Quality of life and illness perception in working and sick-listed chronic RSI patients

Objective To study differences between working and sick-listed chronic repetitive strain injury (RSI) patients in the Netherlands with respect to indices of quality of life and illness perception.
Introduction
The growing global concerns in the 1990s about the effects of work-related upper extremity musculoskeletal disorders (i.e. Repetitive Strain Injuries, or RSI) on the health and well-being of workers, and about the economic and social impact of these conditions, has led to a variety of research on the international level (e.g. Sluiter et al. 2001; Lee et al. 2005; Bongers et al. 2006; Waters et al. 2007), and in the Netherlands governmental actions, new rules, regulations, and professional guidelines were developed (Sluiter et al. 2001; Douwes et al. 2001; NVAB 2003; Blatter et al. 2004). In addition, the epidemiological studies begun in the 1990s that tried to unravel the multifactorial predisposing and precipitating factors of RSI complaints managed to find several significant factors, albeit the perceived relationships were neither very pronounced nor very specific (e.g. Bongers et al. 2006).
In contrast to the recently expressed concerns about multidisciplinary curative actions in the US (Feuerstein and Harrington 2006), many preventive ergonomic actions have been introduced in high risk sectors in the Netherlands during the “Covenant” periods. To prevent long-term work disability, occupational physicians have learned to start taking action as early as three weeks after onset of sickness absence for RSI-like complaints. Long-term sickness absence because of RSI-complaints has decreased in the past few years (Bongers et al. 2006). Moreover, when workers’ sickness absence is of very long duration, some employers invest in their workers’ health by paying for intensive multidisciplinary treatments aimed at a return to work (Meijer et al. 2006).
Despite all these changes, the number of members in, for example, the Dutch RSI Patients’ Association doubled during the last seven years, and prevalences of over 25% for upper extremity complaints are still found; rates are comparable to other European countries (Bongers et al. 2006). All medical professionals deal with patient groups that have medical disorders that may be cared for but not cured with additional costs (Meerding et al. 1998), and also therefore, increasing interest in the patient’s perspectives has grown in the last decade. Perspectives about what are important points of interest to deal with in treatment and knowledge about their quality of life both reveal interesting information for specific focus in treatment (Gafni et al. 1998). Illness perception may be distorted more in work-related disorders compared to other diseases when the ability to return and to keep on working in the job that may have caused the health complaints is questioned. Up to now, only little or even no information was available on chronic RSI patients’ quality of life and illness representation (Picavet and Hoeymans, 2004; Broadbent et al. 2006). Therefore, in 2005 a study that aimed to describe the working vs. sick-listed RSI patients’ perspectives in the Netherlands with respect to their complaints, quality of life, and illness perception was begun in a large group of chronic RSI patients.
Methods
Population
Patients with RSI were identified by approaching all 3,250 members of the Dutch RSI patients’ association. The Dutch RSI patient association was started 11 years ago. In the Netherlands, patients with the same disease are allowed and administratively helped by Governmental Services to join and start an association. Their goal is to gather and spread relevant information to all patients with the same disease in The Netherlands. In addition, their input in sickness-related policy matters is increasingly asked for. Members that were registered in March 2005 were eligible for inclusion. This group defined the study population in this cross-sectional study.
Data collection
In April 2005 questionnaires were sent by the secretariat of the RSI patients’ association to the home addresses of all their current members. An accompanying letter was included from the patients’ association. Patients were requested to complete a set of self-report measures. Return envelopes that were addressed directly to the research institute were included as well. One week later, a reminder letter was sent to all members. Data collection was stopped four weeks after sending the reminder. A total of 1,185 (36%) questionnaires were returned by mail.
Outcome measurements
Quality of life was assessed in three ways: Through seven subscales of the Dutch version of the 36-item Short Form Health Survey (Ware and Sherbourne 1992; Aronson et al. 1998): physical role functioning, emotional role functioning, social functioning, pain, mental health, vitality, and physical functioning. Scores ranged between 0 and 100 (higher scores indicated better functioning). Visual analogue scales (VAS) (Streiner and Norman 2003) were used to rate the level of present general quality of life with respect to health (0 = the worst imaginable; 10 = the best imaginable) and to rate the level, retrospectively, of the estimated general quality of life with respect to health before the RSI complaints started (0 = the worst imaginable; 10 = the best imaginable). The patients were also asked to report on their current work-ability by means of an 11-point scale (ranging from 0 for the least ability imaginable to the participant’s own maximum level of 10, the highest level imaginable) (e.g. Croon et al. 2005).
The brief illness perception questionnaire (IPQ-B) (Broadbent et al. 2006) assessed cognitive illness perception through items on illness “consequences”(how much does your illness affect your life?), “identity” (how much do you experience symptoms from your illness?), “timeline” (how long do you think your illness will continue?), “personal control” (how much control do you feel you have over your illness?), “treatment control” (how much do you think your treatment can help your illness?). It assessed emotional illness perception with items on illness “concern” (how concerned are you about your illness?) and “emotions” (how much does your illness affect you emotionally? [e.g. does it make you angry, scared, upset, or depressed?]), and it assessed illness understanding with an item on illness “comprehensibility” (how well do you feel you understand your illness?). Scores ranged from 0 to 10, and averages on the group level were calculated (Broadbent et al. 2006). The last question of the IPQ-B is open ended, centring on the most important factors believed to cause the illness.
The demographic, complaint-related, and work activities characteristics were used to describe the two groups. Demographics included gender, age, education, and current work activities. Complaint-related variables were pain and stiffness/tingling intensity (assessed with VAS scales ranging from 0 = no complaints at all to 10 = the worst complaints imaginable) (Streiner and Norman 2003), pain duration (in years), extent of pain complaints (number of upper body regions affected) (Sluiter et al. 2001), ranging between 0 and 16. Work activity characteristics were assessed by four psychosocial work characteristics subscales: work pressure, social support from colleagues or supervisor, and job control (from the “Dutch Questionnaire on the Experience and Assessment of Work”, VBBA) (Van Veldhoven and Meijman 1994; Sluiter et al. 2003). VBBA subscale scores ranged between 0 and 100, with higher scores being more unfavourable.
In order to compare the two groups of RSI patients, we classified the “working” group as those patients that had been present at their work for a minimum of 8 h during the previous week, and the “sick-listed” group were RSI patients with a sickness absence certificate following the Dutch social system (i.e. longer than 1 year sick-listed, or those that stated that they did not work according to their contract hours during the previous week before they filled in the questionnaire).
Statistical analysis
Scale scores were calculated according to the original descriptions of the scales used. VAS scores were calculated in mm, ranging from 0 to 100. Means and standard deviations were calculated for every outcome. We divided the respondents in two groups, one group of patients that indicated they worked in a paid job, and one group of patients that indicated they were sick-listed. After testing assumptions, either multivariate ANOVA controlling for age, gender, and education level or nonparametric tests (Mann–Whitney) were performed to test differences between the two groups of RSI patients; P-values < 0.01 were considered significant. Average differences over 1 on a 10-point scale and over 10 on a 100-point scale were considered clinically important in terms of effect size (Streiner and Norman 2003).
Results
A total of 1,185 respondents responded, and data from 1,121 questionnaires could be used in the analyses for this study. Table 1 provides a description of demographic and both complaint-related and work-related variables for the groups under study.
Table 1Total study population and working vs. sick-listed groups: gender, education, age, pain intensity, pain duration, work status, and work-abilityTotal group (n = 1,121)Working group (n = 745)Sick-listed group (n = 376)Difference between groups: P-valueGender (% females)676278a < 0.001Education (% high )6771 60a < 0.001Age in years (mean (SD))40.8 (8.7)40.0 (8.3)42.3 (9.4)a < 0.001Pain intensity (0–100) (mean (SD))41.3 (25.4)36.2 (24.7)51.6 (23.9)a < 0.001Stiffness/tingling intensity (0–100) (mean (SD))37.8 (26.8)33.7 (25.8)45.7 (27.0)a < 0.001Pain duration in years (mean (SD))5.8 (3.2)5.6 (3.1)6.2 (3.3)0.01Pain extent (mean (SD) number of body regions)6.4 (3.9)5.7 (3.6)7.7 (4.1)a < 0.001Work pressure (0–100) (mean (sd))b48.4 (21.1)48.7 (20.8)45.9 (23.6)0.885Social support from colleagues (0–100) (mean (SD))b27.8 (20.1)27.4 (20.0)31.5 (20.4)0.157Social support from direct supervisor (0–100) (mean (SD))b35.1 (26.2)34.4 (26.1)42.0 (26.1)0.138aKolmogorov–Smirnov test P-values < 0.01bFilled in by n = 84 in the sick-listed group
RSI patients in the sick-listed group were two years older on average, and this group contained a relatively higher proportion of women and lower proportion of highly educated persons. In the sick-listed group, 76% was sick-listed longer than one year.
In both groups, complaints were present for several years and extended over several upper body regions. In both groups, over 85% received a diagnostic label, provided by a medical professional, that belong to the umbrella term RSI. With respect to complaint-related variables, the patients in the sick-listed group reported significantly more pain in more regions, and they reported more stiffness/tingling complaints. The sick-listed group reported significantly lower ability to work, and no differences between groups were found in the psychosocial work characteristics experienced. With respect to co-morbidity, no other diseases were reported by 46% in the sick-listed group compared to 64% in the working group; depression and burnout were reported by 12 and 11% in the sick-listed group versus 6 and 5% in the working group. In the working patient group, 35% filled some kind of administrative function, 11% worked in IT, 10% worked in a physical job, and 10% in a management function. In both groups, almost 80% reported long- or short-term overexertion during work as the only main cause of the onset of their illness.
Experienced quality of life on the studied SF-36 subscales is shown in Tables 2 and 3. In Table 2, a matrix of zero-order correlation coefficients is shown for the complete population between work-ability, pain intensity, pain duration, the SF-36 subscales, and the eight B-IPQ dimensions. The highest correlation coefficients were found between the two SF-36 subscales mental health and vitality (r = 0.75), and the SF-36 subscale pain and VAS scale pain intensity (r = 0.72).
