Int J Adv Counselling DOI 10.1007/s10447-012-9166-4 ORIGINAL ARTICLE

A Multidimensional Assessment of Children in Conflictual Contexts: The Case of Kenya Jane E. Atieno Okech

# Springer Science+Business Media, LLC 2012

Abstract Children in Kenya’s Kisumu District Primary Schools (N0430) completed three measures of trauma. Respondents completed the My Worst Experience Scale (MWES; Hyman and Snook 2002) and its supplement, the School Alienation and Trauma Survey (SATS; Hyman and Snook 2002), sharing their worst experiences overall and specifically in schools. Participants also completed the Trauma and Attachment Belief Scale (TABS; Pearlman 2003), addressing their experiences of violence. The study examined children’s perceptions about themselves and others in the aftermath of violent experiences and the relationship between children’s trauma symptoms from experiencing violence and their social and academic functioning. Differences in the presence, frequency, and severity of symptoms emerged, with a large percentage attaining statistical and clinical significance. Research and practice implications are provided. Keywords Kenya . Kisumu . Trauma . Violence . Children . Post-elections

Introduction Millions of children worldwide are affected daily by violence in conflict-afflicted countries (United Nations Children's Fund [UNICEF] 2008). Violence impacts mental health, slowing the rate of psychological recovery (Giacaman et al. 2007; Ratner et al. 2006; Thabet and Vostanis 2000). Current research (Allwood et al. 2002; Seedat et al. 2004) demonstrates that most children exposed to violent trauma continue to meet criteria for Post-Traumatic Stress Disorder (PTSD) long after exposure to traumatic events. Children who do not meet full criteria for PTSD often experience symptoms including depression, anxiety, sleep difficulties, conduct disordered behavior, or abnormal eating habits. Researchers exploring children’s reactions to violent and non-violent war experiences have noted a high prevalence of PTSD and adjustment and behavioral issues (Allwood et al. 2002). Some researchers have

J. E. A. Okech (*) University of Vermont, Burlington, VT, USA e-mail: [email protected]

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also indicated a pattern of gender equivalence in children’s reactions to violence and war experiences (Morgos et al. 2008; Seedat et al. 2004). These pervasive negative effects of violence on children have been documented worldwide. Smyth et al. (2004) found that young men in Northern Ireland’s conflict were more likely to be both perpetrators and victims of violence and Ratner et al. (2006) found a link between non-war-related community-based violence and poor academic performance. Their findings were consistent with those of Schwartz and Gorman (2003), who studied victimization and peer bullying, as well as those of Henrich et al. (2004) who assessed the correlation between community violence exposure and middle-school achievement. The latter research suggested that, regardless of context, exposure to violence negatively affects children’s academic performance. Limited data exist on the effects of exposure to violence for African children. Following violent conflict, stakeholders focus on meeting children's basic needs of shelter, food, and physical safety. Although the psychological impact of violence on children is acknowledged, the effort to address mental health concerns is minimal (Suliman et al. 2005). In Kenya, there are few community-based mental health services or resources to support children impacted by violence. Although Kenya’s Ministry of Education has instituted a policy requiring every school to have a school counselor, there are no standard training or qualification requirements. The majority of public schools have school counselors who also function as full-time teaching staff (Okech and Kimemia 2012). The purpose of this study was to examine children’s perceptions about themselves and others in the aftermath of violent experiences and the relationship between children’s trauma symptoms from experiencing violence and their social and academic functioning. This study was conducted (July 2009 – May 2010) in Kenya, a country recently plagued by violent political and community-based conflict (December 2007 – May 2008). Little is known about the role of gender in these circumstances or the effects this violence has had on Kenyan children. This research is significant because it not only addresses a research gap in African children’s experiences in violent contexts but for its potential to inform schools, nongovernmental organizations, or caregiver interventions with children. This study conducted a multidimensional assessment of children’s perceptions of their experiences of and reactions to violence. The measures used were the My Worst Experience Scale (MWES; Hyman and Snook 2002), the MWES supplementary school focused edition, called the School Alienation and Trauma Survey (SATS; Hyman and Snook 2002), and the Trauma & Attachment Beliefs Scale (TABS; Pearlman 2003). Most of the instruments used to assess trauma have been developed in the United States; therefore, their utility with African populations has not been validated. Using an African sample may improve the instruments’ applicability in identifying and addressing trauma-related symptoms internationally (Seedat et al. 2004). Children’s perspectives must be part of intervention strategies, both to allow them to articulate their experiences of violence and for researchers to make appropriate treatment recommendations. The findings of this study provide important information for improved mental health services for African children. This study sought to address five research questions that were informed by the literature on the field of trauma and violence, 1) Do trauma and emotional distress symptoms manifest themselves in Kenyan children a year after the violence? 2) Do trauma symptoms and emotional distress manifest differently in Kenyan children based on gender? 3) Do different independent variables (such as access to a counselor, academic percentile rank, and ethnic group) predict the severity and endurance of trauma symptoms and distress on children? 4) Do unresolved traumatic symptoms impact the social and academic functioning of Kenyan children? 5) Do children with distressful sexual experiences note more severe symptoms of distress than their peers?

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Method Setting The study locale was Kisumu city (Kenya), an ethnically diverse population estimated at 500,000 (UN-HABITAT 2010). Designated a Millennium city, Kisumu is working to achieve the United Nations Millennium Development Goals by 2015. From December 2007 to May 2008, Kisumu was an epicenter for violence following the Kenyan presidential elections in December 2007. An estimated 1,500 people were killed nationwide and over 300,000 forced to flee their homes (Kenya Red Cross Society [KRCS] 2008). Approximately 100,000 children were internally displaced, with 75,000 living in over 200 displacement camps (KRCS 2008; UNICEF 2008). Participants All students currently enrolled in standard (grade) six, seven, or eight in 10 schools within Kisumu City were invited to participate in the study. A final sample of 430 students was obtained from a pool of 600 potential participants. Of the sample, 107 (24.9 %) were in standard six, 175 (40.7 %) in standard seven, and 148 (34.4 %) in standard eight. The participants included 216 (50.2 %) females and 214 (49.8 %) males. Among the 430 participants, 419 (97.4 %) identified as Black African, four (.9 %) as African Arab, four (.9 %) as Arab, one (.2 %) as Indian, and two (.5 %) as Somali. Their ages ranged from 10 to 16 (M012.9). The most frequent age was 13 (31.2 %, n0132), followed by 12 (26.5 %, n0 112), 14 (21 %, n089), 11 (12.3 %, n052), 15 (6.9 %, n029), 16 (1.7 %, n07), and 10 (0.5 %, n02). There were 414 (96.3 %) Christians, 15 (3.5 %) Muslims, and one (.2 %) Hindu. Participants ethnically identified as: 322 (74.9 %) Luos, 44 (10.2 %) Luhyas, 27 (6.3 %) Kisiis, eight (1.9 %) Arabs, seven (1.6 %) Kambas, seven (1.6 %) Kikuyu, five (1.2 %) Nubians, four (.9 %) Tesos, two (.5 %) Kalenjins, two (.5 %) Somalis, one (.2 %) Indian, and one (.2 %) Nigerian (the only non-citizen). Measures My Worst Experience Scale (MWES). This instrument assesses trauma symptoms with clinical significance experienced by children (Hyman and Snook 2002). The MWES includes 11 subscales, four derived directly from the PTSD criteria in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV): Impact of the Event, Reexperience of the Trauma, Avoidance and Numbing, and Increased Arousal. The MWES was normed against a sample of children ages nine to 18 in the United States with the following ethnic composition: 86 % White, 9 % African American, 3 % Asian, < 1 % Hispanic, and 2 % “Other.” The sample was 47 % male and 53 % female, 4 % were age 9– 10, 21 % were age 11–12, 33 % were age 13–14, 29 % were age 15–16, and 13 % were age 17–18 (Hyman and Snook 2002). The MWES is administered through self-report for children aged nine to 18 in two sections. In Part I, respondents indicate which of 21 experiences (e.g., natural disasters, death of a parent, assault, school problems, etc.) was their worst. Respondents then answer six questions about the experience, including why it was upsetting, age and grade it occurred, if it happened more than once, if it still bothered him/her, and how he/she felt immediately afterward. Part II asks respondents to indicate the frequency and duration of thoughts, feelings, and behaviors that they may have experienced after the traumatic event

