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Journal of Behavior

Preliminary Results of Social Climate’s Impact on Treatment Progress of Juveniles with Sexual Behavior Problems

Original Research | Open Access Volume 2 | Issue 3 |

  • 1. Regent University School of Psychology & Counseling, Virginia Beach, USA
  • 2. Argosy University, Phoenix, USA
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Corresponding Authors
Lee A. Underwood, Regent University School of Psychology & Counseling, 1000 University Drive, CRB 215, Virginia Beach, Virginia 23464, USA, Tel: +1-757-630-4442
Abstract

Social climate is an important, yet less investigated subject as it relates to the treatment of juveniles with sexual behavior problems (JSBPs) in secure care facilities. This study evaluated and compared preliminary results of the perceived social climate of staff and juveniles in two secure care facilities in a southeastern state. Measures included the Ward Atmosphere Scale (WAS) and the Juvenile Sex Offender Assessment Protocol – II (JSOAP-II) to assess treatment progress. The JSOAP-II was administered at pre-test (intake) and at post-test (discharge). The WAS was a one-time administration upon admission. Subjects were 35 adjudicated male JSBPs and 21 staff. Staff and juvenile’s perceptions were found to be significantly different in the WAS System Maintenance domain. The study’s implications, suggestions for future research, and assessment practices implications are discussed.

Citation

Hoard P, Underwood L, Dailey F, Williams C, Etienne R (2017) Preliminary Results of Social Climate’s Impact on Treatment Progress of Juveniles with Sexual Behavior Problems. J Behav 2(3): 1014

Keywords
  • Secure care
  • Risk recidivism
  • Social climate
  • Sex offender treatment
  • Juveniles with sexual behavior problems
INTRODUCTION

Perpetrators of abuse are categorized by the United States Department of Justice into either adult or juvenile offenders [1] based on their age. Deviant sexual behaviors in juveniles have been found to be predictive of both sexual and non-sexual criminal behaviors into adulthood [2]. As such, more consideration has been spent on developing effective programs to prevent sexual assaults and address deviant sexual behavior in juveniles. Within the past 30 years, there has been a growth in the number of treatment programs designed for juveniles with sexual behavior problems (JSBP)[3]. This growth in programs, without proven effectiveness, has continued despite the increasing amount of literature over the past decades which highlight the negative, iatrogenic effects of placing delinquent peers together, questioning the continued use of restrictive environments such as secure-care and residential treatment centers [4,5,6].

Furthermore, the assessment and classification of particularly JSBPs has been inconsistently applied by providers across the nation [7] with inconsistent program efficacy results [8]. Best practice models support those programs that utilize interventions which are informed by current research [9]. Additionally, the treatment should closely follow the level of assessed risk that the juvenile poses to the community [10]. While most best practice models have focused on the specific interventions utilized in the treatment of JSBPs, as well as the most appropriate treatment environment, little research has focused on the social climate of those environments. Social climate is a construct used in this study which denotes the perceived social and emotional environmental makeup of a specific setting. In this study, the term is used synonymously with “ward atmosphere”. Nicholls, Kidd, Threader, and Hungerford [11] include the physical and social elements of the environment and their interactions in their identification of the concept.

However, there is a body of literature on adult correctional facilities concerning social climate. The adult literature suggests that the social climate of correctional facilities significantly impacts treatment success [12] and while there is some literature on social climate of juvenile secure care facilities, more is needed [13,14,6]. The aforementioned iatrogenic effects of secure-care programming also further suggest the potential link between social climate and treatment effectiveness [6]. The utilization of secure care facilities as a treatment option for offenders of all ages has seen considerable fluctuations in a number of juveniles being served over the past decades. The number of juveniles in secure care increased from approximately 81,000 individuals in 1980, to around 250,000 served in 2000 [15]. However, that number has since been on the decline [16]. This fluctuation in the number of juveniles in care has continued alongside an existing division in expert opinion on the overall benefits of secure care [17,18,19,20].

