reported physical activity at 3 months	The target child will complete a modified version of the PAQ-C to assess habitual moderate to vigorous physical activity. The LSI will be used to measure self-reported physical activity in parents. The LSI contains three questions, which assess the frequency of mild, moderate, and strenuous activity performed for at least 15 minutes during free time in a typical week. Change in self-reported physical activity will be examined (3 months minus baseline).	Baseline & 3 months	No
Secondary	Change from baseline in self-reported physical activity at 3 months	The target child will complete a modified version of the PAQ-C to assess habitual moderate to vigorous physical activity. The LSI will be used to measure self-reported physical activity in parents. The LSI contains three questions, which assess the frequency of mild, moderate, and strenuous activity performed for at least 15 minutes during free time in a typical week. Change in self-reported physical activity will be examined (3 months minus baseline)	baseline & 3 months	No