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(Hyman and Snook 2002). The MWES was chosen for this study because the instrument reflects the multifaceted nature of both violence and reactions to violence and for its demonstrated validity in assessing PTSD symptoms associated with traumatic events and events not clinically warranting a PTSD diagnosis (e.g., bullying) (Hyman and Snook 2002). The MWES offers greater agency to children in naming their most traumatic experiences and the subsequent effects. The MWES can also be administered to a large group, allowing for more efficient data collection of a large sample. Finally, the lack of similar instruments normed on African children made the MWES a suitable choice for this study in Kenya. The MWES has demonstrated reliability and validity with diverse populations in the United States. The MWES has been shown to correlate with other clinically accepted measures of children’s affect, behavior, and self-concept, further reflecting its validity (Hyman and Snook 2002). Berna (as cited in Hyman and Snook 2002, p. 43) assessed test-retest reliability for 21 eighth-grade students and attained a correlation of .95 for the TOT score (the TOT is a composite of the participants’ total scores on the instrument). Zahn (as cited in Hyman and Snook 2002, p. 50) compared the MWES results of emotionallydisturbed teenagers with a history of sexual abuse to emotionally-disturbed teenagers with no sexual abuse and to a non-abused control group of teenagers. Results showed that the teenagers who had experienced sexual abuse reported a significantly higher frequency of stress symptoms (TOT077.5T) in comparison to the control group (TOT049.9T) and to the emotionally disturbed, non-abused group (TOT054.4T). School Alienation and Trauma Survey (SATS). The SATS is the MWES’s supplementary form that specifically targets school experiences and was normed against the same sample indicated above (Hyman and Snook 2002). The SATS has 54 questions identifying children’s negative experiences in schools. Respondents indicate the frequency of each item based on a 7-point Likert scale (from “Did not happen” to “Still happening”) and check as many items as apply to them. In the final section they choose one “worst” experience to briefly describe. Two summary questions allow participants to identify the person involved in their worst school experience. Trauma and Attachment Belief Scale (TABS). This instrument assesses the long-term impact of trauma on beliefs about self, others, and relationships (Pearlman 2003). Composed of 84 items, the TABS is administered through self-report format for children age nine and up (Pearlman 2003). “It assesses beliefs about self and others that are related to five needs commonly affected by traumatic experience: safety, trust, self-esteem, intimacy, and control” (Pearlman 2003, p. 6). For each of these five dimensions, the TABS produces two scale scores reflecting “beliefs about self” and “beliefs about others,” resulting in a total of 10 scales. Items on the TABS include statements such as “I can keep myself safe,” and “People don’t keep their promises.” Participants then rate each item on a 6-point scale (10“Disagree Strongly” to 60“Agree Strongly”). The TABS standardization sample was derived from a diverse population age nine to 18. The sample included participants (N01,743) from public schools across the United States, including 1 % American Indian, 3 % Asian American, 6 % African American, 3 % Hispanic/ Latino, 49 % Caucasian, and 38 % “Unspecified” (Pearlman 2003). The TABS was used in this study because it was normed against a large diverse population in an urban context, and even though the racial and ethnic makeup of participants as well as the diversity within participants are very different from the sample against which the instrument was standardized, both samples were expected to have a degree of similarity because of their shared urban context. The TABS has demonstrated validity and reliability in measuring trauma with diverse populations in the United States.

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Pearlman (2003) reported that the standardization sample of 260 college students showed reliability through an internal consistency estimate of .96 and a test-retest correlation of .75, which is well above the accepted 0.60 cutoff mark for sufficient reliability. Along with overall reliability, the TABS subscales have a median internal consistency estimate of .79, with the low end of the range as .67 on the Self-Intimacy subscale and the high end of the range as .87 on the Other-Intimacy subscale (Pearlman 2003). The TABS has also received empirical support for its validity. Dutton, Burghardt, Perrin, Chrestman, and Halle (as cited in Pearlman 2003, p. 40) found a correlation between TABS scores and measures of PTSD for battered women, as well as a correlation between their anticipated likelihood of experiencing more violence in the future and their causal attribution of the violence and their Safety subscale scores on the TABS. Procedure The protocol was approved by the author’s institutional review board and the Municipal Education Office, Kisumu, Kenya. Ten schools within Kisumu Municipality were selected for the study because of the diversity of the student population and their proximity to the city center (all within a 10-mile radius). The radius to the city center was critical; it ensured that the sample included students directly impacted by the post-election violence concentrated in the city center. A pre-notification message of intent to conduct a study was delivered to each school by the principal researcher, who also met with the schools’ head teachers and counselors. All students registered in standards six, seven, and eight were invited to participate. These standards were selected because the students would be literate and able to accurately articulate their experiences. Of the 10 participating schools, seven had a staff person designated as a school counselor. Within one to three weeks of the initial meetings with the schools’ head teachers and counselors, the principal researcher visited the schools again and held informational meetings with potential participants. At this time, the principal researcher explained the purpose of the study, reviewed the informed consent and assent forms, and distributed them to the students. The students could take an informed consent form home written in Dholuo, Kiswahili, or English, depending on their parents’ or guardians’ literacy level and language preference. Kiswahili and English are national languages in Kenya, while Dholuo is the predominant first language spoken in the region. Within 1 week, the principal researcher returned to respond to questions, collect signed informed consent forms and complete the assent process with potential participants. Of the 600 students contacted, 436 (72.5 %) returned signed informed consent forms approving their participation and underwent the assent process. One was sick on the day of the study and unable to participate, two declined to sign the assent form, one was removed from the study due to adverse reaction to the questions, and two were excluded due to serious preexistent trauma-related concerns, resulting in 430 participants (71.6 %). The instruments were administered to all of the participants in a group format in a standardized testing environment. Participants could leave the room as soon as they completed the instruments and they could take as long as they needed to complete the instruments. The participants did not speak to each other during the instrument administration and they addressed all questions to the researcher and the research assistant. Two research assistants were involved: one assisted the principal researcher with the informed consent and assent process and data collection, and the second assisted with scoring the instruments and data entry. Data collection and participant follow-up were completed eight months after the initial informational meeting.