Furthermore, while research has shown continued support for the efficacy of community based treatment programs for juvenile offenders of all types [21,22], Underwood, Robinson, Mosholder, and Warren [20] note that a change has been occurring with a trend to rely more heavily on the juvenile justice system and secure care facilities to provide treatment for JSBPs in particular. Secure-care facilities can take different forms, but include detention centers, correctional facilities, and prisons. In many ways, secure-care facilities are the most extreme form of residential treatment [23]. These programs are designed to house youth, keeping them in a more restrictive environment, separate from the community. A unique feature of secure-care facilities over residential treatment facilities is the “lock-down” nature of a secure-care facility. The result has been an increased need for secure care facilities to be able to provide effective treatment to the juveniles that have been placed with them.

A review of the impact of social climate in secure care environments for juveniles is in order due to the continued recognition in the literature that social climate plays a significant role in treatment progress [13]. Hair [18] identified the inherent difficulties in conducting research into the effectiveness of different variables of secure-care. In his article, he argues that the inability of researchers to perform controlled laboratory experiments severely limits the investigators. As such, the value of data regarding juveniles in secure care environments gathered from reliable, valid assessment tools is of the utmost importance for research purposes. Notwithstanding these difficulties, many aspects of the interventions used in secure-care facilities for the treatment of JSBPs have been investigated [24,25]. However, social climate as a factor in treatment progress and symptom reduction has seen little research [6], despite being a concept that has been assumed for several decades [26].

There has been some growth in recent literature of studies focused on social and group climate, but currently remains a minimally addressed area of research for juveniles [13,14]. The social climate of inpatient hospital treatment units, in general, has been studied more thoroughly and found to have an impact on client satisfaction [27,28]. Although it is important to note that a direct link between social atmosphere and client outcomes has yet to be established. Jörgensen, Römma, & Rundmo [27] did find a connection between climate and symptom reduction, while acknowledging that more research was needed in this area. An important comment on this research is that this research centered on hospital inpatient units and not juvenile secure care facilities. As such, the current study seeks to further the existing body of knowledge on both the effects of a secure-care facility’s climate on JSBPs and their assessed risk for recidivism.

The climate of a facility can also be looked at from the view of the institution or the staff. Molleman and Leeuw [29], in their study of the influence that prison staff can have on inmate conditions, found that “staff and management can help or hinder the satisfaction of the needs of inmates, such as the need for autonomy and activities. That is, these factors are malleable and contribute to the explanation of perceived prison conditions” (p. 229-230). In other words, the attitudes and behaviors of the staff in secure facilities can have a direct impact on the social climate. Further findings indicate that the work situation of staff can also have a direct impact on the approach staff take with inmates and thus affecting the perceived climate of the facility [30]. Day, Casey, Vess, & Huisy [31], in their study of the prison climates of two Australian prisons, note the importance of assessing the staff and juveniles perceptions and the need for further studies on the issue. Furthermore, Collins and Nee [32] identify the prison environment and staff motivation as key factors that can enable or encumber change in sexual offenders. Additionally, Heynen, Van der Helm, Stams, & Korebrits [33] focus on the importance of staff support for particularly juvenile offenders in achieving positive treatment progress from secure-care facilities. As such, a thorough investigation of social climate must also take the staff and organization into account.

PURPOSE OF THE STUDY

The purpose of this study is to better understand the relationship between perceived social climate and treatment progress (as measured by changes in the level of assessed recidivism risk) in JSBPs residing in secure care environments. While information regarding a relationship between social climate and client satisfaction and motivation exists, data pertaining to the relationship between social climate and treatment progress of JSBPs remains unclear. Also, as previously stated, very little is known about the differences between staff and juvenile perceptions of social climate. The term staff is utilized in reference to the direct intervention employees of a secure-care facility whose jobs involve the direct supervision, monitoring and care of juveniles with sexual behavior problems. This study sheds additional light on the extent that both staff and juvenile perceptions of social climate impact the risk level of JSBPs.

METHODOLOGY

Instrumentation

Two primary instruments were utilized to assess the variables: the JSOAP-II, the WAS and demographic information on each of the subjects were collected through a review of the subject’s clinical file and intake assessments to the facility.

