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Record W7067471235

Medication-Free Treatment in Mental Health Care How Does It Differ from Traditional Treatment?

2024· article· en· W7067471235 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPsychosocialNorwegianMental health careHealth careUniversity hospital
DOInot available

Abstract

fetched live from OpenAlex

Kari Standal,1 Ole Andre Solbakken,2 Jorun Rugkåsa,3– 5 Margrethe Seeger Halvorsen,2 Allan Abbass,6 Christopher Wirsching,2 Ingrid Engeseth Brakstad,2 Kristin S Heiervang7,8 1District Psychiatric Center Nedre Romerike, Akershus University Hospital, Lørenskog, Norway; 2Department of Psychology, University of Oslo, Oslo, Norway; 3Health Services Research Unit, Akershus University Hospital, Lørenskog, Norway; 4Department of Mental Health, Oslo Metropolitan University Oslo, Norway; 5Centre for Care Research, University of Southeastern Norway, Porsgrunn, Norway; 6Faculty of Medicine, Dalhousie University, Nova Scotia, Canada; 7Research and Development Department, Division of Mental Health Services, Akershus University Hospital, Lørenskog, Norway; 8Centre of Medical Ethics, Faculty of Medicine, University of Oslo, Oslo, NorwayCorrespondence: Kari Standal, District Psychiatric Center Nedre Romerike, Akershus University Hospital, Akershus universitetssykehus HF, DPS Nedre Romerike, Postboks 1000, Lørenskog, 1478, Norway, Tel +47 679 60 155, Email kari.standal@ahus.noBackground: Norwegian authorities have implemented treatment units devoted to medication-free mental health treatment nationwide to improve people’s freedom of choice. This article examines how medication-free treatment differs from treatment as usual across central dimensions.Methods: The design was mixed methods including questionnaire data on patients from a medication-free unit and two comparison units (n 59 + 124), as well as interviews with patients (n 5) and staff (n 8) in the medication-free unit.Results: Medication-free treatment involved less reliance on medications and more extensive psychosocial treatment that involved a culture of openness, expression of feelings, and focus on individual responsibility and intensive work. The overall extent of patient influence for medication-free treatment compared with standard treatment was not substantially different to standard treatment but varied on different themes. Patients in medication-free treatment had greater freedom to reduce or not use medication. Medication-free treatment was experienced as more demanding. For patients, this could be connected to a stronger sense of purpose and was experienced as helpful but could also be experienced as a type of pressure and lack of understanding. Patients in medication-free treatment reported greater satisfaction with the treatment, which may be linked to a richer psychosocial treatment package that focuses on patient participation and freedom from pressure to use medication.Conclusion: The findings provide insights into how a medication-free treatment service might work and demonstrate its worth as a viable alternative for people who are not comfortable with the current medication focus of mental health care. Patients react differently to increased demands and clinicians should be reflexive of the dimensions of individualism–relationism in medication-free treatment services. This knowledge can be used to further develop and improve both medication-free treatment and standard treatment regarding shared decision-making.Trial Registration: This study was registered with ClinicalTrials.gov (Identifier NCT03499080) on 17 April 2018.Keywords: medication-free, mental health care, psychotropics, choice

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.060
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0140.001

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.

Opus teacher head0.325
GPT teacher head0.599
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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