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Self-Monitoring in the Treatment of Overweight Adolescents

Published online by Cambridge University Press:  22 February 2012

Mary Sandilands*
Affiliation:
School of Health Sciences, RMIT University, Australia. mary@sandilands.id.au
Leah Brennan
Affiliation:
School of Medical Sciences, RMIT University, Australia; School of Psychology and Psychiatry, Monash University, Australia.
Jeff Walkley
Affiliation:
School of Health Sciences, RMIT University, Australia; School of Medical Sciences, RMIT University, Australia; Australian Technology Network Centre for Metabolic Fitness, Australia.
Steve F. Fraser
Affiliation:
School of Medical Sciences, RMIT University, Australia; School of Exercise and Nutrition Sciences, Deakin University, Australia.
Kate Greenway
Affiliation:
School of Medical Sciences, RMIT University, Australia.
*
*Address for correspondence: Mary Sandilands, 2/54 Bayview Road, Seddon VIC 3011, Australia.
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Abstract

The aim of this study was to explore the relationship between the quantity and quality of self-monitoring and per cent fat loss in overweight and obese adolescents participating in a weight-loss intervention. Participants were 55 (33F) over-weight and obese adolescents taking part in a 20-week cognitive–behavioural intervention aimed at improving eating and physical activity behaviours. Food and physical activity self-monitoring from the first 9 weeks of the intervention was coded using 24 components assessing the quantity (20) and quality (4) of self-monitoring. Those who completed treatment (n = 42) were split into groups: Losers (n = 30) and Gainers (n = 12) of per cent body fat as measured by DXA. Group analyses showed that Losers and Gainers could be differentiated by both quantitative and qualitative measures of self-monitoring. The strongest associations were with the classifications of food and drink items into food groups. The number of days monitored and the average number of items recorded did not differentiate the groups. Quantity and quality measures of self-monitoring completed early in treatment could also differentiate those who completed treatment and those who did not complete treatment (n = 13), and the strongest associations were with the amounts of food and drink items recorded, an association not found with treatment outcome. The results indicate that both quantity and quality of self-monitoring may be important predictors of both treatment completion and outcome. Based on these findings a framework of self-monitoring requirements is offered to reduce homework burden while maximising treatment efficacy.

Type
Standard Papers
Copyright
Copyright © Cambridge University Press 2011

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