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Results The MWES asked participants to identify their worst experience from 22 options: war; sexual assault/abuse; physical assault/abuse; death of a parent; death (other than a parent); bad storm; parents’ divorce/separation; problem with friends; school problem; unwanted pregnancy; family fighting; put-down (someone made fun of you); fire; drug/alcohol abuse; earthquake; sickness; loss of a pet; personal failure; kidnapping; robbery; loss of something important; or none of the above. The most common worst experiences identified were death of a parent (n096, 22.3 %), war (n075, 17.4 %), and death of someone other than a parent (n023, 5.3 %). Participants had a mean age of 12.9 (SD01.21) when they had their worst experience. Out of the 419 usable MWES scores, 228 (53 %) of participants found the experience upsetting because it happened to them, as opposed to 118 (27.4 %) who witnessed it happen to someone else. Immediately following the event, 305 (70.9 %) were upset “a lot,” 94 (21.9 %) were upset “a little,” and 19 (4.4 %) were “not really bothered.” Ten participants (2.3 %) indicated that they did not find the experience upsetting, 40 (9.3 %) were upset after it, and 23 (5.3 %) chose multiple options. The event happened more than once for 209 participants (48.6 %) and 190 (46.2 %) experienced it once. Twelve had missing values. In response to whether or not the event still bothered participants, 264 (61.4 %) noted “Yes” and 154 (35.8 %) noted “No”. Inconsistent Responding Index (INC) The Inconsistent Responding Index (INC) was used to check the consistency of each participant’s response. It has 16 pairs of questions (e.g., “I wished I were dead” and “I thought about killing myself”) embedded in the MWES. Scores of seven or above indicate response inconsistency. Of the 430 completed instruments, 19 had missing values. The INC score was calculated out of the 411 usable instruments (M04.63, SD02.57). Of these, 55 had INC scores higher than seven, indicating inconsistent responding. Follow-up was conducted with 43 participants who scored high on the INC index and were raising safety concerns. After follow-up, 20 participants changed the accuracy of their responses, 16 confirmed their response accuracy, and seven responses were kept as originally submitted because they were unavailable for follow-up. Question 1: Do Trauma and Emotional Distress Symptoms Manifest Themselves in Kenyan Children 1 year After the Post-election Violence Events? The MWES Total (TOT) criterion and symptom subscale scores are reported as T-scores. The TOT is a composite of the participant’s total scores on the instrument, including the criterion and symptom subscales. “The TOT alone differentiates children and adolescents from general clinical and non-clinical populations” (Hyman and Snook 2002, p. 19). The MWES subscale Tscores are interpreted as: 40 and below (Very Low); 40–44 (Low Average); 45–54 (Average); 55–59 (Above Average); 60 and above (Clinically Significant); and 70 (Considered Extreme). The MWES criterion subscales that are directly linked to PTSD symptoms using DSM-IV-TR criteria A-D include: Impact of the Event (IMPACT); Re-experience of the Trauma (REEX); Avoidance and Numbing (AVOID); and Increased Arousal (AROUS). The criterion subscale scores were: IMPACT (TS056.61, SD09.68), REEX (TS061.01, SD09.72), AVOID (TS0 58.73, SD08.50); and AROUS (TS059.25, SD09.16). As shown by their T-scores, at least onethird of participants met clinical significance on each of the four PTSD criterion subscales: IMPACT (38.5 %); REEX (59.2 %); AVOID (47.7 %); and AROUS (53.5 %).

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The MWES symptom subscales are: Depression (DEPR); Oppositional Conduct (OPP); Hyper-vigilance (HYPER); Somatic Symptoms (SOM); Hopelessness (HOPELS); Dissociation and Dreams (DISSOC); and General Maladjustment (MAL). T-scores on these scales can be used to evaluate the presence, frequency and severity of PTSD symptoms. On the MWES, T-scores with effect sizes above 0.5 (five T-score points) are considered meaningful. The symptom subscales scores were: DEPR (TS058.77, SD09.65); OPP (TS054.64, SD0 8.68); HYPER (TS060.52, SD08.70); SOM (TS057.43, SD09.66); HOPELS (TS055.65, SD09.71); DISSOC (TS062.37, SD08.94); and MAL (TS061.30, SD09.97). Scores reaching clinical significance were: DEPR (50.1%); OPP (27.7 %); HYPER (58.9 %); SOM (42.1 %); HOPELS (35.3 %); DISSOC (64.2 %); and MAL (61.6 %). Question 2: Do Trauma Symptoms and Emotional Distress Manifest Differently in Kenyan Children Based on Gender and Age? Although greater variability emerged in males’ scores than females’ on the SATS, gender was non-significant [t(421)0-1.44, p00.15]. Scores ranged from 54 to 205. The mean score for females (n0213) was 88.10 with Standard Error of the Mean (SEM)01.90 and the mean score for males (n0210) was 92.44 (SEM02.33). A one-way ANOVA indicated a significant effect for age [F(4,418)03.00, p00.018]. Pairwise comparisons with Bonferroni correction indicated that 15-16-year-olds with the highest mean score (M0104.31, SEM05.66) and 13year-olds with the lowest mean score (M086.45, SEM02.30) were the only significantly different pair. Ten and 11-year-olds were combined, and so were 15 and 16-year-olds because there were so few 10- (n02) and 16-year-olds (n07). The construct of gender reached clinical significance in participants who identified the perpetrator of their worst school experience, with males (n0253, 60.1 %) cited significantly more than females (n0168, 39.9 %). Comparing gender of the perpetrator to gender of the participant, there were 126 (75 %) female-on-female violations, 42 (25 %) female-on-male, 168 (66 %) male-on-male, and 85 (34 %) male-on-female. The primary issues for participants appeared to occur with the same gender (e.g., peers, teachers, drivers, cooks, custodians, etc.). Differences also emerged in the gender of the participant and the gender and status (e.g., teacher or student) of the perpetrator. Male students most often named a teacher as the perpetrator, and female students most often named another student. When the perpetrator was a student, both female and male participants more often identified a student of their same gender as the center of their worst experience: female-on-female 58.7 %; male-onfemale 36.5 %; male-on-male 53 %; and female-on-male 47.6 %. In contrast, when the perpetrator of the worst experience was a teacher, female teachers were cited more often by both male and female students than were male teachers. Male students identified 26.2 % (11) of their female perpetrators as teachers compared to only 7.7 % (13) of their male perpetrators. Female students named 15.1 % (19) of their female perpetrators as teachers compared to 12.9 % (11) of male perpetrators. Question 3: Do Different Patterns of Independent Variables Predict the Severity and Endurance of Symptoms of Trauma and Distress on Children? To assess if participants had been in distress for at least one month, the MWES Enduring Symptoms Tally was tabulated. As with other MWES subscale T-scores, interpretation can be guided as: ≤ 40 (Very Low); 40–44 (Low Average); 45–54 (Average); 55–59 (Above Average); ≥ 60 (Clinically Significant); and 70 (Considered Extreme). Based on 410 usable scores, the mean was 40.37 (SEM01.61). A one-way ANOVA demonstrated a significant

