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Record W6992100734

Kokoro no Kenko: Understanding Mental Health Beliefs from a Culturally Grounded Perspective Using a Mixed-Methods Approach in Japan and Canada

2023· dissertation· en· W6992100734 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicYouth Substance Use and School Attendance
Canadian institutionsnot available
FundersNihon University
KeywordsMental healthPerspective (graphical)Thematic analysisGeneralizability theoryCultural diversityQualitative researchMeaning (existential)Circumstantial evidence
DOInot available

Abstract

fetched live from OpenAlex

Culture plays a crucial role in shaping how people perceive, interpret, and navigate psychological suffering. This dissertation examines cultural variations in mental health beliefs within Japan and Canada, utilizing two mixed-methods research designs. The overarching objective is to engage in interdisciplinary and culturally grounded research practices, driven by the need to address the lack of diversity, inclusion, and global perspectives in psychological science, commonly referred to as the “WEIRD” problem. These research practices entail critically reflecting on the generalizability of Western biomedical models, conducting literature reviews in Japanese, and fostering collaborations with Japanese researchers.
\nManuscript 1 examines the differences in causal and help-seeking beliefs about mental illnesses between Japanese and Euro-Canadian students. In this study, content analysis revealed themes related to social-contextualization and unique cultural perspectives, such as filial piety and resting. Statistical analysis showed group differences in the endorsement of explanatory models across various conditions, including depression, autism spectrum disorder, schizophrenia, alcohol use disorder, and hikikomori. Overall, Japanese students tended to psychologize and recommend social support, whereas Euro-Canadian students tended to medicalize and recommend medication and self-care.
\nManuscripts 2 and 3 apply cultural consensus theory to explore shared beliefs about mental health, depression, and therapeutic alliance among Japanese clinical psychologists. Using a two-phase sequential mixed-methods design, cultural domain analysis identified salient terms reflecting mental health issues and changes in licensure within Japan’s socio-cultural and historical context. Cultural consensus analysis demonstrated shared models for most domains, with exceptions in for beliefs about an incompetent clinician, a difficult client, and external barriers.
\nThis dissertation makes a valuable contribution by exploring culturally distinctive mental health beliefs and advocating for the benefits of mixed-methods approaches. It addresses the limitations of the contemporary psychological literature, which predominantly relies on theories, sampling, and methods prevalent in Western (i.e., “WEIRD”) contexts. These studies are proposed as an initial stride towards developing culturally grounded models for clinical assessment and care, catering to the needs of people from non-Western cultural backgrounds. The findings carry important implications for mental health research, policy, community care, practice, and education, especially in multicultural contexts.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.068
GPT teacher head0.364
Teacher spread0.297 · 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 designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

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