Dersleri yüzünden oldukça stresli bir ruh haline sikiş hikayeleri bürünüp özel matematik dersinden önce rahatlayabilmek için amatör pornolar kendisini yatak odasına kapatan genç adam telefonundan porno resimleri açtığı porno filmini keyifle seyir ederek yatağını mobil porno okşar ruh dinlendirici olduğunu iddia ettikleri özel sex resim bir masaj salonunda çalışan genç masör hem sağlık hem de huzur sikiş için gelip masaj yaptıracak olan kadını gördüğünde porn nutku tutulur tüm gün boyu seksi lezbiyenleri sikiş dikizleyerek onları en savunmasız anlarında fotoğraflayan azılı erkek lavaboya geçerek fotoğraflara bakıp koca yarağını keyifle okşamaya başlar

GET THE APP

Differences in Risk Scores among Intrafamilial and Extrafamilial Sexual Offenders | OMICS International
ISSN: 1522-4821
International Journal of Emergency Mental Health and Human Resilience
Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.

Differences in Risk Scores among Intrafamilial and Extrafamilial Sexual Offenders

Holly C. Johnson*, Lee A. Underwood, Linda J. Baum, Mark Newmeyer

Regent University, 1000 University Drive, CRB 215, Virginia Beach, VA 23464, 910 Oakes Blvd, Naples FL, USA

*Corresponding Author:
Holly C. Johnson
Regent University
1000 University Drive
CRB 215, Virginia Beach
VA 23464, 910 Oakes Blvd
Naples FL, USA
E-mail: holljo1@regent.edu

Visit for more related articles at International Journal of Emergency Mental Health and Human Resilience

Abstract

Adult male sexual offenders are not classified easily as they are a heterogeneous population representing all professions, cultures, ethnicities, and ages. These differences make it difficult to categorize offenders into specific groups. This study examined differences between the type of adult sex offender (ie., intrafamilial, extrafamilial, biological) regarding risk scores as measured by the Static-99 and to determine if there were victim age differences for intrafamilial and extrafamilial offenders. The sample comprised 178 adult males and 14 adult females with ages ranging 18-68 years. Participants were selected from archival data of completed sex offender treatment records and specific psychological evaluations performed for individuals mandated for treatment as a condition of probation or parole in an outpatient treatment program in a southeastern state in the United States. Results indicated that intrafamilial offenders were found to have significantly lower risk factors when compared to extrafamilial offenders. No differences in risk were found between intrafamilial and biological offenders. The study also demonstrated that sexual offenders that were closer to the victim in terms of familial status were more likely to have younger victims than those who were non-related. Specifically, the average age for biological offenders was approximately four years younger than that of the extrafamilial offenders while intrafamilial offenders did not differ significantly from either group. Findings, implications, and suggestions for future research are discussed.

Keywords

Sexual offenders, Offender type, Risk factors, Recidivism, Victim age

Introduction

Adult sexual perpetration against children and child abuse is a critical public concern and social problem (Bonnar-Kidd, 2010; Calkins, et al., 2014; Whitaker, Lutzker & Shelley, 2005). Child Protective Services (CPS) substantiated approximately 62,936 child sexual abuse cases in 2012 (U.S. Department of Health and Human Service [USDHHS], 2012) with the majority of the perpetrators against the children being adult offenders (82.2%). Community surveys have demonstrated that five to 20 percent of men admit to at least one act of sexual aggression (Koss, 1987; Lisak & Miller, 2002). On a given day, according to the National Center for Missing & Exploited Children (NCMEC), there are approximately 265,000 sexual offenders supervised by corrections agencies, and more than 747,000 registered sex offenders in the United States. According to contemporary theories, there are various factors that can be related to the development of sexual offending (Knight & Sims-Knight, 2003; Ward & Siegert, 2002). Identification of the characteristics of those who sexually offend against children provides information that may help treatment providers understand the reasoning behind this disturbing behavior (Hanson & Morton-Bourgon, 2005).

Adult male sexual offenders are not easily differentiated from each other as they are a heterogeneous population representing all professions, cultures, ethnicities, and ages (Chaffin, Letourneau & Silovsky, 2002; Herkov, Gynther, Thomas & Myers, 1996). Previous studies have attempted to determine differences in sexual offenders by personality characteristics (Davis & Archer, 2010; Glowacz & Born, 2013) and sexual interest (Banse, Schmidt, & Clarbour, 2010). Some research has found offenders to be a heterogeneous group as a whole, but a homogeneous group in regards to personality characteristics (Armentrout & Hauer, 1978; Panton, 1978; Reijnen, Bulten, & Nijman, 2009; Valliant & Blasutti, 1992). In addition, one study found sexual offenders to be a homogeneous group related to risk factors (Barsetti, Earls, Lalumière, & Bélanger, 1998). Further research examining the homogeneity or heterogeneity of sex offenders in regard to these risk factors (sexual deviance, relationship to victims, etc), as well as other personality characteristics, is needed for more effective assessment and treatment (Helmus, Thornton, Hanson & Babchishin, 2012; Seto, 2008).

There have been many studies that have attempted to gain a better understanding of the sexual offender (Banse et al., 2010; Davis & Archer, 2010; Glowacz & Born, 2013). Because adult male sexual offenders are not found to have a conclusive psychological profile (Ahlmeyer, Kleinsasser, Stoner, & Retzlaff, 2003; Bickley & Beech, 2001), insight into the differences of the types of sex offenders may provide useful information when considering treatment, assessment, and future research (Seto, 2008). The heterogeneity of sexual offenders is commonly recognized, and there is a need to implement treatment programs that consider the specific needs of these different types of sexual offenders (Woessner, 2010). Research regarding treatment for sexual offenders indicates the importance of the offender’s willingness to openly confront factors that motivate and sustain sexual offending behavior (Kear-Colwell & Pollock, 1997; Marshall, 1997; Marshall & Anderson, 2000; Salter, 1988). Because group treatment is a common modality for sexual offender treatment (Hanson et al, 2002), there is a need to understand and to classify offenders based upon characteristics and types in order to provide more effective therapeutic engagement and group the individuals for more efficacious treatment (Helmus et al., 2012; Seto, 2008).

Regardless of the homogeneity or heterogeneity of sex offenders, the information regarding the adult sexual perpetration of children demonstrates that sexual offending is a significant problem. Due to the significance of this problem, attention should be taken to provide effective treatment and to reduce the risk of recidivism within this population (Davis & Archer, 2010). In order to protect individuals from crimes of sexual abuse, understanding characteristics of adult sexual offenders and circumstances surrounding the perpetration of sexual abuse is necessary for the prevention of sexual abuse, provision of treatment, assessment of risk, and reduction of re-offense (Helmus et al., 2012; Kenny & Wurtele, 2012; Seto, Babchishin, & McPhail, 2013).

Distinctions between Sexual Offenders

Sexual offenses that may be considered criminal acts can be categorized in several ways including sexual acts with contact, noncontact sexual behavior, and incidents related to pornography (Terry, 2013). Contact sexual offenses can include sexual assault and rape (Terry, 2013). Sexual assault is “any type of sexual contact or behavior that occurs without the explicit consent of the recipient” (U. S. Department of Justice, 2012) and is differentiated from rape (Terry, 2013). Non-contact sexual offenses that are commonly considered to be criminal actions include pornography related incidents, acts of voyeurism, and exhibitionism (Terry, 2013).

