Why Service Users Choose Medication-Free Psychiatric Treatment: A Mixed-Method Study of User Accounts
Bibliographic record
Abstract
Kari Standal,1 Ole Andre Solbakken,2 Jorun Rugkåsa,3,4 Astrid Ringen Martinsen,1,2 Margrethe Seeger Halvorsen,2 Allan Abbass,5 Kristin Sverdvik Heiervang6,7 1District Psychiatric Center Nedre Romerike, Division of Mental Health Services, Akershus University Hospital, Lørenskog, Norway; 2Department of Psychology, University of Oslo, Oslo, Norway; 3Health Services Research Unit, Akershus University Hospital, Lørenskog, Norway; 4Centre for Care Research, University of South-Eastern Norway, Porsgrunn, Norway; 5Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada; 6Department of Research and Development, Division of Mental Health Services, Akershus University Hospital, Lørenskog, Norway; 7Centre of Medical Ethics, Faculty of Medicine, University of Oslo, Oslo, NorwayCorrespondence: Kari StandalDistrict Psychiatric Center Nedre Romerike, Division of Mental Health Services, Akershus University Hospital, Postboks 1000, Lørenskog, 1478, NorwayTel +47 679 60 155Email kari.standal@ahus.noPurpose: 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.Keywords: mental health care, medication-free, choice, psychotropics
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 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 teacher head, 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".