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Record W2794837438 · doi:10.1080/15332985.2018.1448325

Graduate social work students’ perceptions and attitude toward mental illness: implications for practice in developing countries

2018· article· en· W2794837438 on OpenAlexaff
Cynthia Akorfa Sottie, Magnus Mfoafo-M’Carthy, Festus Moasun

Bibliographic record

VenueSocial Work in Mental Health · 2018
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsWilfrid Laurier UniversityBooth University College
Fundersnot available
KeywordsMental illnessMental healthStigma (botany)Middle Eastern Mental Health Issues & SyndromesPerceptionPsychologySocial stigmaSocial workMental health lawPsychological interventionCommunity integrationPsychiatrySocial psychologyMedicineFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Mental health stigma is an integral part of the problems faced by individuals diagnosed with mental illness in developing countries. Though Ghana enacted a new Mental Health Law (Act 846) in 2012 with emphasis on community-based care, concerns persist as social workers tend to distance themselves from the field. For CBC to succeed, social workers must opt for a career in the mental healthcare field. The question that arises is how willing social work students are to pursue a career in mental health. The paper explores the perceptions and attitudes of Graduate Social Work students towards mental illness and people living with mental illness. Socio-cultural and religious beliefs about mental illness continue to dominate perceptions about mental illness and fuel stigma. Many social work students are reluctant or unwilling to work with persons living with mental illness due to such beliefs and negative personal experiences. Opportunities to engage positively with persons living with mental illness, and inclusion of core courses in mental health in social work curricular could pave the way for minimising stigma and getting more professionals interested in a career in mental health.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
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 head0.106
GPT teacher head0.497
Teacher spread0.391 · 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 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

Citations8
Published2018
Admission routes1
Has abstractyes

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