Sexual offenders can be described by using the offenses that are committed including sexual assault, rape, child molestation, exhibitionism, and possession of child pornography (“Sexual Abuse”, 2007; Woessner, 2010). Within this broad range, there have been efforts to differentiate offenders into subgroups for effective treatment and reduction of recidivism (Woessner, 2010). Due to the heterogeneity and diversity of personality characteristics of the population of sexual offenders, there is no specific offender profile that is evidenced by research (Chaffin et al., 2002). Understanding the differences in types of sexual offenders provides beneficial information for assessing risk, providing treatment, and guiding future research (Helmus et al., 2012; Seto, 2008; Williams & Finkelhor, 1990).

Questions exist as to the similarity and differences between intrafamilial and extrafamilial sexual abuse (Conte, 1991; Finkelhor, 1984). Although research has shown that intrafamilial and extrafamilial offenders use similar schemes to establish a strategy for sexual activity with children (Lang & Frenzel, 1988), it is important to review distinctions between these two groups of offenders (Abel, Becker, & Cunningham-Rathner, 1984). Knowledge of any potential distinctions between these types of offenders may provide insight regarding treatment efficacy for clinicians who work with this population (Abel et al., 1984).

Intrafamilial Offenders

Miner and Dwyer (1997) classify intrafamilial sexual offenders as individuals who sexually violate children who are related biologically or by marriage. Research has demonstrated that male and female children are more likely to be sexually abused by someone known rather than by a stranger (Finkelhor, Hammer, & Sedlak, 2008; Rennison & Rand, 2003). Intrafamilial sexual abuse generally occurs within the family home (Faller, 1989) by a trusted family member in authority over the victim (Atwood, 2007). Research indicates that intrafamilial offenders generally have lower pedophilic interest than other offenders (Greenberg, Firestone, Nunes, Bradford, & Curry, 2005; Seto et al., 2015).

Biological Parent Offender

Sexual assault by a father against his biological child is the most frequent case of alleged incest on children and adolescents (Gomes, Jardim, Taveira, Dinis-Oliveira, & Magalhães, 2014). This type of abuse generally takes place inside the victim’s home and is often accompanied with verbal and physical threats to prevent disclosure (Gomes et al., 2014). This type of abuse is generally less physically invasive and forceful than in extrafamilial cases; however, the abuse is more emotionally intrusive when the perpetrator is a biological father (Finkelhor, 1994). The familial relationship may lead to delays in the disclosure and/or detection of the abuse. The victims of abuse by a biological parent are generally known to be females with the father as the perpetrator (Finkelhor, 1994). Males are less likely to experience intrafamilial offense, but when it occurs it is generally perpetrated by a female offender (Finkelhor & Hotaling, 1984).

Other Intrafamilial Offenders

Intrafamilial abuse is abuse by a relative including a non-biological step-parent (Bolen, 2001). Although intrafamilial abuse is commonly perpetrated by a parent, the abuse also occurs with some regularity by siblings, uncles, and cousins (Bolen, 2001) and with less regularity by grandfathers and other male relatives (Bolen, 2001). These offenders generally have lower rates of recidivism than extrafamilial offenders (Furr, 1993; Greenberg, Bradford, Firestone, & Curry, 2000; Hanson, Steffy, & Gauthier, 1993; Studer, Clelland, Aylwin, Reddon, & Munro, 2000; Quinsey, 1986). Intrafamilial abuse generally occurs for a longer duration than extrafamilial abuse, and victims are on average three years younger when the abuse begins (Fischer & McDonald, 1998; Kuznestov & Pierson, 1992).

Extrafamilial Offenders

Extrafamilial or non-familial offenders are classified as those who violate children who are not related biologically or by marriage (Larsen, Hudson, & Ward, 1995; Miner & Dwyer, 1991). Extrafamilial abuse is primarily perpetrated by acquaintances, friends of the family, authority figures, strangers, friends, and dates, and this type of sexual abuse generally occurs outside the family home in educational, day care, recreational and religious settings (Faller, 1989). Research reports extrafamilial offenders to have higher rates of recidivism than familial offenders (Hanson & Bussière, 1998; Larsen et al., 1995; Prentky, Knight, & Lee, 1997). Extrafamilial offenders are viewed as more prevalent, accounting for 70% of the abuse cases against children or adolescents (Bolen, 2001). Research demonstrates that these offenders have a greater number of interpersonal problems than their intrafamilial counterparts (Firestone et al., 2000). Extrafamilial abusers are more likely than intrafamilial abusers to use physical and/or verbal force or enticement, and force generally escalates as the age of the victim escalates (Bolen, 2001).

Recidivism Rates

Recidivism rates are a concern for both members of the justice system and the general population at large (Bushway & Owens, 2013). Special policies related specifically to sexual offenders are often implemented to improve public safety by managing the risk of sexual re-offense (Hanson & Morton-Bourgon, 2005). There are challenges in defining recidivism related to sexual offenders, and the variability of re-offense rates found in the literature may be linked to the lack of a uniform definition (Langevin et al., 2004). The varied definitions of recidivism include a new sexual offense, any conviction or arrest which may include an arrest relating to a probation violation, and a self-report of any new criminal activity (Langevin et al., 2004).

Existing research related specifically to recidivism defined as a sexual re-offense indicates factors that may be associated with the recidivism of sexual offenders (Hanson & Bussiere, 1998). Antisocial cognitions and deviant sexual interest are characterized as the most predominant indications of recidivism in sexual offenders (Beech & Ward, 2004; Hanson & Morton-Bourgon, 2005). Additionally, objective measures of personality may be important factors when clinically evaluating the risk of sexual offense, especially when there is a co-morbid presentation of a personality disorder or antisocial orientation (Prentky, 2004). However, Hart, Laws, and Kropp (2003) note that, “risk is a hazard that is incompletely understood and whose occurrence can be forecast only with uncertainty (p. 207).” The uncertainty of the risk of sexual offense underscores the importance of continued understanding of the factors that correspond with sexual offending to facilitate better prediction of risk and reduction of recidivism (Hanson & Thornton, 2000). There have been a number of relevant factors found to be associated with sexual reoffending (Hanson & Morton-Bourgon, 2005). Significant variables for predicting recidivism are related to the type of offense and characteristics of the individuals that commit sexual offenses (Hanson & Morton-Bourgon, 2005).

Risk Assessment

Sexual recidivism produces fear and anger within society and has serious consequences for past and potential victims (Hanson & Bussière, 1998). Predictors of recidivism are related to sexual deviance and criminal history, especially in reference to prior sexual offenses (Hanson & Bussière, 1998; Hanson, 2002). Risk factors can be evaluated by the use of clinical judgment, structured clinical assessments, and actuarial approaches that specify the risk factors to be considered and specify the combination of the factors into an overall evaluation (Hanson & Thornton, 2000). In the empirically guided approach, the final evaluation of risk is left to the judgment of the clinician (Langton et al., 2007). In contrast, the actuarial approach not only specifies the risk factors to be considered, but also specifies the method of combining the factors into an overall evaluation (Hanson & Thornton, 2000). The following section provides a review of several commonly used risk assessments.

Sex Offender Risk Appraisal Guide

The Sex Offender Risk Appraisal Guide (SORAG; Harris, Rice, & Cormier, 1998) is a 14-item actuarial scale that was developed to predict new convictions of violent sexual recidivism. These 14 items are related to demographics (age and marital status), early behavior problems, psychiatric diagnoses (personality disorder and psychopathy), and criminal history. The SORAG is highly correlated with the Violence Risk Appraisal Guide (VRAG; Harris, Rice, & Quinsey, 1993) which was developed to predict violent recidivism in the entire population of serious offenders, not exclusively sexual offenders (Barbaree et al., 2001). Research has demonstrated that the SORAG has a high accuracy in predicting violent recidivism and moderate accuracy in predicting recidivism in offenses that are solely known to be sexual in nature (Barbaree et al., 2001; Rice & Harris, 2002).

