Predictors of community pharmacists' readiness to manage the effective and safe use of oral anticancer medicines in a developing setting.

BACKGROUND: There is a paucity of studies about the readiness of community pharmacists to manage the safe and effective use of oral anticancer medicines (OAMs) in developing settings. OBJECTIVES: Using the readiness component (knowledge and willingness) of the situational theory of leadership, the study assessed community pharmacists' readiness to manage the safe and effective use of OAMs in Qatar, and also identified its significant predictors. METHODS: A cross-sectional assessment of 252 community pharmacists was conducted with a pre-tested 48-item questionnaire. Readiness was assessed with a 5-point Likert-type scale and the maximum obtainable score was 70. The mean was used as the cut-off point to categorize willingness and knowledge as either high (≥ mean) or low (< mean). Independent t-test, one-way analysis of variance and multiple linear regression was used for data analyses. RESULTS: The mean SD score for the readiness of community pharmacists was 39.3 ± 11.2 (min = 11, max = 70). Only a minority of the respondents expressed an excellent understanding of the chemotherapy cycles (19.6%; 45/230), and familiarity with targeted anticancer therapy (14.3%; 33/230), side effects (22.2%; 51/230), and dosing of OAMs (14.4%; 33/230). Employment status, number of OAMs prescriptions dispensed per month and adequacy of the contents related to OAMs in undergraduate training were the significant predictors of readiness (R2 = 0.558, (F (11, 209) = 3.559, p = 0.0001). CONCLUSIONS: Community pharmacists' readiness appear inadequate especially regarding its dosing, side effects, handling, and disposal of OAMs. These inadequacies probably underline community pharmacists' low familiarity and comfortability with dispensing and educating patients on the effective and safe use of OAMs.

Investigating pharmacy students' therapeutic decision-making with respect to antimicrobial stewardship cases.

BACKGROUND: Antimicrobial stewardship programs (ASPs) play a big role in minimizing antimicrobial resistance. Pharmacists are essential members of the health care team and in order for them to fulfill roles on ASP teams and become antimicrobial stewards, they must be prepared adequately by pharmacy schools prior to entry into actual practice. Although programming has been implemented into entry-to-practice programs worldwide, little is known about how students interpret antimicrobial stewardship (AMS) data and arrive at clinical decisions. We aimed to explore students' cognitive processes and determine how they formulate therapeutic decisions when presented with AMS cases. METHODS: This was a qualitative study conducted using a case study approach, in which a sample (n=20) of pharmacy students was recruited to interpret AMS cases. Semi-structured 1-on-1 interviews were arranged with each participant. A think-aloud procedure with verbal protocol analysis was adopted to determine students' decision-making processes. Thematic analysis was used to interpret themes from the interview data. RESULTS: Two themes were interpreted from the data: students' focus and students' approach to case interpretation. Students' focus relates to external factors students consider when interpreting AMS case data and use to make and justify therapeutic decisions including patient-centered factors, drug-related factors, AMS interventions, and pharmacist's role. Students' clinical reasoning describes the approach that students use to interpret the data and the decision-making processes they employ to arrive at a clinical decision including a systematic approach versus non-systematic approach. CONCLUSIONS: Students vary in their focus and the cognitive strategies used to interpret AMS cases. Findings support the notion that clinical reasoning and decision-making should be explicitly taught in pharmacy curricula, in order to help students become aware of their own cognitive processes and decision-making abilities.

Learning emotions latent representation with CVAE for text-driven expressive audiovisual speech synthesis.

Great improvement has been made in the field of expressive audiovisual Text-to-Speech synthesis (EAVTTS) thanks to deep learning techniques. However, generating realistic speech is still an open issue and researchers in this area have been focusing lately on controlling the speech variability. In this paper, we use different neural architectures to synthesize emotional speech. We study the application of unsupervised learning techniques for emotional speech modeling as well as methods for restructuring emotions representation to make it continuous and more flexible. This manipulation of the emotional representation should allow us to generate new styles of speech by mixing emotions. We first present our expressive audiovisual corpus. We validate the emotional content of this corpus with three perceptual experiments using acoustic only, visual only and audiovisual stimuli. After that, we analyze the performance of a fully connected neural network in learning characteristics specific to different emotions for the phone duration aspect and the acoustic and visual modalities. We also study the contribution of a joint and separate training of the acoustic and visual modalities in the quality of the generated synthetic speech. In the second part of this paper, we use a conditional variational auto-encoder (CVAE) architecture to learn a latent representation of emotions. We applied this method in an unsupervised manner to generate features of expressive speech. We used a probabilistic metric to compute the overlapping degree between emotions latent clusters to choose the best parameters for the CVAE. By manipulating the latent vectors, we were able to generate nuances of a given emotion and to generate new emotions that do not exist in our database. For these new emotions, we obtain a coherent articulation. We conducted four perceptual experiments to evaluate our findings.

Is markerless acquisition technique adequate for speech production?

In this study, the precision of markerless acquisition techniques have been assessed when used to acquire articulatory data for speech production studies. Two different markerless systems have been evaluated and compared to a marker-based one. The main finding is that both markerless systems provide a reasonable result during normal speech and the quality is uneven during fast articulated speech. The quality of the data is dependent on the temporal resolution of the markerless system.