Table 2Matrix of zero-order correlation coefficients between 1: work-ability, 2: pain intensity, 3: pain duration, 4–10: SF-36 subscales, and 11–18: the B-IPQ outcomes (n varies between 1,027 and 1,114)1234567891011121314151617181 work-ability–2 pain intensiy−0.48–3 pain duration−0.080.12–4 sf physical role0.54−0.45−0.02–5 sf mental health0.34−0.250.030.32–6 sf emotional role0.26−0.180.050.31–7 sf social functioning−0.010.05−0.01−0.07−0.010.09–8 sf pain0.61−0.72−0.050.590.310.24−0.03–9 sf vitality0.40−0.300.010.400.750.47−0.080.39–10 sf physical functioning0.60−0.52−0.180.480.270.22−0.020.610.38–11 consequences−0.610.510.08−0.58−0.35−0.27−0.001−0.62−0.41−0.49–12 timeline−0.130.180.32−0.10−0.030.010.01−0.15−0.07−0.160.19–13 personal control0.44−0.36−0.0040.350.330.18−0.0010.420.350.34−0.36−0.06–14 treatment control0.29−0.19−0.090.160.100.050.040.210.150.15−0.16−0.160.33–15 identity−0.510.640.07−0.54−0.29−0.230.04−0.67−0.35−0.490.680.23−0.33−0.10–16 concern−0.380.46−0.03−0.46−0.35−0.270.01−0.49−0.37−0.300.570.16−0.36−0.100.58–17 comprehensibility0.20−0.160.040.220.200.14−0.030.190.210.12−0.210.000.310.22−0.16−0.29–18 emotional response−0.380.35−0.07−0.46−0.51−0.390.01−0.41−0.47−0.250.590.08−0.35−0.080.480.64−0.27–Table 3Mean (SD) scores by groups on SF-36 subscales physical role functioning, mental health, emotional role functioning, social functioning, pain, vitality, physical functioning, and work-abilityTotal group (n = 1,121)Working group (n = 745)Sick-listed group (n = 376)Difference between groups: P-valueSF-36 scales (0–100) (mean (SD)) Physical role functioning34.7 (38.2)43.4 (39.2)17.0 (29.0)a < 0.001 Mental health68.5 (16.7)70.6 (15.6)64.3 (18.0)a < 0.001 Emotional role functioning73.9 (38.3)78.7 (34.8)64.1 (43.1)a < 0.001 Social functioning54.5 (9.4)54.6 (8.9)54.2 (10.4)0.208 Pain54.7 (21.6)60.7 (19.2)42.7 (22.0)a < 0.001 Vitality53.6 (17.9)55.7 (17.1)49.3 (18.6)a < 0.001 Physical functioning76.5 (18.0)81.7 (14.6)65.9 (19.6)a < 0.001 Work-ability (0–10) (mean (SD))5.4 (2.7)6.6 (1.8)3.1 (2.6)a < 0.001aKolmogornov–Smirnov test P-values < 0.01
As shown in Table 3, the average scores of all scales but social functioning differed significantly between the two groups to the detriment of the sick-listed RSI patients on the other SF-36 subscales. Clinically relevant differences were found in work-ability and in the SF-36 scales for physical role functioning, emotional role functioning, pain, and physical functioning.
General quality of life with respect to present health was rated as 52.7 on average (SD: 24.4) in the total group of RSI patients, and the average in the working group and sick-listed groups were 57.9 and 42.2, respectively. The group difference was significant (P-value Kolmogornov–Smirnov test < 0.001). In contrast, the estimated general quality of life with respect to health before the onset of RSI complaints was rated as 83.1 on average (SD: 15.4) in the total group of RSI patients. There was only a non-significant difference in the average scores between groups (83.1 in the working group and 83 in the sick-listed group (P-value Kolmogornov–Smirnov test = 0.796)). Combining these results, the general quality of life with respect to health was subjectively decreased by 37% in the total group over time. However, the difference in decrease was significant (Kolmogornov–Smirnov test, P-value < 0.001): only 31% in the working group but 49% in the sick-listed group of patients.
Scores on the eight illness perception dimensions are shown in Table 4.
Table 4Mean (SD) illness perception scores (B-IPQ) by groupsIllness perception dimensionsTotal group (n = 1,121)Working group (n = 745)Sick-listed group (n = 376)Difference between groups: P-valueConsequences6.3 (2.6)5.6 (2.5)7.6 (2.1)a < 0.001Timeline8.3 (2.0)8.2 (2.1)8.5 (1.7)0.557Personal control 6.3 (2.0)6.7 (1.8)5.6 (2.1)a < 0.001Treatment control 5.2 (2.6)5.7 (2.5)4.4 (2.6)a < 0.001Identity6.2 (2.4)5.8 (2.4)7.1 (2.1)a < 0.001Concern5.5 (2.6)5.2 (2.6)6.1 (2.6)a < 0.001Comprehensibility6.9 (2.1)7.1 (2.0)6.6 (2.3)0.014Emotional response5.4 (2.6)5.1 (2.6)6.0 (2.5)a < 0.001aKolmogornov–Smirnov test P-values < 0.01
With the exception of the dimension timeline and comprehensibility, there was a significant difference in the six other illness perception dimensions between the two groups. Clinically relevant differences between the two groups to the detriment of the sick-listed RSI patients were found for the illness perception dimensions of “consequences”, “personal-” and “treatment-control”, and “identity”.
Discussion
The aim of the present study was to describe working vs. sick-listed RSI patients’ perspectives in the Netherlands in 2005 with respect to their complaints, quality of life, and illness perception. The sick-listed RSI patients reported more severe and extensive complaints in the upper extremity, but the long duration (6 years) of their complaints was comparable to the working RSI patients. The sick-listed patients, however, experienced a considerably more decreased quality of life because of their complaints, as well as more distorted illness perceptions.
The quality of life in sick-listed patients was lower than that of the working patients when the SF-36 subscales scores were taken into account. Interestingly, both groups showed comparable but low social functioning scores (averaging around 55). This was also actually quite low compared to a group of patients with rheumatoid arthritis, who averaged over 70 and compared with a small sample of Dutch workers with RSI who averaged 79 (Sprangers et al. 2000; Picavet and Hoeymans 2004). The experienced quality of life decrease over time was found to be substantial in both groups, which might be explained by the severity, duration, and extent of the reported complaints. It is possible to argue that the anchor question that was used to calculate the quality of life decrease was posed post-hoc. But that was one of the proposed solutions among quality of life researchers in the debate about changed perspectives and response shift: by asking for the two rates at a given time in the form of an existing test, there cannot be any recalibration, re-evaluation of re-prioritization, and re-conceptualization (Osborne et al. 2006; Visser et al. 2005).
This may have been the first time that illness representation was assessed in a large group of RSI patients using the recently described brief illness perception questionnaire (IPQ-B) (Broadbent et al. 2006). Illness representation covers the dimensions of illness identity, consequences, cause, timeline, and cure or control. These perceptions about the illness influence patient behaviours, and changing perceptions may improve recovery (e.g. Petrie et al. 2002). If an average difference of over 1 on a 0–10 point scale is considered clinically relevant, illness consequences, personal control, treatment control, and identity (i.e. the number of symptoms because of the illness) clearly differed between sick-listed and working RSI patients. We believe that it would be useful to focus future informational treatment strategies in the sick-listed patient group on changing their illness perception.
We successfully compared two fairly large groups of chronic RSI patients with respect to their current complaints, quality of life, and illness perception. However, some methodological considerations are in place: (1) the used case-definition to identify sick-listed RSI patients may have influenced the outcomes although it is not clear in what direction this may have caused a bias; (2) because not all variables complied with all assumptions for multivariate testing, that would have allowed for controlling for different possible confounders, non-parametric test outcomes have been presented. Post-hoc multivariate testing did not show any differences in the outcomes as were presented. (3) It is acknowledged that a relatively modest proportion of the total study population responded. Considering the variation in responses and the main purpose of this study, the response should not be considered as a bias. Our population, however, is a selected population in several ways and this has been described in the methods section: participants were members of the RSI patients association, they had long-term complaints, it was not possible to take a random sample in the theoretically existing Dutch group of chronic RSI patients who work or are sick-listed, and the number of responders of the total sample was not as much as would be desirable. However, the diagnostic label that was communicated with over 85% of these chronic patients by different physicians was one of the syndromes that fall under the umbrella diagnosing label of “RSI” (Sluiter et al. 2001). In addition, comparisons between two groups of this specific group of patients were reported upon for this study. Summarizing, besides its possible shortcomings, this study is thought to be unique with respect to studying a large group of chronic RSI patients as most of the published literature on work-related upper extremity musculoskeletal disorders deal with acute and sub-acute populations.
It would be interesting to study how the relation between the variables under study developed over time: if the severity of complaints, quality of life level, and illness perception dimensions are relatively stable over time in this subgroup of chronic patients, they could be used as prognostic factors to decide on interventions with respect to future ability to work. It may also be that if activities are increased because of work resumption, they will act as “intervention” in the place-then-train ratio and influence the measures over time. We do know that the differences in the severity of RSI complaints and quality of life indices, to the detriment of the sick-listed group of RSI patients, could be used as an indication for referral to multidisciplinary treatment programmes, because all of these parameters have recently been shown to be influenced positively, even in patients with long-term complaints (Meijer et al. 2006).


The management of anemia in pediatric peritoneal dialysis patients

Anemia is common in chronic renal failure. Guidelines for the diagnosis and treatment of anemia in adult patients are available. With respect to the diagnosis and treatment in children on peritoneal dialysis, the European Pediatric Peritoneal Dialysis Working Group (EPPWG) has produced guidelines. After a thorough diagnostic work-up, treatment should aim for a target hemoglobin concentration of at least 11 g/l. This can be accomplished by the administration of erythropoietin and iron preparations. Although there is sufficient evidence to advocate the intraperitoneal administration of erythropoietin, most pediatric nephrologists still apply erythropoietin by the subcutaneous route. Iron should preferably be prescribed as an oral preparation. Sufficient attention has to be paid to the nutritional intake in these children. There is no place for carnitine supplementation in the treatment of anemia in pediatric peritoneal dialysis patients.
The treatment of anemia in chronic kidney disease has been summarized in the NKF/DOQI guidelines [1], which have recently been updated [2]. European best practice guidelines have also been recently published [3]. These published guidelines pay no, or very limited, attention to the special situation in children.
The European Pediatric Peritoneal Dialysis Working Group (EPPWG) was established in 1999 by pediatric nephrologists with a major interest in peritoneal dialysis and has, among other things, published guidelines on commencing elective chronic peritoneal dialysis [4]. One of the functions of the group is to establish expert guidance in important clinical areas associated with peritoneal dialysis in conjunction with other members of the multidisciplinary team. These guidelines were initiated and discussed at meetings of the group and developed by e-mail discussion to develop a consensus of opinion based upon cumulative clinical experience and reported studies. The present guidelines apply to the management of anemia in pediatric peritoneal dialysis patients.
