<!-- image -->

Research Article                                                                                                                                                        Open Access

## Modeling Patterns of Negative Life Events and Mental Health in Faroese Adolescents

Tóra Petersen, Cherie Armour, Ask Elklit

National Centre for Psychotraumatology, University of Southern Denmark, Odense M, Denmark/ The National Hospital of the Faroe Islands, Torshavn, Faroe Islands

Corresponding Author:

lstorpe@ls.fo

## Abstract

Objectives: The objective of this study was to identify naturally occurring typologies of Faroese adolescents on the basis of their exposure to traumatic and negative life events. It was hypothesized that underlying typologies of trauma and negative life events would be uncovered. Furthermore, it was hypothesized that males would be overrepresented in classes characterized by the endorsement of a wide range of trauma and negative life events. On the basis of prior research, it was also hypothesized that females had endorsed more traumas of a sexual nature and that males had endorsed more traumas of a violent nature. Finally, post-traumatic stress, negative affectivity, and somatization were examined in the different typologies.

Methods: Latent class analyses were conducted with the use of data collected from a self-report questionnaire survey from 687  Faroese  eighth  graders  (85%  response  rate).  The  questionnaire  included  a  traumatic  and  negative  life  event  list,  the Harvard Trauma Questionnaire-Part IV, and the Trauma Symptom Checklist.

Results: Three classes of adolescents were identified on the basis of their exposure to potentially traumatic and negative life events. The baseline class (81.3%) had a low probability of the endorsement of all potentially traumatic and negative life events, except threats of violence and bullying. This group had low scores for post-traumatic symptoms, negative affectivity, and somatization. Class 2 (13.7%) comprised mainly males and had the highest probability of endorsement of threats of violence, physical assault, and bullying; this group also had high scores for post-traumatic stress symptoms, negative affectivity, and somatization. Finally, Class 1 (5.0%) consisted of adolescents with a relatively high risk of exposure to all potentially  traumatic  events  and  negative  life  events,  except  threats  of  violence.  This  group  had  the  highest  scores  for  posttraumatic stress symptoms, negative affectivity, and somatization.

Conclusions: The present study can be said to be a concise picture of trauma exposure and its consequences among Faroese adolescents, and it is thereby a valuable tool for the national planning of preventive and interventional strategies and for empirically founded economic prioritization. These results emphasize the importance of choosing a trauma-informed strategy in various disciplines, such as pediatrics, child and adolescent psychiatry, social work, and school psychology when the aim is to provide the appropriate intervention.

Key words: trauma typologies, adolescents, latent class analysis, total population, posttraumatic stress

## Introduction

Trauma exposure

Exposure to trauma is highly prevalent (1). However,  studies  of  adolescents'  exposure  to  traumatic events  are  still  mainly  focused  on  specific  trauma populations,  and  studies  of  a  broader  range  of events  are  relatively  scarce  (2).  European  studies based on national probability populations of young adolescents from 14 to 15 years old found that the prevalence of direct  and  indirect  exposure  to  trau- matic and negative life events varied from 79% to 81%  among  males  and  from  74%  to  87%  among females  (3).  Alternative  studies  that  use  the  same data as those used for the current study have shown that  the  prevalence  of  direct  and  indirect  exposure was somewhat higher among Faroese adolescents of the  same  age,  given  that  reported  rates  were  89% among males and 94% among females (4).

## Consequences of trauma

Research has shown that exposure to trauma has a negative effect on children and adolescents in various domains and that these consequences might be  prolonged  or  chronic.  Exposure  to  traumatic events alters psychological development and risk of maladjustment. Short- and long-term psychological and physical health problems are significantly more prevalent  among children and adolescents exposed to traumatic events as compared with those who are not exposed to traumatic events (5). Broberg, Dyregrov, and Lilled (6) found that school achievement  among  adolescents  was  significantly worsened after exposure to a traumatic discotheque fire.  Other  studies  have  found  that  post-traumatic stress  disorder  (PTSD)  may  be  a  determinant  of drug use disorder, given that drugs may be used for the self-medication of trauma-related  memories, nightmares,  and  hyperarousal  symptoms  (7).  In  a comprehensive meta-analysis of 16 epidemiological studies that includes more than 23,000 participants, Nanni and colleagues reported that trauma such as childhood  maltreatment  was  associated  with  both recurrent  and  chronic  depression  (8).  In  another meta-analysis of 10 clinical trials, the same researchers  found that childhood maltreatment was associated negatively with treatment outcome (8). Studies among  risk  populations,  such  as  refugees,  have shown  that  the  prevalence  of  PTSD  ranges  from 31%  to  47%,  even  when  the  traumatic  event  had taken  place  9  to  11  years  before  the  study  (9).  A prospective,  longitudinal,  epidemiological  study  of 2548  German  adolescents  and  young  adults  between the ages of 14 and 24 years showed that 48% of those with PTSD and subtreshold PTSD had no significant  decline  in  PTSD  symptoms  34  to  50 months later (10).

