Abstract
In the health sector, the implementation of qualitative data research is very important to improve overall services. However, the use of these methods remains relatively unexplored when compared to quantitative analyses. This article describes the qualitative data analysis process that is based on the description, analysis and interpretation of data. It also describes a practical case study and the use of NVivo software to assist in the development of a theory-based qualitative analysis process. This article intends to be a step forward in the use of qualitatively based methodologies in future research in the health sector.

Abstract

Abstract
The main aim of this article is to investigate the effect of perceived greenwashing on consumers' purchasing behavior of eco-friendly products. Twelve research hypotheses were defined based on contributions from the literature. To test these hypotheses, a quantitative methodology was employed, collecting data through an online survey (N = 270) and using SmartPLS for analysis. The results confirm that perceived both perceived greenwashing and perceived risk have a negative influence on consumer attitudes. While their direct effects on purchase intention were found to be insignificant, both perceived greenwashing and perceived risk had a significant negative indirect effect on purchase intention through attitude. Additionally, it was confirmed that purchase behavior is positively affected by attitude and by willingness to pay more. These results contribute to addressing the limited knowledge regarding the impact of consumers' perceived greenwashing on their behavior, especially concerning different product types. Furthermore, they provide valuable insights for managers, highlighting the importance of mitigating greenwashing and risk perceptions associated with eco-friendly products due to their indirect negative impacts on purchase intention and behavior.

Abstract
Aims. We aim to investigate the origin of the HI Br gamma emission in young stars by using GRAVITY to image the innermost region of circumstellar disks, where important physical processes such as accretion and winds occur. With high spectral and angular resolution, we focus on studying the continuum and the HI Br gamma-emitting area of the Herbig star HD 58647. Methods. Using VLTI-GRAVITY, we conducted observations of HD 58647 with both high spectral and high angular resolution. Thanks to the extensive uv coverage, we were able to obtain detailed images of the circumstellar environment at a sub-au scale, specifically capturing the continuum and the Br gamma-emitting region. Through the analysis of velocity-dispersed images and photocentre shifts, we were able to investigate the kinematics of the HI Br gamma-emitting region. Results. The recovered continuum images show extended emission where the disk major axis is oriented along a position angle of 14 degrees. The size of the continuum emission at 5-sigma levels is similar to 1.5 times more extended than the sizes reported from geometrical fitting (3.69 mas +/- 0.02 mas). This result supports the existence of dust particles close to the stellar surface, screened from the stellar radiation by an optically thick gaseous disk. Moreover, for the first time with GRAVITY, the hot gas component of HD 58647 traced by the Br gamma has been imaged. This allowed us to constrain the size of the Br gamma-emitting region and study the kinematics of the hot gas; we find its velocity field to be roughly consistent with gas that obeys Keplerian motion. The velocity-dispersed images show that the size of the hot gas emission is from a more compact region than the continuum (2.3 mas +/- 0.2 mas). Finally, the line phases show that the emission is not entirely consistent with Keplerian rotation, hinting at a more complex structure in the hot gaseous disk.

Abstract
The need for software developers is growing in a world where software systems play multiple roles in our daily lives. Due to the mental nature of their work, we are driven to address their needs. The concept of developer experience (DX) was defined as an extension of user experience, focusing on the dual role developers have as users and creators. This paper proposes a pattern language that can assist developers in improving their developer experience. In addition, we present a selection of patterns that focus on the cognitive dimension of the mind: Infrastructure Alignment, Adeqate Skills, It Takes A Village, Learning From A Master, Written Knowledge, and Practice Makes Perfect.

Abstract

Background Subcutaneous (SAF) and visceral (VAF) abdominal fat have specific properties which the global body fat and total abdominal fat (TAF) size metrics do not capture. Beyond size, radiomics allows deep tissue phenotyping and may capture fat dysfunction. We aimed to characterize the computed tomography (CT) radiomics of SAF and VAF and assess their incremental value above fat size to detect coronary calcification. Methods SAF, VAF and TAF area, signal distribution and texture were extracted from non-contrast CT of 1001 subjects (57% male, 57?±?10 years) with no established cardiovascular disease who underwent CT for coronary calcium score (CCS) with additional abdominal slice (L4/5-S1). XGBoost machine learning models (ML) were used to identify the best features that discriminate SAF from VAF and to train/test ML to detect any coronary calcification (CCS?>?0). Results SAF and VAF appearance in non-contrast CT differs: SAF displays brighter and finer texture than VAF. Compared with CCS?=?0, SAF of CCS?>?0 has higher signal and homogeneous texture, while VAF of CCS?>?0 has lower signal and heterogeneous texture. SAF signal/texture improved SAF area performance to detect CCS?>?0. A ML including SAF and VAF area performed better than TAF area to discriminate CCS?>?0 from CCS?=?0, however, a combined ML of the best SAF and VAF features detected CCS?>?0 as the best TAF features. Conclusion In non-contrast CT, SAF and VAF appearance differs and SAF radiomics improves the detection of CCS?>?0 when added to fat area; TAF radiomics (but not TAF area) spares the need for separate SAF and VAF segmentations.