Factors associated with hospital service satisfaction in a sample of Arab subjects with schizophrenia

<p>Abstract</p> <p>Background</p> <p>Assessment of patients' satisfaction with health care services could help to identify the strengths and weaknesses of the system and provide guidance for further development. The study's objectives were to: (i) assess the pattern of satisfaction with hospital care for a sample of people with schizophrenia in Kuwait, using the Verona Service Satisfaction Scale (VSSS-EU); ii) compare the pattern of satisfaction with those of similar studies; and iii) assess the association of VSSS seven domains with a number of variables representing met and unmet needs for care, family caregiver burden, severity of psychopathology, level of psychosocial functioning, socio-demographic characteristics, psychological well-being and objective quality of life.</p> <p>Methods</p> <p>Consecutive outpatients in stable condition and their family caregivers were interviewed with the VSSS-EU and measures of needs for care, caregiver burden, quality of life and psychopathology.</p> <p>Results</p> <p>There were 130 patients (66.1%m, mean age 36.8). While over two-thirds expressed satisfaction with the domains of "overall satisfaction", "professionals' skills", "access", "efficacy", and "relatives' involvement", only about one-third were satisfied with the domains of "information" and "types of intervention". The later two domains were the areas in which European patients had better satisfaction than our patients, while our patients expressed better satisfaction than the Europeans in the domain of "relatives' involvement". In multiple regression analyses, self-esteem, positive and negative affect were the most important correlates of the domains of service satisfaction, while clinical severity, caregiver burden and health unmet needs for care played relatively minor roles.</p> <p>Conclusion</p> <p>The noted differences and similarities with the international data, as well as the predictive power of self-esteem and affective state, support the impression that patients' attitudes towards psychiatric care involve a complex relationship between clinical, personal and socio-cultural characteristics; and that many of the factors that impact on satisfaction with service relate to individual psychological characteristics. The weaknesses in the system, highlighted by the pattern of responses of the participants, indicate possible gaps in the provision of comprehensive psychiatric care in the country and obviate the need for public mental health education and development of services to enhance the quality of care.</p

Clinical and biomechanical evaluation of three bioscaffold augmentation devices used for superficial digital flexor tenorrhaphy in donkeys (Equus asinus): An experimental study

The present study was designed to carry out an in vivo and in vitro comparative evaluation of three bio-scaffold augmentation devices used for superficial digital flexor tenorrhaphy in donkeys. Twenty-four clinically healthy donkeys were assigned for three treatment trials (n = 8) using one of three bioscaffold materials (glycerolized bovine pericardium xenograft, tendon allograft and allograft with glycerolized by bovine pericardium). In addition, eight clinically healthy donkeys were selected to serve as control. Clinical signs of each animal were scored and the sum of all clinical indexes was calculated at each time point of the experiment. Four donkeys from each group were euthanized at 45 and 90 days postoperatively, respectively, for biomechanical and histopathological evaluation of treated superficial digital flexor tendon (SDFT). The failure stress in allograft shielding group significantly increased compared to the corresponding values of the other groups at 45 (62.7 ± 6.5 N mm−2) and 90 (88.8 ± 3.5 N mm−2) days postoperatively. The fetlock angle in the allograft shielding group at both 45 (112.8° ± 4.4) and 90 (123.8° ± 1.1) days postoperatively showed a significant increase (p < 0.05) relative to the values of the other groups and a significant decrease (p < 0.05) when compared to normal angle (125° ± 0). However, the histomorphological findings revealed no remarkable changes between the treatment groups. In conclusion, the failure stress, fetlock angle and histomorphological findings may provide useful information about the healing characteristics of SDFT tenorrhaphy. The bio-scaffold augmentation devices, either xenogenic or allogenic, provide good alternative techniques accelerating SDFT healing with minimal adhesions in donkeys

Recognition rate variation in the presence of reverberation, as influenced by diverse feature extraction techniques across different SNR levels.

Recognition rate variation in the presence of reverberation, as influenced by diverse feature extraction techniques across different SNR levels.</p

Output recognition rates of cancelable speaker identification system for different feature extraction techniques at different SNRs.