Rapid Risk Assessment for Sex Offender Recidivism

Another instrument developed for risk assessment is the Rapid Risk Assessment for Sex Offender Recidivism (RRASOR; Hanson, 1997). This instrument is a four-item actuarial scale and was developed by selecting risk factors that were most strongly and significantly related to sexual offense across a series of recidivism studies (Hanson & Bussière, 1998). The RRASOR was shown to be a moderate predictor of sexually motivated recidivism averaged across eight different follow-up studies (n = 2,592) (Hanson, 1997), and Hanson and Morton-Bourgon’s (2005) meta-analysis found RRASOR to demonstrate moderate discrimination between sexual recidivists and nonrecidivists when averaged across 34 diverse follow-up studies.

Static-99

The Static-99 (Hanson & Thornton, 1999) is a brief actuarial instrument developed for use with adult male sexual offenders who are at least 18 years of age and have been previously convicted of at least one sexual offense against a child or non-consenting adult (Harris et al., 2003). A major aim of the instrument is estimating the future probability of sexual recidivism (Hanson & Broom, 2005). Since its inception, the Static-99 is one of the most widely used 744 actuarial instruments used for the risk assessment of sexual violence (Storey, Watt, Jackson, & Hart, 2012).

Purpose of the Study

This study evaluated adult sexual offenders in an attempt to create a more informed distinction between types of offenders based upon offender risk assessment characteristics and their victim age. The study comes from a larger study and the purpose of this study was to determine if there are significant differences in sexual offender groups (intrafamilial offenders and extrafamilial offenders) related to risk assessment as measured by the Static-99 and victim age (Johnson, Underwood, Newmeyer, & Baum, 2016). This was done in order to better identify and to classify the characteristics and risk factors of these individuals to potentially provide more effective treatment interventions. Specifically, it was hypothesized that: (1) Intrafamilial sexual offenders would demonstrate lower risk scores on the Static-99 than extrafamilial sexual offenders (2) biological sexual offenders would demonstrate lower risk scores on the Static-99 than intrafamilial sexual offenders, and (3) intrafamilial offenders would have younger victims than extrafamilial offenders.

Methodology

The research method used is a correlational design and employed Independent Samples T-tests, to examine group differences using archival data from a group of sexual offenders in out-patient treatment at a center in a southeastern state in the United States.

Subjects

Subjects were selected from archival data of completed sex offender treatment records and specific psychological evaluations conducted with individuals mandated for treatment as a condition of probation or parole in an outpatient treatment program in a southeastern state in the United States. One hundred ninety-two sexual offenders were selected from a convenience sample from 10 years of treatment records. For inclusion in this study, the participant must have completed a valid Static-99 and have been 18 years or older at the time of the sexual offense. All participants were convicted of a sexual crime against children and were mandated by Federal or County probation to participate in treatment. This treatment included weekly individual and/or group therapy sessions facilitated by the professional staff of the treatment facility The sample was comprised of 178 adult males and 14 adult females, totaling 192, with ages ranging 18-68 years; the average age of the participants was 32.21 years, SD = 11.73. Individuals identifying as Caucasian/White made up the majority of the sample (85.9%), followed by African-American/Black (5.8%), Hispanic/Latino (5.2%), and Other (3.1%). Additionally, in terms of marital status and employment the majority of participants were single (37.5%) and unemployed (46.4%). Table 1 shows complete demographic information.

Demographic f %
Race
African American/Black 11 5.8
Caucasian/White 165 85.9
Hispanic/Latino 10 5.2
Other 6 3.1
Marital Status
Married 60 31.3
Divorced 29 15.1
Cohabitating 1 0.5
Separated 27 14.1
Single 72 37.5
Widowed 3 1.5
Education Level
High School Graduate 60 31.3
Middle School/Jr High 14 7.3
9th Grade 24 12.5
10th Grade 16 8.3
11th Grade 16 8.3
GED 31 16.2
Some College 21 10.9
Associates Degree 6 3.1
Bachelor’s Degree 3 1.6
Master’s Degree 1 0.5
Doctoral Degree 0 0.0
Type of Employment
Unemployed 89 46.4
Full Time 67 34.9
Part Time 17 8.9
Student 1 0.5
Retired 6 3.1
Homemaker 1 0.5
Disabled 10 5.2
Seasonal/Migrant Worker 1 0.5
Veteran
Yes 13 6.8
No 179 93.2
Current Living Situation
Private Residence 174 90.6
Other Independent Living 1 0.5
Homeless 1 0.5
Institution 4 2.1
Residential Facility 2 1.0
Other 10 5.3
Contact vs. Non-Contact Offender
Contact 166 86.5
Non-Contact 26 13.5
Penetration
With Penetration 83 43.2
Without Penetration 109 56.8
Pedophilic Interest
Yes 76 39.6
No 116 60.4
Gender Interest
Male 12 6.3
Female 180 93.7
Victim Age
Prepubescent (10 and younger) 50 26.0
Pubescent (11 to 14) 81 42.2
Older Teen (15 and up) 47 24.5
No Identified Age 14 7.3
Victim Gender
Male 27 14.1
Female 165 85.9
Type of Offender
Biological Parent 25 13.0
Intrafamilial 56 29.2
Extrafamilial 111 57.8
Multiple Offense Convictions
Yes 41 21.4
No 151 78.7

Table 1: Demographic characteristics of study sample (n=192).

In terms of sexual offender specific demographics, 166 individuals were contact offenders as opposed to 26 non-contact offenders. Of the contact offenders, 83 of the offenders had contact with penetration. Regarding the offenders’ choice of victim, 165 chose female victims and 27 chose male victims; 50 of the individuals’ victims were prepubescent (10 and younger), 81 were pubescent (11 to 14), 47 were older teen (15 and up) and 14 had no identified age. For the majority in this study (141 individuals), the sexual offense was their first offense conviction. Finally, the individuals in this study consisted of 111 extrafamilial offenders, 56 intrafamilial offenders who were not the biological parent, and 25 offenders who were the victim’s biological parent.

Data Collection

Data were compiled from the archival records for the past 10 years (2005-2015) of completed sex offender specific psychological evaluations, clinical intake forms, and criminal background records from a treatment facility in a southeastern state in the United States. An employee of the treatment program collected the needed data, and the primary researcher for this study was provided with blind copies of these data, reporting the data under a participant ID number. Records at the treatment facility were examined for inclusion criteria starting with current year intakes and working backwards in date.

Instruments

Demographic Surveys

The offender’s intake assessment as well as his or her criminal background report was used for demographic purposes and to determine the victim characteristics and offender’s relationship to the victim. Socio-demographic data were obtained from a clinical intake form that was already a standard part of the treatment packet. This form included information regarding date of birth, gender, ethnicity, marital status, current employment, education level, and current living situation. For this study, information from this form is limited to the offender’s gender and age. Other information regarding the relationship to the victim and victim characteristics was gathered from the criminal background reports and polygraph reports available in the individual’s treatment file.

