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. 2022 Feb 10;30(2):161–176. doi: 10.1080/13218719.2021.2003268

Executive function in individuals who are compliant and non-compliant with the conditions of a community-based sentence

Emily M Norman 1,✉, Devon L L Polaschek 1, Nicola J Starkey 1
PMCID: PMC10026818  PMID: 36950189

Abstract

Executive function encompasses multiple processes (e.g. regulating emotions, managing behaviours, problem-solving) essential in daily living. A growing body of neuropsychological research shows a relationship between executive dysfunction and criminal behaviour. However, is executive functioning relevant to sentence management? We examined relationships between self-reported executive functioning and community supervision sentence compliance. Sixty-four individuals serving community-based supervision sentences completed the Behavior Rating Inventory of Executive Function–Adult Version, and their compliance data for six months were collected from probation officer notes. The sample’s mean scores were significantly higher (i.e. poorer executive functioning) than those for the normative sample. Those who complied with sentence conditions had higher mean scores than those who were non-compliant. Subsequent exploratory analyses showed that those with poorer executive functioning received more probation officer support to comply with sentence conditions. Attention to responsivity issues like executive function problems may help avoid entrapping people in the criminal justice system.

Key words: Behavior Rating Inventory of Executive Function–Adult Version, BRIEF-A, community-based sentences, compliance, executive functioning, offenders, probation, probation officers, responsivity

Introduction

Executive functions are necessary for self-regulation and goal-directed behaviours, essential for efficient day-to-day functioning (M. D. Lezak, 1982). People in prison have poorer executive functioning than those in the general population, with meta-analyses showing a strong relationship between executive dysfunction and criminality (Morgan & Lilienfeld, 2000; Ogilvie et al., 2011). In addition, research suggests that poor executive functioning is associated with correctional programme attrition (Fishbein et al., 2009) and recidivism (Olson, 2014; Ross & Hoaken, 2011). Impairments in executive functions in a community corrections setting may be more likely to manifest as compliance and engagement issues, especially when the requirements of the sentence are undertaken in tandem with the duties, responsibilities and difficulties of everyday life (e.g. family, work and social commitments). Imprisonment ordinarily entails a temporary suspension of – and separation from – ‘normal life’: the life of most prisoners is highly regimented and requires little in the way of personal self-regulation skills. By contrast, a community-based sentence can be both less structured and more complex. Certainly, adhering to a community-based sentence against a backdrop of other life obligations is taxing on executive functions, and any executive dysfunction has the potential to negatively influence a supervisee’s ability to meet their sentence obligations. However, no studies have explored the relationship between the executive functioning of offenders serving community-based sentences and their compliance with sentence conditions, despite the important implications for community corrections programmes and supervision practices.

Executive function is an umbrella term to describe a set of self-regulatory functions that direct, manage and organize cognitive activities, emotional responses and overt behaviours (Alexander & Stuss, 2000; Gioia et al., 2001). The operational definition of executive functions and the different cognitive processes involved have varied somewhat among authors (Diamond, 2013; Jurado & Rosselli, 2007; H. D. B. Lezak et al., 2004). However, standard processes that fall under the umbrella of executive functions include initiating behaviour, inhibiting competing actions or stimuli, selecting relevant task goals, planning and organizing to solve problems, shifting problem-solving strategies when necessary, regulating emotions and evaluating one’s behaviour (Roth et al., 2005). The intact frontal/prefrontal cortex is crucial for efficient executive functions (M. D. Lezak, 1982). The prefrontal cortex is the largest region in the human brain and the last region of the brain to develop (Fuster, 2015; Stuss, 1992), making it especially vulnerable to injury due to its long developmental trajectory. Damage to the frontal lobe is associated with executive dysfunction (Morgan & Lilienfeld, 2000; Ogilvie et al., 2011) and criminal behaviour (Brower & Price, 2001).

A growing body of neuropsychological research shows a relationship between impairments in executive functioning and various operationalizations of criminality, including delinquency, physical aggression, conduct disorder, psychopathy and antisocial personality disorder (Morgan & Lilienfeld, 2000). Morgan and Lilienfeld (2000) reviewed 39 studies comprising 4589 male participants for a meta-analysis on executive function and antisocial behaviour. The studies included in the meta-analysis all utilized performance-based measures of executive functioning (i.e. standardized neuropsychological tests). The participants had been convicted of a criminal offence and diagnosed with either conduct disorder or antisocial personality disorder. The findings indicated that antisocial individuals performed significantly more poorly on executive functioning measures, particularly in planning and impulse control, than non-offender groups. Ogilvie et al. (2011) also found a robust and statistically significant association between criminal conduct and poorer executive functioning (assessed by performance-based measures of executive function) in a meta-analysis, including 126 studies involving 14,786 men and women participants (5847 offenders and 6904 non-offenders). Additionally, Meijers et al. (2015) reviewed seven published studies investigating the differences in executive functioning of adult male prisoners versus adult men who had no criminal history. They found that prisoners’ performances were significantly poorer than the comparison sample on tasks measuring attention and set-shifting.