## Traumatization and gender

Studies have found a gender difference with regard to  both  exposure  to  trauma  and  the  consequences of trauma. Most studies have shown that exposure to traumatic events is more prevalent among males, whereas  the  lifetime  prevalence  of  post-traumatic stress  was  higher  among  females  (1;11;12).  Tolin and  Foa  (12)  found  that  this  gender  difference could  not  be  explained  by  methodological  issues, and  it  was  not  likely  to  be  overturned  by  the  filedrawer effect. However, most studies that examine gender differences in mental health and trauma are based  on  convenience  samples  or  specific  trauma groups, which might provide artificial results. When comparing post-traumatic stress among adolescents aged 14 and 15 years from four European countries, Elklit  and  Petersen  (3)  reported  cultural  variations in  this  gender  difference  on  the  basis  of  three  national probability samples and one total population sample:  in  Lithuania  and  Denmark,  the  male-tofemale ratio was 2:1; in the Faroe Islands, it was 3:1; and in Iceland, there were no gender differences. Identification of traumatized adolescents Studies  indicate  that  exposure  to  traumatic  events may  lead  to  an  enhanced  risk  for  further  traumatization.  For  example,  studies  have  found  that  the exposure rate to new traumatic events among adolescents  and  young  adults  rose  from  17%  to  20% during a follow-up period of 34 to 50 months (13). This  rise  may  be  attributable  to  these  adolescents being  more  sensitive  to  new  trauma  or  to  prior trauma increasing the risk of later exposure. Briggs and colleagues (5) argue that making group distinctions  and  identifying  vulnerable  groups  of  children and  adolescents  is  important,  given  the  growing evidence  that  youths  who  report  multiple  traumas are  at  greater  risk  for  subsequent  trauma  exposure as compared with youths who report a single trauma.

The  identification  of  a  trauma  history  in  adolescents  is  important,  given  that  knowledge  of  such can be used to guide treatment plans and to prevent further  traumatization.  In  addition,  it  is  of  great economic interest for society, because studies have shown that childhood exposure to traumatic events is associated with a significantly higher use of mental and physical health services among adults (5;14). A study based on 668 questionnaires from females in a gynecologic clinic found that more than half of the sample - all well-educated, middle-class women between 16 and 76 years old - had been exposed to childhood abuse (15). This study also showed that the females who were exposed to abuse during their childhood reported significantly more psychological and physical problems and more hospitalizations for illnesses  as  compared  with  those  females  without childhood abuse.

Recent  research  has  implemented  more  complex statistical methods for the identification of traumatized groups. Indeed, latent class analysis (LCA) and latent  profile  analysis  (LPA)  have  been  used  with the aim of uncovering naturally occurring typologies of  traumatic  experiences.  LCA  and  LPA  are  ideal statistical  methods  for  uncovering  typologies,  because they categorize individuals into groups on the basis of how they respond to a series of questions. Similar  responders  are categorized together.  To date, studies using LCA and LPA have shown that maltreated  children  can  be  divided  into  different classes  that  are  characterized  by  various  combinations of maltreatment, different severities, and various consequences of the maltreatment (16;17).

## Aims and hypotheses

To  enhance  the  basis  for  planning  preventive  and interventional  strategies  and  to  contribute  to  an empirical  foundation  for  economic  prioritization, the  present  study  was  conducted.  One  aim  was  to identify  naturally  occurring  typologies  of  Faroese adolescents on the basis of their exposure to traumatic and negative life events. It was hypothesized that  underlying  typologies  of  trauma  and  negative life events would be uncovered. Furthermore, it was hypothesized that the male gender would be predictive of membership in classes that endorsed a wide range of trauma and negative life events, given literature that has reported that males experience more trauma than females (12). However, we were mindful  that  males  and  females  have  been  reported  as experiencing  different  types  of  trauma.  For  example,  females  experience  traumas  of  a  sexual  nature more so than males, and males experience traumas of  physical  violence  more  so  than  females  (4;12). Thus, associations between classes and gender may vary  as  a  function  of  the  class  characteristics  (i.e., the  type  of  trauma  and  negative  life  event  endorsed). Another aim was to examine posttraumatic  stress,  negative  affectivity,  and  somatization among the adolescents in the different classes. Given  the  extant  literature  that  associates  trauma and  negative  life  events  with  the  development  of mental  health  issues  (15),  we  hypothesized  that individuals  who  met  the  criteria  for  post-traumatic stress,  negative  affectivity,  and  somatization  would be more likely to be members of classes characterized  by  strong  probabilities  of  endorsing  traumas and negative life events as compared with a baseline class.

## Method

Procedure

The present study is based on data from the Faroese Trauma  Study  among  adolescents.  The  data  was collected  from  a  self-report  questionnaire  survey from  687  Faroese  eighth  graders  (85%  response rate). The study was approved by the Faroese Data Protection  Agency  the  Faroese  Ministry  of  Education, and the Faroese Ethical Board. The ages of the participants ranged from 13 to 16 years (mean, 14.2 years;  standard  deviation, 2.1  years),  and  just  more than half of the sample were males (52.5%). See the articles by Elklit and Petersen (3) and Petersen and colleagues (4) for further details.

## Measures

Event  list: The original  questionnaire  included  a  list of 19 potentially traumatic events and negative life events.  The  adolescents  were  asked  to  choose  the event  that  they  found  most  distressing.  They  were subsequently asked to complete the Harvard Trauma  Questionnaire  -  Part  IV  (HTQ-IV)  for  their most  distressing  event.  We  queried  a  number  of potentially  traumatizing  and  negative  life  events, but, rather than include all of them, we focused on those  from  the  literature  that  are  thought  to  be some of the most traumatizing: physical abuse, sexual  abuse,  neglect  (18),  rape  (19),  physical  assault, having witnessed others injured or killed or threats of  violence  (20),  bullying  (21),  attempted  suicide (22), and serious illness (23;24) (Table 1).