Static-99

The Static-99 is an actuarial risk tool that is used in the assessment of recidivism among adult male sexual offenders (Hanson & Thornton, 2000). The Static-99 consists of 10 items pertaining to 10 static factors which are age (less than 25 years), never married, current convictions for nonsexual violence, prior convictions for nonsexual violence, prior sex offenses, number of prior sentencing dates, convictions for noncontact sex offenses, unrelated victims, stranger victims, and male victims (Hanson & Thornton, 2000). Each of the 10 items is given up to one point with the exception of prior sex offenses which can be given up to three points. The risk categories are based on the final scores as follows: Low (0-1), Moderate-Low (2-3), Moderate-High (4-5), and High (6-12). Inter-rater reliability has been reported to be strong for the Static-99, from 0.80 to as high as 0.96 (Harris et al., 2003). Barbaree et al. (2001) found inter-rater reliability to be 0.90 for the instrument. Bartosh, Garby, Lewis & Gray (2003) found that the Static-99 had significant predictive validity for sexual offense (ROC = 0.636, p<0.05). The Static-99 has shown to be an effective predictor of recidivism in sexual offenders (Hanson & Morton-Bourgon, 2005). Montana and colleagues (2012) have also found that the Static-99 is an effective predictor of recidivism among Catholic clergy who have committed sexual offenses against minors with a moderate to large effect size (area under the curve [AUC] = 0.672; Cohen’s d = 0.808). The Static-99 also significantly predicted sexual or violent recidivism in a sample of men released from Her Majesty’s Prison Service in 1979 (AUCs of 0.72 for sexual recidivism and 0.69 for sexual or violent recidivism) (Hanson & Thornton, 2000). Beech, Beckett, and Fisher (1998) found that the Static-99 had an AUC of .73 in predicting sexual recidivism in a sample of 53 treated sex offenders. In addition, Nunes, Firestone, Bradford, Greenberg, and Broom (2002) found that the Static-99 was a moderate predictor of sexual recidivism in a sample of 258 adult male sexual offenders with an ROC area of 0.70. In this study, the Static-99 was used as a measure of risk assessment to examine difference between intrafamilial, extrafamilial, and biological sexual offenders.

Results

An Independent Samples T-test was conducted to compare the difference in Static-99 scores reported among the intrafamilial and extrafamilial offenders. There was a significant difference in scores between the intrafamilial group (M = 1.40, SD = 1.23) and the extrafamilial group, (M = 1.97, SD = 1.17); t(149) = -2.82, p = .005 (two-tailed). The magnitude of the differences in the means (mean difference = -0.57, 95% CI: -0.98 to -.17) was small (eta squared = .05). Thus, Hypothesis one was supported. Table 2 provides a summary of the means and standard deviations in Static-99 scores according to offender type for Hypothesis one.

Variable n M SD t p
Type of Offender
Intrafamilial 53 1.40 1.23 -2.82 0.005
Extrafamilial 98 1.97 1.17    
Type of Offender
Biological 21 1.57 1.08 0.57 0.57
Intrafamilial 53 1.40 1.23    

Table 2: Means and standard deviations in static-99 scores according to offender type for hypotheses 1 and 2.

Hypothesis two stated that biological sexual offenders would demonstrate lower risk scores on the Static-99 than intrafamilial sexual offenders. An Independent Samples T-test was conducted to compare the difference in Static-99 scores reported among the intrafamilial and biological child groups. There was no significant difference in scores between the intrafamilial group (M = 1.40, SD = 1.23) and the biological child group, (M = 1.57, SD = 1.08); t(72) = 0.57, p = .57 (two-tailed). The magnitude of the differences in the means (mean difference = 0.175, 95% CI: -0.44 to .79) was very small (eta squared = 0.004). Thus, Hypothesis two was not supported. Table 2 provides a summary of the Table 2 provides a summary of the means and standard deviations in Static-99 scores according to offender type for Hypothesis two.

The final hypothesis examined differences between the type of offender (intrafamilial, extrafamilial) and victim age. Hypothesis three stated that intrafamilial offenders’ victims would be younger than extrafamilial offenders’ victims. An Independent Samples T-test was conducted to compare the difference in mean victim age reported among the intrafamilial and extrafamilial groups. There was no significant difference in scores for the intrafamilial group (M = 12.0, SD = 6.97) and the extrafamilial group, (M = 13.06, SD = 4.6); t(149) = -1.123, p = .26 (two-tailed). The magnitude of the differences in the means (mean difference = -1.06, 95% CI: -2.93 to 0.81) was very small (eta squared = 0.008). Thus, hypothesis three was not supported. Table 3 summarizes the means and standard deviations in victim age according to the offender type for hypothesis three.

Variable n M SD t p
Type of Offender
Intrafamilial 53 12.00 6.97 -1.12 0.26
Extrafamilial 98 13.06 4.60    

Table 3: Means and standard deviations in victim age according to offender type for hypothesis 3.

A post-hoc analysis to consider biological offenders, a one-way between-groups analysis of variance was conducted to explore the effect of offender type on victim age when considering biological offenders. Offender type consisted of three groups: biological, intrafamilial, and extrafamilial. There was a statistically significant difference at the p = .05 level in victim age for the three groups: F (2,173) = 3.88, p = 0.02. Despite reaching statistical significance the actual difference in mean scores between groups was quite small. The effect size, calculated using eta squared, was .04. Post hoc comparisons using the Tukey HSD test indicated that the mean score for the biological offenders (M = 9.68, SD = 5.06) was significantly different from the extrafamilial offenders (M = 13.06, SD = 4.60). The intrafamilial offenders (M = 12.00, SD = 6.97) did not differ significantly from either biological or extrafamilial offenders. Table 4 provides a summary of the univariate effects of additional analysis for hypothesis three.

Dependent Variables df dferror F Group Means P
  Victim Age   2   173   3.88 Biological 9.68  
Intrafamilial 12.00 0.02*
Extrafamilial 13.06  
*Significant at the p<0.05 level

Table 4: Univariate effects of additional analysis for hypothesis 3.

Discussion

This study examined the differences in sexual offender groups as related to risk assessment and victim age. Specifically, the study examined the differences between intrafamilial, extrafamilial, and biological offenders by using archival data from the individuals’ clinical records including measures from the Static-99 and demographic data from the clinical intake assessment. The purpose of the study was to (a) test the hypotheses examining the differences between sexual offender groups (intrafamilial offenders, biological offenders, and extrafamilial offenders) risk and victim age and (b) attempt to better identify and to classify the differences in risk factors of these individuals to potentially provide more effective treatment interventions.

Prior research indicates that intrafamilial and biological offenders have a low rate of recidivism (Furr, 1993; Hanson, et al., 1993; Studer et al., 2000; Quinsey, 1986) and this rate is significantly lower than for extrafamilial offenders (Quinsey et al., 1995; Marshall & Barbaree, 1990). This current study predicted that significant risk factors would exist between intrafamilial, and extrafamilial sexual offenders. Significant differences were found between these groups, with the intrafamilial offenders having lower risk scores on the Static-99 than the extrafamilial offenders. These findings are consistent with the research indicating that sexual offenders who offend against familial victims are less likely to recidivate (Hanson et al., 1993; Greenberg et al., 2000; Langevin et al., 2004). One possible explanation for this significance in findings may be due to the difference in sexual interest in these two groups of offenders. The literature indicates that intrafamilial offenders generally have lower pedophilic interest than other offenders (Greenberg et al., 2005; Seto et al., 2015).