Definition of anemia
More than in adult patients, hemoglobin and hematocrit values are age dependent in children [5], (Tables 1, 2, 3, 4). Also, concentrations of ferritin, transferrin, and iron are dependent on age. Early iron deficiency may be diagnosed by an increase in hypochromic red blood cells [6]. The technique for measuring this parameter is not available everywhere. Since children with renal failure generally do not have underlying co-morbidity contributing to anemia, it is obvious that in children on peritoneal dialysis normal hematocrit levels should be aimed for (opinion). The work-up of the anemic child is not different from the work-up that is advocated for adult patients by the DOQI guidelines, although the importance of a stool test for occult blood may be less useful in this age group [2, 7] (opinion):Iron deficiencyClinical historyAssessment of nutritional statusHemoglobin and hematocritRed blood cell indicesReticulocyte countIron parametersSerum ironTable 1. Reference ranges of anemia parameters in children [5]: hemoglobin and hematocrit (M male; F female)Hemoglobin (g/dl)Hematocrit (%)1–3 days14.5–22.545–702 months9.0–14.028–426–12 years11.5–15.535–4512–18 years, M13.0–16.037–49                      F12.0–16.036–46Table 2. Reference ranges of anemia parameters in children [5]: ferritinFerritin (ng/ml)Newborn25–2001 month200–6002–5 months50–2006 months–15 years7–140Table 3. Reference ranges of anemia parameters in children [5]: iron (M male; F female)Iron (μg/dl)0–2 months100–2502–12 months40–1001–12 years50–120Thereafter, M50–160                    F40–150Table 4. Reference ranges of anemia parameters in children [5]: transferrinTransferrin (mg/dl)Newborn130–275Adult200–400
After this work-up has been completed, iron and/or erythropoietin therapy should be initiated to obtain a target hemoglobin concentration of at least 11 g/dl (hematocrit 33%), although there is a tendency to increase this target [8] (opinion).
A target hemoglobin concentration of at least 11 g/l should be aimed for in children on peritoneal dialysis (opinion).
Erythropoietin
Most experience has been obtained with subcutaneous administration of recombinant human erythropoietin [9, 10]. Erythropoietin is available as erythropoietin alpha and beta. Erythropoietin alpha and beta differ noticeably in their formulation excipients. No clear prescription schedules for starting erythropoietin are available for children, and schedules provided in the literature vary greatly. It seems reasonable to start with a subcutaneous dosage of 50–100 U/kg body weight 2 or 3 times per week. In some selected patients (particularly if started in the predialysis period) a lower frequency or dosage can be attempted. In studies in adult patients once weekly subcutaneous administration of erythropoietin was effective for the treatment of renal anemia [11, 12, 13]. It is well known that younger children need relatively more erythropoietin than older ones [14] (evidence). Maintenance recommendations vary from 300 U/kg/week for a child with a weight of <20 kg to 120 U/kg/week for a child with a weight of >30 kg [10] (opinion). Each child will need the dosage titrated to achieve the target hemoglobin concentrations. For the titration of erythropoietin the DOQI guidelines can be used [2]. If the increase in hematocrit after initiation of erythropoietin therapy is less than 2% over a 2- to 4-week period, the dose should be increased by 50%. If the absolute rate of increase in hematocrit after initiation of erythropoietin therapy or after a dose increase exceeds 8% per month, the weekly dose of erythropoietin should be decreased by 25%.
Side effects of erythropoietin therapy are rare; increased clotting tendency, hypertension, and seizures are to be considered the consequence of the therapeutic effect rather than an adverse effect of the preparation. Nevertheless, blood pressure should be carefully monitored during therapy.
Recently, attention was drawn to a severe side effect of erythropoietin therapy, pure red blood cell aplasia due to the occurrence of neutralizing antierythropoietin antibodies [15, 16]. Subsequent investigations showed that this was in most cases associated with subcutaneously administered erythropoietin alpha from one brand, although some cases have also been described using the other brand available on the market. The application of erythropoietin beta is associated with a much lower incidence of this severe side effect. In many countries the subcutaneous administration of erythropoietin alpha is discouraged at present. The administration of darbepoetin alpha is not associated with pure red blood cell aplasia, but it should be remembered that experience with this drug is still limited.
Subcutaneous administration of drugs is psychologically distressing, especially for children (opinion). The use of ultrafine needles and special injection pens may help to alleviate the upset. In adult peritoneal dialysis patients a noncompliance with erythropoietin administration was reported in between 35% and 55% of patients [17, 18]. For children no data on erythropoietin are available, but from clinical practice it is known that subcutaneous administration is frightening and a source of conflict between child and caregivers. Limited data are available on the compliance with another drug which has to be administered subcutaneously, recombinant human growth hormone. Noncompliance was reported to be between 50% and 91% [19, 20, 21]. In one study it was reported that noncompliance increased significantly from 41% at 1 year to 91% at 2 years [21]. Intravenous administration is a more expensive alternative, but will rarely be applied in pediatric peritoneal dialysis patients [22].
Despite some initial discouraging but still frequently cited reports in the literature, erythropoietin can be administered very well by the intraperitoneal route [23, 24]. If erythropoietin is administered in a small volume of dialysis fluid (50-ml bags are commercially available), bioavailability is similar to that after subcutaneous administration of the same amount of hormone [25] (evidence). Mean dosage needed for maintaining the target hematocrit decreased from 279 to 194 U/kg/week if the drug was administered in a 50-ml dialysis bag during the daytime [26, 27]. In a more recent study in 20 patients on nightly intermittent peritoneal dialysis mean dosage was 179 U/kg/week [28]. Dialysis adequacy is a major factor of concern in such a regimen: KT/V urea was ≥2.2 in the group studied. However, in some patients the application of intraperitoneal erythropoietin may be limited by the inability to obtain adequate dialysis (opinion). In patients not achieving adequate dialysis, the daytime period should be used for additional dialysis exchanges. In this category, that period will not be available for intraperitoneal erythropoietin therapy. Peritonitis frequency does not need to increase using intraperitoneal erythropoietin: the two pediatric studies reporting peritonitis rates mention one episode every 14.7 and 11.2 treatment months, respectively [19, 21]. One early study in children was broken off because of a high peritonitis rate [29]; possibly this was due to insufficient training of the caregivers.
Recently, an erythropoietin analogue was developed (darbepoetin alpha or NESP = novel erythropoiesis stimulating protein), which is a hyperglycosylated erythropoiesis-stimulating protein with a presumed threefold longer half-life than erythropoietin in man [30, 31, 32, 33, 34] (evidence). In children a two- to fourfold longer half-life was reported [35]. The pharmacokinetics when administered intravenously and subcutaneously appear to be the same in adult and pediatric patients. A randomized comparative study of darbepoetin and erythropoietin in pediatric patients with chronic or end-stage renal disease is just starting. There are no data available with respect to the intraperitoneal administration of darbepoetin.
The development of an orally active agonist of the erythropoietin receptor will be an interesting future feature [36].
Erythropoietin resistance may be due to a number of causes:InfectionHyperparathyroidismMalnutritionHemolytic disordersFolate or vitamin B12 deficiencyUnderdialysisVitamin C deficiencyACE inhibitorsAnti-erythropoietin antibodies
Since there is an excellent review of these in the adult guidelines [2, 3, 37], and they are not essentially different in children, they are not discussed in detail here. In children responding poorly to erythropoietin therapy, special emphasis should be put on the possible contribution of inflammation or hyperparathyroidism [38]. The possible occurrence of pure red cell aplasia due to the development of neutralizing antierythropoietin antibodies has been discussed before.
Erythropoietin should be administered by the subcutaneous or intraperitoneal route in children on peritoneal dialysis (evidence). Although there is sufficient evidence to advocate the intraperitoneal administration of erythropoietin, most pediatric nephrologists still apply erythropoietin by the subcutaneous route in their peritoneal dialysis patients.
Iron
Iron supplementation is indicated in virtually all pediatric patients with renal anemia who are treated with erythropoietin. According to the DOQI guidelines, transferrin saturation should be maintained above 20% and serum ferritin concentration above 100 ng/ml [2] (evidence). There is no reason to anticipate that these guidelines should be different for children and for adults (opinion). It may be difficult to maintain sufficient iron stores in children on peritoneal dialysis, using oral iron preparations only. Iron supplements should be given to prevent iron deficiency and to maintain adequate iron stores. A dosage of 2–3 mg/kg body weight per day is recommended and administered in two to three divided doses either 1 or 2 h after food.
Iron supplements should not be added to the infant formula or nutrition supplements [39] (evidence). If possible, they should be prescribed with vitamin C to enhance absorption (opinion). However, it is important not to oversupplement with vitamin C for risk of increased oxalate formation. Iron supplements should ideally not be taken with cereals and legumes, tannins (tea, cocoa, chocolate) and dairy products as these interfere with absorption. Micronutrient supplements should also be prescribed following individualized dietary assessment and should account for the potential peritoneal dialysis losses of folic acid and vitamins C and B6. Compliance with oral iron preparations for micronutrient supplements may be difficult and must be reinforced by both medical and dietetic staff [39, 40].
Parenteral iron preparations, commonly used in patients on hemodialysis, are more difficult to apply in children on peritoneal dialysis. After the recent approval of iron gluconate, iron sucrose, and iron saccharate, the application of iron dextran should also be abandoned in the United States [41, 42, 43, 44] (evidence). Recommended dosage is 2 mg iron per kg per week for intravenous iron sucrose treatment [7]. Before starting intravenous therapy the administration of a test dosis is recommended. It is clear, however, that the intravenous administration of iron preparations is cumbersome, and oral administration is preferred [39] (opinion). In rare cases, for example with noncompliance with oral medication, intermittent intravenous administration will be indicated.
Limited but positive experience has been obtained with the intraperitoneal administration of iron dextran, both in rats and men [45, 46, 47]. Reports on the intraperitoneal administration of iron gluconate or iron sucrose are lacking.
Iron should preferably be prescribed as an oral preparation (evidence). In rare cases intermittent intravenous administration will be indicated.