Poor executive functions have been identified as a risk factor for recidivism amongst incarcerated samples (Hancock et al., 2010; Ross & Hoaken, 2011; Valliant et al., 2003) with deficits in areas of planning, mental flexibility, problem-solving, memory and inhibitory control found to be most associated with re-convictions (Meijers et al., 2017; Roszyk et al., 2013; Seruca & Silva, 2015). There is also evidence that executive function problems may impair incarcerated offenders’ ability to respond to rehabilitative programmes as measured by treatment readiness, responsivity, programme completion and behaviour improvement (Fishbein et al., 2009). Amongst incarcerated offenders, those who drop out of treatment programmes have poorer inhibitory control (Fishbein et al., 2009) and poorer attention skills (Cornet et al., 2015), and score lower on memory tasks (Overend, 2011) than those who complete treatment programmes. In fact, treatment attrition is better predicted by attention measures than by motivation to change (Cornet et al., 2015). Findings also indicate that offenders who are unable to shift their thinking or responses based on novel information struggle to meet treatment objectives (Fishbein et al., 2009); higher scores on attention and memory tasks predict achievement of treatment objectives (Overend, 2011). Taken together, this body of research suggests that executive dysfunction may play a role in the successful rehabilitation of an incarcerated individual. However, the importance of executive functioning relative to compliance outcomes amongst offenders while serving non-custodial sentences (i.e. community-based sentences) has received little attention.

Offenders who serve sentences or portions of their sentences in the community – referred to here as supervisees – have a mix of requirements based on their offence and sentence type (e.g. parole, intensive supervision, supervision). In New Zealand, all supervisees are given standard conditions that include reporting to a probation officer, advising the probation officer of changes in residence or employment and attending any correctional programme recommended by the probation officer (Corrections, 2016). Depending on the sentence, supervisees may have additional special conditions, including electronic monitoring, curfews, non-association requirements and prohibitions of substance or alcohol use (Corrections, 2016). Violating a standard or special condition of a supervision sentence is defined as non-compliance (Bottoms, 2001). Non-compliance with the requirements of community-based sentences can impose a substantial social and monetary burden on the community and the supervisee, particularly when it results in incarceration (Liebling & Maruna, 2013). Executive functions enable individuals to engage effectively in purposeful and self-directed behaviour (H. D. B. Lezak et al., 2004), which are likely important competencies for successful compliance with a supervision sentence. Thus, those who serve sentences in the community and present with executive dysfunction may have difficulties complying with sentence conditions and benefitting from rehabilitative programmes that are part of the sentence (Ross & Hoaken, 2011).

In a recent study, community-based sentenced perpetrators of interpersonal violence against women who performed poorly on cognitive flexibility measures had higher rates of treatment attrition and recidivism than perpetrators with better cognitive flexibility performance (Romero-Martínez et al., 2021). The findings suggest that offenders in the community who are unable to adapt behaviour or thinking in response to changing situations are likely not engaging or benefitting from programmes aimed at rehabilitation, which then leads to cycling back into the system (i.e. recidivism). Executive function deficits could also make compliance with other conditions of a sentence such as reporting to probation or non-association or curfews difficult. However, findings from one study that investigated compliance with the conditions of a supervised sentence as opposed to treatment compliance found that scores on traditional performance-based executive functioning tests (Colour Word Inference Test and the Trail Making) – which include a measure of cognitive flexibility – were not significantly different between those who were non-compliant and those who were compliant with conditions of their sentence or re-arrest (Norman, Starkey, & Polaschek, 2021). Like most previous studies, Norman, Starkey, and Polaschek (2021) used performance-based measures of executive function. Traditional measures of executive function have low ecological validity (Chan et al., 2008; Gioia & Isquith, 2004), and individuals who do not display impairment on traditional executive function tasks still may encounter difficulties in everyday duties that require executive control, which may in turn influence adherence to the requirements of a community-based supervision sentence (e.g. attending appointments). A limited number of studies have utilized more ecologically valid tools (e.g. the Behavior Rating Inventory of Executive Function–Adult Version, BRIEF–A; Roth et al., 2005) to assess executive function amongst offenders.

The BRIEF–A (Roth et al., 2005) is an ecologically valid measure of nine domains of executive function that asks participants to rate difficulties with everyday activities (see Method section for more details). Brunton and Hartley (2013) used the BRIEF–A to measure the overall executive functioning of incarcerated adult male offenders (n = 30). The study aimed to explore whether executive function predicted changes in antisocial behaviour as measured by the Adult Behaviour Checklist (ABCL; Achenbach et al., 2003) following a treatment intervention (Enhanced Thinking Skills; ETS) designed to reduce antisocial behaviours. Participants’ antisocial behaviour scores were lower after completion of the intervention, and those participants with poorer executive functioning prior to the intervention showed more considerable reductions in antisocial behaviour scores (i.e. ABCL scores) following ETS. In addition, the authors compared their sample’s scores with that of the BRIEF–A normative sample and did not find any significant difference in overall executive functioning (Brunton & Hartley, 2013). However, the study had a small sample size (n = 30) and only included offenders capable of completing a treatment programme.