Juvenile Sex Offender Adolescent Protocol, 2nd Edition (JSOAP-II): The JSOAP-II assesses risk factors for both violent and sexual recidivism in juveniles developed by Prentky and Righthand [34]. The measure is designed for use with males 12-18 years of age. No cutoff scores have been provided for risk level and it is recommended that the JSOAP-II be used as a piece of a more comprehensive assessment and not alone [35]. The J-SOAP-II has four scales that assesses measures of sexual drive/preoccupation, impulsive/antisocial behavior, intervention variables such as treatment motivation, and community stability/ adjustment. Studies involving the JSOAP-II indicate moderate to high interrater reliability ranging from .75 to .91, as well as internal consistency alphas from .68 to .85 [34,36].

Ward Atmosphere Scale (WAS): Participants respond to 100 brief statements on the WAS (10 per scale), answering true or false whether the statement was indicative of their ward, originally developed by Moos and Houts [37]. Ten subscales tap three general dimensions: (1) Relationships, (2) Personal Growth, and (3) System Maintenance. The Relationship dimension includes the subscales: Involvement, Support, and Spontaneity. The Personal Growth dimension includes: Autonomy, Practical Orientation, Personal Problem Orientation, and Anger and Aggression. The three System Maintenance scales are: Order and Organization, Program Clarity, and Staff Control [38]. The WAS [37] measures perceived social climate and the 10 subscales have been shown to have respectable internal consistency (.68 to .83), high item-to-subscale correlations, and high test–retest reliability for all subscales [37]. Prior research demonstrated the content validity of the WAS using expert judges [39]; its criterion validity has also been established [40].

Demographic Questionnaire: The demographic questionnaire (Appendix 1) was developed and utilized to obtain conceptual information on a wide variety of areas. Information collected included 15 items regarding each subject. Some of the pertinent areas investigated by the questionnaire are the date of the first JSOAP evaluation, mental health diagnoses prior to and/ or during treatment, site where the juvenile received treatment for sexual behavior problems, number of victims, specific and adjudicated charges. The questionnaire was completed by a thorough review of each subject’s archival data file.

Research Question(s) and/or Hypotheses

The intersection of social climate and treatment progress is an important aspect of secure-care treatment that requires attention. The following research questions (RQ) and hypotheses (H) are presented. The study was conducted at two separate sites (A and B), both run by the same administration, but staffed by separate individuals. As such, it is assumed that while their social climate’s may be similar, it cannot be taken for granted. To account for any differences that may exist in the two sites, their results will also be analyzed and compared to one another along with the staff and juvenile results.

Research Questions

RQ1: Is there a statistically significant difference between the client treatment progress, (as measured by the change in JSOAP-II scale 3 scores) in site A and site B, which can be correlated to the social climate as measured by the WAS total scores) in site A and site B?

RQ2: Is there a difference between the WAS total scores of juveniles and staff in secure care Site A as compared to secure care Site B?

RQ3: Is there a difference between the WAS System Maintenance total scores of juveniles and staff in secure care Site A and secure care Site B?

RQ4: Is there a difference between the WAS Order and Organization scores of juveniles and staff in secure care Site A and secure care Site B?

RQ5: Is there a difference between the WAS Program Clarity scores of juveniles and staff in secure care Site A and secure care Site B?

RQ6: Is there a difference between the WAS Staff Control scores of juveniles and staff in secure care Site A and secure care Site B?

Hypotheses

The following hypotheses related to the RQs were developed for this study:

H1: There will be a statistically significant difference between the client treatment progress, (as measured by the change in JSOAP-II scale 3 scores) in site A and site B, which can be correlated to the social climate as measured by the WAS total scores) in site A and site B.

H2: There will be a statistically significant difference between the WAS total scores of juveniles and staff in secure care Site A and secure care Site B

H3: There will be a statistically significant difference between the WAS System Maintenance total scores of juveniles and staff in secure care Site A and secure care Site B.

H4: There will be a statistically significant difference between the WAS Order and Organization scores of juveniles and staff in secure care Site A and secure care Site B

H5: There will be a statistically significant difference between the WAS Program Clarity scores of juveniles and staff in secure care Site A and secure care Site B.

H6: There will be a statistically significant difference between the WAS Staff Control scores of juveniles and staff in secure care Site A and secure care Site B.

Research Methodology and Design

This study relied upon a correlational research methodology to examine the identified questions of how social climate and treatment progress are correlated. Social climate and treatment progress was measured through the use of the JSOAP-II and the Ward Atmosphere Scale. The results of these scales were analyzed for any existing correlation between them. An ex post facto design was used to investigate the predetermined variable of social climate and how it correlates with the treatment progress.