Carnitine
Several studies in adult patients suggest that intravenous supplementation with l-carnitine reduces requirements for erythropoietin by 38–50% [48, 49, 50] (opinion). Published data on the effect of l-carnitine supplementation on the treatment of anemia in children are very scarce. One study showed an increase in the hematocrit by 34% in two children on hemodialysis with l-carnitine supplementation without modification of erythropoietin dosage [51]. Another study in 16 children on dialysis, of whom five were on peritoneal dialysis, showed no beneficial effect of oral supplementation with l-carnitine on erythropoietin requirement [52].
There is no precise place for carnitine supplementation in the treatment of anemia in pediatric peritoneal dialysis patients (opinion).

peritoneal dialysis
children
erythropoietin
iron
carnitine


Fatty acid-induced mitochondrial uncoupling in adipocytes as a key protective factor against insulin resistance and beta cell dysfunction: a new concept in the pathogenesis of obesity-associated type 2 diabetes mellitus

Type 2 diabetes is associated with excessive food intake and a sedentary lifestyle. Local inflammation of white adipose tissue induces cytokine-mediated insulin resistance of adipocytes. This results in enhanced lipolysis within these cells. The fatty acids that are released into the cytosol can be removed by mitochondrial β-oxidation. The flux through this pathway is normally limited by the rate of ADP supply, which in turn is determined by the metabolic activity of the adipocyte. It is expected that the latter does not adapt to an increased rate of lipolysis. We propose that elevated fatty acid concentrations in the cytosol of adipocytes induce mitochondrial uncoupling and thereby allow mitochondria to remove much larger amounts of fatty acids. By this, release of fatty acids out of adipocytes into the circulation is prevented. When the rate of fatty acid release into the cytosol exceeds the β-oxidation capacity, cytosolic fatty acid concentrations increase and induce mitochondrial toxicity. This results in a decrease in β-oxidation capacity and the entry of fatty acids into the circulation. Unless these released fatty acids are removed by mitochondrial oxidation in active muscles, these fatty acids result in ectopic triacylglycerol deposits, induction of insulin resistance, beta cell damage and diabetes. Thiazolidinediones improve mitochondrial function within adipocytes and may in this way alleviate the burden imposed by the excessive fat accumulation associated with the metabolic syndrome. Thus, the number and activity of mitochondria within adipocytes contribute to the threshold at which fatty acids are released into the circulation, leading to insulin resistance and type 2 diabetes.
Introduction
Type 2 diabetes mellitus is generally associated with an enhanced energy intake and too little physical exercise. Also genetic factors determine the susceptibility to develop this disease. Whole-body insulin resistance and a state of low grade inflammation are early marker of the disease process [1]. Subsequently, hyperglycaemia develops due to an accelerated decline in beta cell function [2–4]. Type 2 diabetes mellitus is often accompanied by other co-morbidities such as hypertension and dyslipidaemia. Together, they constitute the metabolic syndrome [2].
Here we present the concept that removal of fatty acids within white adipocytes by fatty acid-induced uncoupled mitochondrial β-oxidation protects the organism against fatty acid leakage out of adipocytes, thereby preventing fatty acid-induced insulin resistance in liver and muscle and lipotoxicity in pancreatic beta cells. A consequence of this concept is that mitochondrial dysfunction in adipocytes, either inherited or acquired, makes the organism more prone to develop insulin resistance and type 2 diabetes.
Mitochondria and fatty acids
One of the main functions of mitochondria, in addition to producing ATP, is to remove fatty acids by β-oxidation. In this way, mitochondria are able to remove NEFA and to protect the organism against fatty acid-induced insulin resistance and pancreatic beta cell lipotoxicity. β-Oxidation can take place in all cell types relevant for glucose homeostasis, including muscle, liver and adipocytes. During this process, fatty acids are oxidised in the mitochondrial matrix by NAD+ and flavin adenine dinucleotide (FAD), yielding acetyl coenzyme A, which is further degraded to CO2 by the citric acid cycle. The resulting NADH and FADH2 need to be recycled into NAD+ and FAD by the respiratory chain so that additional fatty acid molecules can be oxidised. This requires a supply of ADP, which is converted into ATP by respiratory chain activity. The rate of conversion of ATP back into ADP, which is determined by the metabolic activity of the cell, determines the rate at which fatty acids can be removed by mitochondrial activity. If the capacity of the cell to oxidise fatty acids is to be enhanced, ATP needs to be reconverted into ADP at an increased rate. This occurs during exercise in contracting muscle. The resulting enhanced rate of ADP generation provides a major additional sink for the oxidation of fatty acids within the body. Only when mitochondria are in the uncoupled state can regeneration of NAD+ and FAD occur without the conversion of ATP into ADP. The released energy is then converted into heat. Uncoupling is a physiological adaptation process, normally regulated by specific proteins [5]. It is remarkable that, like uncoupling proteins, fatty acids are capable of inducing mitochondrial uncoupling, especially when their concentrations exceed the binding capacity of fatty acid binding proteins [6–8]. This implies that when unbound fatty acids are present in the cytosol of cells, mitochondria become less efficient at ATP production and generate more heat during the oxidation of NADH and FADH2 derived from food.
Mitochondrial uncoupling in adipocytes by fatty acids may protect the organism against fatty acid-induced insulin resistance and lipotoxicity
White adipocytes contain large amounts of mitochondria in their tiny cytosolic compartment [9, 10]. There is no obvious reason why these cells need such a large capacity to produce ATP. We propose that, when uncoupled by fatty acids, these mitochondria prevent the release of fatty acids out of the adipocytes when the antilipolytic action of insulin is attenuated.
Evidence is accumulating that inflammation of adipose tissue is an early step in the pathogenesis of type 2 diabetes. The combination of excessive food intake with a sedentary lifestyle results in the formation of large adipocytes overloaded with triacylglycerols. Through as yet unknown mechanisms the adipose tissue becomes inflamed and infiltrated by leucocytes. This leads to the release of inflammatory cytokines such as TNF-α [11–14], a potent inducer of insulin resistance in adipocytes which also induces lipolysis. As a result, fatty acids are released out of the large triacylglycerol pool [15]. We propose that, initially, a part of these fatty acids are removed inside adipocytes by partially uncoupled mitochondrial β-oxidation. In doing so, these mitochondria create a threshold for fatty acid release into the circulation, which would otherwise trigger the development of whole-body insulin resistance and pancreatic beta cell lipotoxicity, the latter expected to occur when the body cannot utilise these released fatty acids as fuel, for example, in response to high food intake and little physical exercise. Our proposed mechanism is outlined in Fig. 1. When low amounts of fatty acids are released out of the triacylglycerol pool in insulin-resistant adipocytes, these fatty acids can be removed by coupled β-oxidation. The rate of fatty acid removal by this pathway is determined by the rate of ADP regeneration within adipocytes, which is likely to be a more or less constant factor, merely determined by cellular metabolism and not affected by variations in the lipolytic rate. We propose that, when the rate of fatty acid release exceeds the rate of fatty acid removal by coupled β-oxidation, the increase in cytosolic concentrations of fatty acids not bound to binding proteins (unbound) induces a partial uncoupling of the mitochondria. Uncoupling by fatty acids has been shown in multiple in vitro experiments [5–8, 16]. Evidence of uncoupling in vivo is provided by a study in which exposure of heart muscle to fatty acids resulted in a decrease in ATP production and a concomitant increase in oxygen consumption [17]. When uncoupled, the mitochondria are able to remove much larger quantities of fatty acids through generation of heat. The degree of uncoupling increases in with further elevations in fatty acid concentration, thus generating more heat. This represents a dynamic adaptation of the efficiency of the mitochondrion, which is determined by the intracellular concentration of fatty acids. If, however, the rate of fatty acid release exceeds the maximum clearance rate, fatty acids may reach concentrations that are toxic to the mitochondrion [18]. At this point β-oxidation capacity collapses and fatty acids are released out of adipocytes and redistributed over other tissues in the body. These ectopic triacylglycerol deposits are associated with the development of insulin resistance in muscle and liver and lipotoxicity in pancreatic beta cells [19]. At this stage of the disease process physical exercise will, by virtue of the generation of large amounts of ADP in muscle tissue, protect against lipotoxicity and the development of insulin resistance. This is because the muscle switches to β-oxidation to regenerate ATP when fatty acids reach a concentration sufficient to make the muscle resistant to insulin-stimulated glucose uptake [20, 21].
Fig. 1Consequences of fatty acid release from the adipocyte triacylglycerol pool. In insulin-sensitive adipocytes, fatty acid concentrations are kept low by insulin-induced antilipolytic action, re-esterification of fatty acids and mitochondrial β-oxidation. TNF-α induces insulin resistance and lipolysis. At low cytosolic concentrations of unbound fatty acids, the flux through mitochondrial β-oxidation is limited by the rate of ADP generation by cellular metabolism. At intermediate concentrations of unbound fatty acids, uncoupling of mitochondria is induced leading to continuous oxidation of fatty acids, independent of ADP supply. This process generates heat and keeps cytosolic fatty acid concentrations low. When the rate of fatty acid release from the triacylglycerol pool exceeds the rate of fatty acid removal, high cytosolic concentrations of unbound fatty acids develop, which induce mitochondrial damage [18]. This results in a decline in the capacity to remove fatty acids and the release of large amounts of fatty acids into the circulation. Unless these are removed by muscle activity they form ectopic triacylglycerol deposits and induce whole-body insulin resistance and beta cell damage. Dotted arrows indicate consequences; continuous arrows, fluxes
Discussion
In our model for the development of obesity-induced whole-body insulin resistance and beta cell damage leading to type 2 diabetes, we propose a key role for fatty acid removal by adipose tissue mitochondria. The disease process, as outlined in Fig. 2, is initiated by the development of cytokine-induced adipose tissue insulin resistance [11–15] and results in the release of fatty acids into the cytosol of the adipocytes. Further increases in cytosolic fatty acids induce mitochondrial dysfunction [18], decreasing the rate of β-oxidation, augmenting the fatty acid concentration, leading to their release into the circulation. These fatty acids are responsible for the development of insulin resistance in liver and muscle and lipotoxicity in pancreatic beta cells. Fatty acids do not appear to induce insulin resistance in adipocytes [22], which otherwise would create a positive feedback loop whereby the release of fatty acids induces additional insulin resistance and further promotes the release of fatty acids.