In contrast, Sánchez de Ribera et al. (2020) found that adult male incarcerated offenders (n = 334) obtained significantly higher (i.e. poorer executive functioning) BRIEF–A scores than the normative sample in all domains (apart from initiate), indices and overall global score (Global Executive Composite; GEC). Recidivist offenders had significantly more widespread executive dysfunction in several domains (inhibition, emotional control, self-monitor, plan/organize and task monitor) and in the behavioural regulation index and GEC than first-time offenders (Sánchez de Ribera et al., 2020). The studies demonstrate that more ecologically valid measures can be used in offender samples and indicate they are related to variables predictive of outcomes such as recidivism. However, the research utilizing these tools is limited and, as of this writing, only involves incarcerated samples.

More studies using measures to detect real-life difficulties with the planning, organization and emotional regulation not easily identified using traditional measures are needed (Barbosa & Monteiro, 2008). While studies have looked at treatment attrition and reoffending, to our knowledge, no published studies have evaluated the relationship between the self-reported executive functioning of individuals serving community-based sentences and compliance with the general conditions of their supervision order. Consequently, little is known about whether problems with executive function manifest into difficulties complying with conditions of a supervised community sentence. In the present study, we explore the association between executive function and compliance by asking a sample of supervisees on community-based sentences to complete the BRIEF–A. We also interviewed their probation officer, and retrieved their compliance data for a six-month period from probation officer notes located in the New Zealand Corrections data system. The aims of this study were: (a) to describe the self-reported executive functioning of individuals who served a criminal sentence in the community in comparison to a normative sample and (b) to determine whether there was an association between executive functioning and compliance with community-based sentence conditions. We hypothesized that community-based offenders would report significantly poorer executive functioning in all areas than the normative sample. We also hypothesized that poorer executive functioning would be related to non-compliance.

Method

Study design and setting

Individuals serving community-based sentences (supervisees) were recruited from two community probation sites in the North Island of New Zealand during a 6-month period (February–August) in 2019. Supervisees met the criteria to participate in the study if they were serving a community-based sentence of six months or more that included a requirement of supervision by a probation officer and were proficient in spoken English. There were two parts to this study, a semi-structured interview and a neuropsychological assessment session. Additional eligibility criteria for the neuropsychological portion of the study were that the participant had not left school before the age of 11 years old and did not report any neurodevelopmental disorders or hearing or sight impairment that would impede their ability to complete the neuropsychological assessments. The focus of this paper is the data from the self-report executive function inventory.

Participants

The participants’ demographic characteristics are presented in Table 1. Supervisees (n = 64; 47 men and 17 women) had a mean age of 37.42 years. The majority of the sample identified as New Zealand Māori (n = 45, 70%); 16 (25%) participants identified as New Zealand European, and one each (n = 3, 5%) identified as Samoan, Indian and Australian, respectively. Thirty-seven (58%) were serving a community supervision order following a term in prison (i.e. parole), and 27 (42%) were serving a community-based sentence only (i.e. no term in prison for the current offence). We divided the supervisees into groups based on their compliance with sentence conditions to compare those with at least one incident of non-compliance (n = 37) with those with no incidents of non-compliance (n = 27).

Table 1.

Supervisee demographic and criminal justice characteristics.

Variable Total sample
(n = 64)		 Compliant
n = 27 (42%)		 Non-compliant
n = 37 (58%)		 t(63)/Ua χ²(62) p d 95% CI
Gender n (%)                
 Men 47 (73.44) 19 (70.40) 28 (75.70)   0.23 .64    
 Women 17 (26.56) 8 (29.60) 9 (24.30)          
Ethnicity n (%)                
 Māori 45 (70.31) 16 (59.30) 29 (78.40)   5.32 .07    
 European 16 (25.00) 8 (29.60) 8 (21.60)          
 Other 3 (4.69) 3 (11.10) 0 (0.00)          
Agea (years) M (SD) 37.42 (10.75) 39.74 (11.94) 35.73 (9.60) 410.00   .22 0.38 [–0.13, 0.88]
Number of special conditionsa M (SD) 4.73 (3.28) 5.56 (3.74) 4.14 (2.80) 397.50   .16 0.44 [–0.06, 0.94]
Substance use n (%) 24 (37.50) 12 (44.40) 12 (32.40)   0.96 .33    
Mental health n (%) 36 (56.30) 17 (63.00) 19 (51.40)   0.86 .36    
Received additional supports to comply n (%) 27 (42.20) 12 (44.40) 15 (40.50)   0.10 .76    
Supervision order n (%)         1.50 .22    
 Parole 37 (57.80) 18 (66.70) 19 (51.40)          
 Community sentence 27 (42.20) 9 (33.30) 18 (48.60)          
RoC*RoIa M (SD) .34 (.24) .32 (.25) .36 (.23) 559.50   .41 –0.15 [–0.65, 0.35]
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Note: RoC*RoI = actuarial risk of re-conviction/re-imprisonment (low = .00–.40, medium = .41–.70, high = .71–1.00). CI = confidence interval.

aVariables are not normally distributed so non-parametric test statistic (Mann–Whitney U) is reported.

