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- 2025-01
Związany charakter decyzji o przeniesieniu pozwolenia na budowę Glosa aprobująca do wyroku Naczelnego Sądu Administracyjnego z 29 października 2020 r. (II OSK 1713/20)
The commentary is an approving assessment of the ruling of the Supreme Administrative Court of 29/10/2020, II OSK 1713/20. In this ruling, the court considered the related nature of the decision to transfer planning permission. The Supreme Administrative Court held that the administrative body cannot refuse to issue a positive decision regarding the transfer of planning permission if the investor satisfies all the conditions specified in Article 40, para. 1 of the Construction Law. However, this position of the Supreme Administrative Court requires a more in-depth commentary on the legal nature of related decisions.Otwarty dostępArtykułyJournal article - 2025-01-08
Non-verbal communication questionnaire: a measure to assess effective interaction
In five studies, we document the development and validation of the Non-verbal Communication Questionnaire (NVCQ). This eight-item measurement tool assesses how people perceive non-verbal cues across two dimensions of effective communication. These two dimensions, encouraging and discouraging non-verbal cues, are based on Khan and Zeb's (2021) version of the 10-part model of non-verbal communication. Study 1 reports the development of the NVCQ and provides initial support for the factorial structure of the measure in a Pakistani sample. Studies 2 and 3 confirmed the factorial structure and demonstrated the construct validity of the NVCQ. A preregistered Study 4 confirmed the factorial structure in a Polish sample, and provided additional support for the construct validity of the measure, while Study 5 demonstrated its adequate test–retest reliability. We conclude that the NVCQ is a psychometrically sound instrument for assessing effective communication that incorporates non-verbal aspects in every domain of life, from clinical to research settings.Otwarty dostępArtykułyJournal article - 2024-12-20
Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks
Fafrowicz, MagdalenaTutajewski, MarcinSieradzki, IgorOchab, Jeremi K.Ceglarek-Sroka, AnnaLewandowska, KorynaSikora-Wachowicz, BarbaraPodolak, Igor T.Oświęcimka, PawełUnderstanding brain function relies on identifying spatiotemporal patterns in brain activity. In recent years, machine learning methods have been widely used to detect connections between regions of interest (ROIs) involved in cognitive functions, as measured by the fMRI technique. However, it’s essential to match the type of learning method to the problem type, and extracting the information about the most important ROI connections might be challenging. In this contribution, we used machine learning techniques to classify tasks in a working memory experiment and identify the brain areas involved in processing information. We employed classical discriminators and neural networks (convolutional and residual) to differentiate between brain responses to distinct types of visual stimuli (visuospatial and verbal) and different phases of the experiment (information encoding and retrieval). The best performance was achieved by the LGBM classifier with 1-time point input data during memory retrieval and a convolutional neural network during the encoding phase. Additionally, we developed an algorithm that took into account feature correlations to estimate the most important brain regions for the model’s accuracy. Our findings suggest that from the perspective of considered models, brain signals related to the resting state have a similar degree of complexity to those related to the encoding phase, which does not improve the model’s accuracy. However, during the retrieval phase, the signals were easily distinguished from the resting state, indicating their different structure. The study identified brain regions that are crucial for processing information in working memory, as well as the differences in the dynamics of encoding and retrieval processes. Furthermore, our findings indicate spatiotemporal distinctions related to these processes. The analysis confirmed the importance of the basal ganglia in processing information during the retrieval phase. The presented results reveal the benefits of applying machine learning algorithms to investigate working memory dynamics.Otwarty dostępArtykułyJournal article - 2024-12-12
Developing a codebook for assessing auditory hallucination complexity using mixed methods
Introduction: In recent years there has been a notable expansion of psychotherapeutic approaches to treat people experiencing auditory verbal hallucinations (AVH). While many psychotherapists conceptualize voices as “dissociative parts” and apply therapeutic techniques derived from the field of dissociation, research investigating AVH from this perspective is limited. Despite the acknowledgment that voices encountered in dissociative identity disorder (DID) often exhibit high complexity and autonomy, there is a critical need for assessment tools capable of exploring voice complexity across different clinical groups. Such tools hold significant potential for aiding clinicians to identify patients who may benefit more from dissociation-based therapy approaches. This study aims to operationalize the concept of voice complexity (VC) by identifying its different dimensions and indicators. Methods: Using concept mapping procedures, 12 healthcare professionals and two voice-hearers participated in brainstorming, and 24 people with clinical backgrounds performed sorting and rating tasks. Results: Seven dimensions of VC were identified: System Complexity, Content Complexity, Voice’s Interest Complexity, Interaction Complexity with Voice-Hearer, Voice’s Own Life, Voice Influence, and Voice’s Vocal Characteristics. A codebook for assessing VC with indicators for varying levels of complexity across these dimensions was developed and can be used with the Structured Clinical Interview for Voice-Hearers. Inter-rater reliability, measured by comparing the assessments of two interview transcripts by seven raters using Kendall’s Coefficient, indicated substantial agreement in one interview (W = .613) and almost perfect agreement in the second (W = .805). Discussion: The new instrument has promise as an effective tool for comparative studies exploring VC in diverse clinical and non-clinical populations, with potential implications for clinical practice and future research.Otwarty dostępArtykułyJournal article - 2024-12-13
Motivational underpinnings of support for radical political leaders
The present research examined the idea that followers are more strongly motivated by radical as opposed to moderate political leaders. We derived this idea from the significance quest theory that posits that a desire to feel important and meaningful is one of the fundamental human motives (Kruglanski et al., 2018, 2022). We expected that voters would be more willing to support political actors when they perceived them as radical as opposed to moderate, because the goals of those radical actors would be more personally important for voters. Consequently, supporters would experience a greater sense of personal significance from supporting such goals, which would motivate them to get engaged on behalf of their candidates. In five studies (N = 2,154), including two pre-registered replications, spanning two U.S. presidential elections (2016, 2020) and Polish parliamentary elections (2023), we found support for our predictions. The results showed that as followers perceived their candidates as more radical, they viewed the leaders' goals as more personally important, experienced a greater sense of personal significance, and expressed a higher willingness to make sacrifices for the candidates. These results contribute to the understanding of the appeal of radical political actors.Otwarty dostępArtykułyJournal article