Complaints as starting point for vicious cycles in customer-employee-interactions

A ring-model of vicious cycles in customer employee-interaction is proposed: service employees perceive complaints as a threat to their self-esteem resulting in defense responses such as an increased need for cognitive closure, a devaluation of the customer and their information and degrading service behavior. Confronted with such degrading service behavior, customers react defensively as well, by devaluing the employee for example with regard to his/her competence and by reducing repurchase and positive word-of-mouth (WOM). Three studies investigated each link in this ringmodel. In study 1, participants were confronted with an aggressive or neutral customer complaint. Results show that motivated closed-mindedness (one aspect of the need for cognitive closure) increases after an aggressive complaint leading to a devaluation of the customer and their information, and in turn to a degrading service reaction. In study 2, participants were confronted with a degrading or favorable service reaction. Results show that they devaluate the employees' competence after receiving a degrading service reaction and thus reduce their intention to repurchase. In study 3, we finally examined our predictions investigating real customer employee-interactions: we analyzed data from an evaluation study in which mystery callers tested the service hotline of an airline. Results show that the employees' competence is devaluated after degrading behavior and thus reduces positive WOM

The Path or the Goal? Decision vs. Information Focus in Biased Information Seeking after Preliminary Decisions

Research on the phenomenon of selective exposure to information demonstrates that after preliminary or final decisions, people show a preference for supporting rather than conflicting information (confirmation bias). In this article, we examine conditions that increase or decrease distortions in the search for information. We report on four experiments indicating that the confirmation bias is influenced by whether people focus on their decision or on the presented pieces of information during the information search. Focusing on the decision, for example, because a reward for a correct decision is promised or simply because participants repeatedly think of it, increases the confirmation bias. On the other hand, if participants focus on the available pieces of information because they have to invest money in order to search for information or because they have to evaluate the individual pieces of information, the confirmation bias decreases. Implications for theoretical understanding and interventions for decision-making situations are discussed

Effects of a mindfulness based childbirth and parenting program on pregnant women's perceived stress and risk of perinatal depression-Results from a randomized controlled trial

The aim of this study was to test the efficacy of a Mindfulness-Based Childbirth and Parenting Program (MBCP) in reducing pregnant women's perceived stress and preventing perinatal depression compared to an active control condition.; First time pregnant women (n = 197) at risk of perinatal depression were randomized to MBCP or an active control treatment, which consisted of a Lamaze childbirth class. At baseline and post-intervention, participants filled out questionnaires on perceived stress, depressive symptoms, positive states of mind, and five facets of mindfulness.; Compared to the active control treatment, MBCP significantly reduced perceived stress (p = 0.038, d = 0.30) and depressive symptoms (p = 0.004, d = 0.42), and increased positive states of mind (p = 0.005, d = 0.41) and self-reported mindfulness (p = 0.039, d = 0.30). Moreover, change in mindfulness possibly mediated the treatment effects of MBCP on stress, depression symptoms, and positive states of mind. The subscales "non-reactivity to inner experience" and "non-judging of experience" seemed to have the strongest mediating effects.; The outcomes were self-report questionnaires, the participants were not blinded to treatment condition and the condition was confounded by number of sessions.; Our results suggest that MBCP is more effective in decreasing perceived stress and risk of perinatal depression compared to a Lamaze childbirth class. The results also contribute to our understanding of the underlying psychological mechanisms through which the reduction of stress and depression symptoms may operate. Thus, this study increases our knowledge about efficient intervention strategies to prevent perinatal depression and promote mental wellbeing among pregnant women

Assessing the detectability of European spruce bark beetle green attack in multispectral drone images with high spatial- and temporal resolutions

Detecting disease- or insect-infested forests as early as possible is a classic application of remote sensing. Under conditions of climate change and global warming, outbreaks of the European spruce bark beetle (Ips typographus, L.) are threatening spruce forests and the related timber industry across Europe, and early detection of infestations is important for damage control. Infested trees without visible discoloration (green attack) have been identified using multispectral images, but how early green attacks can be detected is still unknown. This study aimed to determine when infested trees start to show an abnormal spectral response compared with healthy trees, and to quantify the detectability of infested trees during the infestation process. Pheromone bags were used to attract bark beetles in a controlled experiment, and subsequent infestations were assessed in the field on a weekly basis. In total, 977 trees were monitored, including 208 attacked trees. Multispectral drone images were obtained before and during the insect attacks, representing different periods of infestation. Individual tree crowns (ITC) were delineated by marker-controlled watershed segmentation, and the average reflectance of ITCs was analyzed based on the duration of infestation. The detectability of green attacks and driving factors were examined. We propose new Multiple Ratio Disease-Water Stress Indices (MR-DSWIs) as vegetation indices (VI) for detecting infestations. We defined a VI range of 5-95% as a healthy tree, and a VI value outside that range as an infested tree. Detection rates using multispectral images were always higher than discoloration rates observed in the field, and the newly proposed MR-DSWIs detected more infested trees than the established VIs. Infestations were detectable at 5 and 10 weeks after an attack at a rate of 15% and 90%, respectively, from the multispectral drone images. Weeks 5-10 of infestation therefore represent a suitable period for using the proposed methodology to map infestation at an early stage

Enhanced Magnetic Resonance Image Synthesis with Contrast-Aware Generative Adversarial Networks

A Magnetic Resonance Imaging (MRI) exam typically consists of the acquisition of multiple MR pulse sequences, which are required for a reliable diagnosis. Each sequence can be parameterized through multiple acquisition parameters affecting MR image contrast, signal-to-noise ratio, resolution, or scan time. With the rise of generative deep learning models, approaches for the synthesis of MR images are developed to either synthesize additional MR contrasts, generate synthetic data, or augment existing data for AI training. However, current generative approaches for the synthesis of MR images are only trained on images with a specific set of acquisition parameter values, limiting the clinical value of these methods as various sets of acquisition parameter settings are used in clinical practice. Therefore, we trained a generative adversarial network (GAN) to generate synthetic MR knee images conditioned on various acquisition parameters (repetition time, echo time, image orientation). This approach enables us to synthesize MR images with adjustable image contrast. In a visual Turing test, two experts mislabeled 40.5% of real and synthetic MR images, demonstrating that the image quality of the generated synthetic and real MR images is comparable. This work can support radiologists and technologists during the parameterization of MR sequences by previewing the yielded MR contrast, can serve as a valuable tool for radiology training, and can be used for customized data generation to support AI training