Youth provision and life outcomes: a study of longitudinal research (executive summary)
Published 29 February 2024
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Summary of key findings
Our research used five datasets to explore the effects of weekly participation in youth clubs on outcomes later in life. Four of the five datasets are longitudinal studies; the fifth is a rolling annual survey. The studies cover different generations of young people from the 1970s to 2000s, and the timing of outcome measurements reflects this.
There is a clear association between participation in youth provision and positive short-term outcomes relating to physical health and wellbeing, pro-social behaviours and education. There is also strong evidence that these short-term outcomes are sustained over decades, and compared with non-participants, people who attended youth clubs continue to score more highly for several of these indicators of wellbeing.
The proportion of young people who participate in youth clubs weekly has increased over time, from c. 20% (the 1970 British Cohort Study) to c. 35% (the Millennium Cohort Study (MCS) and UK Household Longitudinal Study (UKHLS)), possibly because recent datasets adopted a wider definition of ‘youth activity’ as in-person clubs, scouts, girl guides and other enrichment activities.
What factors predict participation in youth activities? Young people with the following characteristics were more likely to participate on a weekly basis:
BCS70: young men, lower parental income/social class, lower reading scores
Next Steps: young men, ethnic minorities
MCS: White and Black Caribbean, living in safe neighbourhoods and devolved nations, higher parental income, higher education level and social class
UKHLS: White British, higher parental income, married or cohabitating parents and parents involved in volunteering activities.
What is the relationship between participation in youth activities and outcomes for young people at the time of participation? Regular attendees were more likely to:
BCS70 (16 years old): be involved in a fight, steal and interact with police
Next Steps (16 years old): do sports weekly, not consume alcohol weekly, carry a knife
MCS (14 years old): not truant, not drink alcohol/take illegal drugs, be in good health
UKHLS (10-16 years old): not truant, not drink alcohol, aspire to university, good health.
What is the relationship between participation in youth activities and outcomes later in life (between the ages of 20 and 30 years)? Participants in youth clubs were more likely to:
BCS70: (30 years): have interacted with police since the age of 16 years
Next Steps (24-25 years): have higher education, not take illegal drugs, have lower earnings
MCS (17 years): be in good health, have a qualification and a paid job
UKHLS: (at 16 years) to be a part of an organisation, want to go to university, be in good physical health; (at 20 years) be in education, volunteer.
Study background and scope
The Department for Culture, Media and Sport (DCMS) commissioned three projects to research youth provision collectively called the Youth Evidence Base. SQW, the University of Essex, University of Warwick and UK Youth carried out the three projects concurrently, advised by the Department and a specially convened Youth Panel enabling us to draw on young people’s lived experience of youth provision.
This report outlines findings from analysis of 5 longitudinal datasets to answer the following research questions:
What are the personal characteristics that predict young people’s participation in youth activities (including youth clubs)?
What is the relationship between participation in youth activities and outcomes for young people at the time of participation?
What is the relationship between participation in youth activities and outcomes later in life (between the ages of 20 and 30 years)?
Are there any ‘cohort effects’ – differences in observed patterns across people from different generations?
The 6 outcome areas were:
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Educational outcomes.
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Employment/career pathways.
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General health.
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Mental health.
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Life satisfaction and wellbeing.
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Crime and anti-social behaviour.
Datasets and approach
Five datasets (listed in Table 1) were used to answer our research questions. They span several decades, the oldest tracking people born in 1970 and the most recent one people born in 2002. The datasets used two different definitions of youth activities:
- BCS70, Next Steps and ALSPAC asked respondents about attending youth clubs
- MCS and UKHLS definition was broader to include youth clubs, scouts, girl guides or other organised activities
Table 1: Datasets used in the research study (in chronological order)
| Name | Type/Date |
|---|---|
| Avon Longitudinal Study of Parents and Children (ALSPAC) | Cohort study: people born in 1991–1992 in the Bristol area (England) |
| British Cohort Study (BCS70) | Cohort study: people born in 1970 |
| Millennium Cohort Study (MCS) | Cohort study: people born in 2000–2002 |
| Next Steps Generational Study (Next Steps) (also known as the Longitudinal Study of Young People in England – LSYPE1) | Cohort study: people born in 1989–1990 |
| Understanding Society (also known as the UK Household Longitudinal Study) (UKHLS) | Rolling annual survey of British households The study started in 2009, including a sample of households who participated in the British Household Panel Study (1991-2009) |
Source: SQW and University of Essex
The research focused on young people who attended weekly as more intensive engagement is more likely associated with observable outcomes. Time between first and longer-term outcome measurements vary due to data availability (Table 2).