Procedure

During meetings with the primary researcher, probation officers were informed about the general purpose of the research project and were asked to pass on information about the study during routine reporting with their supervisees. If supervisees indicated they were interested, the probation officer introduced the primary researcher to the potential participant. The probation officer then left the meeting room. The primary researcher read the information sheet to the potential participant and asked whether they had any questions and agreed to continue with the study. The first author gained informed consent from participants who agreed to participate, which included consent to access their information in the New Zealand Corrections’ electronic database (the Integrated Offender Management System, IOMS) and to interview their probation officer regarding their sentence compliance. Participants participated in an initial interview that included questions regarding demographics, psycho-social history and current sentence compliance. Supervisees returned for a second session during which they completed various neuropsychological tests and the BRIEF–A, a self-report inventory of executive functioning. The researcher read each of the questions from the BRIEF–A to the participant, who responded verbally to each question.

Sources of information

Executive functioning

The BRIEF–A (Roth et al., 2005) is a self-report inventory that asks 75 questions designed to capture real-world manifestations of executive functioning to determine current functioning. The BRIEF–A generates an overall score (Global Executive Composite, GEC), which is the composite of two index scales (the Behavioral Regulation Index, BRI, and the Metacognitive Index, MI). The BRI includes four scales (inhibit, shift, emotional control and self-monitor), and the MI includes five scales (initiate, working memory, plan/organize, task monitor and organization of materials).

Participants rated how often each of the 75 items has been a problem in the past month using a 3-point Likert scale (1 = never, 2 = sometimes, or 3 = often; Roth et al., 2005). Raw scores were converted into standardized age-adjusted t scores (M = 50, SD = 10). Higher scores indicate a greater degree of dysfunction; t scores ≥1.5 standard deviations above the mean (≥65) are considered to indicate clinical impairment (Roth et al., 2005). The BRIEF–A includes three validity scales measuring negativity, infrequency and inconsistency. Participants were excluded from analysis if they scored above the cut-off on any validity scales. The self-report questionnaire took no more than 20 minutes to complete.

Criminal justice data

We extracted data about the participants’ current offences, type of supervision order (i.e. following a term in prison or community sentence only), arrests while on sentence, number of special conditions and actuarial risk of re-imprisonment for a new conviction (RoC*RoI; Bakker et al., 1999) from the IOMS: a New Zealand Corrections’ electronic database. The RoC*RoI is used in New Zealand by the Department of Corrections to estimate an offender’s actuarial risk over the next five years in the community of a re-conviction that results in re-imprisonment. The score is generated by a computer algorithm based on criminal history and demographic variables. The score is expressed as a probability and ranges from 0 to 1. Studies have demonstrated the RoC*RoI’s predictive validity (Bakker et al., 1999).

Other information gathered from probation officers’ notes in IOMS included the supervisees’ substance use or mental health issues. The primary researcher also reviewed probation officers’ documentation of non-compliance in IOMS for a 6-month period – typically the three months prior to entering the study and the three months post entering the study – for each participant. We created a dichotomous variable to identify those with one or more incidents of non-compliance and those without (1 = non-compliant, 0 = compliant). Non-compliance was counted regardless of whether any action was taken by the probation officer (i.e. warnings, sanctions, formal charges).

Semi-structured interview with probation officer

We asked probation officers open-ended questions about each of the supervisees on their caseload who participated in the study, including issues around compliance with their current sentence (e.g. barriers to compliance, incidents of non-compliance) and any strategies the probation officer used to support the particular supervisee’s compliance with sentence conditions.

We coded probation officers as ‘providing additional supports’ when they described utilizing other strategies – such as text reminders, actively involving supervisees’ support people, modifying the implementation of sentence conditions – to support the compliance of the supervisee being discussed. A dichotomous code was created, with 1 representing ‘additional supports’ and 0 indicating ‘no additional supports’ provided. Based on guidelines on selecting and reporting intraclass correlations (Koo & Li, 2016), all three authors coded for 30 of the 64 cases whether the probation officer reported using additional strategies to support the compliance of a particular supervisee. To measure the inter-rater reliability of the ‘additional supports’ variable between the three reviewers, the single measures intraclass correlation coefficient (ICC) and 95% confidence intervals (CIs) were calculated, using absolute agreement and a two-way mixed-effects model. The resulting ICC of .79 (95% CI [.65, .89]) demonstrated moderate to good inter-rater reliability between the three authors on the ‘additional supports’ variable.

