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Impulsivity, Peers, and Delinquency: A Dynamic Social Network Approach

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Abstract

Objectives

Drawing on criminological research about peer delinquency and self-control, we employ a network perspective to identify the potential paths linking impulsivity, peers, and delinquency. We systematically integrate relevant processes into a set of dynamic network models that evaluate these interconnected pathways.

Methods

Our analyses use data from more than 14,000 students in Pennsylvania and Iowa collected from the evaluation of the PROSPER partnership model. We estimate longitudinal social network models to disentangle the paths through which impulsivity and delinquency are linked in adolescent friendship networks.

Results

We find evidence of both peer influence and homophilic selection for both impulsivity and delinquency. Further, results indicate that peer impulsivity is linked to individual delinquent behavior through peer influence on delinquency, but not on impulsivity. Finally, the results suggest that impulsivity moderates both influence and selection processes, as adolescents with higher levels of impulsivity are more likely to select delinquent peers but less likely to change their behavior due to peers.

Conclusions

In sum, this study offers a more holistic framework and stronger theoretical tests than similar studies of the past. Our results illustrate the need to consider the simultaneous network processes related to peers, impulsivity, and delinquency. Further, our findings reveal that a large dataset with ample statistical power is a valuable advantage for detecting the selection processes that shape friendship networks.

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Notes

  1. Other scholars appear to reach a similar conclusion, including Mamayek et al. (2015, p. 427): “self-control appears to entail the individual’s capacity to resist impulsive behavior, yet it also seems to include impulsivity as one of its dimensions—that is, among other things, low self-control is impulsivity.”.

  2. Ousey and Wilcox (2007) labeled their measure as antisocial propensity. We refer to it as impulsivity, however, because they define propensity in terms of impulse control, both conceptually and operationally.

  3. Meldrum et al.’s (2013) study involves a self-report measure of susceptibility to influence and an interaction between this measure and self-control rather than an interaction of self-control with the relationship of peer delinquency to individual delinquency. Thus, it does not operationalize peer influence in the same sense as the other studies or as Fig. 1.

  4. This approach may not be essential for addressing selection, however, because there are indications that the estimates of peer influence it produces may not be meaningfully different from those of a well-specified regression model (Ragan et al. 2022).

  5. The other two studies concern the relationship of self-control to other peer-related factors, namely reports of being pressured by peers (Meldrum 2008) and mothers’ reports about friends’ deviance and teacher’s reports about friends’ prosocial behavior (Meldrum and Hay 2012).

  6. Correlational paths are not typically included in indirect effects, but the correlational path E between peer attributes has different implications for selection processes than for influence processes. For determining selection processes, the correlated attributes of friends’ delinquency and impulsivity (path E) each need to be controlled in determining selection tendencies for the other. Even so, impulsive individuals’ tendency to select more impulsive friends than would be expected based on individual delinquency, as reflected in path B, does imply the consequence of greater exposure to delinquent friends, giving the correlational path E a causal significance for influence. This connects to Schaefer’s (2018) arguments that peer selection must be studied through network selection analysis methods, not conventional regression models, as well as to the value of jointly analyzing influence and selection through network methods (Steglich et al. 2010). For these reasons, our heuristic conceptual model in Fig. 1 is not a conventional causal model.

  7. Although the PROSPER prevention trial is not the focus of the current study, supplemental analyses test for interactions between the treatment condition (entered as a grand-mean centered covariate at the third level of the hierarchical linear models described in our “Modeling Strategy”) and parameters of interest from Table 4. The selection parameters tested were the alter, ego, and similarity effects for both impulsivity and delinquency, as well as for the interaction between the ego parameter for impulsivity and the alter parameter for delinquency. The behavioral parameters were the effects of friends’ delinquency and friends’ impulsivity on delinquency, individual impulsivity on delinquency, and the behavioral interaction between individual impulsivity and friends’ delinquency. Results suggest that the tendency of individuals to select friends with similar levels of delinquency are higher in the school districts that participated in the intervention program. Although past studies reported significant intervention main effects on problem solving (Redmond et al. 2009) and conduct problem behaviors (Spoth et al. 2015), interactions of the treatment condition with the other parameters failed to achieve statistical significance at conventional alpha levels.