Population and Sampling

Subjects consisted of male juveniles who were adjudicated and sentenced by a court magistrate to a secure care program or a non- secure program for committing crimes that were sexually aggressive in nature. Subjects ranged in age from 12-20 years of age. Subjects’ ethnicities varied, as did their number of previous incarcerations, number of victims, and their experience in various systems of care prior to their enrollment in the Sexual Behavior Problem Treatment Program (SBPTP) treatment program. These juveniles were adjudicated from 2008 through 2014 and completed the state’s SBPTP intervention. Subjects resided in two locations: a secure care facility and a non-secure residential or community/outpatient-based clinic. The juveniles participated in an intensive treatment for juveniles with sexual behavior problems that are structured for individual, group and family counseling intervention methods.

Confidentiality was assured by the researcher by implementing a Human Subjects Review Committee (IRB). To ensure the confidentiality of institutionalized youth, a formal confidentially agreement between the program evaluator and JOJJ was executed. The principal investigator developed a coding system and assigned a code to each participant’s folder on a printed label. Only the assigned codes and not the subjects’ names were recorded on data collection documents. All data collection documents were electronic and encrypted with passwords and stored on a primary jump drive and back-up drive, both were password protected.

PROCEDURE

Subjects were chosen from archival data where those who completed the treatment program from 2008 to 2014. Data was collected from the subjects’ initial intake assessment into the program and at their discharge from the program. The assessments were conducted in a classroom setting or office after the provider received the state court mandate to assess the juveniles for risk and sex offender treatment and service needs. Prior to administration, the provider administered a verbal description of the assessment process and its use. Subjects were provided an opportunity to consent or dissent prior to completing the instruments. All subjects were provided directions and monitoring during the test administration process. Following the administration, the provider collected the data and it was securely stored for scoring at a later date [36].

STATISTICAL ANALYSIS

The statistical analyses used in this study are primarily t-tests and Factorial 2X2 ANOVAs. The first research question utilized a t-test to compare the change in JSOAP-II scale three scores. These results were compared with the Factorial 2X2 ANOVA results of the total WAS scores for juveniles and staff in the two sites. The remaining research questions utilized a Factorial 2X2 ANOVA to assess the effects of site and population on WAS scores (or the specific subscale of the WAS being addressed in each of the questions).

RESULTS

The respondents for the JSOAP-II scores consisted of 44 adjudicated juveniles with sexual behavior problems residing in secure care. The subjects range in age from 12 to 21 (as defined by state’s legal statutes) and comprised of the following ethnicities: African American (n = 20), Caucasian (n = 23), bi-racial (n =1; Caucasian and African American). 23 of the respondents on the JSOAP-II were from Site A and 21 were from Site B.

The respondents for the WAS consisted of 56 total respondents. These subjects included both adult staff (n = 21) as well as juveniles (n = 35). Demographic information on the WAS archival was inconsistent with only 19 out of the 56 subjects having any identifying information beyond their role. Of those 19, there were adult females (n = 8) with ages ranging from 23-56. One male, adult staff member aged 35 was identified. The rest of the subjects were male juveniles, housed between the two sites aged between 16 and 19 (n = 10). The total number of subjects from Site A (n = 32) was divided into staff (n = 6) and juveniles (n = 26). Similarly, Site B total subjects (n = 24) were also divided into staff (n = 15) and juveniles (n = 9).

The following results were found through the statistical analyses. They are presented in order by hypotheses.

H1: To address this first hypothesis, a t-test was utilized to find any significant difference between the two sites changes in JSOAP-II 3rd scale scores. No significant difference was found. See Table 1 and 2 for a summary of the results. Therefore, no comparisons could be made between the WAS total scores from the sites and the change in JSOAP-II scale three scores. As such, this hypothesis was rejected.

H2: A 2 x 2 ANOVA was conducted to evaluate the effects of site (Site A versus Site B) and position (juvenile versus staff) on WAS total scores. The results for the ANOVA indicated a significant main effect for site, F(1,52) = 5.17, p = .03, partial η2 = .09, a non-significant main effect for position, F(1,52) = .11, p = .74, partial η2 = .002, and a non-significant interaction between site and position, F(1,52) = .98, p = .33, partial η2 = .02. See Table 3 and 4 for a summary of the WAS total scores of the juveniles and staff as well as Site A and B. The site main effect indicated that Site A scored higher on the WAS total scores than Site B. As a result, the hypothesis was partially accepted.