Fig. 2Proposed sequence of events leading to the development of hyperglycaemia during the metabolic syndrome. When adipocytes become overloaded with triacylglycerol, low-grade inflammation develops and inflammatory cytokines such as TNF-α induce insulin resistance in the adipocytes. This results in an elevated state of lipolysis. When fatty acids are inadequately removed within adipocytes because of mitochondrial dysfunction (for example, induced by fatty acids or HAART therapy, fatty acids appear in the circulation, where they induce insulin resistance of muscle and liver and malfunction of pancreatic beta cells. The elevated circulating fatty acid concentrations may also uncouple mitochondria in artery wall smooth muscle cells, thereby elevating the risk of hypertension [46]. Thiazolidinediones (TZDs) ameliorate the disease process in two ways: (1) by creating more mitochondria in adipose cells [23, 36, 37], thereby enhancing the capacity for oxidation of fatty acids; and (2) by enhanced re-esterification of fatty acids [39, 40]
Is there any evidence to support our model? Several studies have shown that in adipose tissue from obese animal models and humans, mitochondrial (mt) DNA copy number and expression of mitochondrial genes is decreased [23, 24].
In the diabetic state, mitochondrial β-oxidation of fatty acids was found to be attenuated. In addition, mitochondria showed an abnormal morphology [24]. These data support the concept of mitochondrial dysfunction in adipose tissue in states of obesity and type 2 diabetes.
Furthermore, intake of high-fat food by healthy persons rapidly increases the basal metabolic rate. This increase is blunted in obese individuals, whereas obese individuals exhibit an increased thermogenesis. These observations are suggestive for a rapid effect of ingested fatty acids on thermogenesis by mitochondrial uncoupling. The data also suggest that, in obese individuals, mitochondria are already uncoupled or damaged and less responsive to further fatty acid-induced uncoupling [25].
In vitro studies have shown that fatty acid-induced uncoupling of the mitochondrial respiratory chain depends on the chemical nature of these fatty acids. Unsaturated fatty acids, such as oleic acid, are better uncouplers than saturated fatty acids [8]. This could imply that the inclusion of saturated fatty acids in the diet makes mitochondria less prone to uncoupling, resulting in the earlier release of fatty acids, i.e. at a lower fatty acid level.
A further implication of our model is that a decline in mitochondrial function in adipocytes reduces the ability of these cells to store triacylglycerol. Inadvertently released fatty acids out of the triacylglycerol pool enter the circulation and are redistributed in other tissues. This occurs, for example, in individuals starting on highly active antiretroviral therapy (HAART) [26–29]. The nucleoside analogues included in HAART inhibit mtDNA polymerase and induce a ∼30–50% reduction in mtDNA content in adipocytes and other tissues. HAART is associated with the redistribution of peripheral fat to the central and other compartments and with an elevated risk of developing the metabolic syndrome and type 2 diabetes. We see this clinical phenotype as a result of release of fatty acids by peripheral adipocytes, which in turn is due to a decrease in mitochondrial capacity to remove fatty acids. The fatty acids, after entering the circulation, induce insulin resistance and lipotoxicity to pancreatic beta cells and become stored as ectopic triacylglycerol deposits.
Another example of a mitochondrial dysfunction is represented by patients carrying a 3243A>G mutation in mtDNA. This mutation results in an attenuated mitochondrial function. Most of these patients develop the maternally inherited diabetes and deafness (MIDD) syndrome. Remarkably, these patients usually have a BMI of <25 kg/m2. Furthermore, they exhibit ectopic triacylglycerol deposits in multiple tissues [30–33]. This clinical picture suggests the attenuated storage of triacylglycerol in adipose tissue. Around mid-life, these patients show a decrease in insulin secretion, which may result from lipotoxicity to pancreatic beta cells.
Congenital lipodystrophy is another clinical example showing that an inadequate storage of triacylglycerol in adipocytes contributes to ectopic triacylglycerol deposits and the development of severe whole-body insulin resistance and diabetes [34].
In contrast, improved mitochondrial function specifically in adipocytes is seen in individuals taking thiazolidinediones. These drugs are widely used to ameliorate whole-body insulin resistance in patients suffering from type 2 diabetes mellitus and the metabolic syndrome. These drugs bind to peroxisome proliferator-activated receptor-γ receptors which are highly expressed in adipocytes and in cells from the immune system, but low in liver and muscle [35]. These drugs increase mitochondrial copy number and mitochondrial gene expression specifically in adipose tissue [23, 36, 37]. Clinically, these drugs improve storage of triacylglycerol in peripheral adipocytes and ameliorate fatty acid-related insulin resistance. Patients taking these drugs tend to store more triacylglycerol in their adipocytes, leading to weight gain [38]. Together, these clinical data suggest that correct mitochondrial function is needed for adequate storage of fatty acids as triacylglycerol in adipocytes. By this means the organism is protected against the fatty acid-induced development of insulin resistance and lipotoxicity to the pancreas.
As thiazolidinediones also induce the expression of genes involved in the neogenesis of glycerol, these drugs also enhance the re-esterification of fatty acids [36, 39, 40]. This also contributes to the removal of fatty acids from the circulation and protects adipocyte mitochondria against fatty acid-induced damage. Because part of the glycerol in adipocytes is synthesised through pathways that are dependent upon mitochondrial function [36], this suggests that changes in mitochondrial function also may affect the rate of glycerol production and thereby the rate of fatty acid esterification.
To be able to perform, uncoupled β-oxidation mitochondria require the presence of sufficient amounts of oxygen. It has been suggested that a state of hypoxia occurs in expanding adipose tissue during the development of obesity and that this state may contribute to the development of the metabolic syndrome [41, 42]. Our model predicts that hypoxia in adipocytes would lead to a reduced rate of fatty acid removal inside these cells and to more fatty acid release into the circulation.
The sensitivity of an individual to the development of type 2 diabetes as a result of lifestyle is determined by genetic factors. Multiple genetic variants that modulate the risk of an individual for the development of diabetes have been identified, including genetic variants related to mitochondrial function. A high penetrance mutation in mtDNA has been found to be associated with the MIDD syndrome. This mutation predominantly affects the activity of complex I of the respiratory chain [43]. In the same biochemical pathway a mutation in the LARS2 gene, which encodes mitochondrial leucyl-tRNA synthetase 2, also modulates the risk for diabetes [44]. Furthermore, genetically determined changes in expression levels of components of the mitochondrial respiratory chain have been found to be associated with an increased risk of developing type 2 diabetes mellitus [45]. These genetic factors are likely to result in a decreased capacity of the mitochondria to remove fatty acids through uncoupled β-oxidation. Thereby, a genetic predisposition can lower the threshold for fatty acid release by adipocytes into the circulation and as a result enhance the risk for type 2 diabetes.
Our model of the pathogenesis of type 2 diabetes mellitus requires experimental verification of several points, and it certainly does not exclude the involvement of additional factors such as the coregulation of whole-body insulin action and insulin secretion through adipokines and the involvement of uncoupling proteins in setting the threshold for fatty acid-induced uncoupling of mitochondria. However, we see the way fatty acids interact with mitochondria in the cytosol of adipocytes as a major initiating event in the disease process leading to the metabolic syndrome and type 2 diabetes mellitus.

fatty acids
adipocytes
type 2 diabetes mellitus
mitochondria
thiazolidinedione
haart


Assessing Sexual Arousal with Adolescent Males Who Have Offended Sexually: Self-Report and Unobtrusively Measured Viewing Time

Sexual arousal was assessed using three approaches: the Affinity (Version. 1.0) computerized assessment of unobtrusively measured viewing time (VT), Affinity self-report ratings of sexual attractiveness, and a self-report sexual arousal graphing procedure. Data were collected from 78 males, aged 12–18 (M=15.09; SD=1.62), who acknowledged their sexual assaults. The pattern of responses to all three assessment techniques was remarkably similar, with maximal sexual interest demonstrated and reported for adolescent and adult females. Both self-report procedures could significantly distinguish those adolescents who assaulted a child from those who assaulted peers or adults. The self-report procedures could also significantly discriminate those adolescents with male child victims. The Affinity VT approach significantly differentiated those adolescents who assaulted male children from those who assaulted other individuals. No assessment technique could accurately identify those adolescents with exclusively female child victims. Overall, the results suggest that structured, self-report data regarding sexual interests can be useful in the assessment of adolescents who have offended sexually.
Introduction
Much of the treatment that was provided in the 1980's and 1990's to adolescents who offended sexually was predicated on the notion that deviant sexual interests played a critical role in the sexual assaults. For example, adolescents were often asked to track their sexual interests in violence and/or prepubescent children for lengthy time periods by completing deviant fantasy logs and charts and to participate in punishment-based procedures, such as covert sensitization, to reduce the strength and frequency of their presumed deviant sexual interests. In the last several years, however, this heightened focus on the role of deviant sexual arousal has shifted considerably; in part because it is now recognized that most adolescents who commit a sexual offense do not display primarily deviant sexual interests. For example, in their analysis of archival penile plethysmograph (PPG) data, Seto, Lalumière, and Blanchard (2000) reported that 25% (or 10 out of 40) of a small sample of adolescents who had offended sexually demonstrated maximal sexual interest in prepubescent children. With an overlapping yet augmented sample, Seto, Murphy, Page, and Ennis (2003) found that 30% (76 out of 253) of adolescents who had offended sexually responded equally or more to child stimuli during PPG assessments. In a study of 136 adolescents who had committed a sexual offense, Worling (2004) found that 36% of the adolescents were rated by clinicians as having sexual interests in prepubescent children and/or sexual violence. Although deviant sexual interests likely play a role in the etiology and/or maintenance of adolescent sexual offending for some adolescents, there are likely other factors to consider such as intimacy deficits, antisociality, attitudes supportive of sexual offending, and opportunity, for example.