Posttraumatic  stress  symptoms: The  HTQ-IV  (25)  was used to estimate the post-traumatic stress symptoms at the time that followed the potentially traumatic or negative  life  event.  The  HTQ-IV  consists  of  31 items, of which 17 items correspond to the PTSD diagnosis  in  the Diagnostic  and  Statistical  Manual  of Mental  Disorders,  Fourth  Edition (26).  The  items  are scored on a four-point Likert scale (1 = not present, 4  =  very  often  present).  The  HTQ-IV  has  been extensively used in the Nordic countries, but it had not  previously  been  used  in  the  Faroe  Islands.  A translation was assessed and accepted by two independent scholars and a clinical  psychologist  skilled in the Faroese language.

The HTQ-IV measures the intensity of the three core  symptom  groups  of  PTSD:  intrusion,  avoidance,  and  hypervigilance.  Only  symptoms  given  a score of 3 or more count toward a PTSD diagnosis. Both  Mollica  and  colleagues  (25)  and  Bach  (27) reported  good  reliability  and  validity  for  the  scale; however,  HTQ-IV  reliability  and  validity  data  for adolescents  or  Faroese  subjects  is  not  currently available. The internal consistency of the scale was high, with a Cronbach's alpha of 0.98 for the total PTSD scale and alphas of 0.88, 0.91, and 0.90 for the  intrusion,  avoidance,  and  hypervigilance  subscales,  respectively.  The  mean  inter-item  correlations for the subscales were, correspondingly, 0.64, 0.59,  and  0.63,  thereby  indicating  a  moderate  discriminatory power (28).

Negative affectivity and somatization: The Trauma Symptom  Checklist  (TSC)  is  a  broad  symptom  list  that assesses the impact of a traumatic event or negative life  event  on  an  individual's  body,  emotions,  and cognition  in  addition  to  their  social  relations  and self-image.  Each  item  is  scored  on  a  four-point Likert  scale  (0  =  not  present,  3  =  very  often  present). The TSC was originally created by Briere and Runtz  (29),  and  the  validity  and  reliability  of  the TSC have been shown to be good. Factor analysis of the TSC has identified two subscales: the somatization subscale and the negative affectivity subscale (30).  The  somatization  subscale  consists  of  eight items  related  to  headache,  dizziness,  stomachache, and  other  nonspecific  somatic  symptoms.  Adolescents in the current study with scores of more than 23 were defined as having high somatization levels. The  negative  affectivity  subscale  consists  of  10 items related to a mixture of anxiety and depressive symptoms,  such  as  sadness  and  thoughts  of  selfharm. Adolescents in the current study with scores of  more  than  30  were  defined  as  depressed.  The revised  TSC  has  good  reliability  and  good  factor and criteria  validity.  The  alpha  values  in  this  study were  0.82  for  somatization  and  0.85  for  negative affectivity.

## Analysis

All  analyses  within  the  current  study  were  implemented with the use of Mplus version 6 (31). LCA (32)  was  employed  to  determine  if  empirically  derived typologies of binary coded trauma and negative  life  events  exist  among  Faroese  adolescents. LCA is an exploratory and iterative model-building technique that uncovers typologies on the basis of an  individual's  similarity  of  responding  across  a series of manifest variables. The probability of class membership (posterior probabilities) is derived from  two  parameters:  class  probabilities  (i.e.,  class prevalence) and item probabilities (i.e., specific item endorsement probabilities). Individuals are assigned membership  in  a  particular  class  in  a  probabilistic fashion  rather  than  a  deterministic  fashion.  For comprehensive  details  of  this  statistical  technique, please consult the article by Haagenars and McCutcheon (32).

In  the  current  study,  we  specified  and  estimated five latent class models (two to six classes) with the use of the default robust maximum likelihood estimator. To ensure successful convergence on global maxima,  we  employed  500  random  sets  of  initial starting  values  with  10  optimizations.  To  ascertain which  latent  class  solution  provided  optimal  fit  to the data, we consulted several fit indices, including the  Akaike  information  criterion  (AIC)  (33),  the Bayesian information criterion (BIC) (34), the sample-size  adjusted  BIC  (SSABIC)  (35),  the  entropy value (36), and the Lo-Mendell-Rubin adjusted likelihood ratio test (LRT) (37). Optimal fit is indicated by models, which have lower AIC, BIC, and SSABIC  values.  On  some  occasions,  fit  may  improve with the AIC, BIC, and SSABIC continually lowering. DiStefano and Kamphaus (38) noted that the  difference  between  continually  lowering  values should  be  calculated.  In  the  event  that  the  difference between a particular latent class model and one with  an  additional  class  is  particularly  small,  the additional  class  is  said  to  add  little  to  the  model. Nylund  and  colleagues  (39)  recently  conducted  a series of simulation studies in which they concluded that  the  BIC  was  the  most  reliable  indicator  of latent  class  enumeration.  Before  this,  Yang  (40) reported  that  the  SSABIC  was  the  most  reliable indicator  of  latent  class  enumeration.  Entropy  values give a measure of how distinct classes within a latent  class  model  are  from  one  another.  Values range from 0 to 1, and those that reach 1 indicate clear  classification.  A  nonsignificant  LRT  indicates that a latent class model with one less class may be the  more  parsimonious  option.  After  determining which latent class model was the optimal fit to the data,  the  model  parameters  were  fixed  before  the inclusion  of  covariates,  thereby  ensuring  that  the covariates did not impact the latent class structure. Multinomial  logistic  regression  was  subsequently employed  to regress an individual's conditional probabilities  for  indicators  of  gender  and  mental health. The odd ratios and corresponding 95% confidence  intervals  presented  indicate  an  individual's likelihood  of  membership  in  classes  as  compared with the baseline class.

