HELP-SEEKING AND AUTONOMY FOR TREATMENT AMONG PATIENTS WITH MOOD DISORDERS AND SCHIZOPHRENIA: A SCOPING REVIEW
Bibliographic record
Abstract
Abstract Background Help-seeking represents an adaptive coping mechanism to address mental health issues by seeking external assistance. There is a known gap between the prevalence of help-seeking and mental illnesses, with younger individuals often reluctant to seek help. Additionally, autonomy refers to the right of capacitous adults to make decisions regarding their treatment, allowing them to manage their illnesses independently without undue influence. In psychiatric care, shared decision-making is designed to support patients’ autonomy. Both help-seeking and autonomy are critical factors in psychiatric treatment delay. Although help-seeking and autonomy are considered influenced by treatment preferences and differences in social and cultural backgrounds, a comprehensive systematic review of help-seeking and autonomy has not been yet explored in mood disorders and schizophrenia. Aims & Objectives This scoping review aimed to assess the methodologies and assessments employed in research on help-seeking and autonomy concerning the treatment of mood disorders and schizophrenia. Method We searched electronic bibliographic databases such as MEDLINE and EMBASE using keywords related to “help-seeking,” “autonomy,” “mood disorders,” and “schizophrenia”. We included studies conducting evaluations related to help-seeking and autonomy for treatments in patients with mood disorders and schizophrenia. We extracted the following information: author, year of publication, country, study design, participant characteristics, outcome measurements, and study results. Results Of the 12,665 records identified, 40 articles were included (113,899 participants, mean age; 21-52 years). Thirty-seven articles (92.5 %) were related to help-seeking, and three articles (7.5 %) concerned autonomy. Twenty-seven articles (67.5 %) were on mood disorders, 11 articles (27.5 %) were related to schizophrenia, and 2 articles (5.0 %) included mixed populations. Intervention studies of help- seeking were conducted in 25 articles (67.6 %) in mood disorders. Regarding the results of the qualitative studies (13 articles), stigma (4 articles, 30.8 %), and the degree of symptoms (3 articles, 23.1 %) were related to help-seeking. Along with the assessment of autonomy in mood disorders, only one article results showed an association with depressive symptoms. In schizophrenia, help-seeking was reported in 12 articles (32.4 %). The knowledge/education-related (4 articles, 33.3 %) and symptoms (3 articles, 25.0 %) were associated with help-seeking in patients with schizophrenia. For autonomy, only qualitative study was included, which used bio-empirical assessments. The direct association between help-seeking and autonomy was not examined in both articles on mood disorders and schizophrenia. Discussion & Conclusion This scoping review highlighted a notable gap in the existing evidence, indicating a lack of data on autonomy in mood disorders and schizophrenia. A plausible connection exists between help-seeking and autonomy, particularly concerning symptoms in mood disorders and schizophrenia. Since few studies have compared cultural differences, international comparative studies are needed. This review has limitations, such as data on patients over 18 years old or under treatment. Therefore, future research should consider integrating these aspects into their evaluations.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".