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difference [F(2,407)05.29, p00.005] on Enduring Symptoms based on whether a participant lived with both parents (n0236, M035.94, SEM01.95), one parent (n099, M045.69, SEM 03.81), or grandparents/other relatives (n075, M047.29, SEM 03.64, D031.54). Pairwise comparisons with Bonferroni correction showed that children living with both parents versus a single parent (p00.036) or grandparents/other relatives (p00.025) had significantly fewer Enduring Symptoms. One-way ANOVAs further indicated significant differences in the Somatic (SOM) subscale of Enduring Symptoms [F(2,407)04.84, p00.008]. Pairwise comparisons with Bonferroni correction on SOM symptoms showed that children living with both parents (M056.70, SEM00.60) or with grandparents/other relatives (M056.32, SEM01.33) had significantly greater SOM scores (p00.012, p00.035, respectively) than children with one parent (M0 60.03, SEM00.88). Although a significant difference in scores on the other subscales did not emerge between children living with one parent and with grandparents/other relatives, on each subscale the mean for children living with one parent was consistently highest. A Pearson’s correlation coefficient was calculated to assess whether Enduring Symptoms scores correlated with total scores on the MWES, SATS, and the TABS. A positive correlation emerged between the MWES Enduring Symptoms scores and the scores on all three instruments: TABS (r0. 523); SATS (r0. 322); and MWES (r0. 425) and all were significantly different from zero (p<0.001). The correlations indicated a consistency in participants’ scores in all instruments. A linear mixed model analysis was conducted with counselors as the fixed effect and school as the random effect to assess if the presence of school counselors predicted severity or endurance of trauma symptoms. Significant differences in scores on the three instruments or on the Enduring Symptoms scores did not emerge [MWES: F(1,8.97)02.26, p00.17; SATS: F(1,8.84)02.14, p0 0.18; TABS: F(1,8.21)00.92, p00.37; Enduring Symptoms: F(1,8.22)01.10, p00.33]. However, on all instruments and on Enduring Symptoms subscales, mean scores in schools without counselors were higher than in schools with counselors. On the SATS, schools without counselors had a mean of 92.08, versus a mean of 85.63 in schools with counselors. On the MWES, the mean score of schools without counselors was 68.34, compared to a mean of 65.91 with counselors. On the TABS, the mean of schools without counselors was 77.94, while schools with counselors had a mean of 73.72. Question 4: Do Unresolved Traumatic Symptoms Impact the Social and Academic Functioning of Kenyan Children? All participants completed the SATS, which targets traumatic school experiences. Each participant identified the person involved in his/her worst school experience: 49.8 % noted another student; 12.6 % a teacher; and 25.1 % “other.” Participants also identified their worst experience in school. Responses varied: the fewest respondents (0.2 %) chose Q50 (“Someone messed up my clothes on purpose”); and the most (9.8 %) identified Q54 [“Other (not on list)”], which is consistent with the MWES standardization sample, in which 13.6 % chose “Other” as their worst experience (Hyman and Snook 2002). The top 10 identified questions, encompassing 54 % of respondents were: Q54 [“Other (not on list)”] 9.8 %; Q31 (“I saw something really bad happen”) 8.1 %; Q3 (“I was embarrassed”) 7.2 %; Q40 (“Someone made up a story about me”) 6.5 %; Q41 (“I wanted to be friends with someone who did not want to be friends with me”) 6.3 %; Q26 (“Someone lied about me and I got into trouble”) 4.7 %; Q12 (“I was beaten up”) 4.2 %; Q49 (“Someone made me miss class or school”) 3.0 %; and Q1 (“I was teased”) 2.6 %. The responses by the remaining 46 % of participants varied among 39 other questions.

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To determine whether children’s academic percentile rank predicted their reaction to distressing experiences or their recovery from traumatic symptoms, a linear regression was conducted with scores from the MWES, SATS, and TABS. None of the instruments reached clinical or statistical significance; however, a negative relationship emerged for both SATS and TABS, demonstrating that students with higher academic percentile ranks tended to have lower scores on these two instruments [SATS: b0-0.15, t(403)0-1.91, p00.06; TABS: b0-0.05, t(401)0-1.21, p00.23]. MWES and percentile rank had a slightly positive correlation [b00.01, t(390)00.45, p00.65]. A significant effect [b0-0.19, t(390)0-2.31, p0.02] on the MWES Enduring Symptoms subscale emerged: students with higher academic percentile rank had lower scores, suggesting greater capability to cope with the impact of trauma. Participants’ most common worst experiences were death of a parent (22.3 %) and war (17.4 %). Death of someone other than a parent (5.3 %) also stood out. A t-test was run to compare the total scores on the TABS, MWES, and SATS as well as Enduring Symptoms, percentile rank, and gender of children whose worst experience was death of a parent with all other children. Similarly, t-tests were run comparing scores for those whose worst experience was war, with all others; and t-tests were run comparing scores for those whose worst experience was a non-parent’s death, with all others. A significant difference did not emerge between participants whose worst experience was the death of a parent (n096) or another experience. TABS, SATS, MWES scores, gender, Enduring Symptoms, and percentile rank did not reach significance. Participants whose worst experience was a non-parent’s death (n023) did not differ significantly from other participants on any construct except for academic percentile rank, which was higher for those who had experienced a non-parent’s death [t(409)0-2.97, p00.003]. For those whose worst experience was war (n075), only academic percentile rank [t(409)0-2.54, p0 0.01], which was higher than other participants’, reached significance. A t-test was also run to compare TABS, SATS, and MWES scores as well as Enduring Symptoms, percentile rank, and gender for participants who chose death (of a parent or someone else) as their worst experience (n0119) compared to those who chose war (n075). Differences in gender or Enduring Symptoms were not significant. A significant difference [t(182)0-2.06, p00.04] was noted only in percentile rank; participants who chose war as their worst experience had a higher percentile rank than those who chose a death as their worst experience. An Analysis of Covariance (ANCOVA) was conducted to examine the interaction between academic percentile rank and gender. Gender was not a significant factor. The effect of academic percentile rank on the scores of the three instruments (MWES, SATS, & TABS) also was not significant. Additionally, the effect of academic percentile rank was similar in males and females. Irrespective of gender, the higher the academic percentile rank of the participant, the lower his/her scores on the MWES Enduring Symptoms scale [F(1,388)05.52, p00.02]. The TABS assesses long-term impact of trauma on beliefs about self, others, and relationships. TABS T-scores are interpreted as: ≤ 29 (Extremely Low [Very Little Disruption]); 30–39 (Very Low); 40–44 (Low Average); 45–55 (Average); 56–59 (High Average); 60–69 (Very High); and ≥ 70 (Extremely High [Substantial Disruption]). A Pearson product–moment correlation coefficient was calculated to assess the relationship between Self- and Otheroriented T-scores. The significance test of the correlation coefficient is sensitive to the sample size; thus, most items were significantly correlated with other items (Table 1). The correlation coefficients were highest between Self-Control and Other-Control (N0424, r0.52, p<.001), Self-Safety and Other-Safety (N0424, r00.48, p<.001), and Self-Esteem and Other-Esteem (N0424, r00.37, p<.001). When controlled for gender, the non-correlation between SelfIntimacy with “Other-” subscales was consistent.