## Results

## Frequencies of negative life events

The  most  commonly  endorsed  trauma  or  negative life  events  was  threats  of  violence  (31.6%),  closely followed by humiliation or persecution from others (30.1%). The least commonly endorsed negative life events or trauma was rape (4.1%). Table 1 reports participants'  endorsement  across  all  10  trauma  or negative life events.

TABLE 1. Frequency of endorsement of direct trauma exposure and negative life events among Faroese adolescents (n = 687)

| Traumatic events and negative life events             |   Frequency of endorsement (%) |
|-------------------------------------------------------|--------------------------------|
| 1. Physical assault                                   |                            9.6 |
| 2. Rape                                               |                            4.1 |
| 3. Witnessing the injury or death of others           |                            9.6 |
| 4. Threats of violence                                |                           31.6 |
| 5. Suicide attempts                                   |                            9.9 |
| 6. Serious illness                                    |                           12.8 |
| 7. Sexual abuse                                       |                            5.1 |
| 8. Physical abuse                                     |                            7.3 |
| 9. Neglect                                            |                            4.9 |
| 10. Humiliation or persecution from others (bullying) |                           30.1 |

Prevalence of posttraumatic stress, depression, and somatization

Of  the  adolescents  surveyed,  139  (20.2%)  fulfilled the  criteria  for  post-traumatic  stress.  Of  these,  75 (10.9%) had high scores for negative affectivity, and 86 (12.5%) had high somatization scores.

## Latent class analysis

Class  enumeration: The  fit  statistics  for  latent  class models  two  through  six  across  10  binary  negative life  events  (physical  assault,  rape,  witnessed  others injured or killed, threats of violence, attempted suicide,  serious  illness,  sexual  abuse,  physical  abuse, neglect, and humiliation)indicators are presented in Table  2.  The  value  of  the  AIC  continually  lowers from the two-class solution to the six- or five-class solution,  with  a  slight  increase  from  the  five-class solution  to  the  six-class  solution.  The  largest  decrease  occurs  from  the  two-class  solution  to  the three-class solution, thereby indicating that the three-class solution provides optimal fit. The lowest BIC value is found for the three-class solution. The lowest value for the SSABIC is found for the fourclass  solution;  however,  it  is  merely  1  point  lower than the BIC value for the three-class solution. In addition,  when  applying  the  recommendations  of DiStefano and Kamphaus (38), the largest decrease for  the  SSABIC  value  occurs  from  the  two-class solution  to  the  three-class  solution;  this  suggests that  the  three-class  solution  is  optimal,  although there  is  a  slight  rise  in  value  from  the  four-class solution to the five-class solution and from the fiveclass solution to the six-class solution. The entropy values  are  highest  for  the  two-,  four-,  and  threeclass  solutions,  respectively.  However,  a  value  of 0.860  indicates  that  individuals  in  the  three-class solution  are  clearly  classified.  The  LRT  value  becomes  nonsignificant  for  the  five-class  solution, thereby  indicating  that  the  four-class  solution  may be  the  more  parsimonious  option.  Taking  all  fit statistics into consideration and based on DiStefano and  Kamphaus  (38),  Nylund  and  colleagues  (39), and Yang (40), the three-class solution provides an optimal fit to the data.

TABLE 2. Fit indices for latent Classes 2 through 6

|         |      AIC |      BIC |   SSABIC |   Entropy | LRT ( P value)   |
|---------|----------|----------|----------|-----------|------------------|
| Class 2 | 4118.539 | 4213.718 | 4147.040 |     0.901 | 591.512 (0.0000) |
| Class 3 | 4059.463 | 4204.498 | 4102.893 |     0.860 | 79.963 (0.0315)  |
| Class 4 | 4042.828 | 4237.718 | 4101.187 |     0.885 | 38.105 (0.0436)  |
| Class 5 | 4035.082 | 4279.828 | 4108.370 |     0.754 | 29.337 (0.1789)  |
| Class 6 | 4036.071 | 4330.672 | 4124.288 |     0.780 | 20.723 (0.0364)  |

AIC, Akaike information criterion; BIC, Bayesian information criterion; SSABIC, sample-size adjusted Bayesian information criterion; LRT (P value) = Lo-Mendell-Rubin adjusted likelihood ration test value and associated significance level

three-fold  risk  of  being  in  Class  2  (versus  Class  3) when compared with females (odds ratio [OR], 2.4; confidence  interval  [CI],  1.81  to  3.42).  Diagnosis with  PTSD  significantly  predicted  membership  in Classes  1  and  2.  Indeed,  individuals  who  met  the diagnostic criteria for post-traumatic stress had about a two-fold risk for being in Class 1 (OR, 2.41;

