Batch growth and β‐carotene production of Dunaliella salina CCAP19/18 was investigated in flat‐plate gas‐lift photobioreactors with a light path of 2 cm, operated in physically simulated outdoor conditions. Dunaliella salina CCAP19/18 showed robust growth with respect to pH 8.0‐9.0 and 15–35°C at increasing salinity, simulating the evaporation of open photobioreactors. The highest β‐carotene concentration of 25 mg L‐1 (3 mg gCDW−1) was observed in batch processes at pH 8.5, 15–30°C and increasing salinity up to 110 g L‐1, simulating a typical Mediterranean summer climate. Intracellular β‐carotene accumulation of D. salina CCAP19/18 was shown to be independent of light availability, although nutrient limitation (K2HPO4, MgSO4, and/or ammonium ferric citrate) seems to enable stable β‐carotene content in the algal cells despite increasing cell densities in the photobioreactor. Fully controlled, lab‐scale photobioreactors simulating typical climate conditions of any region of interest are valuable tools for enabling a realistic characterization of microalgae on a laboratory scale, for production processes projected in open photobioreactor systems (e.g. thin‐layer cascade photobioreactors).
Background Choosing an antipsychotic medication is an important medical decision in the treatment of schizophrenia. This decision requires risk-benefit assessments of antipsychotics, and thus, shared-decision making between physician and patients is strongly encouraged. Although the efficacy and side-effect profiles of antipsychotics are well-established, there is no clear framework for the communication of the evidence between physicians and patients. For this reason, we developed an evidence-based shared-decision making assistant (SDM-assistant) that presents high-quality evidence from network meta-analysis on the efficacy and side-effect profile of antipsychotics and can be used as a basis for shared-decision making between physicians and patients when selecting antipsychotic medications. Methods The planned matched-pair cluster-randomised trial will be conducted in acute psychiatric wards (n = 14 wards planned) and will include adult inpatients with schizophrenia or schizophrenia-like disorders (N = 252 participants planned). On the intervention wards, patients and their treating physicians will use the SDM-assistant, whenever a decision on choosing an antipsychotic is warranted. On the control wards, antipsychotics will be chosen according to treatment-as-usual. The primary outcome will be patients’ perceived involvement in the decision-making during the inpatient stay as measured with the SDM-Q-9. We will also assess therapeutic alliance, symptom severity, side-effects, treatment satisfaction, adherence, quality of life, functioning and rehospitalizations as secondary outcomes. Outcomes could be analysed at discharge and at follow-up after three months from discharge. The analysis will be conducted per-protocol using mixed-effects linear regression models for continuous outcomes and logistic regression models using generalised estimating equations for dichotomous outcomes. Barriers and facilitators in the implementation of the intervention will also be examined using a qualitative content analysis. Discussion This is the first trial to examine a decision assistant specifically designed to facilitate shared-decision making for choosing antipsychotic medications, i.e., SDM-assistant, in acutely ill inpatients with schizophrenia. If the intervention can be successfully implemented, SDM-assistant could advance evidence-based medicine in schizophrenia by putting medical evidence on antipsychotics into the context of patient preferences and values. This could subsequently lead to a higher involvement of the patients in decision-making and better therapy decisions. Trial registration German Clinical Trials Register (ID: DRKS00027316, registration date 26.01.2022).
Objectives Decision aids (DAs) are promising tools to foster evidence‐based shared decision‐making between practitioners and service users. Nevertheless, it is still obscure how an evidence‐based DA for people with severe mental illness, especially psychosis, should look in an inpatient treatment setting to be useful and feasible. Therefore, we conducted focus groups with psychiatrists and service users to collect and assess their expectations and wishes regarding an evidence‐based DA. From these findings, we derived immediate recommendations for the future development of DAs. Methods We held two group interviews with service users ( n = 8) and three group interviews with psychiatrists ( n = 10). We used an open, large‐scale topic guide. First, we presented data from a current meta‐analysis on antipsychotics to the interviewees and, in a second step, asked for their expectations and wishes towards a DA that integrates these data. Results Our thematic analysis revealed six key themes addressed by the respondents: (1) general considerations on the importance and usefulness of such a DA, (2) critical comments on psychiatry and psychopharmacotherapy, (3) communicative prerequisites for the use of a DA, (4) form and content of the DA, (5) data input, data processing and output as well as (6) application of the DA and possible obstacles. Conclusions Participants identified several important features for the development of DAs for selecting antipsychotics in inpatient psychiatric treatment. The digital format was met with the greatest approval. Especially the adaptability to different needs, users and psychopathologies and the possibility to outsource information dissemination via app seemed to be a decisive convincing argument. Further research is required to test specific features of DAs to be developed in clinical settings.
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