The long-term effects of an intervention to exercise.

Last registered on February 21, 2023


Trial Information

General Information

The long-term effects of an intervention to exercise.
Initial registration date
February 14, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
February 21, 2023, 6:44 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.


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Primary Investigator


Other Primary Investigator(s)

PI Affiliation
Norwegian School of Economics
PI Affiliation
University California Santa Barbara
PI Affiliation
University California San Diego
PI Affiliation
Norwegian School of Economics

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
This project will evaluate the long-term effects of an exercise intervention among university students. The exercise intervention consisted of a free gym membership in the academic spring semester of 2016 (January – June), and was provided as part of a randomized-controlled trial, where a total of 778 university students in Bergen, Norway, participated: 398 students received the free gym card and were thus treated, whereas the remaining students did not receive free access to attend the student gym and thus constitute the control group. The immediate effects of the intervention – i.e., the effects in the spring semester 2016 – are documented in the published article “Exercise Improves Academic Performance” (forthcoming in the Journal of Political Economy), which in turn built on the pre-analysis plan AEARCTR-0001949. In the current project we will investigate the long-term effects of the intervention – i.e., the effects after the free gym card expired in June 2016 – addressing three distinct research questions.

First, speaking to literature on habit formation we want to understand whether the exercise intervention enabled the formation of an exercise habit in subsequent semesters (focusing on the fall 2016). More specifically, we will analyze whether treated students are more likely to buy a gym card at a cost (capturing people's exercise intentions) as well as actual gym attendance using administrative scanner data.

Second, speaking to the literature on the dynamics of academic achievements, we will analyze whether the boost in completed study points observed in the spring 2016 (caused by the exercise intervention) promotes sustained academic success or whether it crowds out academic performance in subsequent semesters (focusing on the fall 2016). Importantly, the long-term effects on academic performance may be completely independent of whether exercise is habitual or not.

Third, using comprehensive data from an endline survey conducted two years after the intervention (spring 2018, 92% response rate) we will adress the effects of the exercise intervention on a broader set of life outcomes (outside the sphere of exercise and academic performance), including a health index, BMI, life satisfaction, a self-control index, and occupational status.

We will consider whether to write three separate papers based on this project or bundle the findings into one paper, but for complete overview we specify all the analysis in one single pre-plan.
External Link(s)

Registration Citation

Cappelen, Alexander et al. 2023. "The long-term effects of an intervention to exercise.." AEA RCT Registry. February 21.
Experimental Details


The intervention consisted of (some) students at the University of Bergen and the Bergen City College receiving a free membership to the student gym SIB during the spring semester 2016. This membership costed 1,100NOK (≈122USD) at the time of the intervention.

As described in the published paper on the immediate effects, and the accompanying pre-plan, we had three subtreatments in our study design, with some treated students being assigned a personal trainer or a bonus scheme in addition to the free gym card. We did, however, pre-specify that we would focus on the combined treatment group in the main analysis to gain maximum power, and we will do this also in the current study on long-term effects.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
As stated, we aim to address three different research questions that differ with respect to the main outcome variable and the underlying data source of the main outcome variable. The intention is therefore to publish the results of the three main outcomes in three separate papers. The three main outcomes are:

1) Exercise habits
2) Academic Performance
3) Overall life outcomes two years after the intervention

We explain the details of each main outcome variable in the next section.
Primary Outcomes (explanation)
1) Exercise habits: We will use scanner data from the student gym to test whether there is a causal effect on gym habits in subsequent semesters. We will consider two dimensions: i) do people buy a gym card/visit the gym at least one time (capturing their intention); ii) total number of gym visits per semester (capturing actual habit). We expect the largest effect in the fall 2016, and will use that period as the main test, but we will also analyze the accumulated effects until the spring 2018. As a point of reference, in the intervention period (spring 2016) 11.6 percent of control group students visited the gym at least one time, whereas the same number in the treated group was 68.6 percent (a 57 pp. difference), while the treatment effect on the number of gym visits was 0.63 S.D. We expect smaller effects in subsequent semesters when treated students also need to pay for their gym card.

