Does Empathy Attenuate the Criminogenic Effect of Low Self-Control in Late Life?

Figures & data

Table 1. Descriptive statistics and correlations (product-moment correlation coefficients).

	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.
1. Offending	1.00
2. Empathy	−.09***	1.00
3. Risk-taking	.17***	−.08***	1.00
4. Impulsivity	.09***	−.54***	.11***	1.00
5. Mobility	.15***	.04*	.15***	.02	1.00
6. Criminal associations	.20***	−.02	.10***	.05**	.11***	1.00
7. Age	−.09***	.09***	−.06**	−.08***	−.22***	−.12***	1.00
8. Gender	.10***	−.11***	.15***	−.01	.05**	.05*	.01	1.00
9. Social status	.01	.06**	.03	−.04*	.21***	−.01	.05**	.03	1.00
10. Migration background	−.01	−.02	−.00	−.00	−.03	.04*	−.05*	−.02	−.09***	1.00
Arithmetic mean/Standard deviation	0.11/0.39	12.78/2.28	4.75/1.51	11.24/3.26	6.27/1.90	0.08/0.27	64.42/10.07	0.49/0.50	3.62/0.78	0.06/0.23

* p < .05; ** p < .01; *** p < .001

Table 2. Linear regression models predicting late life offending.

	Model 1		Model 2		Model 3		Model 4		Model 5
	b	t	b	t	b	t	b	t	b	t
Empathy	−.02*	2.91	−.00	0.22	−.00	0.48	−.01	0.60	−.01	0.59
Risk-taking			+.07***	5.64	+.06***	5.67	+.05***	4.50	+.05*	2.48
Impulsivity			+.02**	2.54	+.03*	2.60	+.02*	2.12	+.02*	1.90
Risk-taking*Empathy					−.02*	1.79	−.02*	1.80	−.02*	1.75
Impulsivity*Empathy					+.00	0.56	+.00	0.05	+.01	1.09
Criminal associations							+.07***	5.23	+.07***	5.25
Mobility							+.04***	3.63	+.04***	3.72
Age							−.00	1.55	−.00	1.62
Gender							+.06***	3.76	+.06***	3.87
Social status							−.01	0.62	−.01	0.59
Migration background							−.03	1.07	−.03	1.11
Empathy (squared)									+.01	1.34
Risk-taking (squared)									+.00	0.10
Impulsivity (squared)									+.01	0.86
Overall model	R^2 = .003; p = .004		R^2 = .034; p = .000		R^2 = .037; p = .000		R^2 = .086; p = .000		R^2 = .087; p = .000

Note: The predictors “empathy,” “risk-taking,” “impulsivity,” “mobility” and “criminal associations” are converted into Z-scores. All models are based on robust standard errors.

* p < .05; ** p < .01; *** p < .001; b … unstandardised regression coefficient; t … t-value

Figure 1. The interaction of risk-taking and empathy.

Note: Risk-taking and empathy were dichotomised at the median.

Table 3. Marginal effects of risk-taking at representative values of empathy (marginal effects from negative binomial regression models).

	Risk-taking	Impulsivity
Conditional effects	ME (p)	ME (p)
High empathy (µ + 1 SD)	0.025 (.000)	0.029 (.003)
Medium empathy (µ)	0.028 (.000)	0.030 (.001)
Low empathy (µ – 1 SD)	0.032 (.000)	0.031 (.000)
Equality tests	Z (p)	Z (p)
High/low	1.67 (.047)	0.46 (.324)
High/medium	1.77 (.038)	0.47 (.321)
Medium/low	1.59 (.056)	0.45 (.327)

ME … marginal effect; Z … Z-value; p … error probability

Table

Offending	Crime variety scale based on the perpetration of 11 distinct crimes in the last 12 months [crime (prevalence)]: - drunk driving (3.8%) - tax fraud (2.1%) - illicit work (1.9%) - fare dodging (1.6%) - bribery (0.8%) - shoplifting (0.5%) - physical assault (0.1%) - vandalism (0.0%) - theft of a bike or other vehicle (0.0%) - theft from a person (0.0%) - social security fraud (0.0%)
Risk-taking	Assessment of 4 statements: (alpha = .81) I like to test myself every now and then by doing something dangerous; Sometimes I take a risk just for the fun of it; I sometimes find it exciting to do things for which I might get in trouble; Excitement and adventure are more important to me than security. 4-point scale: strongly agree – strongly disagree
Impulsivity	Assessment of 6 statements: (alpha = .71) Often I cannot prevent anger and joy blurting out of me; I live by the rule ‘Think before you act’ (r); I always have my feelings under control (r); I react too often quick-tempered on other people; In stressful situations I am often more self-restrained than most other people I know (r); Even under great stress I take the time for contemplating my behaviour (r). 4-point scale: strongly agree – strongly disagree
Empathy	Assessment of 4 statements: (alpha = .76) In almost every situation I try to see the facts also from the perspective of my dialog partner; Even in cases of disagreement I normally succeed in seeing things with the eyes of my vis-à-vis; In most situations I try to see the world with the eyes of my conversation partner; It is no problem for me to understand the feelings of other people. 4-point scale: strongly agree – strongly disagree
Criminal associations	Do you have friends, acquaintances or relatives who have committed the following crimes in the last 12 months? [fair dodging, shoplifting, theft of a bike or other vehicle, vandalism, physical assault] Dichotomy: yes/no
Mobility	Answers to three questions: (alpha = .70) “How often did you attend cultural events in the last 12 months?” “How often did you go to concerts or the movies in the last 12 months?” “How often did you go to pubs, bars or dancing events in the last 12 months?” 5-point scale: never – several times a week
Socio-economic status	How do you assess your own economic position? 5-point scale: very bad – very good
Migration background	Is it true that at least one of your parents was born abroad or does not have German nationality? Dichotomy: yes/no

Table

	Model 1		Model 2		Model 3		Model 4		Model 5
	b	Z	b	Z	b	Z	b	Z	b	Z
Empathy	−0.19**	2.84	−0.14*	2.11	−0.13*	1.89	−0.04	0.57	−0.02	0.25
Risk-taking			+0.41***	7.37	+0.26***	4.85
Impulsivity							+0.26***	3.39	+0.26***	3.25
Criminal associations					+0.30***	6.89			+0.32***	7.04
Mobility					+0.33***	5.04			+0.38***	5.75
Age					−0.02*	2.44			−0.02**	2.95
Gender					+0.52***	3.79			+0.68***	4.90
Social status					−0.08	0.92			−0.06	0.70
Migration background					−0.33	1.06			−0.27	0.85
Model fit	χ^2 = 8.04; p = .005		χ^2 = 61.79; p = .000		χ^2 = 166.36; p = .000		χ^2 = 18.59; p = .000		χ^2 = 153.19; p = .000

Note: The predictors “risk-taking,” “empathy,” “mobility” and “criminal associations” were converted into Z-scores.

*p < .05; ** p < .01; *** p < .001; b … unstandardised regression coefficient; Z … Z-value