  8. While the variable names in the current study are generally consistent with those used in previous studies that have analyzed the PROSPER social network data (e.g., Osgood et al. 2015), the measure for delinquency is named conduct problem behaviors in other studies (e.g., Spoth et al. 2015) and the measure for impulsivity shares items with problem solving (e.g., Redmond et al. 2009).

  9. Although Niezink et al. (2019) propose a differential equation method that would allow continuous dependent variables, their method was not available in the public SIENA code at the time this manuscript was written. Our measure of delinquency is based on a variety scale, which is commonly used in criminological research and generally preferable to frequency scales and dichotomous measures (Sweeten 2012). Further, variety scales are often highly-correlated with IRT scales (Osgood et al. 2002; Sweeten 2012); the correlation between the measure of delinquency employed in the current study and the IRT version based on the same items is 0.96.

  10. All SAB models also include behavior and friendship rate functions that adjust for the number of changes in individual behavior and network ties, respectively. Shape effects represent a preference, over time, toward higher values on the outcome and are included in each model as well. Rate and shape estimates are not reported alongside the other estimates because they are not of substantive interest in the current study, but are available from the authors upon request.

  11. The structural parameters in the models derive from a larger effort to assess and improve the goodness of fit tests. This effort involved comparing goodness of fit tests for models with different sets of structural network parameters, including those that have been used in the prior studies using these data but also several recommended by one of the SIENA developers. We determined which configuration produced, on average, the best goodness of fit statistics. One conclusion of this effort has been that different configurations seem to have relatively little effect on the estimates of the substantive (non-structural) parameters.

  12. One district-cohort network is omitted due to a missing wave of data and two because a school closing after a fire created a chaotic pattern of school transitions that precluded analysis with SIENA. Two additional networks are omitted due to unsatisfactory convergence (i.e., the simulations did not match the observed data). The convergence t values, which represent the extent to which the simulated data vary from the actual data, are less than + /– .10 across all networks for all parameters, and the overall maximum t-ratio for convergence is below .25 for each model. All estimates are from models with five phase-2 sub-phases and 4000 iterations during phase 3.

  13. The similarity selection effect is a form of interaction between the ego and alter effects, which means that those two effects each vary across levels of the other variable. Because SIENA centers all variables on their means, the coefficients for ego and alter are average effects, and thus usefully summarize the overall relationship. Appendix 3 uses selection tables (Ripley et al. 2021) to illustrate how the three selection effects combine. These tables show the selection implications of our full model (Table 4) for combinations of ego and alter impulsivity, of ego and alter delinquency, and of ego impulsivity and alter delinquency.

  14. These items were taken from students’ responses to questions asking how often they “compromise to get something positive from the situation,” “do something dangerous because someone dared you to do it,” or “do crazy things just to see the effect on others.” The revised measure was created with the same procedure as our original measure of impulsivity (i.e., we rounded the average of all items to the nearest integer).

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Acknowledgements

Grants from the W.T. Grant Foundation (8316), National Institute on Drug Abuse (R01-DA018225), and National Institute of Child Health and Development (R24-HD041025) supported this research. The analyses used data from PROSPER, funded by grant R01 DA013709 from the National Institute on Drug Abuse, and co-funded by the National Institute on Alcohol Abuse and Alcoholism. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Authors and Affiliations

  1. University of New Mexico, Albuquerque, NM, USA

    Daniel T. Ragan

  2. Pennsylvania State University, State College, PA, USA

    D. Wayne Osgood & Derek A. Kreager

Authors
  1. Daniel T. Ragan
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  2. D. Wayne Osgood
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  3. Derek A. Kreager
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Correspondence to Daniel T. Ragan.