Int J Adv Counselling Table 1 Pearson Correlations in the Trauma Attachment & Beliefs Scales (TABS) All groups (n0424)

Kisii (n027)

Luhya (n044)

Luo (n0316)

TABS

r

p-value

r

p-value

r

r

p-value

Self-Safety with Self-Trust

.32

< .001

.33

.088

.37

.015

.31

< .001

Self-Safety with Self-Esteem

.40

< .001

.34

.084

.56

< .001

.40

< .001

Self-Safety with Self-Intimacy

.28

< .001

.40

.041

.27

.075

.26

< .001

p-value

Self-Safety with Self-Control

.43

< .001

.56

.002

.62

< .001

.41

< .001

Self-Safety with Other-Safety

.48

< .001

.58

.001

.48

.001

.47

< .001

Self-Safety with Other-Trust

.24

< .001

.29

.142

.44

.003

.21

< .001

Self-Safety with Other-Esteem Self-Safety with Other-Intimacy

.32 .42

< .001 < .001

-.09 .35

.646 .071

.52 .52

< .001 < .001

.33 .41

< .001 < .001

Self-Safety with Other-Control

.43

< .001

.56

.003

.47

.001

.41

< .001

Self-Trust with Self-Esteem

.37

< .001

.07

.730

.45

.002

.37

< .001

Self-Trust with Self-Intimacy

.22

< .001

.33

.097

.19

.213

.22

< .001

Self-Trust with Self-Control

.30

< .001

.17

.390

.40

.007

.28

< .001

Self-Trust with Other-Safety

.23

< .001

.29

.147

.36

.017

.22

< .001

Self-Trust with Other-Trust

.18

< .001

.02

.917

.25

.098

.16

.004

Self-Trust with Other-Esteem Self-Trust with Other-Intimacy

.22 .33

< .001 < .001

-.24 .11

.237 .594

.33 .33

.028 .030

.26 .33

< .001 < .001

Self-Trust with Other-Control

.29

< .001

Self-Esteem with Self-Intimacy

.16

.001

Self-Esteem with Self-Control

.44

Self-Esteem with Other-Safety

.36

Self-Esteem with Other-Trust

.24

.222

.37

.013

.30

< .001

-.09

.675

.12

.453

.20

< .001

< .001

.33

.098

.57

< .001

.44

< .001

< .001

.20

.330

.39

.009

.38

< .001

.20

< .001

.08

.688

.45

.002

.15

.009

Self-Esteem with Other-Esteem

.37

< .001

.10

.627

.48

.001

.37

< .001

Self-Esteem with Other-Intimacy Self-Esteem with Other-Control

.49 .40

< .001 < .001

.50 .43

.008 .026

.63 .45

< .001 .002

.44 .41

< .001 < .001

Self-Intimacy with Self-Control

.13

.008

.12

.568

.28

.071

.13

.025

Self-Intimacy with Other-Safety

.17

< .001

.36

.063

-.09

.569

.19

.001

Self-Intimacy with Other-Trust

.08

.097

.28

.152

-.04

.792

.05

.365 .060

Self-Intimacy with Other-Esteem

.10

.037

.06

.764

.21

.169

.11

Self-Intimacy with Other-Intimacy

.13

.007

.29

.141

.13

.402

.10

.092

Self-Intimacy with Other-Control

.16

.001

.07

.721

.36

.016

.13

.019

Self-Control with Other-Safety Self-Control with Other-Trust

.39 .32

< .001 < .001

.25 .32

.204 .104

.37 .51

.014 < .001

.45 .28

< .001 < .001

Self-Control with Other-Esteem

.35

< .001

.12

.554

.61

< .001

.34

< .001

Self-Control with Other-Intimacy

.55

< .001

.49

.010

.57

< .001

.57

< .001

Self-Control with Other-Control

.52

< .001

.57

.002

.67

< .001

.51

< .001

Other-Safety with Other-Trust

.22

< .001

.10

.634

.43

.004

.21

< .001

Other-Safety with Other-Esteem

.34

< .001

-.03

.872

.45

.002

.36

< .001

Other-Safety with Other-Intimacy

.38

< .001

.18

.377

.38

.012

.42

< .001

Other-Safety with Other-Control Other-Trust with Other-Esteem

.34 .39

< .001 < .001

.34 .02

.081 .903

.40 .62

.007 < .001

.35 .38

< .001 < .001

Other-Trust with Other-Intimacy

.40

< .001

.35

.078

.30

.047

.43

< .001

Other-Trust with Other-Control

.30

< .001

.39

.042

.48

.001

.25

< .001

Int J Adv Counselling Table 1 (continued)

TABS

All groups (n0424)

Kisii (n027)

Luhya (n044)