H3: A 2 x 2 ANOVA was conducted to evaluate the effects of site (Site A versus Site B) and position (juvenile versus staff) on WAS System Maintenance scores. One case (21) was excluded as an outlier. The results for the ANOVA indicated a significant main effect for site, F(1,51) = 8.50, p = .005, partial η2 = .14, a significant main effect for position, F(1,51) = 10.25, p = .002, partial η2 = .17, and a non-significant interaction between site and position, F(1,51) = 2.39, p = .13, partial η2 = .05. See Table 5 and 6 for a summary of the WAS System Maintenance scores of the juveniles and staff as well as Site A and B. The site main effect indicated that Site A scored higher on the WAS System Maintenance Total scores than Site B. The position main effect indicated that staff scored higher than juveniles. As a result, the hypothesis was accepted.

H4: A 2 x 2 ANOVA was conducted to evaluate the effects of site (Site A versus Site B) and position (juvenile versus staff) on WAS Order and Organization scores. The results for the ANOVA indicated a non-significant main effect for site, F(1,52) = .94, p = .34, partial η2 = .02, a non-significant main effect for position, F(1,52) = 3.32, p = .07, partial η2 = .06, and a non-significant interaction between site and position, F(1,52) = 1.88, p = .18, partial η2 = .04. See Table 7 and 8 for a summary of the WAS Order and Organization scores of the juveniles and staff as well as Site A and B. As a result, the hypothesis was rejected.

H5: A 2 x 2 ANOVA was conducted to evaluate the effects of site (Site A versus Site B) and position (juvenile versus staff) on WAS Program Clarity scores. The results for the ANOVA indicated a significant main effect for site, F(1,52) = 3.90, p = .05, partial η2 = .07, a non-significant main effect for position, F(1,52) = .05, p = .82, partial η2 = .001, and a non-significant interaction between site and position, F(1,52) = 1.57, p = .22, partial η2 =.03. See Table 9 and 10 for a summary of the WAS Program Clarity scores of the juveniles and staff as well as Site A and B. The site main effect indicated that Site A scored higher on the WAS Program Clarity scale scores than Site B. As a result, the hypothesis was partially accepted.

H6: A 2 x 2 ANOVA was conducted to evaluate the effects of site (Site A versus Site B) and position (juvenile versus staff) on WAS Staff Control scores. The results for the ANOVA indicated a non-significant main effect for site, F(1,52) = .01, p = .93, partial η2 < .001, a significant main effect for position, F(1,52) = 3.93, p = .05, partial η2 = .07, and a non-significant interaction between site and position, F(1,52) = .04, p = .84, partial η2 =.001. See Table 11 and 12 for a summary of the WAS Staff Control scores of the juveniles and staff as well as Site A and B. The site main effect indicated that Site A scored higher on the WAS Staff Control scores than Site B. the position main effect indicated that staff scored higher than juveniles. As a result, the hypothesis was partially accepted.

Table 1: Descriptive Statistics for Hypothesis 1

Site N Mean Std. Deviation Std. Error Mean
  A 21 4.7190 3.19666 .69757
  B 23 3.5565 4.17643 .87085

Table 2: Independent Samples Test for Equality of Means for Hypothesis 1

  F Sig. t df Sig. (2-tailed) Mean Difference
Equal Variances Assumed 1.273 .266 1.029 42 .005 1.16253
Equal Variances Not Assumed     1.042 40.809 .128 1.16253

Table 3: Descriptive Statistics for WAS Total Score

Subjects Mean Std. Deviation N
Staff 507.0952 62.85690 21
Residents 517.5714 43.96007 35
Total 513.6429 51.55136 56

Table 4: Univariate Analysis of Variance for WAS Total Score for Hypothesis 2

Source Type III Sum of Squares  f  Mean Square    F Sig. Partial η²
site2 13034.846   13034.846 5.172 .027 .090
Position2 285.918   285.918 .113 .738 .002
Site2 * Position2 2480.501   2480.501 .984 .326 .019