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Appendices

Appendix 1: Descriptive Statistics for Change in Friendship Networks, Impulsivity, and Delinquency

 

Wave 2

Wave 3

Wave 4

Wave 5

Wave 6

Wave 7

Wave-specific statistics

      

Network size

      

 Mean

172.51

186.35

191.47

187.82

171.00

152.86

 Minimum

64

79

84

68

54

63

 Maximum

352

437

420

443

365

326

Friendship ties

      

 Average degree

6.04

5.90

5.66

4.88

4.59

4.30

 Density (%)

2.86

2.77

2.67

2.29

2.16

2.03

Impulsivity

      

 1 (Never)

19.83

17.01

15.62

13.89

15.45

15.78

 2 (Occasionally)

39.58

36.69

37.02

36.52

37.19

38.20

 3 (Sometimes)

27.92

30.13

30.34

32.75

31.75

29.66

 4 (Usually-always)

12.66

16.17

17.03

16.84

15.62

16.36

Delinquency

      

 0 (0 behaviors)

63.15

56.84

50.86

48.65

47.72

48.47

 1 (1 behaviors)

16.58

17.47

16.58

16.28

16.70

17.66

 2 (2–3 behaviors)

11.73

13.52

15.79

15.87

16.25

15.37

 3 (4–12 behaviors)

8.54

12.17

16.77

19.20

19.33

18.51

 

Wave 2–3

Wave 3–4

Wave 4–5

Wave 5–6

Wave 6–7

Between-wave changes

     

Change in friendship ties

     

 Distance (n of changed ties)

726.37

788.92

669.20

559.86

427.96

 Jaccard index (%)

24.78

27.48

28.41

31.13

32.59

Average Change in impulsivity

     

 "Increasers"

45.73

42.63

41.53

35.69

32.41

 "Maintainers"

66.41

73.33

75.06

71.90

61.88

 "Decreasers"

32.98

41.18

36.80

37.10

32.12

Average change in delinquency

     

 "Increasers"

39.31

42.78

39.43

36.94

29.57

 "Maintainers"

94.29

93.55

87.65

82.94

71.94

 "Decreasers"

24.67

27.59

29.94

28.98

27.33

Appendix 2: Items Used in Scale Construction

Impulsivity

  1. 1.

    Get information that is needed to deal with the problem.

  2. 2.

    Think about which of the choices is best.

  3. 3.

    Think about the risks of the different ways to deal with the problem.

  4. 4.

    Think about the consequences of each choice.

  5. 5.

    Do what feels good, regardless of the consequences.

Delinquency

  1. 1.

    Taken something worth less than $25 that didn’t belong to you.

  2. 2.

    Taken something worth $25 or more that didn’t belong to you.

  3. 3.

    Beat up someone or physically fought with someone because they made you angry (other than just playing around).

  4. 4.

    Purposely damaged or destroyed property that did not belong to you.

  5. 5.

    Broken into or tried to break into a building just for fun or to look around.

  6. 6.

    Thrown objects such as rocks or bottles at people to hurt or scare them.

  7. 7.

    Been picked up by police for breaking a law.

  8. 8.

    Run away from home.

  9. 9.

    Skipped school or classes without an excuse.

  10. 10.

    Carried a hidden weapon.

  11. 11.

    Avoid paying for things such as movies, rides, food or computer services.

  12. 12.

    Taken something from a store that you did not pay for.

School adjustment and bonding

  1. 1.

    I like school a lot.

  2. 2.

    I try hard at school.

  3. 3.

    Grades are very important to me.

  4. 4.

    School bores me.

  5. 5.

    I don’t feel like I really belong at school.

  6. 6.

    I feel very close to at least one of my teachers.

  7. 7.

    I get along well with my teachers.

  8. 8.

    I feel that teachers are picking on me.

Family Relations

(Child monitoring)

  1. 1.