Data preparation and planned analyses

We entered data into SPSS 27 for statistical analysis. Prior to any analysis, we performed Kolmogorov–Smirnov and Shapiro–Wilks tests on the variables to test for normal distributions. We used non-parametric tests for variables that were not normally distributed (Mann–Whitney U Test).

We conducted descriptive statistics for demographic characteristics and criminal justice variables. Next, we calculated univariate statistics to determine any differences between those who were compliant with their sentence conditions and those who were not on each variable to establish whether any other co-variates were associated with compliance.

We used single-sample t tests to compare our community sentenced sample with the BRIEF–A normative sample (Roth et al., 2005). Then we calculated independent-sample t tests to compare those supervisees who were compliant with their sentence conditions and those supervisees who were not on the scores for the nine domains, two indices and global score of the BRIEF–A. For each participant, we counted the number of domains in which they scored in the clinical impairment range (i.e. ≥65) and performed independent-sample t tests to compare those supervisees who were compliant with their sentence conditions and those supervisees who were not on the number of domains in clinical impairment range. We estimated effect sizes for the univariate analysis by means of Cohen’s d (Cohen, 1988), and the 95% confidence intervals around the effect size estimates were also computed (Cumming, 2013). Using Cohen’s criteria, we described these effect sizes qualitatively as small (0.20), medium (0.50) and large (≥0.80).

Results

Demographic and criminal justice characteristics

Table 1 shows the descriptive statistics, demographic and criminal justice characteristics, for the sample overall and for those supervisees who were and were not compliant with their sentence conditions. Over half the sample had a mental health diagnosis, and over a third had a substance use problem identified by the probation officer. Just under half received additional supports from their probation officers to comply with their sentence conditions. Overall, this sample was at low risk for re-conviction/re-imprisonment based on RoC*RoI scores.

On average, sample members’ sentences included 4.73 special conditions in addition to the standard conditions. Thirty-seven supervisees were non-compliant at least once, with some supervisees having multiple incidents and types of non-compliance during the six-month review period. Failure to report to the probation officer was the most common non-compliant activity; 95% (n = 35) of non-compliant supervisees violated this condition. Other acts of non-compliance included curfew violations, alcohol/substance use violations, failure to attend a programme, non-association violations and not advising the supervising probation officer of an address change. Analyses showed no significant differences or associations between those who were compliant and those who were non-compliant regarding demographic or criminal justice variables described in Table 1.

Executive functioning of the community sentenced sample versus the normative sample

Table 2 presents executive function scores (from the BRIEF–A) of the supervisees’ and the normative sample (Roth et al., 2005). The supervisees obtained significantly higher mean scores (indicative of poorer executive function), with large effect sizes across all domains and indices compared to the normative sample, with the exception of organization of materials. On average, supervisees’ mean scores were above the cut-off indicative of clinical impairment (i.e. ≥65) for working memory and were very close to the cut-off for clinical impairment for inhibitory control and the behavioural regulation index. In the domains of shift, self-monitor, planning/organizing and the overall global executive composite (GEC), the supervisee sample was at least one standard deviation (SD = 10) above the mean, a difference that would likely result in executive functioning issues that impact day-to-day life (H. D. B. Lezak et al., 2004).

Table 2.

Mean BRIEF–A scores for the current sample and normative sample.

Domains of executive functioning Current sample
(n = 64)
M (SD) 		Normative sample
(n = 377a)
M (SD) 		t(63) p d 95% CI
Behavioral Index 64.31 (10.28) 50.00 (10.00) 11.14 <.001 1.39 [1.05, 1.73]
 Inhibitory control 64.89 (9.24) — 12.00 <.001 1.50 [1.14, 1.86]
 Shift 61.14 (9.53) — 9.35 <.001 1.17 [0.85, 1.49]
 Emotional control 59.83 (10.27) — 7.66 <.001 0.96 [0.66, 1.25]
 Self-monitor 63.83 (12.02) — 9.20 <.001 1.15 [0.83, 1.46]
Metacognition Index 59.66 (10.04) — 7.69 <.001 0.96 [0.66, 1.27]
 Initiate 57.66 (10.63) — 5.76 <.001 0.72 [0.44, 0.99]
 Working memory 65.59 (11.72) — 10.65 <.001 1.33 [0.99, 1.67]
 Planning/organizing 62.50 (12.00) — 8.33 <.001 1.04 [0.73, 1.34]
 Task-monitor 59.09 (9.28) — 7.84 <.001 0.98 [0.68, 1.28]
 Organization of materials 50.11 (9.36) — 0.09 .93 0.01 [–0.23, 0.25]
Global executive composite 62.62 (10.31) — 9.80 <.001 1.22 [0.90, 1.55]
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Note: M = 50, SD = 10; clinical impairment range ≥ 65. BRIEF–A = Behavior Rating Inventory of Executive Function–Adult Version (Roth et al., 2005); CI = confidence interval.

aThe original normative sample from the BRIEF–A is n = 525; we excluded age groups 70–79 years (n = 70) and 80–90 years (n = 78) because our sample did not include participants older than 65 years.

