Why Service Users Choose Medication-Free Psychiatric Treatment: A Mixed-Method Study of User Accounts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Medication has been a central part of treatment for severe mental disorders in Western medicine since the 1950s. In 2015, Norwegian Health Authorities decided that Norwegian health regions must have treatment units devoted to medication-free mental health treatment to enhance service users' freedom of choice. The need for these units has been controversial. The aim of this study was to examine why service users choose medication-free services. This article examines what purpose these units serve in terms of the users' reasons for choosing this service, what is important for them to receive during the treatment, and what factors lay behind their concerns in terms of medication-related views and experiences. METHODS: Questionnaires were answered by 46 participants and 5 participants were interviewed in a mixed-method design integrated with a concurrent triangulation strategy applying thematic analysis and descriptive statistics. RESULTS: Negative effects of medications and unavailable alternatives to medication in ordinary health care were important reasons for wanting medication-free treatment. Medication use may conflict with personal values, attitudes, and beliefs. CONCLUSION: This study broadens the understanding of why the demand for separate medication-free units has arisen. The findings may contribute to making medication-free treatment an option in mental health care in general. To this end, clinicians are advised to communicate all treatment alternatives to service users and to be mindful of the effect of power imbalances in their interactions with them.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it