The second hypothesis predicted that significant risk factors would exist between intrafamilial and biological sexual offenders. However, no significant differences were found between these groups. Caution is recommended in interpreting these results due to the small sample size for both the intrafamilial (N = 53) and the biological (N = 21) offender groups. No studies were found examining intrafamilial and biological offenders and thus there is no comparison for these results. One possible explanation for the lack of significance may be due to the commonalities of these individuals. Research has demonstrated that these groups have no significant differences in personality characteristics (Coxe & Holmes, 2001; Erickson, Luxenberg, Walbeck, & Steely, 1987; Scott & Stone, 1986; Valliant & Blasutti, 1992) or sexual interest (Seto et al., 2015). These individuals may also share commonalities in risk factors as well.

Environmental factors may have also contributed to the lack of significant difference in scores between groups. Research has shown that an assessment of environmental factors such as social support, employment, relationship quality, and victim access may strongly affect the predictive accuracy of risk factors (Scoones, Willis, & Grace, 2012). Since biological and interfamilial offenders often share the same environmental characteristics of living with and having a personal connection with the victim, it is plausible that they would experience the same influences when it comes to risk factors. In addition, dynamic risk factors may account for the differences in recidivism rates for sexual offenders rather than static factors (Hanson, 2002; Quinsey et al., 1995; Marshall & Barbaree, 1990). Dynamic risk factors are psychological or behavioral characteristics of the offender that are amenable to change (Hanson, 2009). Dynamic risk factors related to recidivism are sexual deviancy, antisocial personality characteristics, and antisocial traits such as problems with self-regulation, employment instability, and anger issues (Hanson & Morton-Bourgon, 2005). This study used a measure of static risk factors and was not able to focus on dynamic risk factors that may have contributed to the delineating group differences in recidivism rates.

Regarding the final hypothesis, the literature shows that younger children are more often victimized by intrafamilial offenders and older children victimized by extrafamilial offenders (Seto et al., 2015). This current study initially failed to replicate these findings that intrafamilial offenders had younger victims than extrafamilial offenders. However, after an additional analysis that separated biological offenders from intrafamilial offenders, the victim age for biological offenders (M = 9.68, SD = 5.06) was much younger than the victim age for extrafamilial offenders (M = 13.06, SD = 4.60). This is consistent with research by Fischer and McDonald (1998) which demonstrates that biological offenders’ victims are on average three years younger than victims of extrafamilial offenders when the abuse begins.

When considering sample characteristics, the initial non-significant findings regarding age is understood given that intrafamilial and extrafamilial offenders had victims with average ages that were only one year different from each other. This result is in contrast to the literature that finds extrafamilial offender’s victims are often older than intrafamilial offender’s victims (Fischer & McDonald, 1998; Kuznestov & Pierson, 1992). However, the additional analysis confirms the typical findings that younger victims are associated with biological offenders. One possible explanation for this difference in victim ages could be due to access to the victim. This could be related to the longer access to the victim or that sexual activities within a family are less likely to be questioned by others (De Jong et al., 1983). Further research is needed to determine other ways that these groups of offenders could differ as no current literature is available to explore this assumption (Levenson & Cotter, 2005).

Limitations and Future Research

This study contains limitations that may influence the generalizability of the results. Most notably, the first limitation is regarding the sample of participants. The sample was a convenience sample, obtained from archival data from one treatment program in a southeastern state in the United States. This program evaluates and treats sexual offenders; therefore, the ability to generalize to the greater population of sexual offenders was limited. For increased generalizability, replication of this study with a larger, more diverse sample size would improve the strength of the study and increase the generalizability of the results. In addition, a larger, more diverse sample size utilizing individuals that were not on probation or incarcerated would increase the reliability of the study.

Another limitation is the use of archival data which restricts the measures that could be used in the analyses. Using archival data does not allow the opportunity to use additional measures of recidivism that may have provided further elaboration or investigation of differences. In addition, risk factors and personality characteristics may vary from the time of the committed offense to the time that the sexual offenders begin or complete a treatment program. Controlling for extraneous factors such as relationship quality, negative mood, and substance abuse may provide further insight into possible differences. Future research could also explore differences across the types of sexual offenders regarding additional criminal activities, mental health diagnoses, and the presence of substance abuse disorders at the time of the offense. Also, it would be important to know more about environmental factors and behavioral history to have a more complete understanding of the risk of recidivism between the groups.

A final recommendation would be to conduct further research regarding the differences in victim age between the types of offenders as well as other factors that may be involved. Since biological offenders tend to have younger victims, it would be important to address other factors that lead to moving from non-contact to contact within the home at such an early age. Factors to consider within the home would be relationship quality, family functioning, and family dynamics. Studies of these characteristics would be beneficial in order to determine effects that these dynamics have on sexual offending.

Implications

The results of this study indicated that there appears to be a significant difference in regards to risk assessment among intrafamilial versus extrafamilial offenders. This would be important for the case conceptualization and treatment planning for extrafamilial offenders. More focus on recidivism prevention would be important for providers working with these offenders. Research has suggested that the CBT model that focuses on understanding the offense process and coping with dynamic risk factors is effective in avoiding future sexual offense (Pithers, 1990; Ward & Gannon, 2006). Dynamic risk factors, such as emotional loneliness, low self-esteem, and unemployment, are obstacles that discourage or hinder the acquisition of primary human goods such as healthy living, knowledge, recreational pursuits, autonomy, inner peace, relatedness, community, spirituality, and creativity (Ward & Gannon, 2006). When treatment providers offer offenders the necessary skills and support to meet their primary needs in more adaptive ways, the supposition is that they will be less likely to reoffend or to bring harm to others. Focusing on these dynamic risk factors especially with extrafamilial offenders, helps to ensure the future safety of child victims.

Another implication from this study is regarding the victim age as related to the type of offender. The results of this study are in contrast to the literature that finds extrafamilial offender’s victims are often older than intrafamilial offender’s victims (Fischer & McDonald, 1998; Kuznestov & Pierson, 1992). However, the study further distinguishes that biological offender’s victims are younger than other intrafamilial offender’s victims. This finding is plausible because biological offenders may have earlier access to the children than do other intrafamilial offenders. This could be related to the longer access to the victim or that sexual activities within a family are less likely to be questioned by others (De Jong et al., 1983). Investigating familial relationships, social interactions, and life stressors is important for treatment providers when working with intrafamilial and biological offenders. The offender may have resorted to a child as a substitute for the lack of an adult partner and working on building social interaction and quality relationships may be beneficial. In addition, extraneous factors such as the loss of employment, divorce, or excessive drug or alcohol usage may have led to the individual feeling out of control in his life, and treatment to mediate stressors and teach effective coping skills may prohibit future sexual offenses.

In addition to information for the treatment of offenders, this study provides implications to consider when providers are working with victims suggesting that a younger victim may have been more likely to have been victimized by an intrafamilial offender, especially a biological offender. Teaching at-risk children to develop protective factors such as increased self-esteem, social engagement, and other resilience building factors could be beneficial in preventing revictimization (Smallbone, Marshall, & Wortley, 2008).

Finally, providers should remain engaged in current research efforts and continue to seek updated knowledge regarding efficacious treatment for the sex offender population. Continued research is needed to find out the distinctions between types of offenders to promote understanding, prevention, and more effective treatment for sexual offenders.