Table 2: Ages (years) at which contemporaneous and later life outcomes are captured in each dataset
| Study | Age that contemporaneous outcomes were measured | Age that outcomes later in life were measured |
|---|---|---|
| ALSPAC | 16 | 25-26 |
| BCS70 | 16 | 26 and 30 |
| MCS | 14 | 17 |
| Next Steps | 16 | 24-25 |
| UKHLS | 10-16 | 16, 20 and 24 |
Source: SQW and University of Essex
Interpretation of the findings of the analysis presented in this report rests on understanding the different cohorts of people who were captured in these different datasets, their ages at which outcomes were observed and the types of youth club activity that were available to them contemporaneously.
Analysis
We adopted a systematic and consistent approach to the analysis of all five datasets that utilised appropriate statistical techniques (and robustness checks) as well as triangulation of results across the studies. In broad terms we accounted for a number of personal and familial characteristics including gender, ethnicity, local area (e.g., neighbourhood safety) and family background. Even though the overall approach was common across all five longitudinal studies, elements of the analysis such as exact model specifications and particular outcome measures varied slightly but were included to allow us to maximise the use of data.
Notable features of our analysis are:
We uncovered statistical associations but did not establish a direct causal relationship. Controlling for observable characteristics helped isolate the effect of attending youth clubs/activities (to a degree) but did not categorically establish causality.
The older studies suffer from attrition and missing responses (both these factors reduce the sample size available for analysis) while the newer studies naturally cover a shorter time period which limits our ability to trace the effect over longer periods of time.
None of the studies we analysed were designed to solely focus on participation in youth activities, and this required us to adjust our research design accordingly.
Key findings
Key findings are summarised, above. There are differences in results relating to the characteristics of young people attending the youth clubs: for example, in BCS70 people from lower social class families were more likely to attend whereas the opposite was true in MCS. We note the strong relationship between net parental monthly income and youth participation rates reported in UKHLS and that while having a very low income did not deter all participation (presumably because at least some provision is free) having the disposable income to pay for subscriptions, trips, and uniforms etc. appeared to promote participation.
In some cases, the outcomes associated with participation were positive (better health or education participation for example). In others the outcomes are more subtle. For example, in BCS70 there are ‘negative’ contemporaneous outcomes associated with youth participation. However, in relation to most outcomes in later life, we observed no statistically significant differences between the groups of participants and non-participants in BCS. This lack of negative associations are important because this ‘convergence’ of outcomes could be interpreted as a ‘reduction in negatives,’ indirect evidence for positive long-term effects from youth participation (given the initial socio-economic imbalance between the groups).
Reflections on findings
The profile of young people who participated in youth club activities differs between earlier and later datasets. The proportion of young people surveyed who regularly attended youth activities also increased over time (although that may be due to different definitions). Similarly, the types of outcome that were observed statistically to be associated with youth club participation were also different. Consequently, some findings need to be understood within the context of each dataset, the way questions were phrased, or the duration between contemporaneously reported effects and those observed later in life.
Changes in the funding landscape and types of activities offered through youth services may have an important role in explaining the differences in results across the studies (i.e. the cohort effects). For example, young people in the devolved nations had higher participation rates, possibly linked to differences in youth provision funding across the UK and funding decisions made in devolved nations.
The report concludes with recommendations regarding building the evidence base to help establish the causal impact of youth provision, the economic impact of youth services, and the impact of youth provision on different young people.