Table 5: Descriptive Statistics for WAS System Maintenance

Subjects Mean Std. Deviation  N
Staff 58.38 8.576 21
Residents 55.03 8.002 35
Total 56.29 8.307 56

Table 6: Univariate Analysis of Variance for System Maintenance (without outlier) for Hypothesis 3

Source Type III Sum of Squares  df  Mean Square    F Sig. Partial η²
site2 2563.696  1 2563.696 8.501 .005 .143
Position2 3090.572  1 3090.572 10.248 .002 .167
Site2 * Position2 721.807  1 721.807 2.393 .128 .045

Table 7: Descriptive Statistics for WAS Order and Organization

Subjects Mean Std. Deviation  N
Staff 58.38 8.576 21
Residents 55.03 8.002 35
Total 56.29 8.307 56

Table 8: Univariate Analysis of Variance for Order and Organization for Hypothesis 4

Source Type III Sum of Squares  df  Mean Square    F Sig. Partial η²
site2 61.985  1 61.985 .944 .336 .018
Position2 217.610  1 217.61 3.315 .074 .060
Site2 * Position2 123.324  1 123.324 1.879 .176 .035

Table9: Descriptive Statistics for WAS Program Clarity

Subjects Mean Std. Deviation  N
Staff 53.43 10.097 21
Residents 56.71 9.803 35
Total 55.48 9.953 56

Table 10: Univariate Analysis of Variance for Program Clarity for Hypothesis 5

Source Type III Sum of Squares  df  Mean Square    F Sig. Partial η²
site2 365.169  1 365.169 3.895 .054 .070
Position2 4.976  1 4.976 .053 .819 .001
Site2 * Position2 147.238  1 147.238 1.571 .216 .029

Table 11: Descriptive Statistics for WAS Staff Control

Subjects Mean Std. Deviation  N
Staff 53.43 10.097 21
Residents 56.71 9.803 35
Total 55.48 9.953 56

Table 12: Univariate Analysis of Variance for Staff Control for Hypothesis 6

Source Type III Sum of Squares  df  Mean Square    F Sig. Partial η²
site2 .752  1 .752 .007 .933 .000
Position2 420.263  1 420.263 3.930 .053 .070
Site2 * Position2 4.168  1 4.168 .039 .844 .001
DISCUSSION

The first hypothesis stated that a correlation would be found between treatment progress and social climate. The data indicated that a significant difference exists in social climate between the sites. However, due to the lack of significant differences that were noted in treatment progress between Site A and Site B, no conclusions were able to be drawn from the data. The second hypothesis examined the WAS total scores. This hypothesis stated that a significant difference would be noted between sites as well as between position of staff or juvenile for the total score. This hypothesis focused on social climate as a complete whole. The data indicated that a significant difference exists between Site A and B, but not between position. As such, this hypothesis was partially accepted.

The third hypothesis began breaking the concept of social climate into its smaller parts by exclusively addressing the WAS domain of System Maintenance. It was hypothesized that this domain could yield some of the highest and most significant differences between staff and juveniles because it encompasses the subscales that directly deal with staff-juvenile interaction. When examining the differences between the staff and juveniles this domain appeared to be pertinent. The results showed that this hypothesis was accepted as significant differences between sites and position were identified.

The fourth hypothesis then moved the focus to a more specific section of the System Maintenance domain, Order and Organization. This and the following hypotheses sought to break down social climate to its most basic elements and examine where significant differences may lie. Order and Organization on the WAS is a subscale that assesses the degree of order or chaos perceived at the facility. This hypothesis was rejected as no significant differences were identified between staff and juveniles or between Site A and Site B.

The fifth hypothesis examined Program Clarity, another subscale of the System Maintenance domain. Program Clarity is defined as “the extent to which clients know what to expect in their day-to-day routines and the explicitness of the program rules and procedures” (p. 330) [38]. The data indicated that a significant difference exists between Site A and B, but not between position. As such, this hypothesis was partially accepted. The final hypothesis addressed the last subscale of the WAS System Maintenance domain, Staff Control. This subscale assesses the degree to which staff implements measures to exert the necessary control of the juveniles. The scale gauged the control present in the facility. The results showed that this hypothesis was accepted as significant differences between sites and position were identified.

