A Longitudinal Investigation of the Changes in Work Motivation and Employees’ Psychological Health

Organizations strive to motivate employees to thrive at work. However, employees’ motivation is likely to vary over a short period (e.g., a few months) to cope with the routine dynamics of organizations’ activities. These motivation dynamics covary with employees’ affective, cognitive, and behavioral outcomes in the workplace. Moreover, employees’ psychological health, a multidimensional concept focused on the individual’s well/ill-being simultaneously, changes over time. Using the integrated theoretical frameworks of self-determination theory (SDT) and the hierarchical model of self-determined motivation (H-SDT), this research sought to examine the motivational changes following the dual-path model. In particular, this work sought to unpack the temporal dynamics in employees’ subjective well/ill-beings predicted by the changes in basic needs satisfaction/frustration through autonomous/controlled motivation, while considering the characteristics of people’s general causality orientations (trait-level motivation). Over four months, longitudinal field data were collected from the employees in several private small businesses in the consumer product retail industry. Latent growth modeling (LGM) results supported the positive dual relations between the changes in employees’ psychological health and basic psychological needs satisfaction/frustration, but neither the changes of autonomous/controlled work motivation nor the indirect change paths via autonomous/controlled work motivation were significant. Finally, we discussed the theoretical and practical implications of the findings. Limitations and possible future research directions to further this line of research on the dynamic of work motivation were also summarized

A Longitudinal Investigation of the Changes in Work Motivation and Employees’ Psychological Health

Organizations strive to motivate employees to thrive at work. However, employees’ motivation is likely to vary over a short period (e.g., a few months) to cope with the routine dynamics of organizations’ activities. These motivation dynamics covary with employees’ affective, cognitive, and behavioral outcomes in the workplace. Moreover, employees’ psychological health, a multidimensional concept focused on the individual’s well/ill-being simultaneously, changes over time. Using the integrated theoretical frameworks of self-determination theory (SDT) and the hierarchical model of self-determined motivation (H-SDT), this research sought to examine the motivational changes following the dual-path model. In particular, this work sought to unpack the temporal dynamics in employees’ subjective well/ill-beings predicted by the changes in basic needs satisfaction/frustration through autonomous/controlled motivation, while considering the characteristics of people’s general causality orientations (trait-level motivation). Over four months, longitudinal field data were collected from the employees in several private small businesses in the consumer product retail industry. Latent growth modeling (LGM) results supported the positive dual relations between the changes in employees’ psychological health and basic psychological needs satisfaction/frustration, but neither the changes of autonomous/controlled work motivation nor the indirect change paths via autonomous/controlled work motivation were significant. Finally, we discussed the theoretical and practical implications of the findings. Limitations and possible future research directions to further this line of research on the dynamic of work motivation were also summarized

Molecular Cloning and Analysis of an Acetyl-CoA C-acetyltransferase Gene (EkAACT) from Euphorbia kansui Liou

Terpenoids are the largest class of natural products and are essential for cell functions in plants and their interactions with the environment. Acetyl-CoA acetyltransferase (AACT, EC2.3.1.9) can catalyze a key initiation step of the mevalonate pathway (MVA) for terpenoid biosynthesis and is modulated by many endogenous and external stimuli. Here, the function and expression regulation activities of AACT in Euphorbia kansui Liou (EkAACT) were reported. Compared with wild-type Arabidopsis, the root length, whole seedling fresh weight and growth morphology of EkAACT-overexpressing plants were slightly improved. The transcription levels of AtAACT, AtMDC, AtMK, AtHMGR, and AtHMGS in the MVA pathway and total triterpenoid accumulation increased significantly in transgenic Arabidopsis. Under NaCl and PEG treatment, EkAACT-overexpressing Arabidopsis showed a higher accumulation of total triterpenoids, higher enzyme activity of peroxidase (POD) and superoxide dismutase (SOD), increased root length and whole seedling fresh weight, and a decrease in the proline content, which indicated that plant tolerance to abiotic stress was enhanced. Thus, AACT, as the first crucial enzyme, plays a major role in the overall regulation of the MVA pathway

MicroRNAome Profile of Euphorbia kansui in Response to Methyl Jasmonate

miRNAs play vital regulatory roles in different plant developmental stages and in plant response to biotic and abiotic stresses. However, information is limited on the miRNA regulatory mechanism to methyl jasmonate (MeJA). In this study, we used the microRNAome profile to illustrate the relevant regulatory mechanisms of Euphorbia kansui in response to methyl jasmonate (MeJA) through Illumina RNA-Seq. As a result, we identified 875 miRNAs corresponding to 11,277 target mRNAs, among them, 168 known miRNA families representing 6019 target mRNAs sequences were obtained. 452 miRNA-mRNA pairs presented an anti-correlationship (Cor < −0.50 and p-value of correlation ≤ 0.05). The miRNA with a fold change ≥ 2 and a p (p-Value) < 0.05 in pairwise comparison were identified as significant differentially expressed miRNAs (DEMs). The DEMs in MeJA treatment of 0, 24, 36 and 48 h were compared by using Short Time Expression Miner (STEM) cluster and 4 significant gene profiles (p-value ≤ 0.02) were identified. Through the kyoto encyclopedia of genes and genomes (KEGG) pathway and gene ontology (GO) enrichment analysis on all miRNA targets, we identified 33 mRNAs in terpenoid biosynthesis, which were regulated by miRNAs under MeJA treatment, so the miRNA maybe involved in the response of E. kansui plant to exogenous MeJA and the results would provide very useful information on illustrating the regulatory mechanism of E. kansui and also provide an overall view of the miRNAs response to MeJA stress of a non-model plant

NA now for double blinded review process

This study examined the relationship among autistic traits, gender, and perceptions of artificial intelligence (AI) tools for second language (L2) speaking practice among neurotypical university students. The investigation included 111 participants and utilized the Broad Autism Phenotype Questionnaire to assess Autistic Traits (AU) and the sub-traits Aloof (AF), Rigid (RD), and Pragmatic Language (PL). It also employed various scales to measure perceptions, including Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude (AT), Behavioral Intention (BI), and Usage Behavior (UB). The findings indicated no significant differences in AU, AF, RD, and PL between males and females. Similarly, there were no significant differences in PU, AT, BI, and UB between genders, although males demonstrated marginally higher scores in PEOU than females. Autistic traits showed specific correlations with perceptions of AI tools: AU was negatively correlated with PU, AT, and marginally with PEOU; AF was marginally negatively correlated with PU and AT; RD was negatively correlated with PEOU, AT, and BI, and marginally with PU. Furthermore, the study highlighted the moderating role of gender in the relationship between autistic traits and perceptions of AI tools. Specifically, the effects of autistic traits on perceptions were more pronounced in males than in females, particularly the relationships between PEOU and AF, UB and AU, and UB and PL. This research highlighted the importance of considering autistic traits in educational technology deployment, advocating for customizable AI solutions to better meet diverse learner needs. The outcomes contributed to a more inclusive understanding of educational technology, emphasizing the need to adapt AI tools to enhance learning experiences for all students, regardless of gender or neurodiversity