    During the day, my parents know where I am.

  2. 2.

    My parents know who I am with when I an away from home.

  3. 3.

    My parents know when I do something really well at school or some place else away from home.

  4. 4.

    My parents know when I get into trouble at school or some place else away from home.

  5. 5.

    My parents know when I do not do things they have asked me to do.

    (Inductive reasoning)

  6. 6.

    My parents give me reasons for their decision.

  7. 7.

    My parents ask me what I think before making a decision that affects me.

  8. 8.

    When I don’t understand why my parents make a rule for me, they explain the reason.

    (Joint activities)

  9. 9.

    Work on homework or a school project together.

  10. 10.

    Do something active together, like playing sports, bike riding, exercising, or going for a walk.

  11. 11.

    Talking about what’s going on at school.

  12. 12.

    Work on something together around the house.

  13. 13.

    Discuss what you want to do in the future.

  14. 14.

    Do some other fun activity that you both enjoy.

    (Mothers’ affective quality)

  15. 15.

    Let you know she really cares about you.

  16. 16.

    Act loving & Affectionate toward you.

  17. 17.

    Let you know that she appreciates you, your ideas, or the things you do.

    (Fathers’ affective quality)

  18. 18.

    Let you know he really cares about you.

  19. 19.

    Act loving and Affectionate toward you.

  20. 20.

    Let you know that he appreciates you, your ideas, or the things you do.

    (Affective quality toward mother)

  21. 21.

    Let her know you really care about her.

  22. 22.

    Act loving and affectionate toward her.

  23. 23.

    Let her know that you appreciate her, her ideas, or the things she does.

    (Affective quality toward father)

  24. 24.

    Let he know you really care about him.

  25. 25.

    Act loving and affectionate toward him.

  26. 26.

    Let him know that you appreciate him, his ideas, or the things he does.

Self-control (supplementary analyses)

  1. 1.

    Get information that is needed to deal with the problem.

  2. 2.

    Think about which of the choices is best.

  3. 3.

    Think about the risks of the different ways to deal with the problem.

  4. 4.

    Think about the consequences of each choice.

  5. 5.

    Do what feels good, regardless of the consequences.

  6. 6.

    Compromise to get something positive from the situation.

  7. 7.

    Do something dangerous because someone dared you to do it.

  8. 8.

    Do crazy things just to see the effect on others.

Appendix 3: Log Odds of Selection as Deviations from Mean Log Odds (Table 4 Estimates)

 

Alter impulsivity

 

1

2

3

4

Ego impulsivity

1

0.053

0.047

0.042

0.036

2

− 0.023

0.041

0.035

0.030

3

− 0.099

− 0.035

0.029

0.023

4

− 0.175

− 0.111

− 0.047

0.017

 

Alter delinquency

 

0

1

2

3

Ego delinquency

0

0.050

0.027

0.003

− 0.020

1

− 0.022

0.063

0.039

0.016

2

− 0.094

− 0.010

0.075

0.052

3

− 0.167

− 0.082

0.003

0.088

 

Alter delinquency

 

0

1

2

3

Ego impulsivity

1

0.063

0.060

0.056

0.053

2

0.000

0.020

0.040

0.060

3

− 0.063

− 0.020

0.024

0.067

4

− 0.126

− 0.059

0.007

0.074

Appendix 4

See Table 5, 6, 7 and 8.

Table 5 Descriptive statistics
Full size table
Table 6 Selected SIENA parameter estimatesa: self-control
Full size table
Table 7 Selected SIENA parameter estimatesa: delinquency and self-control
Full size table
Table 8 Selected SIENA parameter estimatesa: delinquency
Full size table

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Ragan, D.T., Osgood, D.W. & Kreager, D.A. Impulsivity, Peers, and Delinquency: A Dynamic Social Network Approach. J Quant Criminol 39, 735–768 (2023). https://doi.org/10.1007/s10940-022-09547-8

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