Class characteristics: Class 3 (81.3%) was characterized by  individuals  who  had  low  probabilities  of  the endorsement  of  all  potentially traumatic events, with the exception of the threats of violence indicator and the bullying indicator; however, the probability  of  endorsement  was  still  low  as  compared with that of the alternative classes. Therefore, Class 3  can  be  referred  to  as  the baseline  class. Class  2 (13.7%)  was  characterized  by  individuals  who  had the highest probability of endorsement of the threats  of  violence  indicator.  The  probabilities  of endorsement  of  the  physical  assault  and  bullying indicators  were  also  high  in  Class  2  relative  to  the alternative  potentially  traumatic  events;  however, they  were  lower  than  the  probabilities  of  the  endorsement  of  these  indicators  for  individuals  in Class 1, albeit only marginally. Class 2 will therefore be referred to as the physical assault, threats of violence, and bullying class .  Class 1 (5.0%) was the smallest of all three classes, and it was characterized by relatively  high  probabilities  of  the  endorsement  of  all  potentially  traumatic  events.  In  particular,  individuals in this class had high probabilities of endorsing the rape, sexual abuse, and bullying indicators as compared with alternative negative life events or trauma. Notably, the individuals in this class had the highest probabilities of endorsement for all potentially traumatic events, except threats of violence. Therefore, Class 1 will be referred to as the multiple, wideranging, potentially traumatic events class. The latent class profile plot is presented in Figure 1.

## Logistic regressions

Logistic  regression  was  conducted  with  the  use  of the covariates of gender, post-traumatic stress, somatization,  and  negative  affectivity  to  determine if  those  individuals  of  male  gender  (males  =  1; females = 0), those who met the diagnostic criteria for post-traumatic stress disorder (yes = 1; no = 0), and those  who  had  high  scores  on  somatization  and negative affectivity (yes = 1; no = 0) had a relative higher risk of being members of Classes 1 (multiple, wide-ranging, potentially traumatic events class) and 2 (physical assault, threats of violence, and bullying class)  as  compared  with  Class  3  (baseline  class). There was no significant association found between gender  and  membership  in  Class  1  as  compared with membership in Class 3. However, membership in Class 2 as compared with Class 3 was significantly  predicted  by  gender  in  that  males  had  a  nearly CI, 1.17 to 4.50) or Class 2 (OR, 2.45; CI, 1.73 to 3.47)  as  compared  with  Class  3.  High  scores  on somatization and negative affectivity both provided significant  associations  with  Classes  1  and  2  as compared  with  Class  3.  Individuals  who  met  the criteria  for  somatization  had  a  three-fold  risk  of being in Class 1 (OR, 2.76; CI, 1.36 to 5.59) and a Probability of Endorsement

0.95

0.9

0.85

0.8

0.75

0.7-

0.65

Physical Assault- more  than  two-fold  risk  of  being  in  Class  2  (OR, 2.45;  CI,  1.60  to  3.74)  as  compared  with  Class  3. Finally, individuals who met the criteria for negative affectivity had a more than five-fold risk of being in Profile  plot  of  three  traumatic events and negative  life events classes. Class 1, Multiple,  wide-ranging,  negative life events class; Class 2, Physical  assault,  threats  of violence, and bullying class; Class 3, Normative/baseline class

FIGURE 1

<!-- image -->

TABLE 3. Characteristics of the three classes of Faroese adolescents (n = 687)

|                                                                            | Class 3: Normative/ baseline class   | Class 2: Physical assault, threats of violence, and bullying class   | Class 1: Multiple, wide- ranging, negative life events class   |
|----------------------------------------------------------------------------|--------------------------------------|----------------------------------------------------------------------|----------------------------------------------------------------|
| Percentage of population                                                   | 81.3%                                | 13.7%                                                                | 5.0%                                                           |
| Percentage of males*                                                       | 46.4%                                | 56.6%                                                                | 47.1%                                                          |
| Mean score for negative affectivity (standard deviation)                   | 21.2 (7.7)                           | 26.9 (7.8)                                                           | 28.8 (8.4)                                                     |
| Mean score somatization (standard deviation)                               | 16.5 (5.8)                           | 20.9 (6.4)                                                           | 22.3 (6.6)                                                     |
| Mean score on Harvard Trauma Questionnaire- Part IV (standard devia- tion) | 57.9 (19.3)                          | 74.9 (25.4)                                                          | 82.9 (25.3)                                                    |
| Subjects with post- traumatic stress disorder                              | 16.5%                                | 37.7%                                                                | 44.1%                                                          |
| Depressed subjects                                                         | 7.3%                                 | 26.0%                                                                | 38.2%                                                          |
| Subjects with high somatization scores                                     | 9.0%                                 | 28.6%                                                                | 35.3%                                                          |

## Discussion

Three classes of adolescents were identified on the basis of their exposure  to  potentially traumatic events  and  negative  life  events.  The  baseline  class

(81.3%) had a low probability of endorsement of all potentially traumatic events and negative life events, except  threats  of  violence  and  bullying.  Class  2 (13.7%)  consisted  of  adolescents  with  the  highest probability  of  the  endorsement  of  threats  of  violence, physical assault, and bullying. Finally, Class 1 (5.0%) consisted of adolescents who were characterized by a relatively high risk of exposure to all potentially  traumatic  events  and  negative  life  events, except threats of violence.