The findings in this study regarding the System Maintenance domain and its subscale of Staff Control, help to identify these areas as the primary ways in which the perceptions of staff and juveniles differ. As previously discussed, much of the current research on the discrepancy between staff and juvenile perceptions is still underdeveloped and lacking in depth and detail [38,41,42].

The results of this preliminary study are not surprising in that they are consistent with the existing literature in noting discrepancies between staff and juveniles. However, in helping to specify the Staff Control subscale of the WAS, the importance of this discrepancy becomes much more important. As Molleman and Leeuw [29] noted in their study, “staff and management can help or hinder the satisfaction of the needs of the population, such as the need for autonomy and activities. That is, these factors are malleable and contribute to the explanation of perceived prison conditions” (p. 229-230). In other words, the control and management of the facility by staff can have a direct impact on important factors related to treatment, motivation, and satisfaction of juveniles. These findings show that staff and juveniles often have very different experiences of staff control, which allows for many questions regarding the degree of actual control exhibited by staff, the effectiveness of staff interventions, and the ability for policy makers to make informed judgments about staff and programming at secure care facilities, given the inconsistent perceptions of such.

LIMITATIONS

The results of this preliminary study are encouraging regarding social climate’s impact on the treatment of JSBPs in secure. When considering the limitations of this study, adjustments to its design and methodologies, should be considered. The following section identifies limitations followed by suggestions on how these might be improved.

The size of the sample population of this study is a limiting factor. This study was utilized a total pool size of 56 subjects. However, given the specific population (JSBPs) being examined, small sample sizes are commonly found in the literature. This number was then further reduced when comparing the different position and site. An adverse result of this compartmentalizing is that the statistical power was reduced along with the size of each group. Comparisons across site and position were unable to be effectively made.

This study was unable to examine the WAS and JSOAP-II scores of the same subjects. The result of this is that the averages of each site were used. Therefore, the findings were restricted. Were this not a limitation, a much more in-depth analysis of the data could have yielded far more significant findings and implications. This inherently allows for a level of discrepancy between how the social climate of the site was perceived by the different individuals responding to the two different scales. Staff turnover, time, different personalities of the juveniles all can skew the data in ways that could lead to erroneous inferences from the results. This is especially possible with concepts like social climate that are so inherently fluid and open to fluctuations.

Furthermore, the dependent variable of this study, treatment progress, was assessed through the changes in pre and post treatment JSOAP-II scale 3 scores. While this is not a unique or unprecedented method of assessing treatment progress [36], it is complex. Using a single assessment tool to evaluate treatment progress leaves room for improvement. These outcomes did not take into account treatment over time, such as 6-12month follow-up; doing so could further measure treatment gains over time.

IMPLICATIONS

This study yielded several significant results that shed more light on the current understanding of social climate and juveniles with sexual behavior problems in secure care. These implications can be organized into two different categories of theoretical and clinical implications.

Theoretical implications

This study found a significant difference between staff and juvenile perceptions of social climate, specifically the Staff Control subscale. This is important as it shows the more specific part of social climate that can be affected by position. The natural question that flows from these results is why. Why does the staff perceive their level of control of the facility to be higher than the juveniles’ perception of staff control? The answer is unknown at this point, but could lie in a number of different places.

The aspect of Staff Control being rated higher by staff brings to the foreground the nature of social climate and how it is being measured. The existence of this discrepancy between staff and juveniles indicates the necessity for the construct to be even more fully understood as an individual perception and not merely objective reality. The significance of these findings gains further importance when it is connected with the previously identified literature that specifies the impact that staff behaviors and attitudes can have on treatment motivation and outcomes [14,30,33]. The Staff Control subscale could be linked closely with what Van der Helm, Stams, & Van der Laan, [14] argue as being one of the primary factors that shape social climate. Additionally, when considering the dangers of deviancy training inherent in secure care treatment, the aspect of Staff Control may be a significant factor in identifying and implementing strategies to minimize this effect. Therefore, when treatment facilities are taking the social climate into consideration, it is of the utmost importance that Staff Control is understood as being one aspect in particular that can stand out as an anomaly amongst the other elements, particularly in how it is perceived and experienced by those in different positions.

