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Record W2033795942 · doi:10.2190/2g8n-mnne-pggp-pjjq

Somatization in Primary Care: A Comparative Survey of Immigrants from Various Ethnic Groups in Rome, Italy

2005· article· en· W2033795942 on OpenAlexfundno aff
Massimiliano Aragona, Lorenzo Tarsitani, Francesco Colosimo, Barbara Martinelli, Hassan Raad, Salvatore Geraci

Bibliographic record

VenueThe International Journal of Psychiatry in Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
FundersHealth Canada
KeywordsSomatizationEthnic groupMedicineImmigrationDemographyConfoundingPrimary careGerontologyClinical psychologyAnxietyFamily medicinePsychiatryGeographyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Those responsible for interviewing immigrants in primary care settings often underestimate the importance of somatic symptoms arising from psychological distress. This study investigates the current prevalence of somatization in immigrants, and evaluates the comparative rates of somatic complaints in four ethnic groups (Caucasians, Asians, South/Center Americans, and Africans). METHODS: We studied the 301 consecutive outpatients (aged between 16 and 70 years) attending the "Caritas" primary care unit for immigrants in Rome (Italy) from January to December 2003, all of whom completed the 21-item version of the Bradford Somatic Inventory (BSI-21). Patients scoring 14 or more on the BSI-21 were considered at risk for somatization. RESULTS: The current prevalence of somatization was 35.2%; 62.3% of the somatizers were women. A multiple regression analysis adjusting for the possible confounding effects of sex, age, education, and months of stay in Italy showed that South/Central Americans had significantly higher somatization scores than the other three groups. CONCLUSIONS: These findings suggest a high probability of somatization syndromes in immigrant patients. South/Central Americans tend to somatize more than other ethnic groups. A psychosomatic approach may be useful for immigrants in primary care settings.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.333
Teacher spread0.303 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations48
Published2005
Admission routes1
Has abstractyes

Explore more

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