In comparison, a study based on a national probability sample of 4023 adolescents between the ages of 12 and 17 years identified six classes on the basis of  trauma  profile  (41).  Ford  and  colleagues  identified four poly-victimized classes, in which 4% of the adolescents belonged to the sexual abuse and assault poly-victimized class; this can be compared with the 5% of such individuals found in the present study. Another  4%  of  the  adolescents  in  the  study  belonged  to  the  physical  abuse  and  assault  polyvictimization  class  (41).  In  the  present  study,  adolescents with the highest probability of having been exposed to physical abuse also had been exposed to sexual abuse, whereas those with the highest probability of the endorsement of physical assault (13.7%) had the highest probability of exposure to threats of violence and exposure to bullying.

·. - · C-. - Class 3,81.3% (Normative / Baselne class)

Class 1 (OR, 5.18; CI, 2.38 to 11.28) and an almost three-fold  risk  of  being  in  Class  2  (OR,  2.80;  CI, 1.79 to 4.37) as compared with Class 3.

Another study, which was based on 4053 children between the ages of 2 and  17 years, demonstrated that  79% of the poly-victimized children had been exposed to some kind of maltreatment as compared with 18% among the other victimized children (42).

Various secondary symptoms are often seen among individuals with PTSD, and sometimes these secondary  symptoms  are  the  most  tormenting  for the person who is experiencing them (43). The most prevalent  secondary  symptoms  that  have  been  reported include depression, anxiety, impulsive behavior,  and  somatization  (44).  In  a  study  of  2030  respondents between the ages of 2 and 17 years, the poly-victimized  individuals  were  mainly  males,  and poly-victimization was the highest predictor of anxiety,  depression,  and  anger  symptoms,  even  when sexual  abuse  was  taken  into  account  (45).  These findings have been replicated in another study made by the same researcher group in another sample of 2-  to  17-year-old  subjects  (42).  Alternatively,  a  descriptive  Australian  study  of  117  children  between the ages of 3 and 6 years old who were in foster care and 60 children matched for age and socioeconomic status  with  the  use  of  analysis  of  variance  demonstrated that the children in foster care could be divided  into  four  different  maltreatment  subgroups. Of these children, 11 (10%) had been exposed to all four  forms  of  maltreatment:  sexual  abuse,  physical abuse, emotional maltreatment, and  neglect; 19 (6%) had been exposed to physical  abuse,  neglect, and  emotional  maltreatment;  13  (12%)  had  been exposed  to  sexual  abuse,  emotional  maltreatment, and  neglect;  and  68  (61%)  had  been  exposed  to supervisory neglect and emotional maltreatment. All of these groups had significantly more posttraumatic stress symptoms when compared with the control group. When comparing the four maltreatment  groups,  the  sexual  abuse  groups  had  high scores for posttraumatic stress, whereas the physical abuse group had high scores for dissociation (46).

As expected, we found that adolescents exposed to trauma (i.e., those in Classes 1 and 2) had more symptoms  of  post-traumatic  stress,  negative  affectivity,  and  somatization as compared with the adolescents  in  Class  3.  This  is  also  in  line  with  other studies  of  children  and  adolescents,  which  have shown that exposure to trauma has a serious impact on  psychological  health  (47)  and  that  exposure  to multiple  traumas  increases  psychological  distress and post-traumatic stress (12). Ford and colleagues also  found  that  high  exposure  was  associated  with high reports of trauma symptoms; those researchers found  the  poly-victimized  adolescents  to  be  more likely to have PTSD, major depressive disorder, and substance abuse disorder (41).

Nylund and colleagues (39) found that victimized students felt less secure at school. As in the present study, the researchers also found that the group of nonvictimized students was the largest group.

There  was  no  significant  association  found  between gender and Class 1 as compared with Class 3. This is contrary to what we expected, because Class 1  is  characterized  by  sexual  trauma  (i.e.,  rape  and sexual abuse). Other studies have found the prevalence of sexual trauma to be higher among females. For  instance,  Karsberg,  Lasgaard,  and  Elklit  (48) found  the  prevalence  of  sexual  abuse  to  be  4.4% among Greenlandic  male  adolescents  as  compared with  10%  among  female  Greenlandic  adolescents. Briggs and colleagues (5) also found a higher prevalence  of  sexual  maltreatment  among  American  female  children  and  adolescents  as  compared  with American male children and adolescents.

In  line  with  the  literature  that  demonstrates  a greater  prevalence  of  physical  abuse  among  males (12,49), we found that membership in Class 2 (physical assault, threats of violence, and bullying class) as compared with Class 3 (the baseline class) was significantly  predicted  by  gender  in  that  males  were almost three times as likely to belong to Class 2 as compared with Class 3 (OR, 2.4; CI, 1.81 to 3.42). In their comprehensive study of 11,104 children and adolescents in a national clinic-referred sample, Briggs and colleagues (5) did not find any significant difference  in  exposure  to  violent  trauma  among females  as  compared  with  males.  In  line  with  the present  study,  adolescents  who  belonged  to  the poly-victimized  classes  (including  those  involving sexual abuse) were more likely to be females (41). In the present study, however, adolescents in the polyvictimized  classes  defined,  as  including  threats  of violence,  physical  assault,  and  bullying  were  more likely  to  be  males. This is contrary to the study by Ford  and  colleagues  but  in  line  with  other  studies that  found  physical  assault  to  be  more  prevalent among males (49).

The current findings emphasize the importance of researchers and clinicians making more careful and broad  assessments  of  trauma  exposure  in  children and adolescents. All professionals in the fields that concern children and adolescents need to be aware of  the  very  likely  associations  between  adverse  life events  and  trauma:  the  Faroese  adolescents  who were exposed to bullying had also been exposed to physical  assault,  and  the  Faroese  adolescents  who were  exposed  to  physical  abuse  had  also  been exposed to sexual abuse.