Luo (n0316)

r

r

r

r

p-value

p-value

p-value

p-value

Other-Esteem with Other-Intimacy

.38

< .001

.21

.304

.48

.001

.38

< .001

Other-Esteem with Other-Control

.32

< .001

.12

.562

.57

< .001

.32

< .001

Other-Intimacy with Other-Control

.45

< .001

.70

< .001

.38

.010

.47

< .001

When controlled by ethnic group, the Luo (n0316), Luhya (n044), and Kisii (n027) met numerical criteria for Pearson’s correlation computations (Table 1). Among the T-scores of the Luo participants, the highest correlations between the “Self” and “Other” scales were between Self-Control with Other-Intimacy (n0316, r0.57, p<.001), and Self-Control with OtherControl (n0316, r0.51, p<.001). Among the Luos, a pattern emerged of Self-Intimacy not correlating with most of the Other-oriented subscales, namely, Other-Trust, Other-Esteem, Other-Intimacy, and Other-Safety (Table 1). Among the Luhya, the highest correlations were between Self-Esteem with Other-Intimacy (n044, r0.63, p<.001) and Self-Control with OtherEsteem (n044, r0>61, p<.001). The exception to the correlation trend was Self-Intimacy, which was significantly negatively correlated with Other-Safety (n044, r0-.088, p>.01) and Other-Trust (n044, r0-.041, p>.01). Among the Kisii, the highest correlations were between Self-Safety with Other-Safety (n027, r0.58, p0.001) and Self-Control with Other-Control (n0 27, r0.57, p0.002). For the Kisii, Other-Esteem was not correlated to the Self-oriented scales and Self-Trust was not correlated to Other-Trust or Other-Esteem (Table 1). When interpreting TABS scores, elevated T-scores on Other-Safety indicate participants’ concerns with the safety of their loved ones, elevated Self-Trust T-scores indicate intrapersonal struggles with trusting one’s own judgments and perceptions, and elevated SelfIntimacy T-scores indicate struggles with being alone or thinking about personal experiences (Pearlman 2003). Participants’ T-scores were elevated on Other-Safety (M065.1; SD08.13), Self-Trust (M065.07; SD09.85), and Self-Intimacy (M068.67; SD09.76). Their scores on the other subscales ranged from High-Average (Other-Trust) to Low (Other-Control). When controlled for age, the 15-16 age group consistently had the highest scores on all 10 TABS subscales, with T-scores elevated on Other-Safety (M067.68; SD06.84), Self-Trust (M0 67.54; SD07.08), and Self-Intimacy (M070.07; SD07.85). The findings for the other age groups were inconsistent: 14-year-olds scored the lowest on Self-Control, Other-Control, Self-Safety, Other-Safety, Other-Trust, Self-Esteem, Other-Esteem, and Other-Intimacy; 1011-year-olds were the lowest on Self-Control and Other-Control; and 13-year-olds were the lowest on Self-Intimacy. Question 5: Do Children with Distressful Sexual Experiences Note More Severe Symptoms of Distress Than Their Peers? Four SATS questions indicated distressful experiences related to sex: Q25 (“Someone talked about sex and I didn’t like it”); Q29 (“Sexual comments were made about me”); Q30 (“I was touched sexually”); and Q33 (“I was forced to have sex”), with participants noting frequency of occurrence. Responses were categorized into three groups: “did not happen”, “one time”, and “more than one time”. One-way ANOVAs were run to assess differences between participants’ TABS scores and scores on these four SATS questions. If any one-way ANOVA was significant at p<0.05, pairwise comparisons with Bonferroni correction were

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run to compare levels of the SATS variable. These analyses revealed that, for Q25 and Q29, participants who indicated “more than one time” on both questions had the highest scores on the TABS Self-oriented and Other-oriented scales, except for Self-Intimacy, on which mean T-scores were similar to the other two groups. On Q30, participants who noted “one time” scored the highest on the TABS Self- and Other-oriented subscales compared to the entire sample. The same pattern was evident in the responses to Q33, with the exception of OtherSafety and Other-Esteem, on which scores were similar to other participants (see Tables 2 & 3 for additional details). A one-way ANOVA was run to assess differences between participants’ Enduring Symptoms scores and scores on these four questions. If the one-way ANOVA was significant at p<0.05, pairwise comparisons with Bonferroni correction were run to compare levels of the SATS variable. On Q25, participants who re-experienced the event tended to have the highest

Table 2 TABS Subscales analysis with SATS Question 25 and 29 ANOVA F(2,414)

p-value

Mean (SEM)

Mean (SEM)

Mean (SEM)

Did not happen (n0261)

One time (n058)

More than one time (n098)

55.6 (0.56) a

55.0 (0.99) a

59.5 (0.97) b

Q25

Self-Safety

7.44

0.001

Self-Trust

1.91

0.15

64.7 (0.64)

63.7 (1.19)

Self-Esteem

7.23

0.001

50.4 (0.57) a

51.1 (1.11)

Self-Intimacy

1.41

0.25

Self-Control

6.08

0.002

Other-Safety

6.27

Other-Trust Other-Esteem Other-Intimacy Other-Control Total Enduring Symptoms

66.6 (0.92) ab

54.4 (0.86) b

69.1 (0.60)

66.7 (1.24)

68.6 (1.01)

52.8 (0.59) a

52.9 (1.30) ab

56.6 (0.88) b

0.002

64.4 (0.51) a

64.0 (1.01) a

67.6 (0.81) b

1.00 6.47

0.37 0.002

56.2 (0.56) 54.5 (0.56) a

58.0 (1.12) 57.1 (1.15) ab

56.8 (0.98) 58.0 (0.82) b

4.15

0.016

51.2 (0.53) a

51.0 (0.97) ab

54.0 (0.88) b

0.041

51.2 (0.55)

a

50.8 (1.10)

ab

53.7 (0.95) b

34.7 (1.84)

a

38.1 (3.97)

a

52.8 (3.72) b

3.23 11.89

<0.001

Q29 Did not happen (n0368)

One time (n025)

More than one time (n024) 63.2 (2.09) b

Self-Safety

7.20

0.001

56.0 (0.47) a

56.6 (1.54) a

Self-Trust

0.43

0.65

64.9 (0.52)

64.6 (1.42)

66.8 (2.15)

Self-Esteem

7.95

<0.001

51.0 (0.46) a

50.4 (1.90) a

58.4 (2.19) b

Self-Intimacy

0.85

0.43

68.7 (0.50)

70.1 (2.12)

66.5 (2.12)

Self-Control

4.18

0.016

53.3 (0.50) a

54.4 (1.79) ab

59.0 (1.65) b

Other-Safety Other-Trust

5.00 3.05

0.007 0.048

64.9 (0.42) a 56.5 (0.47) a

64.0 (1.84) a 54.3 (2.00) ab

70.1 (1.59) b 60.5 (1.94) b

Other-Esteem

0.31

0.74

55.6 (0.46)

55.3 (1.60)

57.0 (2.12)

Other-Intimacy

6.27

0.002

51.4 (0.44) a

52.2 (1.71) ab

57.6 (1.62) b

Other-Control

5.02

0.007

51.2 (0.47) a

55.6 (1.88) b

55.5 (1.70) ab

0.002

a

a

Total Enduring Symptoms

6.48

38.3 (1.62)

36.1 (6.68)

62.5 (9.08) b

*Means with the same superscripted letter are not significantly different from each other (pairwise comparisons, Bonferroni corrected)