Conclusions

This study sought to identify differences in intrafamilial and extrafamilial sexual offenders in order to better identify and to classify the different risk factors and victim characteristics of these individuals. This study added to the literature by investigating differences according to offender type (intrafamilial vs extrafamilial) regarding risk assessment and victim age. Specifically, intrafamilial offenders were found to exhibit lower risk factors than extrafamilial offenders and sexual offenders that were closer to the victim in terms of familial status were more likely to have younger victims than those who were non-related. These distinctions help to inform treatment providers and improve the efficacy of treatment for all types of sexual offenders. This information may help professionals to gain needed insights into working with the sex offender population and to aid in the development and implementation of treatment protocols that will help to prevent recidivism and ultimately work to keep children safe. Further research needs to be conducted to examine other dynamics that may provide insights to the differences in sexual offenders including family dynamics, marital relationships, and characteristics of family functioning to help further inform treatment providers who work with this population.

References

  1. Abel, G.G., Becker, J.V. & Cummingham-Rathner, J. (1984). Complications, consent and conditions in sex between children and adults. International Journal of Law & Psychiatry, 7, 89-103
  2. Ahlmeyer, S., Kleinsasser, D., Stoner, J. & Retzlaff, P. (2003). Psychopathology of incarcerated sex offenders. Journal of Personality Disorders, 17, 306-318
  3. Armentrout, J. A., & Hauer, A. L. (1978). MMPIs of rapists of adults, rapists of children, and non-rapist sex offenders. Journal of Clinical Psychology, 34, 330-332
  4. Atwood, J.D. (2007). When love hurts: Preadolescent girls' reports in incest. American Journal of Family Therapy, 35, 287-313
  5. Banse, R., Schmidt, A.F. & Clarbour, J. (2010). Indirect measures of sexual interest in child sex offenders: A Multimethod Approach. Criminal Justice & Behavior, 37, 319
  6. Barbaree, H.E., Seto, M.C., Langton, C.M. & Peacock, E.J. (2001). Evaluating the predictive accuracy of six risk assessment instruments for adult sex offenders. Criminal Justice and Behavior, 28, 490-521.
  7. Bartosh, D.L., Garby, T., Lewis, D. & Gray, S. (2003). Differences in the predictive validity of actuarial risk assessments in relation to sex offender type. International Journal of Offender Therapy and Comparative Criminology, 47, 422-438
  8. Barsetti, I., Earls, C. Lalumière, M. & Bélanger, N. (1998). The differentiation of intrafamilial and extrafamilial heterosexual child molesters. Journal of Interpersonal Violence, 13, 275-286
  9. Becerra-García, J.A., García-León, A. & Egan, V. (2013). A cross-cultural comparison of criminological characteristics and personality traits in sexual offenders against children: Study in Spain and the United Kingdom. Psychiatry, Psychology, and Law, 20, 344-352
  10. Beech, A., Beckett, R.C. & Fisher, D. (1998). STEP 3: An evaluation of the prison sex offender treatment programme. London: Home Office.
  11. Beech, A. & Ward, T. (2004). The integration of etiology and risk in sexual offenders: A theoretical Framework. Aggression and Violent Behavior, 10, 31-63
  12. Bickley, J. & Beech, A. (2001). Classifying child abusers: Its relevance to theory and clinical practice. International Journal of Offender Therapy and Comparative Criminology, 45, 51-69.
  13. Black, M.C., Basile, K.C., Breiding, M.J., Smith, S.G., Walters, M.L., Merrick, M.T. et al. (2011). The National Intimate Partner and Sexual Violence Survey (NISVS): 2010 Summary Report. Atlanta, GA: National Center for Injury Prevention and Control, Centers for Disease Control and Prevention
  14. Bolen, R.M. (2001). Child sexual abuse: Its scope and our failure. New York: Kluwer Academic/Plenum Publishers.
  15. Bonnar-Kidd, K.K. (2010). Sexual offender laws and prevention of sexual violence or recidivism. American Journal of Public Health, 100, 412–419
  16. Bushway, S.D. & Owens, E.G. (2013). Framing punishment: Incarceration, recommended sentences, and recidivism. The Journal of Law & Economics, 56, 201-331.
  17. Calkins, C., Jeglic, E., Beattey, R.A., Zeidman, S. & Perillo, A.D. (2014). Sexual violence legislation: A review of case law and empirical research. Psychology, Public Policy, And Law, 20, 443-462
  18. Catalá-Miñana, A., Walker, K., Bowen, E. & Lila, M. (2014). Cultural differences in personality and aggressive behavior in intimate partner violence offenders: a comparison of English and Spanish offenders. Journal of interpersonal violence, 29, 2652-2669.
  19. Chaffin, M., Letourneau, E. & Silovsky, J.F. (2002). Adults, adolescents and children who sexually abuse children: A developmental perspective. In J. E. B. Meyers, L. Berliner, J. Briere, C.T. Hendrix, C. Jenny, & T.A. Reid (Eds.), The APSAC handbook on child maltreatment (2nd ed., pp. 205–232.) Thousand Oaks, CA: Sage.
  20. Conte, J. R. (1991). The nature of sexual offenses against children. In C. R. Hollin & K. Howells (Eds.). Clinical approaches to sex offenders and their victims (pp. 11-34). Toronto: Wiley.
  21. Coxe, R. & Holmes, W. (2009). A comparative study of two groups of sex offenders identified as high and low risk on the static-99. Journal of Child Sexual Abuse, 18, 137-153
  22. Davis, K.M. & Archer, R.P. (2010). A critical review of objective personality inventories with sex offenders. Journal of Clinical Psychology, 66, 1254-1280
  23. De Jong, A.R., Hervada, A.R. & Emmett, G.A. (1983). Epidemiologic variations in childhood sexual abuse. Child Abuse & Neglect, 7, 155-162.
  24. De Vogel, V., De Ruiter, C., van Beek, D. & Mead, G. (2004). Predictive validity of the SVR-20 and Static-99 in a Dutch sample of treated sex offenders. Law and Human Behavior, 28, 235
  25. Erickson, W.D., Luxenberg, M.B., Walbeck, N.H., & Seely, R.K. (1987). Frequency of MMPI two-point code types among sex offenders. Journal of Consulting and Clinical Psychology, 55, 566-570
  26. Faller, K.C. (1989). The role relationship between victim and perpetrator as a predictor of characteristics of intrafamilial sexual abuse. Child and Adolescent Social Work, 6, 217-229
  27. Finkelhor, D. (1984). Child sexual abuse. New York, New York: Free Press
  28. Finkelhor, D. (1994). Current information on the scope and nature of child sexual abuse. The Future of Children, 4, 31-53
  29. Finkelhor, D., Hammer, H. & Sedlak, A.J. (2008). Sexually assaulted children: National estimates and characteristics. National Incidence Studies of Missing, Abducted, Runaway, and Throwaway Children. NISMART-2 Bulletin. Washington, DC: U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention.
  30. Finkelhor D. & Hotaling, G.T. (1984). Sexual abuse in the national incidence study of child abuse and neglect: An appraisal. Child Abuse and Neglect, 8, 23-32
