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Positive Psychology, human capital and wellbeing: Experimental Evidence from Pakistan
Last registered on January 10, 2020


Trial Information
General Information
Positive Psychology, human capital and wellbeing: Experimental Evidence from Pakistan
Initial registration date
January 08, 2020
Last updated
January 10, 2020 11:26 AM EST

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Primary Investigator
University of New South Wales
Other Primary Investigator(s)
PI Affiliation
University of New South Wales
PI Affiliation
University of New South Wales
PI Affiliation
University of Melbourne
Additional Trial Information
On going
Start date
End date
Secondary IDs
We conduct a Randomised Control Trial (RCT) with school going children (aged 10-14 years) from a sample of districts in Pakistan’s Punjab. We aim to assess the impact of a low cost, easily scalable, touch-and-go psychological intervention aimed at improving well-being and, consequently, test scores. We implement this positive psychology intervention among 1000 school children across 30 schools. Our intervention is randomised at the school level. The treatment group receives the positive psychology intervention, while the control group engages in the meantime in non psychology-related activities. We will measure the impact of our intervention on improving child well-being and academic performance in the short run (immediately after the intervention), medium run (six-months after the intervention), and one-year mark. Our findings will contribute to understanding the production function of human capital and whether light touch psycho-social interventions can improve outcomes for children in low income settings.
External Link(s)
Registration Citation
Baranov, Victoria et al. 2020. "Positive Psychology, human capital and wellbeing: Experimental Evidence from Pakistan." AEA RCT Registry. January 10. https://doi.org/10.1257/rct.5246-1.0.
Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
We have two primary variables of interest: (i) child psycho-social well-being, (ii) child test-scores,
Primary Outcomes (explanation)
(i)Child’s psycho-social well-being: questions from the Students’ Life Satisfaction Scale (Huebner, 1991) and Australian child well-being survey. This is our primary outcome of interest to assess the impact of the intervention.
(ii) Test scores: These are the test-scores/ report cards provided by the schools. We have also administered some tests of our own that measure basic English, Mathematics, Urdu and General Knowledge aptitude to compliment the test scores provided by the schools and construct measure that are consistent across the schools in our sample. All test scores will be normalised to have mean zero and variance 1 as is the convention in intervention impact assessment on test scores (see Berry et al., 2018). This another primary outcome of interest to assess how effective the intervention has been in improving human capital.
Secondary Outcomes
Secondary Outcomes (end points)
Our secondary variables of interest are as follows: (i) parental investment decision in the experimental game, (ii) parental psycho-social well-being and (iii) exposure to conflict.
Secondary Outcomes (explanation)
(i) Parental investment decision is measured as the parent's choice in the experimental game.
(ii)Parental psycho-social well-being: measured using the K-10 well-being survey.
(iii) Questions on conflict exposure from the Life in Transition Survey.
Experimental Design
Experimental Design
We randomly select 15 treatment schools and 15 control schools. Within treatment schools, we randomly select 30-35 students in the age group of 10-14 years who will receive the positive psychology intervention. Treatment is assigned at the school level.
Experimental Design Details
Not available
Randomization Method
Assignment to treatment for the schools was randomized by the investigators via the sampsi function in Stata. The randomization of students was done in the field based on enrolment rosters provided by the schools. The source of exogenous variation is thus the randomised treatment assigned at the school level.
Randomization Unit
Treatment was assigned at the school level.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
15 control schools (with 500 students) and 15 treatment schools (500 students).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Our power calculations are informed by Berry et al., (2019)’s classroom-based intervention, who study India’s school meal programs. We cluster our treatment at the school level, with the number of clusters equal to 30. We assume 0.80 power, alpha of 0.05 and rho of 0.1 based on Berry et al. (2019). We conduct power calculations for the effect of the positive psychology intervention on student test scores. We target 1000 students, 500 in control and 500 in treatment, across 30 schools. This sample of 1000 participants is comparable to other similar studies. For example, Baranov et al. (2019a) conducted similar treatments on a sample of 903 women across 40 communities, while Gupta and Zimmer (2018) had a sample of 315 children. With our sample of 1000 students across 30 schools, we will be able to detect at minimum a 33% increase in test scores as a result of the positive psychology intervention.
IRB Name
University of New South Wales HREC
IRB Approval Date
IRB Approval Number
Analysis Plan

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