Output recognition rates of cancelable speaker identification system for different feature extraction techniques at different SNRs.</p

Output recognition rates of the speaker identification system for different feature extraction techniques at different SNRs without reverberation effect.

Output recognition rates of the speaker identification system for different feature extraction techniques at different SNRs without reverberation effect.</p

Features from different transforms.

This paper introduces a method aiming at enhancing the efficacy of speaker identification systems within challenging acoustic environments characterized by noise and reverberation. The methodology encompasses the utilization of diverse feature extraction techniques, including Mel-Frequency Cepstral Coefficients (MFCCs) and discrete transforms, such as Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), and Discrete Wavelet Transform (DWT). Additionally, an Artificial Neural Network (ANN) serves as the classifier for this method. Reverberation is modeled using varying-length comb filters, and its impact on pitch frequency estimation is explored via the Auto Correlation Function (ACF). This paper also contributes to the field of cancelable speaker identification in both open and reverberation environments. The proposed method depends on comb filtering at the feature level, deliberately distorting MFCCs. This distortion, incorporated within a cancelable framework, serves to obscure speaker identities, rendering the system resilient to potential intruders. Three systems are presented in this work; a reverberation-affected speaker identification system, a system depending on cancelable features through comb filtering, and a novel cancelable speaker identification system within reverbration environments. The findings revealed that, in both scenarios with and without reverberation effects, the DWT-based features exhibited superior performance within the speaker identification system. Conversely, within the cancelable speaker identification system, the DCT-based features represent the top-performing choice.</div

Output recognition rates of the cancelable speaker identification system in the presence of reverberation for different feature extraction techniques at different SNRs.

Output recognition rates of the cancelable speaker identification system in the presence of reverberation for different feature extraction techniques at different SNRs.</p

MFCCs extraction.

This paper introduces a method aiming at enhancing the efficacy of speaker identification systems within challenging acoustic environments characterized by noise and reverberation. The methodology encompasses the utilization of diverse feature extraction techniques, including Mel-Frequency Cepstral Coefficients (MFCCs) and discrete transforms, such as Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), and Discrete Wavelet Transform (DWT). Additionally, an Artificial Neural Network (ANN) serves as the classifier for this method. Reverberation is modeled using varying-length comb filters, and its impact on pitch frequency estimation is explored via the Auto Correlation Function (ACF). This paper also contributes to the field of cancelable speaker identification in both open and reverberation environments. The proposed method depends on comb filtering at the feature level, deliberately distorting MFCCs. This distortion, incorporated within a cancelable framework, serves to obscure speaker identities, rendering the system resilient to potential intruders. Three systems are presented in this work; a reverberation-affected speaker identification system, a system depending on cancelable features through comb filtering, and a novel cancelable speaker identification system within reverbration environments. The findings revealed that, in both scenarios with and without reverberation effects, the DWT-based features exhibited superior performance within the speaker identification system. Conversely, within the cancelable speaker identification system, the DCT-based features represent the top-performing choice.</div

Magnitude and phase responses of a comb filter.

This paper introduces a method aiming at enhancing the efficacy of speaker identification systems within challenging acoustic environments characterized by noise and reverberation. The methodology encompasses the utilization of diverse feature extraction techniques, including Mel-Frequency Cepstral Coefficients (MFCCs) and discrete transforms, such as Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), and Discrete Wavelet Transform (DWT). Additionally, an Artificial Neural Network (ANN) serves as the classifier for this method. Reverberation is modeled using varying-length comb filters, and its impact on pitch frequency estimation is explored via the Auto Correlation Function (ACF). This paper also contributes to the field of cancelable speaker identification in both open and reverberation environments. The proposed method depends on comb filtering at the feature level, deliberately distorting MFCCs. This distortion, incorporated within a cancelable framework, serves to obscure speaker identities, rendering the system resilient to potential intruders. Three systems are presented in this work; a reverberation-affected speaker identification system, a system depending on cancelable features through comb filtering, and a novel cancelable speaker identification system within reverbration environments. The findings revealed that, in both scenarios with and without reverberation effects, the DWT-based features exhibited superior performance within the speaker identification system. Conversely, within the cancelable speaker identification system, the DCT-based features represent the top-performing choice.</div