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Updated: Apr 1, 2026

Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design
Published on: May 31, 2021
Use of weekly assessment data to enhance evaluation of a subjective wellbeing intervention
Lucia Colla1, Matthew Fuller-Tyszkiewicz2, Adrian J Tomyn1
1School of Psychology, Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia.
Purpose:
While intervention effects in target outcomes have typically been tested based on change from baseline to post-intervention, such approaches typically ignore individual differences in change, including time taken to see improvement. The present study demonstrates how weekly patient-reported data may be used to augment traditional pre-post intervention evaluations in order to gain greater insights into treatment efficacy.
Methods:
Two hundred and fifty-two adolescent boys and girls (M age = 13.6 years, SD = 0.6 years) from four secondary schools in Victoria, Australia, were assigned by school into control (n = 88) or intervention (n = 164) groups. The intervention group participated in a 6-week course designed to improve subjective wellbeing (SWB) by fostering resilience, coping skills, and self-esteem. In addition to baseline, post-intervention, and 3-month follow-up assessments of SWB, intervention group participants also completed weekly summarise of affective experiences for the duration of the intervention phase.
Results:
While standard pre-post data showed significant improvement in SWB for the intervention group relative to controls, weekly data showed individual differences in the trajectory of change during this intervention phase; low SWB individuals experienced initial worsening of symptoms followed by improvement in the second half of the intervention phase, whereas high SWB individuals experienced initial gains, followed by a plateau from Week 4 onwards.
Conclusions:
Addition of weekly data provided greater insights into intervention effects by: (1) contradicting the notion that early responsiveness to treatment is predictive of level of improvement by post-intervention, and (2) providing data-based insights into ways to enhance the intervention.
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