## Conclusion

Adolescents  are,  by  definition,  experiencing  a  developmental  period  during  which  they  seek  autonomy  and  independence.  This  fact  may  reinforce their  resistance  to  seek  help  when  problems  arise.

Dyregrov and Dyregrov (50) found that adolescents find  it  difficult  to  seek  health  care;  these  subjects also  reported that, if  they  do  seek  help,  they  often feel  overlooked.  Therefore,  more  effort  must  be made to identify those who are at risk and to offer them  necessary  treatment.  LCA  is  a  relatively  new but important tool in epidemiologic research involving trauma exposure. Because LCAs are exploratory and empirically driven, they provide latent variables that best describe the population being studied. The present study can be said to offer a concise picture of how Faroese adolescents are exposed to trauma and what consequences that exposure has on their psychological well-being. Therefore, the results obtained  here  may  be  valuable  for  the  national planning of preventive and interventional strategies, and they may contribute to an empirically founded economic prioritization. When the aim is to provide appropriate  help  and  interventions  to  adolescents, these results demonstrate the importance of choosing trauma-informed  strategies in various disciplines, such as pediatrics, child and  adolescent psychiatry, social work, and school psychology.

## References

1. Kessler RC, Sonnega A, Bromet E, Hughes M, Nelsen A. Posttraumatic stress disorder in the national comorbidity survey. Arch Gen Psychiatry 1995;52:1048-60.
2. Elklit A. Victimization and PTSD in a Danish national youth probability sample. J Am Acad Child Adolesc Psychiatry 2002;41:174-181.
3. Elklit A, Petersen T. Exposure to traumatic events among adolescents in four nations. Torture, 2008;18(1):2-11.
4. Petersen T, Elklit A, Olesen JG. Victimization among Faroese Adolescents. Scand J Psychology 2010;51:56-62.
5. Briggs EC, Fairbank JA, Greeson JKP, Amaya-Jackson LM, Gerrity ET, Belcher HME et al. Links between child and adolescent trauma exposure and service use histories in a national clinicreferred sample. Psychological Trauma: Theory, Research, Practice, and Policy 2012;4:1-9.
6. Broberg AO, Dyregrov A, Lilled L. The Göteborg discotheque fire - posttraumatic stress, and school adjustment as reported by the primary victims 18 months later. J Child Psychology and Psychiatry 2005;46:1279-86.
7. Reed PL, Anthony JC, Breslau N. Incidence of drug problems in young adults exposed to trauma and posttraumatic stress disorder. Arch Gen Psychiatry 2007;64:1435-42.
8. Nanni V, Uher R, Danese A. Childhood maltreatment predicts unfavorable course of illness and treatment outcome in depression: A meta-analysis. Am J Psychology 2012;169:141-51.
9. Onyut LP, Neuner F, Schauer E, Ertl V, Odenwald M, Schauer M et al. The Nakivale camp mental health project: Building local competency for psychological assistance to traumatized refugees. Intervention 2004;2(2):90-107.
10. Perkonigg A, Pfister H, Stein MB, Hofler M, Lieb R, Maercker A, Wittchen H-U. Longitudinal course of posttraumatic stress disorder and posttraumatic stress disorder symptoms in a community
11. sample of adolescents and young adults. Am J Psychiatry 2005;162:1320-27.
11. Ditlevsen DN, Elklit A. The combined effect of gender and age on posttraumatic stress disorder: Do men and women show differences in the lifespan distribution of PTSD? Ann Gen Psychiatry 2010;9:32.
12. Tolin DF, Foa EB. Sex differences in trauma and posttraumatic stress disorder: a quantitative review of 25 years of research. Psychol Bulletin 2006;132:959-92.
13. Stein MB, Hofler M, Perkonigg A, Lieb R, Pfister H, Maercker A et al. Patterns of incidence and psychiatric risk factors for traumatic events. Int J Methods Psychiatr Res 2002;11(4):143-53.
14. Davidson JRT, Hughes D, Blazer DG, George LK. Post-traumatic stress disorder in the community: an epidemiological study. Psychol Medicine1991;21:713-21.
15. Moeller TP, Bachmann GA, Moeller JR. The combined effects of physical, sexual, and emotional abuse during childhood: Long-term health consequences for women. Child Abuse & Neglect 1993: 7: 623-40.
16. Pears KC, Kim HK, Fisher PA. Psychosocial and cognitive functioning of children with specific profiles of maltreatment. Child Abuse & Neglect 2008;32:958-71.
17. Nooner KB, Litrownik AJ, Thompson R, Margolis B, English DJ, Knight ED et al. Youth self-report of physical and sexual abuse: A latent class analysis. Child Abuse & Neglect 2010;34:146-54.
18. Joubert D, Webster L, Hackett RK. Unresolved attachment status and trauma-related symptomatology in maltreated adolescents: An examination of cognitive mediators. Child Psychiatry Hum Dev 2012;43(3):471-83.
19. Walsh K, Danielson CK, McCauley J, Hanson RF, Smith DW, Resnick HS et al. Longitudinal trajectories of posttraumatic stress disorder symptoms and binge drinking among adolescent girls: The role of sexual victimization. J Adolesc Health 2012;50:54-59.
20. Dimitry L. A systematic review on the mental health of children and adolescents in areas of armed conflict in the Middle East. Child: care, health, and development 2011;38:153-61.
21. Penning SL, Bhagwanjee A, Govender K. Bullying boys: The traumatic effects of bullying in male adolescent learners. J Child Adolesc Ment Health 2010;22:131-43.
22. Ganz D, Sher L. Adolescent suicide in New York City: plenty of room for new research. Int J Adolesc Med Health 2011;24(2):99104.
23. Benjet C, Borges G, Medina-Mora ME, Zambrano J, Cruz C, Méndez E. Descriptive epidemiology of chronic childhood adversity in Mexican adolescents. J Adolesc Health 2009;45:483-89.
24. Graham-Bermann SA, Castor LE, Miller LE, Howell KH. The impact of intimate partner violence and additional traumatic events on trauma symptoms and PTSD in preschool-aged children. J Traumatic Stress 2012;25:393-400.
25. Mollica RF, Caspi-Yavin Y, Bollini P, Truong T, Tor S, Lavelle Jl. The Harvard Trauma Questionnaire: Validating a cross-cultural instrument for measuring torture, trauma, and posttraumatic stress disorder in Indochinese refugees. J Nerv Ment Dis 1992;180(2):111-16.
26. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders, 4 th  Ed. Washington DC: American Psychiatric Association; 1994.
27. Bach ME. En empirisk belysning og analyse af 'emotional numbing' som eventuel selvstændig factor i PTSD. Psykologisk Studieskriftserie 2003;6(1):1-132.

