A systematic review on mental health literacy among working women in Malaysia
Bibliographic record
Abstract
Mental health literacy (MHL) is defined as knowledge and beliefs about mental disorders which influence individual’s recognition, management, and prevention. Over the years, numerous MHL studies in the western countries such as Australia and Canada have been well-documented. However, research on MHL from the Eastern countries mainly Malaysia is still embryonic despite the rising numbers of people affected mainly among women population. In fact, mental health has been an issue of great concern specifically among working women as it poses adverse psychological effects which deteriorates their social life and overall wellbeing. Therefore the aims of this review are twofold; 1) to review existing evidence on the knowledge and attitudes of working women in Malaysia towards mental health and/or mental disorders; 2) to discuss MHL findings in Asia countries and specifically Malaysia. Methods: Three databases including PubMed, PsycInfo and the Cochrane will be searched against a comprehensive list of related search terms (E.g. mental health, mental health literacy, helpseeking, working women etc.). Searches will be run individually in each database to reflect each unique set of relevant subject heading. Inclusion and exclusion criteria were developed and refined by the research team. Two reviewers will participate in each search stage including abstract/title and full text screening, data extraction and appraisal, to ensure reliability. This systematic review will potentially contribute significantly to the area of MHL in Malaysia and within the Asia region at large. It will also serve as a guidepost for future research mainly in developing interventions that may help to improve Malaysians’ MHL.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".