Measurement of Sexual Arousal
Given the assumption that individuals will be reluctant to reveal their sexual thoughts and feelings during an interview, some believe that it is necessary to utilize a physiological measure of sexual interest. The most popular technique for measuring sexual arousal with adult males is the PPG. Although it has been argued by some that the PPG can provide valuable information for adult male clients who have offended sexually (Lalumière & Harris, 1998; Seto, 2001), there are some concerns regarding the reliability and validity of PPG data collected from adult males (Konopasky & Konopasky, 2000; Marshall & Fernandez, 2000). There are also several ethical and empirical concerns regarding the use of the PPG with adolescents (Becker & Harris, 2004; Hunter & Lexier, 1998; Worling, 1998). For example, adolescence is a period of emerging sexual development and teenagers are continuously developing and refining their sexual scripts, identities, and preferences. The potential for iatrogenic harm from exposing adolescents to visual and/or auditory depictions of deviant sexual activities is considerable, yet this has never been examined. Second, there is little compelling evidence regarding the reliability or validity of a PPG procedure with adolescents. Indeed, in studies with adolescents, PPG data are significantly influenced by such variables as the adolescent's age (Kaemingk, Koselka, Becker, & Kaplan, 1995) and history of physical and sexual abuse (Becker, Hunter, Stein, & Kaplan, 1989; Becker, Kaplan, & Tenke, 1992). Furthermore, although PPG data are predictive of subsequent sexual offending for adults (Hanson & Bussière, 1998; Hanson & Morton-Bourgon, 2004), the available research with adolescents indicates that there is no significant relationship between phallometrically-measured sexual deviance and sexual assault recidivism (Gretton, McBride, Hare, O’Shaughnessy, & Kumka, 2001; Gretton et al., 2005). Becker et al. (1992) also found that a majority of adolescents who denied their sexual offenses provided invalid deviant-arousal data. In a chart-review study by Seto et al. (2000), it was found that PPG data were only moderately discriminative for adolescent males who sexually assaulted male victims and that adolescents who offended against female children could not be differentiated from a nonoffending population. Hunter, Becker, and Goodwin (1994) similarly found that only those adolescents with male victims demonstrated significant deviant arousal using the PPG. In their review of the research, Becker and Harris (2004) concluded that the PPG may be useful only for the following adolescent clients: (i) older teenage males, (ii) individuals who acknowledge their sexual assaults, and (iii) those who offend sexually against males.
Given the scientific and ethical concerns regarding phallometric assessment, a number of researchers and clinicians have begun to use an alternative physiological measure: unobtrusively measured viewing time (VT). With this procedure, clients are asked to rate the sexual attractiveness of photographs of a variety of models while the response time to provide the ratings is unobtrusively recorded. The assumption underlying this technique is that people will look longer at stimuli that they find sexually attractive relative to stimuli that they find sexually unattractive. In several VT assessment systems that are commercially available, the models in the photographs are clothed and are not displayed in sexual poses. For many clinicians, therefore, the VT assessment addresses some of the ethical concerns raised by the PPG.
In studies with nonoffending adults, it has been demonstrated that VT is significantly correlated with self-reported ratings of sexual arousal (e.g., Harris, Rice, Quinsey, & Chaplin, 1996; Lang, Searles, Lauerman, & Adesso, 1980; Quinsey, Ketsetzis, Earls, & Karamanoukian, 1996) and with sexual arousal as measured by the PPG (Harris et al., 1996; Quinsey et al., 1996). There have also been several investigations of the efficacy of VT with adults who have offended sexually. For example, Harris et al. (1996) found that men who sexually assaulted children viewed slides of children longer than they viewed slides of adults. In several studies conducted with the Abel Assessment for Sexual InterestTM (AASI), a VT assessment methodology using photographs of clothed models, Abel and his colleagues have reported encouraging data with respect to the internal consistency and discriminant validity of the AASI with adult males who acknowledged sexual assaults against children (Abel, Jordan, Hand, Holland, & Phipps, 2001; Abel, Lawry, Karlstrom, Osborn, & Gillespie, 1994; Abel, Huffman, Warberg, & Holland, 1998). In one of the few studies of the utility of the AASI conducted outside of the developer's laboratory, Letourneau (2002) found that PPG and AASI responses from 57 adult males were significantly correlated for most stimulus categories, and that both assessment approaches significantly differentiated those participants with male child victims from those with victims from other groups. Furthermore, the AASI VT procedure could identify those men with adolescent female victims. More recently, Gray and Plaud (2005) compared the AASI and the PPG using data collected from 39 men who had offended sexually against a child less than 11 years of age. They found that both procedures significantly identified sexual interest in children.
There have been few published studies of the utility of VT with adolescents. In one paper, Smith and Fisher (1999) used Abel's VT system (AASI) with 81 adolescent males. They concluded that this particular approach yielded little convincing evidence with respect to reliability or validity. However, it is important to note that Abel (2000) later disputed many of the results and interpretations presented by the investigators. More recently, Abel et al. (2004) evaluated the AASI with data collected from 1,704 males aged 11 to 17. The authors reported that VT for images of children was moderately correlated to the number of child victims (r=.18) and the number of acts of child sexual offending (r=.23). It was also noted that VT for child stimuli could moderately differentiate those adolescents who offended sexually against children from those who offended against peers or adults (AUC=.64).
Despite the prevailing assumption that self-reported sexual interests from individuals who commit sexual offenses will be necessarily biased and prejudicial, there is growing evidence of the utility of self-reported data. For example, Laws, Hanson, Osborn, and Greenbaum (2000) found that self-reported sexual interests showed more classification accuracy than PPG data with respect to victim gender in a sample of men who offended against children. Laws et al. also found that the self-report methodology used (card sort) had excellent levels of internal consistency. In a similar study, Day, Miner, Sturgeon, and Murphy (1989) found that self-report data from a structured questionnaire regarding sexual thoughts, feelings, and behaviors could accurately classify men according to the gender of their child victims.
Turning to research with adolescents, Seto et al. (2000) found that most participants who acknowledged a sexual interest in children were classified as “pedophilic” using the PPG. Furthermore, Seto et al. found that those participants who offended sexually against children but who denied sexual interest in children scored significantly lower on the pedophilic index. Daleiden, Kaufman, Hilliker, and O’Neil (1998) found that adolescents who offended sexually disclosed significantly more deviant sexual behaviours relative to both nonsexual offenders and a nonoffending group. Results such as these suggest that individuals may be quite open regarding deviant sexual thoughts, interests, and/or behaviors.
Method
Participants
After obtaining informed consent (and parental consent when required), data were collected from 78 males aged 12–18 (M=15.09; SD=1.62). Participants were assessed at a residential treatment facility in Minnesota (n=44) or at one of three community-based treatment centers in the Greater Toronto (Ontario, Canada) area (n=34). Females were not specifically excluded; rather the facility in Minnesota provides services only to males, and the 34 consecutive Canadian referrals who chose to participate were male.
All participants for this study acknowledged a contact sexual offense. During the course of this investigation, none of the adolescents who completely denied their sexual offenses and who were approached to participate (n=5) volunteered for this study. Sixty-seven percent (52/78) of the adolescents committed a sexual offense against at least one child (defined as under the age of 12 and 4 or more years younger than that adolescent at the time of the offense); the remainder (33% or 26/78) of the adolescents committed sexual assaults against peers or adults exclusively (5 of these 26 offended against male peers). With respect to the participants' ethnic origin, 81% (63/78) were Caucasian, 12% were African American/Canadian, 5% (4/78) were native American/Canadian, and 2% (2/78) were Hispanic. Information regarding intellectual functioning was available for 52 of the 78 adolescents: 19% (10/52) of these adolescents had IQ's less than 80, 6% (3/52) of the adolescents had IQ's above 120, and 75% (39/52) had an IQ's within the average range (i.e., IQ between 80 and 120). Assessors reported that 50% (39/78) of the participants disclosed a childhood sexual victimization history and 42% (33/78) of the adolescents disclosed physical abuse within their families.
Self-Report Sexual Arousal Graphs
To collect self-reported sexual arousal data, adolescents were asked to complete 2 graphs (1 graph for each gender) on which they rated their sexual arousal for 8 age-based categories: 0–3 years, 4–6 years, 7–9 years, 10–12 years, 13–15 years, 16–18 years, 18–24 years, and over 24 years (see Appendix A for self-report arousal graphs and instructions). Adolescents were first asked to rate their level of sexual arousal to the various age groups if there was no physical force or violence involved in the sexual interaction; they were then asked to use a different color of pen and indicate how their sexual arousal would change for each age group when the thought of forced sexual contact was introduced. All ratings were made on a scale from 0 (low) to 10 (high). For all participants, the graph to address sexual arousal to males was completed first, followed by the graph to capture sexual arousal to females. The graphing procedure was completed with the adolescents by a psychologist or social worker during the completion of a comprehensive assessment. There were 7 different clinicians (1 in Minnesota and 6 in Ontario) at the various agencies who assisted the adolescents to complete the graphs.
Affinity Assessment of Sexual Interest
The Affinity procedure is explained in detail elsewhere (Glasgow, Osborne, & Croxen, 2003), and assessors followed the assessment protocol outlined in the Affinity 1.0 manual (Glasgow, 2001). Briefly, the assessment involves the computerized presentation of photographs of 28 males and 28 females in 4 age categories: toddlers, preadolescents, adolescents, and adults. All of the photographs are of clothed individuals, and none of the models are depicted in sexual poses. The 56 images are presented in a fixed, random order, and participants are asked to rate the sexual attractiveness of each image using a mouse pointer. The on-screen self-report rating scale accompanying each photograph includes the anchors “Very unattractive,” “Neutral,” and “Very attractive,” and there are 19 different, unnumbered gradients on the scale. The Affinity computer program registers a self-report rating score for each photograph ranging from 0 to 18, and it records the time taken (in seconds; accurate to ±0.02 s) to provide each attractiveness rating. The later measure is referred to as on-task latency (OTL). Immediately prior to the debriefing procedure where the nature of the Affinity program was explained, participants were asked to rate—on a scale from 1 (Not at all upsetting) to 10 (Very upsetting)—how upsetting they found the experience of rating the Affinity photographs. They were also asked to indicate how enjoyable the experience was using a scale from 1 (Not at all enjoyable) to 10 (Very enjoyable), and participants’ comments regarding the assessment process were recorded by the assessor.
Average Sexual Arousal Scores
As a result of the fact that the Affinity program uses four age groups (toddler, preadolescent, adolescent, and adult) for each gender, the eight age groups examined using the self-report graphing procedure were collapsed to approximate the same four Affinity groups to facilitate raw-score comparisons. Specifically, self-report sexual arousal graph data were collapsed as follows: ages 0–3 and 4–6 (toddler); ages 7–9 and 10–12 (preadolescent); 13–15 and 16–18 (adolescent); 18–24 and 24 and over (adult).
