Objective: The objectives of this study were to identify community pharmacist (CP)-led cognitive services and CPs' precautions taken related to COVID-19, perceived enablers and barriers related to pharmaceutical services and burnout levels during the COVID-19 pandemic.

Method: In this descriptive study, the survey was administered online to CPs in all regions of Turkey. The frequency of their provision of patient counselling, provision of medication information and practices towards precautions during the pandemic were evaluated based on CP self-reports. The Turkish version of the Burnout Measure Short Form was used, and a 30-item questionnaire based on the 12-domain Theoretical Domains Framework was developed to determine CPs' perceived enablers of and barriers to pharmaceutical service delivery during the COVID-19 pandemic. Data were collected using convenience sampling methods. Besides internal consistency reliability, principal component analysis, and correlation analysis, Mann-Whitney U-test was conducted in group comparisons.

Results: A total of 1098 complete responses were received, for a response rate of 4.11% among 26 747 CPs. The CPs' median burnout score was 3.3 (2.5-4.2). More than half of the CPs (54.5%) referred probable patients with COVID-19 to the hospital. Commonly delivered cognitive CP-led services included preventive health services (89.5%) and medication information services (86.3%). Perceived barriers to delivering pharmaceutical services were a lack of environmental resources and support and a lack of innovation in pharmaceutical services. Perceived enablers were CPs' knowledge, skills, self-confidence, actions, impacts, emotions and perceived behavioural control.

Conclusion: To increase the preparedness of pharmacists for future pandemics or disasters, this study highlighted CP-led cognitive services, precautions taken related to COVID-19, perceived enablers and barriers and burnout during the COVID-19 pandemic. Pharmaceutical services guidelines that could be followed during a pandemic or other disaster should be designed by addressing these findings.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8646293PMC
http://dx.doi.org/10.1111/ijcp.14834DOI Listing

Publication Analysis

Top Keywords

perceived enablers
20
enablers barriers
16
pharmaceutical services
16
cognitive services
12
covid-19 pandemic
12
services
10
descriptive study
8
practices precautions
8
barriers burnout
8
cp-led cognitive
8

Similar Publications

Immersive exposure to simulated visual hallucinations modulates high-level human cognition.

Conscious Cogn

January 2025

Humane Technology Lab, Catholic University of Sacred Heart, Milan, Italy; Applied Technology for Neuro-Psychology Lab., Istituto Auxologico Italiano IRCCS, Milan, Italy. Electronic address:

Psychedelic drugs offer valuable insights into consciousness, but disentangling their causal effects on perceptual and high-level cognition is nontrivial. Technological advances in virtual reality (VR) and machine learning have enabled the immersive simulation of visual hallucinations. However, comprehensive experimental data on how these simulated hallucinations affects high-level human cognition is lacking.

View Article and Find Full Text PDF

Spectrum sensing is recognized as a viable strategy to alleviate the scarcity of spectrum resources and to optimize their usage. In this paper, considering the time-varying characteristics and the dependence on various timescales within a time series of samples composed of in-phase (I) and quadrature (Q) component signals, we propose a multi-scale time-correlated perceptual attention model named MSTC-PANet. The model consists of multiple parallel temporal correlation perceptual attention (TCPA) modules, enabling us to extract features at different timescales and identify dependencies among features across various timescales.

View Article and Find Full Text PDF

Artificial intelligence (AI), particularly through advanced large language model (LLM) technologies, is reshaping coal mine safety assessment methods with its powerful cognitive capabilities. Given the dynamic, multi-source, and heterogeneous characteristics of data in typical mining scenarios, traditional manual assessment methods are limited in their information processing capacity and cost-effectiveness. This study addresses these challenges by proposing an embodied intelligent system for mine safety assessment based on multi-level large language models (LLMs) for multi-source sensor data.

View Article and Find Full Text PDF

Existing autonomous driving systems face challenges in accurately capturing drivers' cognitive states, often resulting in decisions misaligned with drivers' intentions. To address this limitation, this study introduces a pioneering human-centric spatial cognition detecting system based on drivers' electroencephalogram (EEG) signals. Unlike conventional EEG-based systems that focus on intention recognition or hazard perception, the proposed system can further extract drivers' spatial cognition across two dimensions: relative distance and relative orientation.

View Article and Find Full Text PDF

DynamicVLN: Incorporating Dynamics into Vision-and-Language Navigation Scenarios.

Sensors (Basel)

January 2025

Department of Electronics and Electrical Engineering, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.

Traditional Vision-and-Language Navigation (VLN) tasks require an agent to navigate static environments using natural language instructions. However, real-world road conditions such as vehicle movements, traffic signal fluctuations, pedestrian activity, and weather variations are dynamic and continually changing. These factors significantly impact an agent's decision-making ability, underscoring the limitations of current VLN models, which do not accurately reflect the complexities of real-world navigation.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!