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Record W4306989162 · doi:10.1186/s12888-022-04313-3

Thematic analysis of the raters’ experiences administering scales to assess depression and suicide in Arab schizophrenia patients

2022· article· en· W4306989162 on OpenAlexaboutno aff
Iman Amro, Suhaila Ghuloum, Samer Hammoudeh, Yahya Hani, Arij Yehya, Hassen Al‐Amin

Bibliographic record

VenueBMC Psychiatry · 2022
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
FundersQatar National Research Fund
KeywordsThematic analysisPsychologyClinical psychologyFocus groupPsychiatrySuicide preventionQualitative researchSchizophrenia (object-oriented programming)Sociocultural evolutionPoison controlMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: This study aimed to enhance the cultural adaptation and training on administering the Arabic versions of the Calgary Depression Scale in Schizophrenia (CDSS) and The International Scale for Suicidal Thinking (ISST) to Arab schizophrenia patients in Doha, Qatar. METHODS: We applied the qualitative thematic analysis of the focus group discussions with clinical research coordinators (CRCs). Five CRCs met with the principal investigator for two sessions; we transcribed the conversations and analyzed the content. RESULTS: This study revealed one set of themes related to the scales themselves, like the role of the clinician-patient relationship during administration, the semantic variations in Arabic dialects, and the design of scales to assess suicide and differentiate between negative symptoms and depression. The other set of themes is relevant to the sociocultural domains of Muslim Arabs, covering religion, families' roles, and stigma. It also covered the approaches to culturally sensitive issues like suicide, taboos in Islam, and the gender roles in Arab countries and their impact on the patients' reports of their symptoms. CONCLUSIONS: Our results highlight several cultural and religious aspects to tackle when approaching schizophrenia patients through in-depth discussions and training to improve the validity of the assessment tools and treatment services.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.051
GPT teacher head0.367
Teacher spread0.317 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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