To facilitate visual comparisons between the three assessment techniques, raw scores were converted to z scores. The average standardized raw scores for the three assessment approaches are displayed in Fig. 1. The raw data distributions are remarkably similar across approaches, despite the differences in measurement scales and assessment methodology. Specifically, average self-reported sexual arousal ratings and VT scores for female adults and adolescents are significantly higher than the arousal data for all remaining stimulus categories. Furthermore, there was significant overlap in the arousal data provided for males of any age and for female toddlers and preadolescents.Fig. 1Average standardized raw scores for Affinity On-Task Latency (OTL; n=78), Affinity Self-Report (n=78), and Self-Report Sexual Arousal Graph (n=72) procedures across stimulus groups. Bars represent 95% confidence intervals. MTOD: Male Toddler; MPRE: Male Preadolescent; MADO: Male Adolescent; MADU: Male Adult; FTOD: Female Toddler; FPRE: Female Preadolescent; FADO: Female Adolescent; FADU: Female Adult
Internal Consistency
Internal consistency estimates (Cronbach's α) for the 8 Affinity stimulus categories are displayed in Table 1. With the exception of the α for OTL measure for the 7 photographs of female adolescents, all internal consistency estimates were above .70 for the OTL values across the age/gender categories. Note, however, that higher internal consistency estimates were found for all Affinity stimulus categories based on self-report ratings.Table 1Internal consistency estimates for Affinity on-task latency and Affinity self-report ratingsAffinity on-task latency (measuredAffinity self-report ratings (scaleStimulus categoryin seconds) Cronbach's αfrom 0–18) Cronbach's αFemale toddlers.82.96Female preadolescents.79.95Female adolescents.62.87Female adults.72.94Male toddlers.73.97Male preadolescents.82.97Male adolescents.77.94Male adults.77.94
Internal consistency estimates (Cronbach's α) for the self-report sexual arousal graphs were .83 for females (collapsed across the four age groups) and .89 for males (collapsed across the four age groups). For children 12 and under (for both males and females), the internal consistency estimate was .92; for the 4 age groups of both males and females over the age of 12, internal consistency was .77.
Validity
The assumption underlying VT is that, when asked to rate the sexual attractiveness of a particular model, individuals look longer at photographs that they find sexually arousing relative to the time that they spend looking at photographs that they find not sexually arousing. The correlations pertaining to this issue are displayed in Table 2, and it can be seen that for 7 of the 8 stimulus categories, the time spent viewing the slides (Affinity OTL) was significantly correlated with self-report ratings for the same slides (Affinity Self-Report). The average correlation between Affinity OTL and Affinity self-report ratings across all slide categories was r=.31, p < .01. There was, however, a significant, negative correlation between OTL and Affinity Self-Report for the slides of the adult females. In other words, there was a marked tendency for those adolescents who rated the photographs of adult females as sexually attractive to provide their ratings more quickly than those adolescents who found the photographs less sexually attractive. This, of course, is counter to the assumption that forms the premise of the VT approach.Table 2Correlations between Affinity on-task latency, Affinity self-report, and self-report sexual arousal graph proceduresSelf-report sexualStimulus groupAffinity self-reportArousal graphsMale Toddler Affinity OTL.38**.35** Affinity self-report.64**Male preadolescent Affinity OTL.67**.55** Affinity self-report.79**Male Adolescent Affinity OTL.61**.46** Affinity self-report.63**Male adult Affinity OTL.52*.21* Affinity self-report.50**Female toddler Affinity OTL.49**.44** Affinity self-report.80**Female preadolescent Affinity OTL.48**.38** Affinity self-report.73**Female Adolescent Affinity OTL.24*.16 Affinity self-report.34**Female Adult Affinity OTL−.26*−.17 Affinity self-report.48**Note. OTL: On-task latency. n=78 for all correlations between Affinity self-report and Affinity OTL. n=72 for all correlations with the Self-report sexual arousal graphs.*p < .05; **p < .01.
Although the Affinity self-report is based on photographs of various models, and the self-report sexual arousal graphs simply require a rating in response to a numeric age group, the correlations between these two measures of sexual arousal were significant for all 8 stimulus categories. The correlations between OTL and the self-report graphs were also significant for 6 of the 8 stimulus categories.
The validity of the two Affinity procedures (OTL and self-report) and the self-report graphing procedures was examined by comparing subgroups of adolescents formed on the basis of the age and gender of their victims. First, an Affinity OTL deviance index was calculated for each participant by dividing the highest mean OTL (in seconds) for male or female toddlers or preschoolers by the highest mean for male or female adolescents or adults.1 An Affinity Self-Report deviance index was calculated using the same mathematical procedure: the highest mean Affinity self-report rating for male or female toddlers or preschoolers was divided by the highest mean self-report rating for male or female adolescents or adults. Finally, a deviance index was calculated in the same fashion for the self-report graphing procedure by dividing the highest rating for a male or female child aged 0 to 12 by the highest rating for a male or female aged 13 and over.
To examine the discriminative validity of the three assessment procedures, the area under the Receiver Operating Characteristic (ROC) curve (AUC) was calculated for several different between-group comparisons (see Table 3). Both of the self-report procedures could significantly identify those adolescents with single child victims, multiple child victims, or male child victims (whether defined as ever a male child or exclusively male child victims), and there were no significant differences between the two self-report methodologies, all ZΔ’s ≤ .03, all p’s ≤ .05. The Affinity OTL deviance index was only able to discriminate those adolescents with a male child victim from those adolescents with victims from all other age/gender groups, and neither self-report measure was superior to the Affinity OTL for this discrimination, all ZΔ’s ≤ .03, all p’s > .05. Interestingly, none of the deviance indices examined correctly identified those adolescents with female child victims: whether this was defined as if ever a female child victim or exclusively female child victims. It should also be pointed out that of the 30 adolescents who had 2 or more child victims, 23/30 (or 77%) had at least one male child victim. Only 7/30, or 23%, had 2 or more child victims that were exclusively female.Table 3Area under the ROC curve (AUC) classification data for three measures of deviant sexual interestSexual assault victim(s)Affinity on-task latency deviance index AUC (n=78)95% CIAffinity self-report deviance index AUC (n=78)95% CISelf-report sexual arousal graph deviance index AUC (n=72)95% CIEver a child victim.61.47–.75.67*.54–.79.66*.53–.792 or more child victims.60.47–.73.73**.61–.86.70**.59–.82Ever a male child victim.69**.57–.81.72**.60–.84.72**.60–.84Only male child victim(s).73**.60–.86.74**.60–.89.76**.64–.88Ever a female child victim.42.30–.55.48.35–.61.45.33–.58Only female child victim(s).43.29–.56.42.28–.56.41.27–.56Note. Affinity On-Task Latency Deviance Index = (highest mean on-task latency for male or female toddlers or preadolescents)/(highest mean on-task latency for male or female adolescents or adults). Affinity Self-Report Deviance Index = (highest mean self-reported ratings for male or female toddlers or preadolescent)/(highest mean self-reported ratings for male or female adolescents or adults). Self-Report Sexual Arousal Graph Deviance Index = (highest rating for male and female children aged 0–3, 4–6, 7–9, and 10–12)/(highest rating for males and females aged 13–15, 16–18, 18–24, and 24 and over).*p < .05; **p < .01.Table 4Mean (and SD) deviance indexes for between-group comparisonsComparisonAffinity on-task latency deviance index (n=78)FAffinity self-report deviance index (n=78)FSelf-report sexual arousal graph deviance index (n=72)FEver a child victim Yes.72 (.20)1.6.17 (.27)2.2.29 (.29)1.79 No.65 (.24).08 (.24).19 (.32)2 or more child victims Yes.74 (.20)1.6.24 (.31)7.4 **.34 (.25)4.1* No.67 (.23).08 (.20).19 (.31)Ever a male child victim Yes.77 (.20)7.1 **.24 (.31)7.4 **.37 (.28)7.1 ** No.65 (.21).08 (.20).18 (.29)Only male child victim(s) Yes.84 (.20)10.9 **.32 (.37)11.7 **.39 (.29)4.2* No.66 (.21).09 (.19).20 (.29)Ever a female child victim Yes.66 (.18)1.9.10 (.16)1.6.24 (.27)0.2 No.73 (.24).18 (.31).27 (.32)Only female child victim(s) Yes.64 (.19)0.1.08 (.13)0.2.17 (.26)0.2 No.72 (.22).17 (.29).28 (.31)Participant a victim of sexual abuse Yes.68 (.22)0.4.20 (.03)0.9.24 (.29)0.7 No.72 (.21).31 (.05).27 (.30)Participant a victim of physical abuse Yes.67 (.23)0.7.13 (.22).07.20 (.25)1.7 No.71 (.21).15 (.28).29 (.32)Location of participant Minnesota.70 (.22)0.0.23 (.03)0.1.26 (.31)0.2 Greater Toronto area.70 (.22).33 (.07).23 (.28)Note. Affinity On-Task Latency Deviance Index = (highest mean on-task latency for male or female toddlers or preadolescents) / (highest mean on-task latency for male or female adolescents or adults). Affinity Self-Report Deviance Index = (highest mean self-reported ratings for male or female toddlers or preadolescent)/(highest mean self-reported ratings for male or female adolescents or adults). Self-Report Sexual Arousal Graph Deviance Index = (highest rating for male and female children aged 0–3, 4–6, 7–9, and 10–12)/(highest rating for males and females aged 13–15, 16–18, 18–24, and 24 and over).*p < .05; **p < .01.
Given that there are few published data using the Affinity assessment system, one-way ANOVAs were also computed for the 3 deviance measures for each of the comparisons described above. The means and standard deviations for these comparisons are presented in Table 4 to facilitate the calculation of effect sizes and comparisons with future investigations. The pattern of group differences is similar to that found with the ROC analyses. Also note in Table 4 that there were no significant differences on any of the deviance measures as a function of sexual or physical victimization history or location of data collection. It should also be pointed out that there was no significant correlation between participant age and the deviance index calculated for Affinity OTL (r=.02), Affinity Self-Report (r=.09), or the self-report sexual arousal graphs (r=−1.1), all p’s > .05. Correlations between the three deviance measures and the number of known child victims are displayed in Table 5.Table 5Correlations between deviance indices and number of known child victimsVariableAffinity on-task latency deviance index (n=78)Affinity self-report deviance index (n=78)Self-report sexual arousal graphs deviance index (n=72)Number of child victims.07.23*.14Number of male child victims.33**.50**.34**Number of female child victims−.13−.04−.05Note. Affinity On-Task Latency Deviance Index = (highest mean on-task latency for male or female toddlers or preadolescents)/(highest mean on-task latency for male or female adolescents or adults). Affinity Self-Report Deviance Index = (highest mean self-reported ratings for male or female toddlers or preadolescent)/(highest mean self-reported ratings for male or female adolescents or adults). Self-Report Sexual Arousal Graph Deviance Index = (highest rating for male and female children aged 0–3, 4–6, 7–9, and 10–12)/(highest rating for males and females aged 13–15, 16–18, 18–24, and 24 and over).*p < .05; **p < .01.
