Well-being after trauma: A review of posttraumatic growth among refugees.
Bibliographic record
Abstract
The United Nations Refugee Agency (UNHCR, 2015) has estimated that close to 60 million people have been impacted by war and armed conflicts worldwide. Those affected include refugees, refugee claimants/asylum seekers as well as internally displaced and stateless persons. With respect to refugees in particular, there are approximately 16 million refugees worldwide. This figure is of significant global concern given that the number of refugees continues to escalate. Most refugees originate from Middle Eastern countries, with Syrian refugees currently accounting for the largest proportion (4.2 million). Afghani refugees account for another 2.6 million. In addition, countries in the Horn of Africa and surrounding regions, such as Somalia, Ethiopia, and Sudan, continue to be a significant source of refugees.Although Canada has traditionally been viewed as a safe haven for refugees, only an average of 1% have been resettled yearly (UNHCR, 2015). Given the Syrian refugee crisis and recent changes in governmental policies, the acceptance rate for Syrian refugees has increased dramatically (Immigration, Refugees, & Citizenship Canada, 2016). Recent statistics indicate that over 28,000 Syrian refugees have resettled in Canada. Moreover, an additional 2,700 Syrians have been granted refugee status and are due to arrive imminently.In response to the Syrian refugee crisis, Canadian psychologists and other mental health professionals have become more active in refugee research, are expanding their clinical services, and are engaging in advocacy work (Canadian Psychological Association, 2016). As part of this special issue of Canadian Psychology, this review article will synthesize and discuss the literature on posttraumatic growth (PTG) among refugees. Refugees experience high levels of trauma and tend to have poorer adjustment and well-being outcomes (Kirmayer et al., 2011; Young & Chan, 2015). However, there is emerging research suggesting that some refugees experience positive well-being (Kroo & Nagy, 2011; Teodorescu et al., 2012). In the following sections, the mental health sequelae of refugee trauma will be reviewed. The literature on PTG will then be explored as well as factors that are related to PTG. A much more recent concept, vicarious PTG (vPTG) among mental health providers, will also be introduced. This review paper will conclude with new directions for PTG research with refugees in Canada and abroad.Refugee TraumaRefugees experience a host of stressful and traumatic events during the various stages of migration (Kirmayer et al., 2011; Teodorescu et al., 2012; Young & Chan, 2015). In their countries of origin, many refugees experience the following typical traumatic events: physical and sexual assaults, persecution, torture, witnessing the deaths of loved ones, friends, and neighbours, and having one's home ransacked and belongings destroyed (Kilic, Magruder, & Koryurek, 2016; Teodorescu et al., 2012). Often, basic needs, such as food, water, housing, and medical care, are either very limited or unavailable. Women living in armed conflict areas are disproportionately affected because of the prevalence of gender-based violence (Young & Chan, 2015). Intimate partner violence, rape, and ethnic cleansing often come to mind in the context of women and war. Within refugee families, family members may be separated in the chaos of flight and parents are sometimes faced with the difficult choice of parting from their children (i.e., smuggling their children out of the country) to ensure their survival (Young & Chan, 2014).During flight, refugees often encounter additional traumatic experiences, such as undertaking dangerous and arduous journeys and/or ending up in refugee camps (Ssenyonga, Owens, & Olema, 2013). Despite lay notions, refugee camps are often overcrowded with rationed food and little potable water. Women and children are often sexually violated (Young & Chan, 2015). …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".