  31. Firestone, P., Bradford, J.M., McCoy, M., Greenberg, D.M., Curry, S. & Larose, M.R. (2000). Prediction of recidivism in extrafamilial child molesters based on court-related assessments. Sexual Abuse: A Journal of Research and Treatment, 12, 203-221.
  32. Fisher, D.G. & McDonald, W.L. (1998). Characteristics of intrafamilial and extrafamilial child abuse. Child Abuse and Neglect, 22, 915-929.
  33. Furr, K.D. (1993). Prediction of sexual or violent recidivism among sexual offenders: A comparison of prediction instruments. Annals of Sex Research, 6, 271-286
  34. Glowacz, F. & Born, M. (2013). Do adolescent child abusers, peer abusers, and non-sex offenders have different personality profiles? European Child & Adolescent Psychiatry, 22, 117-125
  35. Gomes, V., Jardim, P., Taveira, F., Dinis-Oliveira, R. J. & Magalhães, T. (2014). Alleged biological father incest: A forensic approach. Journal of Forensic Sciences, 59, 255-259
  36. Greenberg, D., Bradford, J., Firestone, P. & Curry, S. (2000). Recidivism of child molesters: A study of victim relationship with the perpetrator. Child Abuse & Neglect, 24, 1485-1494
  37. Greenberg, D.M., Firestone, P., Nunes, K.L., Bradford, J.M. & Curry, S. (2005). Biological fathers and stepfathers who molest their daughters: Psychological, phallometric, and criminal features. Sexual Abuse: A Journal of Research and Treatment, 17, 39-46
  38. Hall, G.C.N., Graham, J.R. & Shepherd, J.B. (1991). Three methods of developing MMPI taxonomies of sexual offenders. Journal of Personality Assessment, 56, 2-13
  39. Hanson, R.K. (1997). The development of a brief actuarial scale for sexual offense recidivism. Ottawa, Ontario, Canada: Department of the Solicitor General.
  40. Hanson, R.K. (2002). Recidivism and age: Follow-up data from 4,673 sexual offenders. Journal of Interpersonal Violence, 17, 1046-1062
  41. Hanson, R.K. (2009). The psychological assessment of risk for crime and violence. Canadian Psychology, 50, 172
  42. Hanson, R.K. & Broom, I. (2005). The utility of cumulative meta-analysis: application to programs for reducing sexual violence. Sexual Abuse: A Journal of Research and Treatment, 17, 357-373
  43. Hanson, R.K. & Bussière, M.T. (1998). Predicting relapse: A meta-analysis of sexual offender recidivism studies. Journal of Consulting and Clinical Psychology, 66, 348-362
  44. Hanson, R.K. & Morton-Bourgon, K.E. (2005). The characteristics of persistent sexual offenders: A meta-analysis of recidivism studies. Journal of Consulting and Clinical Psychology, 73, 1154-1163.
  45. Hanson, R.K., Steffy, R.A. & Gauthier, R. (1993). Long-term recidivism of child molesters. Journal of Consulting and Clinical Psychology, 61, 646-652
  46. Hanson, R.K, & Thornton, D. (1999). Static 99: Improving actuarial risk assessments for sex offenders (Vol. 2). Ottawa, Canada: Solicitor General Canada.
  47. Hanson, R.K. & Thornton, D. (2000). Improving risk assessments for sex offenders: A comparison of three actuarial scales. Law and Human Behavior, 24, 119-136
  48. Harris, G.T., Rice, M.E. & Quinsey, V.L. (1993). Violent recidivism of mentally disordered offenders: The development of a statistical prediction instrument. Criminal Justice and Behavior, 20, 315-335.
  49. Harris, G.T., Rice, M.E., Quinsey, V.L., Lalumière, M.L., Boer, D. & Lang, C. (2003). A multisite comparison of actuarial risk instruments for sex offenders. Psychological Assessment, 15, 413.
  50. Hart, S., Laws, D.R. & Kropp, P.R. (2003). The risk-need model of offender rehabilitation. In T. Ward, D. R. Laws, & S. M. Hudson (Eds.), Theoretical issues and controversies in sexual deviance (pp. 338-354). London: Sage
  51. Helmus, L., Thornton, D., Hanson, R.K. & Babchishin, K.M. (2012). Improving the predictive accuracy of Static-99 and Static-2002 with older sex offenders: Revised age weights. Sexual Abuse: A Journal of Research and Treatment, 24, 64-101
  52. Herkov, J.M., Gynther, D.M., Thomas, S., & Myers, C.W. (1996). MMPI differences among adolescent inpatients, rapists, sodomists, and sexual abusers. Journal of Personality Assessment, 66, 81-90
  53. Johnson, H., Underwood, L., Newmeyer, N. & Baum, L. (2016). Sexual offender differences regarding personality patterns, risk factors, and sexual interest (Unpublished doctoral dissertation). Regent University, Virginia Beach, VA.
  54. Kear-Colwell, J. & Pollock, P. (1997). Motivation or confrontation: Which approach to the child sex offender? Criminal Justice and Behavior, 24, 20-33
  55. Kenny, M. & Wurtele, S. (2012). Preventing childhood sexual abuse: An ecological approach. Journal of Child Sexual Abuse, 21, 361-367
  56. Knight, R.A. & Sims-Knight, J.E. (2003). The developmental antecedents of sexual coercion against women: Testing alternative hypotheses with structural equation modeling. In R. A. Prentky, E.S. Janus, & M.C. Seto (Eds.). Annals of the New York Academy of Sciences: Vol. 989. Sexually coercive behavior: Understanding and management (pp. 72-85). New York: New York Academy of Sciences
  57. Koss, M.P. (1987). Hidden rape: Sexual aggression and victimization in a national sample of students in higher education. In A.W. Burgess (Ed.), Rape and sexual assault II (pp.3–25). New York: Garland.
  58. Kuznestov, A., & Pierson, T. A. (1992). Victim age as a basis for profiling sex offenders. Federal Probation, 56, 34
  59. Lang, R.A. & Frenzel, R.R. (1988). How sex offenders lure children. Annals of Sex Research, 1, 303-317
  60. Langevin, R., Curnoe, S., Fedoroff, P., Bennett, R., Langevin, M., Peever, C. et al. (2004). Lifetime sex offender recidivism: A 25-year follow-up study. Canadian Journal of Criminology & Criminal Justice, 46, 531-552
  61. Langton, C.M., Barbaree, H.E., Seto, M.C., Peacock, E.J., Harkins, L. & Hansen, K.T. (2007). Actuarial assessment of risk for re-offense among adult sex offenders: Evaluating the predictive accuracy of the Static-2002 and five other instruments. Criminal Justice and Behavior, 34, 37-59
  62. Larsen, J., Hudson, S.M., & Ward, T. (1995). Evaluation of attributional change in a relapse prevention program for child molesters. Behavior Change, 12, 127-138.
  63. Levenson, J.S., & Cotter, L.P. (2005). The impact of sex offender residence restrictions: 1,000 feet from danger or one step from absurd? International Journal of Offender Therapy and Comparative Criminology, 49, 168-178
  64. Lisak, D. & Miller, P.M. (2002). Repeat rape and multiple offending among undetected rapists. Violence and Victims, 17, 73-84
  65. Marshall, W. L. (1997). Pedophilia: Psychopathology and theory. In D.R. Laws & W.O Donahue (Eds.), Sexual deviance: Theory, assessment, and treatment (pp. 152- 174). New York: Guilford.
  66. Marshall, W. L., & Anderson, D. (2000). Do relapse prevention components enhance treatment effectiveness? In D.R. Laws, S. M. Hudson, & T Ward (Eds.)
  67. Remaking relapse prevention with sex offenders: A sourcebook (pp. 39-55). Thousand Oaks, CA: Sage.