Combinatory deviance scores were also computed to determine whether the results from multiple assessment methods could enhance discriminatory power. Specifically, the following combined deviance scores were examined: Affinity OTL + Affinity self-report; Affinity OTL + self-report arousal graph; Affinity self-report + self-report arousal graph; and Affinity OTL + Affinity self-report + self-report arousal graph. For the six between-groups comparisons outlined in Table 3, there was no significant increase in predictive efficiency for any of the combinatory deviance scores, all ZΔ’s ≤ .06, all p’s > .05. The highest AUC value obtained for any comparison was 0.79 (95% CI; .66–.91), and this represented the ability to detect multiple child victims using the combination of Affinity self-report plus the self-report sexual arousal graphing procedure.
Given the relative novelty of the self-report sexual arousal graphs, a final examination of the validity of this technique involved an analysis of the frequency with which adolescents ever rated their sexual arousal over the “0” line for male or female children aged 0 to 12 years. The data related to this analysis are presented in Table 6, and it can be seen that if an adolescent ever provided a rating over “0” for children aged 0 through 12 years, this was significantly related to the choice of a single child victim, multiple child victims, and male child victims. As with all previous analyses, however, this particular procedure could not discriminate those adolescents with female child victims.Table 6Frequency of self-report sexual arousal graph ratings over “0” for children aged 0 to 12Ever more than “0” sexual arousalNoYesTotalEver a child victim No16925 Yes153247 Total314172χ2 = 6.9*Ever 2 or more child victims No261945 Yes52227 Total314172χ2 = 10.6**Ever a male child victim No261844 Yes52328 Total314172χ2 = 11.87**Only male child victim(s) No282755 Yes31417 Total314172χ2 = 5.86*Ever a female child victim No192342 Yes121830 Total314172χ2 = 0.20Only female child victim(s) No213253 Yes10919 Total314172χ2 = 0.97Note. Ratings were provided on a scale from 0 (low) to 10 (high).*p < .05; **p < .01.
Finally, participants were asked to rate how upset they were after completing the Affinity rating task. On the scale from 1 (Not at all upsetting) to 10 (Very upsetting), the mean rating was 2.38 (SD=1.88). Only 6 adolescents provided a rating of 5 or higher, and 66% of the participants provided a rating of 1 or 2. Anecdotally, those adolescents who rated the Affinity procedure as somewhat upsetting most often commented that there were too many photographs of young children or that there were too many photographs of males. Participants were also asked to rate how enjoyable they found the Affinity computerized assessment using a scale from 1 (Not at all enjoyable) to 10 (Very enjoyable). The mean rating for this variable was 3.70 (SD=2.10). Those adolescents who found the procedure enjoyable most often commented that it was “interesting”; those who rated the Affinity assessment as Not at all enjoyable most often mentioned that it was “boring.”
Discussion
Adolescent sexual interest was assessed using three different assessment procedures: the Affinity (version 1.0) VT procedure, the Affinity self-report procedure, and a self-report sexual arousal graphing procedure. Overall, the internal consistency estimates for all three measures were acceptable for most age and gender groups, and all three assessment approaches significantly differentiated those adolescents with male child victims from those adolescents who never offended sexually against a male child. On the other hand, none of the assessment techniques could successfully differentiate adolescents with female child victims from those who offended sexually against other groups.
The finding that those adolescent males with male child victims demonstrated the highest interest in prepubescent children—either through VT or self-report—is consistent with results from several studies in which the PPG was used (Becker et al., 1989; Hunter et al., 1994; Murphy, DiLillo, Haynes, & Steere, 2001; Seto et al., 2000). As has been noted by many of these researchers, it is quite likely, therefore, that many adolescents who commit a sexual offense against a male child are motivated, at least in part, by a sexual interest in prepubescent children. Of course, not all adolescents who target male children demonstrate deviant sexual arousal, and other factors, such as opportunity or antisocial attitudes, for example, need to be considered in the etiology and/or maintenance of their sexual offenses.
Similarly, the fact that many participants who offended sexually against female children did not demonstrate or report significant sexual interest in prepubescent children is also consistent with PPG data collected from adolescents (e.g., Seto et al., 2000) and with both PPG and VT data collected from adults (e.g., Letourneau, 2002). As has been noted by others, this may be a result of the fact that the various assessment procedures are not yet able to discern such a sexual interest. Alternatively, given the fact that this finding has been observed with both adults and adolescents—using PPG, VT, and self-report—it is possible that there are many males who commit sexual offenses against prepubescent girls for reasons other than deviant sexual interest. As noted with respect to some of those who offend against boys, it could be that factors such as opportunity or abuse-supportive attitudes, for example, are critical in the formation and/or continuation of offending behaviors.
The AUC reported by Abel et al. (2004) for the AASI to differentiate those adolescents who ever assaulted a child from those who sexually assaulted a peer or adult was .64. The AUC for the Affinity VT in the present study (AUC=.61) was remarkably similar for the same comparison. As noted clearly by Abel et al. (2004), this suggests that VT alone should not be used to classify adolescents who have offended sexually with respect to victim age. Of course, despite the fact that both of the self-report procedures significantly differentiated adolescents with versus without child victims, no one assessment methodology produced an AUC over .74 regardless of the discrimination examined, and no combinatory deviance score produced an AUC over .79. This indicates that there is certainly much room for improvement, and that neither self-report procedure should be used on its own, or in combination, to determine whether or not an adolescent has committed a sexual offense against a person from a specific age/gender category. Of course, it is also possible that researchers will never find that they can get better discrimination between subgroups on the basis of victim gender and/or age because of the fact that sexual interests and attitudes are still being formed during adolescence. Although victim gender and/or age may be proxy markers of sexual interest for some adults who offend sexually, particularly those who offend against boys, it is likely that the choice of victim is less often related to fixed sexual interests for adolescents.
Despite the encouraging results reported regarding both self-report procedures, it should be stressed that there were no adolescents who completely denied their sexual crimes included in this study. As such, these results should not be generalized to that subgroup. It would be interesting to investigate the utility of both VT and self-report with those who deny their sexual offenses as Becker et al. (1992) found that the PPG was not useful with this group as most of these adolescents were classified as “nonresponders.” There were also no female participants included in this study. Given the relative ease with which both Affinity and the self-report graphing procedures can be carried out with both male and female adolescents, it would be beneficial to learn about the psychometric properties of these assessment techniques with female participants. It would also have been ideal to have included a group of adolescents without a history of sexual offending. This would have permitted analyses regarding normative responses for both VT and self-report, and there may have been greater discrimination accuracy for specific subgroups if nonoffending youth were included. Finally, it should also be pointed out that there were only 78 participants in this investigation; therefore, the probability of a Type 1 error should be considered given the number of statistical tests herein.
Although VT was significantly correlated with ratings of sexual interest for the same photographs within most of the stimulus categories, there was a significant negative correlation between VT and sexual attractiveness ratings for photographs of adult females. It is difficult to comment on the uniqueness of this finding, however, as few researchers have published correlations between self-reported ratings and VT scores for separate stimulus categories. Rather, it is more common for researchers to report an average correlation across the various age/gender categories (r=.31 in the present study). One can quickly see in Fig. 1 that, on average, adolescents viewed photographs of adolescent and adult females for approximately the same amount of time, but that the sexual attractiveness ratings provided for the photographs of the adult females were significantly higher than those ratings given to the photographs of adolescent females. Given that the relationship between VT and self-reported attractiveness ratings were in the expected direction for most stimulus categories, it may be that this result is spurious and sample specific. On the other hand, there may be something about the seven photographs of adult women used in the Affinity program that contributed to this unexpected result. Alternatively, it is possible that some participants provided exaggerated ratings to the slides depicting adult females in an effort to appear more socially desirable. Finally, it is possible that there is an inverted-U-shaped distribution of VT responses such that respondents provide the fastest ratings to categories that they find both highly attractive and highly unattractive. Given that the majority of adolescents in this study found only 2 of the 8 categories of photographs as highly sexually attractive (adolescent and adult females), the fast VT responses to the 6 remaining categories would account for an overall positive correlation between low VT and low attractiveness ratings. In other words, participants provided low average attractiveness ratings after low average viewing times for 75% (42/56) of the slides. It would be ideal for researchers to examine the possibility of such an inverted-U-shaped distribution in future research with VT technology; particularly given the assumption underlying the technique that there is a linear relationship between viewing times and attractiveness ratings for all age/gender categories.
Most of the adolescents found that participating in the Affinity VT assessment was not very upsetting, and many even found the process to be at least somewhat enjoyable. Given the potential intrusiveness of the PPG procedure, it is interesting that researchers have never collected information from adolescents regarding their experience of providing PPG data. Given the current scientific limitations of the PPG with adolescents, and the ethical concerns involved in conducting such an assessment, it is encouraging that at least one VT approach (Affinity 1.0) can produce some useful information regarding sexual interests without significant negative impact. Furthermore, it is important to point out that age at time of assessment, childhood sexual victimization history, and physical abuse history were not significantly related to deviance indices calculated for Affinity VT, Affinity Self-Report, or the self-report graphing procedure. Recall that some researchers have found that PPG data are correlated with these factors.
The results of the present study also lend support to the growing evidence that structured, self-report methodologies can provide the assessor with valuable information regarding an adolescent's sexual interests. For example, adolescents with a history of sexual offenses who rated their sexual arousal to children 12 years of age and under over the “0” mark on the self-report arousal graphs were significantly more likely to have offended against a single child victim, multiple child victims, or male child victims. Of course, regardless of the particular assessment methodology chosen, it is always prudent to supplement any sexual-interest data with information from official documentation and with reports from parents and other adults who may be familiar with the adolescent. It is also essential to be mindful of the fact that sexual interests are not necessarily crystallized for many adolescents and, furthermore, that victim choice may not necessarily be a proxy for sexual preferences. Even when deviant sexual interests are identified, however, there is very little research regarding how best to help adolescents in this regard. Although covert sensitization is by far the most popular behavioral treatment for deviant-arousal reduction in programs in the United States for adolescents who have offended sexually (McGrath, Cumming, & Burchard, 2003), there are no published data regarding the efficacy of this approach for adolescents. In addition to the continued refinement of measurement strategies, therefore, it is critical that we examine the impact of treatment and management techniques for those adolescents who evidence deviant sexual interests.

sexual arousal
adolescents
self-report
viewing time
sexual interests
sexual offending