Int J Adv Counselling Table 3 TABS Subscales analysis with SATS Question 30 and 33 ANOVA F(2,414)

p-value

Mean (SEM)

Mean (SEM)

Mean (SEM)

Did not happen (n0381)

One time (n023)

More than one time (n013)

Q30

Self-Safety

1.59

0.21

56.2 (0.47)

59.4 (1.74)

58.2 (2.74)

Self-Trust Self-Esteem

1.89 2.96

0.15 0.053

64.8 (0.50) 51.1 (0.47)

66.6 (2.22) 55.7 (1.41)

69.7 (2.36) 52.7 (2.57)

Self-Intimacy

0.04

0.97

68.6 (0.50)

68.8 (2.14)

69.3 (2.58)

Self-Control

7.19

0.001

53.4 (0.49) a

60.5 (1.59) b

50.1 (2.42) a

Other-Safety

2.00

0.14

64.9 (0.41)

68.3 (1.83)

Other-Trust

3.12

0.045

56.3 (0.46) a

61.2 (2.11)

Other-Esteem

0.44

0.64

55.6 (0.46)

57.4 (2.09)

Other-Intimacy

2.86

0.058

51.6 (0.43)

55.9 (2.05)

52.2 (1.56)

Other-Control Total Enduring Symptoms

4.06 2.04

0.018 0.13

51.4 (0.46) a 38.7 (1.66)

56.6 (1.63) b 42.3 (7.16)

53.9 (2.64) ab 55.9 (8.48)

Did not happen (n0399)

One time (n011)

More than one time (n07)

66.1 (2.71) b

56.0 (2.48) ab 56.1 (1.44)

Q33

Self-Safety

2.80

0.06

56.3 (0.45)

62.8 (2.44)

55.7 (6.29)

Self-Trust Self-Esteem

0.66 4.88

0.52 0.008

64.9 (0.49) 51.2 (0.45) a

65.7 (3.08) 59.7 (1.96) b

69.1 (3.86) 51.7 (3.94) ab

Self-Intimacy

0.03

0.97

68.6 (0.49)

69.0 (3.17)

67.9 (3.33)

Self-Control

0.83

0.44

53.6 (0.48)

57.4 (2.86)

53.4 (3.42)

Other-Safety

3.33

0.037

64.9 (0.41)

70.1 (2.21)

69.7 (2.36)

Other-Trust

0.13

0.88

56.5 (0.46)

57.9 (3.16)

56.9 (3.10)

Other-Esteem

1.00

0.37

55.6 (0.45)

57.4 (2.87)

59.9 (3.69)

Other-Intimacy

3.49

0.031

51.6 (0.42) a

58.2 (2.00) b

53.9 (3.52) ab

Other-Control Total Enduring Symptoms

2.05 2.29

0.13 0.10

51.6 (0.45) 39.0 (1.61)

56.4 (2.27) 60.8 (13.61)

55.1 (2.90) 37.6 (11.75)

*Means with the same superscripted letter are not significantly different from each other (pairwise comparisons, Bonferroni corrected)

Enduring Symptoms scores and those with low Enduring Symptoms scores tended to note that it did not happen. On Q29, a significant difference (p00.001) emerged whereby participants who noted a frequency of more than once scored higher on Enduring Symptoms (Table 2). Analysis of Q33 (p00.10) and Q30 (p00.13) yielded no statistically significant findings (Table 3). Although Q33 (“I was forced to have sex”) did not reach statistical significance (p00.10), the mean Enduring Symptom score for those who noted that the experience happened once was more than 20 points higher than for those who said it never happened and for those to whom it happened more than once. Participants who reported being forced to have sex more than once had the lowest scores, suggesting that when frequently sexually abused, participants may become resigned or numbed to the experience. For this group of participants, the effects of the abuse appeared to ameliorate in comparison to those who were forced to have

Int J Adv Counselling

sex once. Yet, because of the small sample size (n07), interpretations are subject to further exploration (Table 3). To establish whether students who had distressful sexual experiences reported heightened symptoms of trauma compared with other participants, a Spearman’s rho was calculated between total Enduring Symptoms and participants’ scores on the four SATS questions. Scores on Q25 were positively correlated with Enduring Symptom scores. Results of chisquare tests determined that responses to these four questions did not vary significantly based on gender or with whom participants lived. A one-way ANOVA compared academic percentile rank with the frequency with which participants experienced these four events. A significant difference between the means did not emerge for Q25, Q29, or Q30 (all p-values > 0.49). On Q33 (p0.075) participants who experienced the event more than once had a lower academic percentile rank than the other groups, but no significance was noted at p<0.05. There were many statistically significant findings in the analysis of the four SATS questions and the TABS subscales. The effect size of five points was met in most of the subscales; thus, most findings were both statistically and clinically significant. For Q29 (“Sexual comments were made about me”), significant findings with an effect size of five or more was found with Self-Safety, Self-Esteem, Self-Control, Other-Safety, Other-Trust, and Other-Intimacy. For Q30 (“I was touched sexually”) similar findings were evident in Self-Control, Other-Trust, and Other-Control (Table 3). Finally, for Q33 (“I was forced to have sex”) similar findings were evident in Self-Esteem, Other-Safety, and Other-Intimacy (Table 3).

Discussion The findings of this study contribute to the trauma and violence literature by enhancing the understanding of children’s perspectives of their experiences in war prone areas and the impact that this trauma has on them. All five research questions elicited responses that resulted in clinically significant findings and partially statistically significant findings. This study found clinically significant T-scores on all three self-report instruments administered. On the MWES, participants met clinical significance on all four PTSD criterion subscales, with T-scores ranging from 38.5 % to 59.2 % on Impact of the Event (IMPACT), Reexperience of the Trauma (REEX), Avoidance and Numbing (AVOID), and Increased Arousal (AROUS). Among these four criterion subscales, REEX (59.2 %) and AROUS (53.5 %) yielded the highest scores among participants. Of these four criterion subscales, the same symptoms as REEX and AVOID have been cited in other studies (e.g., Seedat et al. 2004). These findings indicate that in Kisumu, trauma and emotional distress symptoms continued to manifest themselves among school children 1 year after the violence. The significant scores on IMPACT and AROUS suggest unresolved emotional reactions to traumatic events. Participants also met clinical significance on the MWES symptom subscales of Depression (DEPR), Oppositional Conduct (OPP), Hyper-vigilance (HYPER), Somatic Symptoms (SOM), Dissociation and Dreams (DISSOC), and General Maladjustment (MAL), with scores ranging from 27.7 % to 64.2 %. DISSOC (64.2 %) and MAL (61.6 %) yielded the highest scores among participants in the symptom subscales. Scores on REEX, AROUS, DISSOC, and MAL met criteria significance on DSM-IV-TR criteria for diagnosing PTSD. This high level of clinical significance is consistent with findings in other studies conducted in Africa. In a study assessing PTSD among South African Adolescents, Seedat et al. (2004, p. 7) “found high rates of trauma exposure on both clinician