Clinical Implications

The significance of “Staff Control” being rated differently by staff and juveniles is an important note given clinical importance of social climate. With the ability to isolate this element of social climate as one that is more directly impacted by position, this study highlights the clinical significance of incorporating this into the treatment of juveniles with sexual behavior problems. Previously identified research has shown the dangers of deviancy training and the motivational importance of social climate in mental health treatment. The staff control sub-scale helps to lend more importance to both of these elements of the treatment provided by secure care facilities. Staff control must be well assessed and understood by behavioral health providers working with this population in this setting. It is possible to speculate how inappropriate staff interactions could easily endanger clinical progress being made in groups or individual therapy. Furthermore, given the fact the environment is an important element of the treatment provided by staff in secure care facilities, this study underscores the clinical significance of accurately assessing and managing this aspect of social climate [5,14].

RECOMMENDATIONS

These findings presented in this study provide crucial information regarding the social climate of secure care facilities. However, while this study has helped answer some questions, it has equally helped identify several more. These questions can be seen as important paths that future studies are recommended to follow in the further pursuit of a more accurate and full understanding of social climate.

The first recommendation drawn from this study is to more fully explore the link between treatment progress and social climate. This study identified the significance of social climate and how it’s perceived by both staff and juveniles. However, the study fell short to establish the hypothesized relationship between the perceived social climate and treatment progress. Therefore, the first recommendation is for researchers to continue to examine the correlation between treatment progress and social climate. A future study might be to ensure that the same subjects complete the scales used to assess both constructs. Furthermore, because social climate is not a construct that will be stable throughout a juvenile’s entire treatment, reassessments of the social climate throughout the juveniles stay at the facility is recommended. Additionally, the concept of treatment progress is also a complex subject. Therefore, it is also recommended that treatment progress be assessed through multiple tools to provide a fuller picture of each subject’s progress.

The second recommendation is to fully investigate the concept of social climate and the difference between staff and juveniles. As previously mentioned, social climate is not a construct that can be assumed to be consistent. Reassessing the same subjects over an extended period would allow for a more robust examination of the subject. Moreover, this study utilized one tool to assess social climate. It is recommended that future studies utilize additional scales in assessing the construct to allow for comparisons across the scales and a dynamic investigation of the subject. These studies should also take care to analyze the various subscales and elements of social climate to better identify how they interact with one another as well as the construct as a whole.

Given the difference noted in social climate between staff and juveniles on the subscale of “Staff Control”, future research could help shed further light on the subject of staff turnover and longevity. Further studies are encouraged to take the length of a staff’s tenure into consideration to see what effect experience and amount of training has on the perceived social climate of the facility. This could greatly assist directors and managers in identifying and rewarding effective staff and helping to mold newer staff into more effective treatment providers.

Additionally, it is recommended that social climate be examined against other known constructs in JSBP treatment. Specifically, it is recommended that any possible relationship between JSBPs in secure care and anxiety, trauma, cognitive distortions and depression. While this study sought to investigate the relationship between social climate and treatment progress, several other noteworthy aspects of JSBP and juvenile offender treatment could be correlated to social climate. It is recommended that future researchers work to begin investigating any links that may exist which could aid treatment providers and program managers in developing and running more effective treatment programs for JSBPs.

CONCLUSION

This study sought to examine the significance of social climate in the secure care treatment of juveniles with sexual behavior problems. The study also examined what differences may exist between staff and juvenile perceptions of the construct of social climate in secure care. Finally, the study shed light onto how the social climate of two different sites may be perceived differently by the staff and juveniles at each.

The data obtained from this study identified that the domain of System Maintenance and specifically the subscale of Staff Control to be significantly different between staff and juveniles. Furthermore, the results of the study noted significant differences between two sites with regards to the social climate identified in each. As a result, this study adds support to the growing body of knowledge that supports the importance of social climate in secure care treatment. The analysis provided in the previous chapter examines in detail the full implications of these findings. Moreover, the chapter detailed the future recommendations for both researchers and treatment providers in light of the findings from this study. All in all, the construct of social climate was found to be complex and dynamic.

DISCLOSURE

The authors declare no conflicts of interest.

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Received : 13 Jun 2017
Accepted : 05 Dec 2017
Published : 18 Dec 2017
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