Executive functioning of compliant versus non-compliant supervisees

Table 3 presents the differences in mean scores on the BRIEF–A between those supervisees who were and those who were not compliant with sentence conditions. Compliant supervisees obtained higher scores – indicating poorer functioning – in all the domains and indices on the BRIEF–A than those who were non-compliant. Supervisees who were compliant obtained means scores in the clinical impairment range (i.e. ≥65) in three domains (inhibitory control, self-monitor, working memory), on the behavioural regulation index and on the overall GEC measure. On average, supervisees who were non-compliant did not score in the clinical impairment range on any of the indices or domains. However, in some domains – inhibitory control, shift, self-monitor, working memory, planning/organizing – and on the BRI index and GEC, the scores were above 60 (i.e. 1 SD above the mean). Analyses revealed that those who were compliant had significantly higher mean scores, with medium effect sizes, in three areas of executive functioning – initiate, task-monitor and organization of materials – than those supervisees who were non-compliant.

Table 3.

Mean BRIEF–A scores for supervisees who were compliant versus non-compliant with sentence conditions.

Domains of executive functioning Compliant
(n = 27) M (SD) 		Non-compliant (n = 37) M (SD) t(63) U p d 95% CI
Behavioral Index 66.04 (11.22) 63.05 (9.49) 1.15   .26 0.29 [–0.21, 0.79]
 Inhibitory control 67.48 (9.67) 63.00 (9.81) 1.82   .07 0.46 [–0.05, 0.96]
 Shift 61.78 (10.43) 60.68 (8.93) 0.45   .65 0.12 [–0.38, 0.61]
 Emotional control 60.70 (10.96) 59.19 (9.84) 0.58   .56 0.15 [–0.35, 0.64]
 Self-monitor 66.19 (11.48) 62.11 (12.27) 1.35   .18 0.34 [–0.16, 0.84]
Metacognition Index 62.41 (11.00) 57.65 (8.91) 1.91   .06 0.48 [–0.02, 0.99]
 Initiate 61.44 (11.26) 54.89 (9.35) 2.54   .01 0.64 [0.13, 1.15]
 Working memorya 66.74 (12.36) 64.76 (11.33)   446.50 .51 0.17 [–0.33, 0.67]
 Planning/organizing 64.56 (12.73) 61.00 (11.38) 1.17   .25 0.30 [–0.20, 0.80]
 Task-monitora 62.33 (8.86) 56.73 (8.96)   321.50 .02 0.62 [0.12, 1.13]
 Organization of materialsa 52.96 (10.11) 48.03 (8.30)   348.50 .04 0.54 [0.04, 1.05]
Global executive composite (GEC) 65.26 (11.22) 60.70 (9.29) 1.78   .08 0.45 [–0.06, 0.95]
Total number of domains in the clinical impairment range 4.00 (3.08) 2.86 (2.56) 1.61   .11 0.41 [–0.10, 0.91]
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Note: M = 50, SD = 10; clinical impairment range ≥ 65. BRIEF–A = Behavior Rating Inventory of Executive Function–Adult Version (Roth et al., 2005); CI = confidence interval.

aResults were not normally distributed, so non-parametric test statistic (Mann–Whitney U) is reported.

We undertook further analyses to explore why, contrary to expectations, non-compliant supervisees obtained lower scores on the BRIEF–A, indicating better executive function. Researchers of compliance with community-based sentence conditions have suggested that probation officers’ case-management strategies (e.g. relationship building, modifying condition requirements, text reminders) influence the compliance of supervisees (Blasko et al., 2015; Norman, Wilson, et al., 2021; Ostermann & Hyatt, 2020). In fact, in a study that found no differences in the executive functioning of compliant and non-compliant supervisees with intellectual disabilities, the authors conjectured these results were because the probation officers’ management of the supervisees lessened the impact of executive dysfunction on compliance outcomes (Mason & Murphy, 2002). Thus, we investigated whether supervisees who received additional supports to comply had significantly different executive functioning from those supervisees who did not receive additional supports to comply.

The BRIEF–A scores comparing those supervisees who did and did not receive additional support from their probation officers are presented in Table 4. Supervisees who received additional support to comply obtained significantly higher scores (indicating more dysfunction) on the domains of inhibitory control, initiate, working memory, planning/organizing, organization of materials and the metacognition index and the GEC than those who did not, with medium to large effect sizes. Those with additional supports to comply scored in the clinically impaired range in significantly more domains than those without additional supports to comply, producing a medium effect size.

Table 4.

Mean BRIEF–A scores for supervisees who did and did not receive additional support to comply from the probation officer.

