INTRODUCTION: Retrospective video analysis (RVA) has been a popular method of analysis in many research fields, evidenced by autism behavioral research, child play behavior, and caregiver-resident interactions (Baranek, 1999; Gilchrist et al., 2018; Gilmore-Bykovskyi, 2015). Given the widespread use of RVA, the number of studies using it to augment their study designs provide sparse details about the training methods for this level of analysis, making it difficult to maintain a standard level of rigor across different institutions (Haidet, Tate, Divirgilio-Thomas, Kolanowski, & Happ, 2009). METHODS: A structured training program was developed for naïve coders (n=5). The structured training program was composed of five stages with careful introduction of behaviors and regular checkpoints. Statistical Analysis: The output generated by the naïve trainees was analyzed with paired t-tests, Fisher’s Exact Test, ANOVA, percent agreement, and Cohen’s kappa. RESULTS: No difference was found between the different trainees, demonstrating the trainees were trained to a similar level of expertise. The overall recognition of behaviors increased by 2.1% from the first to last training video analysis. Discrete behaviors had a higher level of agreement. CONCLUSIONS: The structured training program demonstrated a small increase in the recognition of behaviors, with a higher recognition in the derived MDS-UPDRS behaviors.

No description available.

No description available.

No description available.

No description available.

No description available.

Sedan 2015, får röntgensjuksköterskor vid ett stort sjukhus, som arbetar på MR och DT-avdelningen, självständigt sedera barn mellan sex månader och sex år med läkemedlet kallat Dexdor.

No description available.

No description available.

This project had its primary focus on running a campaign to recruit healthy volunteers for a test study involving the utilization of a microwave sensor and ultrasound measurements. The key system used was the Muscle Analyzer System (MAS), which consisted of the Bandstop Filter Sensor (BFS), a microwave sensor transmitting microwaves into the selected medium through transmission and a FieldFox Vector Network Analyzer which was used to transmit these microwaves. The second system utilized in the project was ultrasound imaging, which enabled the measurement of the size of the Rectus Femoris muscle in the thigh and the thickness of the fat and skin layers on the volunteer. This information served as a basis for interpreting the resonant frequency obtained from the MAS system. The goal was to compare these results to assess the muscle quality of the volunteers. A total of nine volunteers participated in the study, with data from four volunteers being suitable for follow- up data analysis and further research. The primary method used to obtain these results involved collecting measurements from the volunteers and comparing them with results from previous measurements conducted on sick patients in Maastricht. The resonant frequency observed for the volunteers in Uppsala was approximately 2.15 GHz, with the fat layer ranging from 5 to 18 mm in thickness, the skin layer measuring 2 mm thick, and the Rectus Femoris muscle having an area of 4 to 8 cm2. When these measurements were compared with the measurements from Maastricht on sick patients, a significant difference was observed. The patients' measurements showed values of approximately 1.98 GHz, even though there wasn't a substantial difference in the muscle and fat layer areas. In order to draw meaningful conclusions however, it would be necessary to conduct measurements using the same Vector Network Analyzer (VNA) for both healthy volunteers and sick patients with sarcopenia.