Social Workers’ Evidence-Based Practice Use and Challenges in Rural Environments: A Systematic Review

Over the past decade, the demand for Evidence-Based Practice (EBP) in the social work field has increased. Previous studies indicate that EBP promotes clinical decision making based on current best evidence and decreases the use of ineffective interventions. However, social workers still face a variety of barriers to become evidence-based practitioners. Particularly, social workers practicing in rural areas face increased barriers to make use of evidence in practice. This study conducted a systematic review of current literature to find evidence related to social workers’ use of EBP and their barriers in rural settings. Reviews were limited to social work studies published between 2000 and 2014. Elements of rural culture that influence social work practice are consid-ered. Implications for social work practitioners are also presented, including suggestions for en-hancing EBP in rural settings

Impact of Providers’ Cultural Competence on Clients’ Satisfaction and Hopefulness in Rural Family Services: A Pilot Study

Cultural competence has been discussed in professional disciplines. However, previous studies focused on ethnic sensitivity in practice, and limited work has addressed the cultural competence of rural social work practitioners. This study examined relationships between families’ perceptions of cultural competence, therapeutic alliance, and practice outcomes in rural practice settings. Forty-five youth and their parents receiving intensive in-home family preservation services at Integrated Services of Appalachian Ohio completed a questionnaire regarding their providers’ cultural competence in rural settings, and their therapeutic alliance, hopefulness, and satisfaction with services. Families rated their provider as culturally competent in rural practice settings; and provider competence in rural culture was positively associated with practice outcomes – satisfaction and hopefulness. Suggestions for enhancing social work practitioners’ cultural competence in rural settings are provided

Beamforming Allocation and Backhaul Capacity Allocation for Integrated Access and Backhaul Networks

In this paper, we consider beamforming vector allocation and backhaul link capacity allocation in millimeter wave (mmWave) integrated access and backhaul (IAB) networks. We consider out-of-band backhaul and each base station (BS) has a Line-of-Sight (LoS) probability. We then derive a sum ergodic capacity using stochastic geometry. We also formulate the sum ergodic capacity maximization problem subject to the beamforming vector and backhaul link capacity allocations of the macro base station (MBS). Then, we show the optimization problem is a convex problem, and hence, we obtain a global optimal solution for our optimization problem using the Karush-Kuhn-Tucker (KKT) condition. Finally, from numerical simulation, we show that the proposed solutions achieve higher sum ergodic capacity than baseline schemes. We also explore the impacts of a backhaul-access bandwidth partitioning ratio and a density of small base stations (SBSs)

Beamforming Design for Cache-enabled Integrated Access and Backhaul Networks

In this paper, we consider a cache-enabled integrated access and backhaul (IAB) network. We first derive the sum achievable data rate. Then, we formulate the sum achievable data rate maximization problem with respect to (w.r.t.) the beamforming designs of the macro base station (MBS) and small base stations (SBSs). By using successive convex approximation (SCA), we obtain a stationary point of the non-convex problem. Finally, by using numerical results, we show the proposed solution achieves a higher sum achievable data rate than the baseline schemes. Moreover, We show the impacts of the number of content types and Zipf exponent. © 2022 IEEE

Timely Update Probability Analysis of Blockchain Ledger in UAV-assisted Data Collection Networks

In recent years, blockchain technology has been frequently exploited to address new security requirements for unmanned aerial vehicle (UAV)-assisted data collection (U-DC). However, the new latency to commit data to the blockchain ledger has emerged as a new issue. In this paper, therefore, we analyze the timely update probability (TUP) of the blockchain ledger, which is the probability that collected data from a UAV is updated in the blockchain within a given target latency. For analysis, we first define the TUP of the blockchain ledger in U-DC networks, using both the UAV communication and blockchain latencies. We then derive a closed-form expression of the TUP, and then validate our analysis. We conclude by exploring the impacts of some UAV communication and blockchain parameters on the TUP for their optimal deployment. © 2022 IEEE

Predictions for Three-Month Postoperative Vocal Recovery after Thyroid Surgery from Spectrograms with Deep Neural Network

Despite the lack of findings in laryngeal endoscopy, it is common for patients to undergo vocal problems after thyroid surgery. This study aimed to predict the recovery of the patient’s voice after 3 months from preoperative and postoperative voice spectrograms. We retrospectively collected voice and the GRBAS score from 114 patients undergoing surgery with thyroid cancer. The data for each patient were taken from three points in time: preoperative, and 2 weeks and 3 months postoperative. Using the pretrained model to predict GRBAS as the backbone, the preoperative and 2-weeks-postoperative voice spectrogram were trained for the EfficientNet architecture deep-learning model with long short-term memory (LSTM) to predict the voice at 3 months postoperation. The correlation analysis of the predicted results for the grade, breathiness, and asthenia scores were 0.741, 0.766, and 0.433, respectively. Based on the scaled prediction results, the area under the receiver operating characteristic curve for the binarized grade, breathiness, and asthenia were 0.894, 0.918, and 0.735, respectively. In the follow-up test results for 12 patients after 6 months, the average of the AUC values for the five scores was 0.822. This study showed the feasibility of predicting vocal recovery after 3 months using the spectrogram. We expect this model could be used to relieve patients’ psychological anxiety and encourage them to actively participate in speech rehabilitation