Family members’ experiences of courtesy stigma associated with mental illness
Bibliographic record
Abstract
Background: The stigma of mental illness has been in existence from medieval times to date and it is extended to families of people diagnosed with mental illness. Families with a member diagnosed with a mental illness experience courtesy stigma of mental illness and it affects the quality of their lives. Aim: This study aimed to explore and describe the experiences of courtesy stigma of families with a member diagnosed with a mental illness in Lobatse, Botswana. Setting: The study was conducted at a psychiatric hospital in Lobatse, Botswana. Methods: A qualitative contextual phenomenological design was used for this study. The population comprised of members from families with a person diagnosed with a mental illness and the sample size was 15 participants. Semi-structured in-depth individual interviews were conducted telephonically. Results: The study yielded three main themes and related subthemes. The themes were: families' experiences of received stigma, families' experiences of stigma by association, and families' experiences of internal stigma. Conclusion: Families with a member diagnosed with mental illness experience received stigma, associated stigma and internal stigma. The families experienced that they received dehumanising labels from the public because of their association with their mentally ill family members. Contribution: With the insights gained from the findings of this study, programmes can be developed that raise awareness on stigma of mental illness and to promote support of families of people diagnosed with a mental illness.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".