  68. Marshall, W. L. & Barbaree, H. E. (1990). Outcome of comprehensive cognitive-behavioral treatment programs. In W.L. Marshall, D. R. Laws, & H. E. Barbaree (Eds.), Handbook of sexual assault: Issues, theories, and treatment of the offender (pp. 363-385). New York: Plenum Press.
  69. Marshall, W.L., Champagne, F., Brown, C. & Miller, S. (1997). Empathy, intimacy, loneliness, and self-esteem in non-familial child molesters: A brief report. Journal of Child Sexual Abuse, 6, 87-98
  70. Miner, M.H. & Dwyer, S.M. (1997). The psychosocial development of sex offenders: Differences between exhibitionists, child molesters, and incest offenders. International Journal of Offender Therapy and Comparative Criminology, 41, 36-44
  71. Montana, S., Thompson, G., Ellsworth, P., Lagan, H., Helmus, L. & Rhoades, C.J. (2012). Predicting relapse for Catholic clergy sex offenders: The use of the static-99. Sexual Abuse: A Journal of Research and Treatment, 24, 575-590.
  72. Nunes, K.L., Firestone, P., Bradford, J.M., Greenberg, D.M. & Broom, I. (2002). A comparison of modified versions of the Static-99 and the Sex Offender Risk Appraisal Guide. Sexual Abuse: A Journal of Research and Treatment, 14, 249-265
  73. Panton, J.H. (1978). Personality differences appearing between rapists of adults, rapists of children and non-violent sexual molesters of female children. Research Communications in Psychology, Psychiatry & Behavior, 3, 385–393
  74. Parent, G., Guay, J.P. & Knight, R.A. (2011). An assessment of long-term risk of recidivism by adult sex offenders: One size doesn’t fit all. Criminal Justice and Behavior, 38, 188-209
  75. Pithers, W.D. (1990). Relapse prevention with sexual aggressors. In W. L. Marshall, D. R. Laws, & H. E. Barbaree (Eds.), Handbook of sexual assault: Issues, theories, and treatment of the offender (pp.231-255). New York: Plenum Press.
  76. Prentky, R.A. (2004). Can sex offender classification inform typologies of male batterers? A response to Holtzworth-Munroe and Meehan. Journal of Interpersonal Violence, 19, 1405-1411.
  77. Prentky, R.A., Knight, R.A., & Lee, A.F.S. (1997). Risk factors associated with recidivism among extrafamilial child molesters. Journal of Consulting and Clinical Psychology, 65, 141-149
  78. Quinsey, V.L. (1986). Men who have sex with children. In D. N. Weisstub (Ed.), Law and mental health: International perspectives (Vol. 2, pp.140-172). New York, NY: Pergamon Press.
  79. Quinsey, V.L., Harris, G.T., Rice, M.E. & Cormier, C.A. (1998). Violent offenders: Appraising and managing risk. Washington, DC: American Psychological Association
  80. Quinsey, V.L., Rice, M.E. & Harris, G.T. (1995). Actuarial prediction of sexual recidivism. Journal of Interpersonal Violence, 10, 85-105
  81. Reijnen, L., Bulten, E. & Nijman, H. (2009). Demographic and personality characteristics of Internet child pornography downloaders in comparison to other offenders. Journal of Child Sexual Abuse, 18, 611-622
  82. Rennison, C.M. & Rand, M.R. (2003). Criminal victimization, 2002. Washington, DC: U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.
  83. Rice, M.E. & Harris, G.T. (2002). Men who molest their sexually immature daughters: Is a special explanation required? Journal of Abnormal Psychology, 111, 329-339
  84. Salter, A. (1988). Treating child sex offenders and victims: A practical guide. Newbury Park, CA: Sage Publications.
  85. Schneider, S.L. & Wright, R.C. (2004). Understanding denial in sexual offenders: A review of cognitive and motivational processes to avoid responsibility. Trauma, Violence, & Abuse, 5, 3-20
  86. Scoones, C.D., Willis, G.M., & Grace, R.C. (2012). Beyond static and dynamic risk factors: The incremental validity of release planning for predicting sex offender recidivism. Journal of Interpersonal Violence, 27, 222-238
  87. Scott, R.L., & Stone, D.A. (1986). MMPI profile constellations in incest families. Journal of Consulting and Clinical Psychology, 54, 364-368
  88. Seto, M.C. (2008). Pedophilia and sexual offending against children: Theory, assessment, and intervention. Washington, D. C: American Psychological Association.
  89. Seto, M.C., Babchishin, L.P. & McPhail, I.V. (2013). What Else Distinguishes Intrafamilial and Extrafamilial Offenders Against Children. Proceedings from the 32nd Annual Research and Treatment Conference of the Association for the Treatment of Sexual Abusers. Chicago, IL
  90. Seto, M.C., Babchishin, K.M., Pullman, L.E. & McPhail, I.V. (2015). The puzzle of intrafamilial child sexual abuse: a meta-analysis comparing intrafamilial and extrafamilial offenders with child victims. Clinical Psychology Review, 39, 42-57
  91. Sexual Abuse. (2007). Title 18 U.S. Code, Sec. 2242, Chapter 109A
  92. Smallbone, S.W., Marshall, W.L. & Wortley, R. (2008). Preventing child sexual abuse: Evidence, policy and practice. Portland, OR: Willan Publishing.
  93. Stadtland, C., Hollweg, M., Kleindienst, N., Dietl, J., Reich, U. & Nedopil, N. (2005). Risk assessment and prediction of violent and sexual recidivism in sex offenders: Long-term predictive validity of four risk assessment instruments. Journal of Forensic Psychiatry & Psychology, 16, 92-108
  94. Storey, J.E., Watt, K.A., Jackson, K.J. & Hart, S.D. (2012). Utilization and implications of the Static-99 in practice. Sexual Abuse: A Journal of Research and Treatment, 24, 289-302
  95. Studer, L.H., Clelland, S.R., Aylwin, A.S., Reddon, J.R. & Monro, A. (2000). Rethinking risk assessment for incest offenders. International Journal of Law and Psychiatry, 23, 15-22
  96. Terry, K.J. (2013). Sexual offenses and offenders: Theory, practice, and policy (2nd Ed.). Belmont CA: Wadsworth
  97. Valliant, P.M. & Blasutti, B. (1992). Personality differences of sex offenders referred for treatment. Psychological Report, 71, 1067–1074.
  98. Ward, T. & Gannon, T.A. (2006). Rehabilitation, etiology, and self-regulation: The comprehensive good lives model of treatment for sexual offenders. Aggression and Violent Behavior, 11, 77-94.
  99. Ward, T. & Siegert, R.J. (2002). Toward a comprehensive theory of child sexual abuse: A theory knitting perspective. Psychology, Crime and Law, 9, 319-351
  100. Whitaker, D.J., Lutzker, J.R. & Shelley, G.A. (2005). Child maltreatment prevention priorities at the Centers for Disease Control and Prevention. Child Maltreatment, 10, 245–259.
  101. Williams, L. M. & Finkelhor, D. (1990). The characteristics of incestuous fathers: A review of recent studies. In W. L. Marshall, D. R. Laws, & H. E.
  102. Barbaree (Eds.), Handbook of sexual assault: Issues, theories, and treatment of the offender (pp.231-255). New York: Plenum Press.
  103. Woessner, G. (2010). Classifying sexual offenders: An empirical model for generating type-specific approaches to intervention. International Journal of Offender Therapy and Comparative Criminology, 54, 327-345.
--
Post your comment

Share This Article

Recommended Journals

Article Usage

  • Total views: 14742
  • [From(publication date):
    June-2016 - Jul 17, 2024]
  • Breakdown by view type
  • HTML page views : 13883
  • PDF downloads : 859
Top