2) Academic performance: In the short-term analysis we pre-specified that we would investigate the effects on both completed study points in graded courses (CSP) and the grade average conditional on passing a course (GA). We also pre-specified that we expected a larger treatment effect among students that scored low on life satisfaction, health, study hours and self-control. The analysis revealed that students passed more courses as shown by a significant treatment effect on CSP (≈0.15SD), while maintaining the same grade average on completed courses (no significant effect on GA, but positive point estimate). We also found that the effect on CSP was larger (≈0.40SD) in the subsample that struggled along the four dimensions mentioned above. In the long-run analysis on academic performance we will continue to focus on both of these measures, to understand whether the increase in completed study points in the spring 2016 helped students to complete more courses / receive higher grades in the next semester, or whether it has a crowding-out effect implying that treated students complete fewer courses in the next semester. We will also report treatment effects for the full sample and separately for the subsample that struggled initially. As for exercise, we expect the largest long-term effect (in absolute terms) during the fall 2016, and we will use that period for the main test. In addition, we will analyze accumulated effects from the spring 2016 until the spring 2018. It should be noted that we used registered study points (RSP) as a control variable in the short-term analysis. That was uncontroversial since students registered for courses prior to the intervention, and the variable balanced across treatment. Because of the treatment effect on completed study points in the spring 2016, there could be a difference in how many courses students register for at the beginning of the academic semester in the fall 2016 and onwards. Hence, RSP in the fall 2016 is a potential outcome variable in the long-term analysis, and to use it as a control variable (to increase power) we need to confirm that it balance across treatment. It should also be mentioned that we will record CSP and RSP as zero if there is no data in the academic records for a person in a given semester. The rationale is that the person has neither registered nor completed any study points at one of the two academic institutions. We will discuss in detail how to interpret the estimated effect on academic success. Given our definition of how to record CSP and RSP, people who have successfully finished their Bachelor or Master degree and entered the labor market will get the same value (i.e. zero) as university dropouts. We will therefore compare the average treatment effect on the full sample with the average treatment effect on the subsample of students that was in their first or second year of study in the spring 2016. These students should be unlikely to have completed their degree before the fall semester 2016, and we can thus assume that any missing observations in this subsample can be ascribed to the person dropping out of university rather than anything else. Importantly, we intentionally over-sampled bachelor students in the first two years of their studies, to facilitate the study of long-term effects on academic performance, and they turned out to make up about 75% of the total sample. Hence, although power is slightly reduced in this analysis we have a meaningful sample size to make qualitative judgements that will inform us about the size and sign of the bias in the overall sample. In explorative analysis on academic performance we will also study the effects on the likelihood and time to complete a Bachelor/Master degree.

3) Overall life outcomes: In May 2018, two years after the intervention, participants answered an endline survey (92% response rate ). The survey covered many aspects including: health (BMI, and a lifestyle index variable consisting of self-reported satisfaction with health, sleep habits and alcohol usage); a self-control index consisting of the answer to four questions (resist temptations, follow plans, tendency to procrastinate, think before acting); life satisfaction (overall, social sphere, financial, academic, work); and occupational status (full time employed, part time employed, in higher education, other). In the short-term analysis we found a 0.15 SD treatment effect on both the lifestyle index and the self-control index. The question is whether those effects remain, and, in addition, if there are any effects on BMI, the likelihood to be (un)employed, and life satisfaction.

Secondary Outcomes

Secondary Outcomes (end points)
To investigate the possibility that people start exercising at other gyms in subsequent semesters we will also report the results from a question in the endline survey that asked whether the person was member at any gym in the fall 2016 (yes/no), spring 2017 (yes/no), fall 2017 (yes/no) and so on. We expect to observe similar patterns from this question as in the objective scanner data, because the student gym fee is subsidized for students, and also cheaper for non-students in comparison to other gym chains. Hence, SIB is likely to be the preferred gym chain for the majority of our sample, also after the free gym card expired and the student finished their studies.

We will also construct a variable called Graded Study Points (GSP), which simply multiplies the completed study points with the achieved grade (A=5, B=4, C=3, D=2, E=1) summed over all courses per semester, to capture both dimensions of academic performance in one single outcome variable.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study is based on a between-subject design. Treated subjects receive a free gym card to the student gym for the spring semester 2016, whereas control group subjects do not get the free gym card. Due to random assignment of treatment we can evaluate how the free gym card affects gym exercise and other outcomes both in the intervention period (the published paper) and afterwards (the current project).

We will use the same OLS estimation strategy as in the analysis on the immediate effects, and control for the same set of background variables to improve precision in the statistical tests, namely: age, gender, year of study, institution, and dummies for being above the median in terms of i) study hours, ii) life style index, iii) self-control index, iv) overall life satisfaction (as well as Registered Study Points in the spring 2016 for analysis on academic outcomes).
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
778 individuals.
Sample size: planned number of observations
778 individuals.
Sample size (or number of clusters) by treatment arms
Treated group = 398
Control group = 380
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power calculations in STATA reveal that we have 80% power to detect effects of about 0.2 standard deviations. For exercise this implies that we are able to detect an effect on the fraction buying a gym card in the fall 2016 of about 10 percentage points (e.g. from 10% in control to 20% in treatment group), or that 1/3 of the short-term effect on gym attendance (i.e. 0.6 SD) remains in the fall 2016. Hence, although we expect smaller effects on exercise in the fall 2016 and onwards we have sufficient power to detect meaningful habit effects. For academic performance and other life outcomes the short-term effects were approximately 0.15 standard deviations and statistically significant at 5% with control variables. Hence, in the long-term analysis we have sufficient power to detect sustained, increasing or fully-reversed effects on these outcomes, but will struggle to detect diminished positive or negative effects (i.e. effects in the range from -0.15 S.D. to 0.15 S.D.).

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number