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administered and self-report measures in adolescents.” These findings suggest a need for effective clinical interventions and further studies in these clinical areas. The study also examined if patterns of unresolved traumatic symptoms manifest themselves in children’s social and academic functioning. A statistically significant relationship emerged between the academic percentile rank of participants and their scores on the three instruments. Students with higher academic percentile rank also scored lower on the Enduring Symptoms subscale of the MWES, which was consistent with the research on resiliency and academic success (Scales et al. 2006). Participants who reported a high academic rank also reported fewer clinically significant responses to traumatic experiences and a much shorter length of time that the trauma affected their functioning. As other research (e.g., Solber et al. 2002) has suggested, academically high achieving students may have greater resiliency as shown by their responses to emotional and social challenges. High achieving students may be better able to access support resources than low achieving students. This argument could be supported by the fact that academic performance and school rank remain a key focus of Kenyan public schools (Okech and Kimemia 2012). Thus, Kenyan school staff may be more concerned by high achieving students’ distress and more motivated to provide them with support because students with high ranks are more systemically valued than students with low ranks. The study also examined whether or not gender was a factor in the manifestation of trauma symptoms and emotional distress. Gender did not demonstrate a significant difference in scores on the three instruments or in the length of time that participants experienced symptoms. This finding is congruent with other studies of children that have found gender equivalency in the presence of PTSD symptoms (Giaconia et al. 2000; Morgos et al. 2008) and the presentation and rate of diagnosis of PTSD (Seedat et al. 2004). The incongruence between the current study’s findings and prior research that highlighted gender differences (Quota and Sarraj 2004; Vizek-Vidović et al. 2000) in which girls scored higher may be related to mean age of the sample (12.9 years), or contextual and cultural settings of the research. Gender only emerged as a factor in school settings. Participants’ worst experiences in school settings tended to occur with students of the same gender (except for when events occurred with teachers). When the perpetrator of the participant’s worst experience was a teacher, male and female students predominantly identified female teachers over males. This suggests a need to review the interactions between teachers and students in public schools and, specifically, to cross-gender dynamics within schools. This study also examined variables that might predict severity and endurance of trauma and distress symptoms among participants. A significant effect of age emerged on the MWES: 15-year-olds had the highest mean scores and 10-year-olds had the lowest, raising questions about the link between age and level of trauma. Similar studies have arrived at inconclusive findings with older children, reporting “significantly more depressive and anxiety reactions, while younger children reported more PTSRs and better psychosocial adaptation” (Vizek-Vidović et al. 2000, p. 304). Participants’ mean age at their worst experience was 12.9 (SD01.21) and the mean age of participants one year after the postelection violence was 13; there appears to be a correlation between the timing of the violent events and the timing of their worst experiences. Over half of participants named death or war (combined n0194, 51.5 %) as their worst experience. Given Kenya’s high rates of violence in the post-election era and death rates from HIV/AIDS, identifying children struggling with grief is essential for appropriate school interventions. Additionally, in examining findings from all three instruments and the MWES Enduring Symptoms subscale, the mean scores for participants in schools without counselors were consistently higher than those of students in schools with counselors. Although this result

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did not reach statistical significance, the difference in mean value may indicate that the presence of school counselors improves the overall school environment and how children feel in school. However, the presence of counselors does not clearly affect how students cope with trauma. It is possible that a lack of professional counseling training impairs school counselors’ ability to clinically address trauma, or that school resources are insufficient to address these symptoms. There were many statistically and clinically significant findings in the SATS analysis of participants who reported sexually-rooted distress in comparison to other participants. Children who reported having sexual comments made about them consistently had the highest Enduring Symptoms scores in the study. Similarly, those who reported having been ‘touched’ sexually or having been forced to have sex in the SATS also tended to have the highest scores in the TABS “Self-” and “Other-” oriented scores, which is consistent with empirical support for the validity of the TABS (Pearlman 2003). For these participants, disruptions in safety, esteem, and control may have led to heightened concerns about the safety of self and others, self doubt, mistrust of others, and self-blame for their experiences. These findings are consistent with the literature on sexual trauma (Underwood et al. 2007; Wasco 2003) that reflects that survivors of sexual abuse have prolonged challenges in dealing with traumatic experiences and are more likely to generalize lower feelings of self-worth and self-efficacy across their life experiences. The findings of this study imply that more effective interventions are required for the population of participants who report distress that is grounded in sexual experiences.

Limitations, Research and Counseling Implications In interpreting these findings, one must consider its limitations. The main cultural issue related to language that emerged was not literacy, as anticipated; rather, it was the unfamiliar American lingo used in the instruments as opposed to the British English terms to which Kenyan students are more accustomed. Consequently, after several questions during the first two administration sessions of the study, a glossary was provided to participants to avoid multiple questions being left blank (e.g., “vomit” for “throw up”; “I bullied other kids” for “I picked on other kids”; “I mouthed off to adults” for “I was rude to adults”, etc). Additional translation of words into Dholuo or Kiswahili also seemed sufficient. Another limitation is that all of the data were obtained through self-report measures in a group format. It is possible that some participants who did not understand a question chose not to ask for help or gave arbitrary responses. Additionally, as with most children completing self-report measures, some participants were unable to differentiate between the severity of violent experiences. This resulted in reports of violent experiences ranging from sexual or physical violence to minor disagreements with friends in the schoolyard.

Recommendations for Future Research Because this was the first study in Kisumu (Kenya) to conduct a multi-dimensional assessment of children’s experiences and reactions in a conflictual context, replication and expansion of this study to include clinician-based assessments is needed. The development of more culturally relevant instruments and the adaptation of contemporary instruments to the Kenyan context would yield more meaningful results in future studies. Future studies could also use multiple measures that include clinician-based assessments, individual

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interviews, observation of participants, and individual administration of the measures to yield additional data adding depth of understanding to the findings. Since the findings related to the role of school counselors in this context are inconclusive, research involving more schools could facilitate the effective review of the impact of school counselor presence. The expansion of the sampling pool and context may also help assess significance in the impact made by trained professional counselors vs. teachers who serve as school counselors without any formal counseling training. Acknowledgements This research was supported in part by a grant from the University of Vermont’s Office of the Vice-President for Research and Graduate Studies. The Kenya Female Advisory Organization (KEFEADO) generously provided a research administration office and storage facilities in Kisumu, Kenya. The author is also deeply indebted to Allan Howard of the University of Vermont’s Statistical Consulting Clinic (SCC) for his assistance in analyzing the data reported in this manuscript. The author thanks the students, administrators, teachers, parents, and guardians in the primary schools in Kisumu who participated in this investigation.

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