AI Article Synopsis
- - The study investigated how long-term and short-term frequent attendees perceive patient-centered care in Finland’s primary healthcare system, focusing on differences in their experiences.
- - Researchers surveyed 495 frequent attenders and analyzed the data using various statistical methods to assess their perceptions of care factors like coordination, emotional support, and access to information.
- - Findings showed that long-term frequent attenders had poorer perceptions of patient-centeredness compared to short-term attenders, suggesting a need to reconsider how healthcare services address their unique needs.
Article Abstract
Aim: The study aimed to compare long- and short-term frequent attenders' (FAs) perceptions of patient-centredness and to assess the equivalence of the factor structure of patient-centred primary care (PCPC) instrument for long- and short-term FAs.
Methods: A cross-sectional survey of long-term (n = 234) and short-term (n = 261) FAs within the primary healthcare of one city in Finland. The data collected in January-July 2020 via 'the 36-item PCPC instrument' were analysed using Pearson's chi-squared test, Mann-Whitney U-test, Cronbach's alpha, and multigroup confirmatory factor analysis (MGCFA).
Results: Long-term FAs had worse perceptions of patient-centredness than short-term FAs across all subscales: patients' preferences, physical comfort, coordination of care, continuity and transition, emotional support, access to care, information and education, and family and friends. The MGCFA indicated a good fit for the predicted eight-factor model.
Conclusions: Long-term FAs' care needs are currently not being met, indicating the need for considering how the way healthcare services are arranged and care is provided affects prolonged and high care needs. Various dimensions of patient-centredness need to be addressed when developing not only FAs' care but also wider service paths. A distinction should be made between long- and short-term frequent attendance when identifying and addressing FAs' service needs.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/scs.13256 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Analyzing robust dividend payout policy with dynamic panel regression: Application of speed of adjustment to half-life.
PLoS One
January 2025
Faculty of Business Administration, Thongsook College, Bangkok, Thailand.
This study aims to observe the effects of financial metrics, free float shareholders, GDP growth and firm age on dividend payout policy in both the short- and long-term scenarios. The study introduces the dynamic panel regression models, i.e.
View Article and Find Full Text PDFEvaluating the Effectiveness of a Mobile Health Intervention on Enhancing HIV Knowledge in Sexual and Gender Minority Men.
J Acquir Immune Defic Syndr
November 2024
Columbia University School of Nursing, New York, NY, United States.
Background: In the United States, young men who have sex with men (YMSM) and young transgender women (YTGW) are disproportionately affected by HIV infection. Adequate HIV knowledge is critical for protecting adolescents and young adults at risk for HIV. This study aimed to evaluate the effectiveness of the mLab App intervention in enhancing HIV knowledge among YMSM and YTGW.
View Article and Find Full Text PDFA novel multi-user collaborative cognitive radio spectrum sensing model: Based on a CNN-LSTM model.
PLoS One
January 2025
School of Electronic Information Engineering, Inner Mongolia University, Hohhot, Inner Mongolia, China.
Cognitive Radio (CR) technology enables wireless devices to learn about their surrounding spectrum environment through sensing capabilities, thereby facilitating efficient spectrum utilization without interfering with the normal operation of licensed users. This study aims to enhance spectrum sensing in multi-user cooperative cognitive radio systems by leveraging a hybrid model that combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. A novel multi-user cooperative spectrum sensing model is developed, utilizing CNN's local feature extraction capability and LSTM's advantage in handling sequential data to optimize sensing accuracy and efficiency.
View Article and Find Full Text PDFAn ensemble deep learning framework for energy demand forecasting using genetic algorithm-based feature selection.
PLoS One
January 2025
Department of Information Systems and Cybersecurity, University of Bisha, Bisha, KSA.
Accurate energy demand forecasting is critical for efficient energy management and planning. Recent advancements in computing power and the availability of large datasets have fueled the development of machine learning models. However, selecting the most appropriate features to enhance prediction accuracy and robustness remains a key challenge.
View Article and Find Full Text PDFDesign Rational for Total Ankle Arthroplasty: An Update.
J Am Acad Orthop Surg
November 2024
From the Medical University of South Carolina, Charleston, SC (Gross and Scott), the University of California Irvine, Orange, CA (Hsu), and the Palomar Health Medical Group, San Diego, CA (Palanca).
The design of total ankle arthroplasty (TAA) systems is rapidly evolving as device companies try to keep pace with the expansion of surgical indications and a refinement of techniques for TAA. Even since the publication of the latest "update," published in 2018, three new designs and three updates on preexisting third-generation implants came onto the market. Improvements in third-generation TAA systems include minimal bone resection, retaining ligamentous support, and anatomic balancing.
View Article and Find Full Text PDFWant 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!