Variable Additional support n = 27
M (SD)		 No additional support n = 37
M (SD)		 t(63) U p d 95% CI

Behavioral Index 66.04 (9.73) 63.05 (10.61) –1.15   .26 –0.29 [–0.79, 0.21
 Inhibitory control 67.93 (9.60) 62.68 (9.68) –2.15   .04 –0.54 [–1.05, –0.37]
 Shift 62.89 (9.67) 59.86 (9.35) –1.26   .21 –0.32 [–0.82, 0.18]
 Emotional control 59.22 (10.10) 60.27 (10.51) 0.40   .69 0.10 [–0.40, 0.60]
 Self-monitor 67.19 (11.67) 61.38 (11.83) –1.95   .06 –0.49 [–1.00, 0.01]
Metacognition Index 63.74 (9.07) 56.68 (9.77) –2.94   .01 –0.75 [–1.26, –0.23]
 Initiate 61.48 (9.94) 54.86 (10.36) –2.57   .01 –0.65 [–1.16, –0.14]
 Working memorya 69.37 (9.63) 62.84 (12.44)   677.50 .02 –0.58 [–1.08, –0.07]
 Planning/organize 68.19 (10.27) 58.35 (11.57) –3.52   <.001 –0.89 [–1.41, –0.37]
 Task-monitora 61.04 (8.99) 57.68 (9.35)   597.00 .18 –0.37 [–0.86, 0.14]
 Organization of materialsa 54.37 (10.08) 47.00 (7.50)   732.50 .002 –0.85 [–1.36, –0.33]
Global executive control 66.15 (9.71) 60.05 (10.10) –2.42   .02 –0.61 [–1.12, –0.10]
Total number of domains in the clinical impairment range 4.22 (2.36) 2.70 (2.99) –2.19   .03 –0.55 [–1.05, –0.05]
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Note: M = 50, SD = 10; clinical impairment range ≥ 65. BRIEF–A = Behavior Rating Inventory of Executive Function–Adult Version (Roth et al., 2005); CI = confidence interval.

aVariables are not normally distributed, so non-parametric test statistic (Mann–Whitney U) is reported.

Discussion

The main purpose of this study was to assess the self-reported executive functioning of individuals who served a criminal sentence in the community compared to a normative sample and to determine whether there was an association between executive functioning and compliance with community-based sentence conditions. In addition, we examined differences between those supervisees who were compliant with their sentence conditions and those who were not on a variety of demographic and criminal justice characteristics. We found no significant differences between those supervisees who were compliant with their sentence conditions and those not on demographic and criminal justice characteristics. Compared to the BRIEF–A normative sample, our community-based sample had significantly poorer executive function in all domains, apart from the organization of materials domain. In contrast to our expectations, non-compliant supervisees reported better executive functioning in the domains of initiate, task-monitor and organization of materials than the compliant group. Our findings failed to support the hypothesis that non-compliant supervisees would report poorer executive functioning than those who were compliant. Further analysis found that those supervisees who received additional support to comply from their probation officer had significantly poorer executive functioning in the areas of inhibitory control, initiate, working memory, planning/organizing, organization of materials, and the metacognition index and the GEC than those supervisees who did not receive additional support to comply.

In sum, our study did not find that executive dysfunction was associated with non-compliance with sentence conditions amongst individuals serving community-based sentences. Instead, our findings indicate that executive dysfunction – in several of the domains – was related to receiving additional support from the supervising probation officer, suggesting that the impact of executive dysfunction on compliance outcomes may be compensated for by probation officers’ support. In our study, on average, supervisees without additional supports to comply obtained scores in the non-clinical range (i.e. less than 1.5 SDs above the normative mean of 50) in all domains and indices. Meanwhile, supervisees who received additional supports to comply obtained scores in the clinical impairment range in four domains – inhibitory control, self-monitor, working memory, planning/organizing – and the behavioural index and GEC. Supervisees with these executive impairments (inhibitory control, self-monitor, working memory, planning/organizing) are likely to have difficulties with, for example, appreciating how one’s behaviour impacts others, following complex instructions, setting goals and consuming large amounts of information, each of which presumably affects day-to-day functioning (Roth et al., 2005), and research has shown is related to recidivism (Meijers et al., 2017; Roszyk et al., 2013; Seruca & Silva, 2015). Our findings support previous speculations that probation officers who supervise those with cognitive deficits detect and compensate for the difficulties experienced by the supervisee, potentially influencing compliance with sentence conditions outcomes (Mason & Murphy, 2002).

