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Record W4319439880 · doi:10.3389/fpsyt.2023.1086468

Mechanisms of action and processes of yoga-based group intervention for inpatients with schizophrenia spectrum disorders–A longitudinal qualitative study

2023· article· en· W4319439880 on OpenAlexaboutno aff
Laura Töbelmann, Inge Hahne, Theresa Schulze, Niklas Bergmann, Lukas M. Fuchs, Marco Zierhut, Eric Hahn, Kerem Böge

Bibliographic record

VenueFrontiers in Psychiatry · 2023
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialPositive and Negative Syndrome ScaleThematic analysisSchizophrenia (object-oriented programming)Intervention (counseling)PsychologyClinical psychologyLongitudinal studyMedicineQualitative researchPsychiatryPsychosis

Abstract

fetched live from OpenAlex

Background Research exploring the effects of yoga therapy (YT) on individuals with schizophrenia spectrum disorders (SSD) is scarce. Therefore, the current study aimed to explore possible mechanisms of actions and processes, as well as adverse effects of a novel yoga-based group intervention (YoGI) for in-patients with SSD in a German university hospital setting. Material and methods A longitudinal qualitative study was integrated into a rater-blinded randomized controlled trial, exploring the impact of a 4-week YoGI as add-on treatment. In-depth interviews were conducted with participants receiving YoGI (n = 19) in addition to treatment as usual (TAU) and a control group (n = 14) which only received TAU. Interviews were conducted at baseline (n = 33) and 4 weeks post-intervention (N = 28) to assess the participant’s experiences and how they changed over time. The interviews (N = 61) were audio-taped, translated, coded, and analyzed by means of inductive thematic analysis. Separate case summaries were prepared for each participant to analyze longitudinal changes within subjects. The research team members collaboratively discussed the final list of themes and subcodes. Rater-based questionnaires, such as the Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale for Schizophrenia (CDSS), and Personal and Social Performance Scale (PSP) were administered at baseline to assess clinical outcomes. Results At baseline, participants reported a desire to improve their stress- and symptom management. A minority of participants expressed reservations toward yoga, and several psychosocial barriers were named, including worries about symptom exacerbation. At post-intervention, four mechanisms of change became evident from the interviews: (1) acquiring competence in relaxation, (2) increased interoceptive awareness, (3) feeling connected, and (4) a sense of spiritual wellbeing. A small number of participants reported difficulties with YoGI. Conclusion Generally, YoGI positively influenced participants’ experiences of their inpatient stay, regarding distress, self- and body awareness, social connectedness, and spiritual wellbeing. However, participants also illuminated necessary adjustments to improve the intervention. YoGI will therefore be adapted and further developed in an iterative process based on a participant involvement approach. The efficacy regarding outcomes and processes needs to be investigated in a future larger-scaled randomized controlled trial.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.027
GPT teacher head0.354
Teacher spread0.327 · 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 designQualitative
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

Citations12
Published2023
Admission routes1
Has abstractyes

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