28. Briggs RS, Cheek JM. The role of factor analysis in the development and evaluation of personality scales. J Personality 1986;54:106-48.
29. Briere JN, Runtz MG. The Trauma Symptom Checklist (TSC-33): Early data on a new scale. J Interpersonal Violence 1989;4:151-63.
30. Krog T, Duel M. Trauma symptom checklist (TSC). Psykologisk Studieskriftserie 2003;6(4):1-144.
31. Muthén LK, Muthén BO. Mplus user's guide (6th ed.), 1998-2010. Los Angeles, California: Muthén & Muthén.
32. Haagenars JA, McCutcheon AL (Eds.). Applied Latent Class Analysis. Cambridge University Press, Cambridge; 2002.
33. Akaike H. Factor analysis and the AIC. Psychometrika 1987;52:317-32.
34. Schwartz G. Estimating the dimensions of a model. Ann Statistics 1978;6:461-64.
35. Sclove SL. Application of model-selection criteria to some problems in multivariate analysis. Psychometrika1987;52:333-34.
36. Ramaswamy V, Desarbo WS, Reibstein DJ, Robinson WT. An empirical pooling approach for estimating marketing mix elasticities with PIMS data. J Acad Marketing Science 1993;12:10324.
37. LoY, Mendell N, Rubin D. Testing the number of components in a normal mixture. Biometrika 2001;88:767-78.
38. DiStefano C, Kamphaus RW. Investigating subtypes of child development. A comparison of cluster analysis and latent class cluster analysis in typology creation. Educ Psychol Measurement 2006;66:778-94.
39. Nylund K, Bellmore A, Nishina A, Graham S. Subtypes, severity, and structural stability of peer victimization: What does latent class analysis say? Child Dev 2007;78:1706-22.
40. Yang C. Evaluating latent class analysis in qualitative phenotype identification. Computer & Statistical Data Analysis 2006;50:10901104.
41. Ford JD, Elhai JD, Connor DF, Frueh BC. Poly-victimization and risk of posttraumatic, depressive, and substance use disorders and involvement in delinquency in a national sample of adolescents. J Adolesc Health 2010;46: 545-52.
42. Turner HA, Finkelhor D, Ormrod R. Poly-victimization in a national sample of children and youth. Am J Preventive Medicine 2010;38:323-30.
43. Uddo M, Allain AN, Jr, Sutker PB. Assessment of posttraumatic stress disorder: A conceptual overview. In: Miller TW (Ed.) Theory and assessment of stressful life events. Madison, CT: International Universities Press; 1996:181-207.
44. Peterson CK, Prout FM, Schwartz AR. Post-traumatic stress disorder. A clinician's guide. New York: Plenum Press; 1991.
45. Finkelhor D, Ormrod RK, Turner HA. Poly-victimization: A neglected component in child victimization. Child Abuse & Neglect 2007;31:7-26.
46. Hulette A, Freyd JJ, Pears KC, Kim HK, Fisher PA, Becker-Blease KA. Trauma symptoms in children. Dissociation and posttraumatic symptoms in maltreated preschool children. J Child & Adolesc Trauma 2008;1:93-108.
47. Garnefski N, Diekstra R. Child sexual abuse and emotional and behavioral problems in adolescence: gender differences. J Am Acad Child Adolesc Psychiatry 1996;36:323-29.
48. Karsberg SH, Lasgaard M, Elklit A. Victimization and PTSD in a Greenlandic youth sample. Int J Circumpolar Health 2012;71:1-11.
49. Tolin DF, Breslau N. Sex differences in risks of PTSD. PTSD Research Quarterly 2007;18:1-7.
50. Dyregrov K, Dyregrov A. Helping the family following suicide. In: Monroe B, Kraus F (Eds.) Brief interventions with bereaved children. 2 nd  ed. Oxford: Oxford University Press; 2009:213-28.