Probation officers’ effectiveness in ensuring compliance lies in their ability to be flexible and meet the supervisee’s complex needs (Barklage et al., 2006), which in some cases includes cognitive problems. However, cognitive problems can pose a substantial obstacle to overcoming offending behaviours and being successful on a sentence. Studies show that cognitive problems are associated with treatment attrition and reoffending for those receiving rehabilitative services in the community (Romero-Martínez et al., 2021), which suggest that these individual level cognitive factors are important responsivity issues for offenders in the community. In New Zealand, probation officers have reported that supervisees who display poor cognitive skills in areas including planning, memory and problem-solving have difficulties understanding and abiding by sentence conditions, including participating in required correctional interventions (Norman, Wilson, et al., 2021). In cases where a supervisee is viewed as having cognitive problems, some probation officers have described utilizing different strategies such as text message reminders and even referring the sentence back to the court to support sentence compliance (Norman, Wilson, et al., 2021). These reports from probation officers parallel research that has suggested that amongst incarcerated offenders, poorer functioning in planning, problem-solving, memory and inhibitory control are associated with re-convictions (Meijers et al., 2017; Roszyk et al., 2013; Seruca & Silva, 2015), and executive dysfunction is associated with decreased treatment readiness, responsivity and completion (Fishbein et al., 2009). Indeed, dysfunction in inhibitory control and self-monitor are argued to underlie criminogenic risks such as substance use and poor academic or career achievement (Cheng et al., 2019), and neuropsychological functioning has been raised as a responsivity issue in the criminal justice literature (Dowden & Andrews, 2004). The probation officers’ role is to promote compliance and address offending-related needs to reduce recidivism. Our study suggests that probation officers can identify supervisees with problems related to poor executive function that without additional support could hamper compliance.

Consistent with studies that include incarcerated samples (Sánchez de Ribera et al., 2020), our sample reported poorer executive functioning on each of the BRIEF domains and indices, apart from organization of materials, than the normative BRIEF sample. Half the sample obtained scores that met the clinical cut-offs for impairment in inhibitory control and self-monitor. In addition, nearly half of the sample obtained scores that suggest impairment in working memory and planning/organizing. These results indicate that a number of supervisees in the community have executive function problems that are potentially compromising their ability to comply. However, it is difficult to draw any conclusions concerning probation officer support, other than that probation officers utilize additional supports in an effort to ensure compliance, likely influencing compliance outcomes.

Implications

Our findings indicate that individuals serving community sentences have significantly poorer executive functioning than normative samples. In addition, while our results regarding executive functioning and compliance were the opposite to what we had predicted, our exploratory analysis suggests that this unexpected pattern may result from probation officers offering additional support to supervisees with poorer executive functioning to improve compliance. While responsiveness is necessary, where the priority is to ensure compliance rather than engagement in change or addressing offending-related needs, the efforts may be futile. Corrections departments need to invest in developing services that offenders with cognitive problems can engage with and learn from, along with training and support for probation officers who manage these needs. For instance, it may be worthwhile to integrate assessment and skill building of executive functioning into probation services and training as part of the responsivity principle of the risk needs and responsivity model of offender assessment and rehabilitation (Bonta & Andrews, 2016). In addition, assessment of executive function and cognitive skills would help probation officers provide the appropriate support to those with specific areas of dysfunction. For example, using a self-report measure such as the BRIEF–A could be a helpful, cost effective and time-efficient screening instrument for corrections departments to adopt. Community corrections is an alternative to prison. Reducing non-compliance through increased responsivity practices can help eliminate entrapping people in the criminal justice system and increasing prison populations.

Future research

Our study indicates that many individuals serving community-based sentences have executive function problems. We suggest further research into how specific probation officer practices used to support supervisees with executive dysfunction are related to compliance, perhaps looking into how specific areas of dysfunction elicit specific strategies to ensure compliance. These additional supports could then become part of training and practice. It would be worthwhile for future research to investigate how specific deficits create barriers to engaging with and benefiting from the services, programmes or treatments offered by corrections. Findings from such research will have important policy and practice implications for probation services and quality of life implications for offenders.

Study limitations

In terms of generalizing our results to other community-based correctional clients, limitations include (a) the small and non-representative nature of the sample; it is unlikely that the results are representative of all New Zealand community-based sentenced offenders (e.g. employed people were less likely to be available for recruitment); (b) comparison with the BRIEF–A normative sample, which is a United States sample and thus does not match the characteristics of a New Zealand population; and (c) the use of compliance with sentence conditions being a difficult variable to assess because there may be variability in the compliance information recorded by the probation officers (Sorsby et al., 2017).

Conclusions

In conclusion, despite the established association between poor executive function and antisocial behaviour, very little research has focused on exploring the impact of supervisee executive function on compliance with conditions of a supervised community-based sentence. This study expands on the small previous literature in this area by demonstrating that executive function amongst community-based offenders is significantly poorer than in a normative sample. Furthermore, probation officers appear to provide additional support to those supervisees with poorer executive functioning. Although more research is needed, our study signals that probation officers’ behaviours are a mechanism influencing compliance and that supervisees who have cognitive difficulties are helped by additional support and individualized management. These findings suggest that offenders’ executive functioning needs to be considered by correctional services in their management of offenders to avoid punitive consequences, including imprisonment, for non-criminal acts (e.g. failing to report). Information on the supervisee’s neuropsychological abilities can lead to more effective and efficient sentence management, including developing strategies that assist the supervisee in successfully engaging with and learning from their sentence conditions.

Ethical standards

Declaration of conflicts of interest

Emily M. Norman has declared no conflicts of interest

Devon L. L. Polaschek has declared no conflicts of interest

Nicola J. Starkey has declared no conflicts of interest

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee [University of Waikato Human Ethics Committee, HREC(Health) 2018#69] and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study

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