Supporting young adults neither in education, emplyment or training

Last registered on February 23, 2023

Pre-Trial

Trial Information

General Information

Title
Supporting young adults neither in education, emplyment or training
RCT ID
AEARCTR-0009167
Initial registration date
February 19, 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, 10:35 AM EST

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

Last updated
February 23, 2023, 4:57 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Affiliation
Universitetet i Stavanger

Other Primary Investigator(s)

PI Affiliation
University of Stavanger
PI Affiliation
University of Stavanger

Additional Trial Information

Status
In development
Start date
2023-02-20
End date
2025-12-31
Secondary IDs
Research Council Norway: 296390
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Technological advances and automation are making workplaces increasingly knowledge-intensive, with many routine and well-defined jobs becoming redundant. The new labor market requires workers with high competencies who are not afraid of change, challenges, and acquiring new skills. For many young adults, this could be a major risk factor for labor market exclusion. Indeed, today almost 10 percent of young adults in Norway are "Not in Education, Employment or Training" (NEET).

Based on protocols from psychology, we have developed an app (RØST), supporting young education or job applicants. By investigating the effects of RØST, this project will provide new knowledge about young NEETs, and how society can support them in entering the labor market or education.
External Link(s)

Registration Citation

Citation
Haaland, Venke, Simone Valerie Häckl-Schermer and Mari Rege. 2023. "Supporting young adults neither in education, emplyment or training." AEA RCT Registry. February 23. https://doi.org/10.1257/rct.9167-1.1
Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-02-20
Intervention End Date
2023-12-31

Primary Outcomes

Primary Outcomes (end points)
Sub project 1:
(1) Register data measures on labor market participation or education enrollment: employed, enrollment in education, participation in labor market programs initiated by NAV, and social security benefits.

(2) Survey measures on current life situation: 1) Perceived stress (PSS-10; Cohen and Williamson, 1988); 2) Warwick-Edinburgh mental well-being scale (Stewart-Brown et al., 2009; Tennant et al., 2007); 3) Symptoms checklist (SCL-10; Strand et al., 2003).

In follow up studies we will also look at educational attainment and income in registry data.

Sub project 2:
(1) Indicator for consent, indicator for program completion, time spent on program and surveys
(2) Survey measures on personality: 1) Time preferences (Falk et al., 2022); 2) Conscientiousness (BFI-2 XS, Soto and John, 2017); 3) Self efficacy (Gaumer Erickson et al., 2016)
(3) Survey measures on current life situation: 1) Perceived stress (PSS-10; Cohen and Williamson, 1988); 2) Warwick-Edinburgh mental well-being scale (Stewart-Brown et al., 2009; Tennant et al., 2007); 3) Psychological distress symptoms checklist (SCL-10; Strand et al., 2003).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Sub project 1:
Mechanisms
(1) Self efficacy (Gaumer Erickson et al., 2016)
(2) Stress mindset (Yeager et al., 2021)
(3) Procrastination (IPS; Steel, 2002 & 2010; translation to Norwegian by Svartdal, 2015)

Treatment Fidelity
(1) Fixed mindset scale (Yeager, 2016)
(2) Stress manipulation test (Yeager et al., 2021)

Other outcomes
(1) Locus of control (Pearlin and Schooler, 1978)
(2) Number of job applications (Bjorvatn et al., 2021)
(3) Knows future career (Resnjanskij et al., 2021).
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
All youths registered at the Norwegian public employment office (NAV) will be invited to participate. After consenting to participation, logging on to the web application and completing the baseline survey, subjects will be automatically randomized to different treatment arms, involving different material in the web application. The participants will receive an SMS each week for five consecutive weeks, with a note that a new session in the app is available. There will also be reminders to complete the content in each session. Subjects are blind to treatment.
Experimental Design Details
Not available
Randomization Method
Randomization of the invitation with and without incentives will be performed by a computer at NAV Statistical section at the individual level, with a witness present.
Randomization happens individually and is automated in the app at the individual level.
Randomization Unit
In both subprojects we randomize at the individual level with equal probability of each treatment.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1300 Individuals
Sample size: planned number of observations
First field implementation: We invite all youths registered as unemployed during the last two months at NAV Rogaland aged 18-29 years, for whom NAV has not registered any special difficulties making regular employment highly unlikely. This will give us a sample size of about 1300. Based on previous studies, we expect 383 participants to sign up. Second field implementation: We will invite all youths aged 18-29 years registered at NAV in Norway except from Rogaland, for whom NAV has not registered any special difficulties. We will have a first-serve policy up until at least 1000 youths have consented to participate.
Sample size (or number of clusters) by treatment arms
First field implementation:
The 1300 youths are randomized to receive an invitation to experiment A or B with equal probability, leading to 650 participants in each group. We expect a 35 % uptake in A and a uptake of 24 % in B, giving a sample of 227 in A and 156 in B .

Second field implementation:
We will have 500 in treatment and 500 in control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
First field implementation: We calculate the MDES using Optimal Design Software (Spybrooke et al., 2001). For investigating effects on participation, we have 1300 observations. With this sample size, we are able to detect an effect of 0.16 standard deviations assuming 80 percent power and a two-sided 95-percent confidence interval. Assuming as above a 35% response rate, this translates into a difference of 7 percentage points. For investigating effects on selection, our sample is reduced to those who agreed to participate in the project. We expect our sample to be 383 individuals with 227 in experiment A and 156 in experiment B. This reduces the MDES to 0.30 standard deviations when comparing differences between participants in A and B. Second field implementation: We calculate the MDES using Optimal Design Software (Spybrooke et al., 2001). We have individual-level randomization and a sample of 1000 youths who have signed-up to participate. This sample is equally split between treatment and control. Assuming 80 percent power and a two-sided 95-percent confidence interval, we have a MDES of 0.18 standard deviations, not including any control variables. If we assume that control variables explain 20% of the variation in the outcome variables (R^2=0.2) the MDES reduces to 0.16 standard deviations. If we assume an R^2 of as high as 0.8 (as we observe baseline values of most of our outcome variables), it would even go down to 0.08 standard deviations. Adding data from the first field implementation may give us even more precision.
IRB

Institutional Review Boards (IRBs)

IRB Name
NSD Data Protection Official for Research
IRB Approval Date
2022-04-11
IRB Approval Number
353487