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Record W2548123386 · doi:10.1176/appi.pn.2016.11a12

Clinicians Share Strategies For Treating Refugees

2016· article· en· W2548123386 on OpenAlexaboutno aff
Aaron Levin

Bibliographic record

VenuePsychiatric News · 2016
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeMental healthDepression (economics)Intervention (counseling)AnxietyImmigrationPsychologySession (web analytics)PsychiatrySociologyPolitical scienceMedicineBusinessLaw

Abstract

fetched live from OpenAlex

Back to table of contents Previous article Next article Clinical and Research NewsFull AccessClinicians Share Strategies For Treating RefugeesAaron LevinAaron LevinPublished Online:2 Nov 2016https://doi.org/10.1176/appi.pn.2016.11a12AbstractAgencies provide care for refugees of all backgrounds and from many countries to recover from multiple traumas.Refugees, no matter where they're from or how old they are or what drove them from their homes, have experienced stresses serious enough to threaten their mental well-being, said speakers at APA's fall meeting, IPS: The Mental Health Services Conference, held in Washington, D.C., in October.All face a higher risk of depression, anxiety, PTSD, and other reactions to their experiences, even once they have migrated to relative safety, noted session organizer Amy Gajaria, M.D., a PGY-4 at the University of Toronto.Children arriving across the Mexico-U.S. border often need some kind of mental health intervention, says Gaurav Mishra, M.D., M.B.B.S., of the Imperial County (Calif.) Behavioral Health Services.Aaron LevinChildren are an especially high-risk group, said Gaurav Mishra, M.D., M.B.B.S., a child psychiatrist with the Imperial County (Calif.) Behavioral Health Services, near the border with Mexico. He sees young people who come from Nicaragua, Honduras, and El Salvador, as well as surprising numbers from Haiti and Africa. Many faced violence back home, separation from their parents, and exploitation or abuse on the way to the United States, said Mishra. In addition, young children's reactions may be heightened by the fact that they have little say in the decision to emigrate.Imperial County provides age-graded services for children, adolescents, and young people up to age 25 who have behavioral problems or diagnosed mental illnesses. For instance, the Vista Sands Program addresses behavioral issues among 7- to 12-year-olds by giving them half a day in school and half a day of group work on social skills, anger management, and self-control. Funding comes from California's 1 percent tax on incomes over $1 million."I also see my role as an educator to others, particularly to the rest of the medical community in the area," said Mishra.Another subpopulation more vulnerable than most to the effects of forced migration is the elderly, said Peter Ureste, M.D., a geriatric psychiatry fellow at the University of California, San Francisco, and an APA Public Psychiatry Fellow."They may face malnutrition when food is rationed after a disaster," said Ureste, "and their physical limitations may hamper navigating makeshift shelters or reaching dropoff points for food and water. Plus, it's hard for those with chronic illnesses to stay on medications."Older people have longstanding attachments to their homelands and so may experience grief, depression, or anxiety when forced to leave, he said. However, older people can also serve as carriers of cultural traditions to shore up communities and, on a practical level, care for children and the sick while younger people work or rebuild."Refugees from Syria are all affected by loss of home, money, jobs, family, and friends," said Ashley Nemiro, Ph.D., the technical advisor for mental health for the International Rescue Committee (IRC), which helps refugees resettle in the United States. "They experience stress from the conflicts in their home country, from their displacement, and from daily life in the places where they have resettled. They face a unique set of psychosocial needs and have a high level of severe emotional disorders."Coming from a war zone, all have lost friends or family members and have relatives still back in Syria about whom they worry. They often don't know what to expect when they arrive in the United States and may even face hostility.Curiously, refugees from rural areas sometimes cope better than middle-class professionals, she said. The latter may have academic credentials that aren't valid in this country and have had steeper losses of identity, status, and income.IRC uses the Refugee Health Screen (RHS-15) to screen clients for anxiety, depression, and PTSD and then determine their placement and track their progress. Also, all female refugees are screened for domestic violence and sexual assault—with a 25 percent positive rate so far.The organization has developed a variety of support systems for refugees by creating partnerships and integrating services with existing community programs. In Baltimore, for instance, community health workers visit the refugees to connect them with community services; in Dallas they connect with clients through a local mosque; and in Phoenix, they use high school and adult group therapy. "It's difficult in practice," said Nemiro. "We need to let people tell us their stories and then help them to do the tasks of daily living themselves."It may be difficult for those who serve them as well, said Steven Moffic, M.D., the discussant at the session and a retired professor of psychiatry and behavioral medicine at the Medical College of Wisconsin."Working with these populations can be a route to burnout," said Moffic. "It's important how organizations deal with that possibility and provide support for their mental health professionals." ■For more about mental health care for refugees, see "Aid Agencies Find Different Ways to Help Staff Cope With Disaster Stress,", and "Child Refugees May Have Harrowing Journey North," ISSUES NewArchived

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.037
GPT teacher head0.383
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Published2016
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