Measuring personal recovery in a low-intensity community mental healthcare setting:validation of the Dutch version of the individual recovery outcomes counter (I.ROC)

BackgroundMeasuring progress in treatment is essential for systematic evaluation by service users and their care providers. In low-intensity community mental healthcare, a questionnaire to measure progress in treatment should be aimed at personal recovery and should require little effort to complete.MethodsThe Individual Recovery Outcome Counter (I.ROC) was translated from English into Dutch, and psychometric evaluations were performed. Data were collected on personal recovery (Recovery Assessment Scale), quality of life (Manchester Short Assessment of Quality of Life), and symptoms of mental illness and social functioning (Outcome Questionnaire, OQ-45) for assessing the validity of the I.ROC. Test–retest reliability was evaluated by calculating the Intraclass Correlation Coefficient and internal consistency was evaluated by calculating Cronbach’s alpha. Exploratory factor analysis was performed to determine construct validity. To assess convergent validity, the I.ROC was compared to relevant questionnaires by calculating Pearson correlation coefficients. To evaluate discriminant validity, I.ROC scores of certain subgroups were compared using either a t-test or analysis of variance.ResultsThere were 764 participants in this study who mostly completed more than one I.ROC (total n = 2,863). The I.ROC aimed to measure the concept of personal recovery as a whole, which was confirmed by a factor analysis. The test–retest reliability was satisfactory (Intraclass Correlation Coefficient is 0.856), as were the internal consistency (Cronbachs Alpha is 0.921) and the convergent validity. Sensitivity to change was small, but comparable to that of the OQ-45.ConclusionsThe Dutch version of the I.ROC appears to have satisfactory psychometric properties to warrant its use in daily practice. Discriminant validity and sensitivity to change need further research

Performance of 16s rDNA Primer Pairs in the Study of Rhizosphere and Endosphere Bacterial Microbiomes in Metabarcoding Studies

Next-generation sequencing technologies have revolutionized the methods for studying microbial ecology by enabling high resolutioncommunity profiling. However, the use of these technologies in unraveling the plant microbiome remains challenging. Many bacterial 16S rDNA primer pairs also exhibit high affinity for non-target DNA such as plastid (mostly chloroplast) DNA and mitochondrial DNA. Therefore, we experimentally tested a series of commonly used primers for the analysis of plant associated bacterial communities using 454 pyrosequencing. We evaluated the performance of all selected primer pairs in the study of the bacterial microbiomes present in the rhizosphere soil, root, stem and leaf endosphere of field-grown poplar trees (Populus tremula x Populus alba) based on (a) co-amplification of non-target DNA, (b) low amplification efficiency for pure chloroplast DNA (real-time PCR), (c) high retrieval of bacterial 16S rDNA, (d) high operational taxonomic unit (OTU) richness and Inverse Simpson diversity and (e) taxonomic assignment of reads. Results indicate that experimental evaluation of primers provide valuable information that could contribute in the selection of suitable primer pairs for 16S rDNA metabarcoding studies in plant-microbiota research. Furthermore, we show that primer pair 799F-1391R outperforms all other primer pairs in our study in the elimination of non target DNA and retrieval of bacterial OTUs

Correction: Protocol of the Healthy Brain Study:An accessible resource for understanding the human brain and how it dynamically and individually operates in its bio-social context

[This corrects the article DOI: 10.1371/journal.pone.0260952.]

Concept mapping study: Potential predictive factors for successful referral from specialist mental-health services to less intensive treatment

Data from a concept mapping study in potential predictive factors for successful referral from specialist mental-health services to less intensive treatment. <div><br></div><div>The data has been generated and analysed with proprietary software (global max by concept systems), so it might not be easy to analyse without this software. </div

Measuring the intensity of mental healthcare: development of the Mental Healthcare Intensity Scale (MHIS)

Abstract Background There are considerable differences among mental healthcare services, and especially in developed countries there are a substantial number of different services available. The intensity of mental healthcare has been an important variable in research studies (e.g. cohort studies or randomized controlled trials), yet it is difficult to measure or quantify, in part due to the fact that the intensity of mental healthcare results from a combination of several factors of a mental health service. In this article we describe the development of an instrument to measure the intensity of mental healthcare that is easy and fast to use in repeated measurements. Methods The Mental Healthcare Intensity Scale was developed in four stages. First, categories of care were formulated by using focus group interviews. Second, the fit among the categories was improved, and the results were discussed with a sample of the focus group participants. Third, the categories of care were ranked using the Segmented String Relative Rankings algorithm. Finally, the Mental Healthcare Intensity Scale was validated as a coherent classification instrument. Results 15 categories of care were formulated and were ranked on each of 12 different intensities of care. The Mental Healthcare Intensity Scale is a versatile questionnaire that takes 2-to-3 min to complete and yields a single variable that can be used in statistical analysis. Conclusions The Mental Healthcare Intensity Scale is an instrument that can potentially be used in cohort studies and trials to measure the intensity of mental healthcare as a predictor of outcome. Further study into the psychometric characteristics of the Mental Healthcare Intensity Scale is needed

Heat treatment optimization via thermo-physical characterization of AlSi7Mg and AlSi10Mg manufactured by Laser Powder Bed Fusion (LPBF)

The current paper aims at unraveling the threefold interrelationship between process, microstructure and properties of two materials, AlSi7Mg and AlSi10Mg, processed by laser powder bed fusion (LPBF) on a 3D Systems ProX® DMP 320, and subsequently heat treated under different conditions in argon atmosphere. Three thermo-physical characterization techniques were employed to monitor microstructural and concomitant mechanical property changes during heat treatment of LPBF processed Al-Si-Mg based alloys. The evolution of dissolved Si in the FCC Al matrix was monitored by electrical resistivity (ER) measurements, precipitation reactions were monitored by combining differential scanning calorimetry (DSC) with elastic property and damping measurements using the impulse excitation technique (IET). The evolution of the microstructure upon heat treatment was linked to characteristic phenomena captured by each of the three thermo-physical characterization techniques. Finally, the evolution of internal and residual stresses of both processed alloys upon heat treatment was monitored via the cantilever method.status: publishe

Statements and corresponding ratings on expected predictive value.

<p>Statements and corresponding ratings on expected predictive value.</p

Map of the statements (in numbers) and their distances according to multi-dimensional scaling, visualized in the final clusters.

<p>Map of the statements (in numbers) and their distances according to multi-dimensional scaling, visualized in the final clusters.</p

Statements generated.

<p>Statements generated.</p