Help needed in medication self-management for people with visual impairment: case-control study

Background: Visual impairment (VI) is rising in prevalence and contributing to increasing morbidity, particularly among older people. Understanding patients' problems is fundamental to achieving optimal health outcomes but little is known about how VI impacts on self-management of medication.

Aim: To compare issues relating to medication self-management between older people with and without VI.

Design and setting: Case-control study with participants aged =65 years, prescribed at least two long-term oral medications daily, living within the community.

Method: The study recruited 156 patients with VI (best corrected visual acuity [BCVA] 6/18 to 3/60) at low-vision clinics; community optometrists identified 158 controls (BCVA 6/9 or better). Researchers visited participants in their homes, administered two validated questionnaires to assess medication adherence (Morisky; Medication Adherence Report Scale [MARS]), and asked questions about medication self-management, beliefs, and support.

Results: Approximately half of the participants in both groups reported perfect adherence on both questionnaires (52.5% Morisky; 43.3%, MARS). Despite using optical aids, few (3%) with VI could read medication information clearly; 24% had difficulty distinguishing different tablets. More people with VI (29%) than controls (13%) (odds ratio [OR] = 2.8; 95% confidence interval [CI] = 1.6 to 5.0) needed help managing their medication, from friends (19% versus 10%) or pharmacists (10% versus 2.5%; OR = 4.4, 95% CI = 1.4 to 13.5); more received social service support (OR = 7.1; 95% CI = 3.9 to 12.9).

Conclusion: Compared to their peers without VI, older people with VI are more than twice as likely to need help in managing medication. In clinical practice in primary care, patients' needs for practical support in taking prescribed treatment must be recognised. Strategies for effective medication self-management should be explored.

A review of behaviour change theories and techniques used in group based self-management programmes for chronic low back pain and arthritis

Background: Medical Research Council (MRC) guidelines recommend applying theory within complex interventions to explain how behaviour change occurs. Guidelines endorse self-management of chronic low back pain (CLBP) and osteoarthritis (OA), but evidence for its effectiveness is weak. Objective: This literature review aimed to determine the use of behaviour change theory and techniques within randomised controlled trials of group-based self-management programmes for chronic musculoskeletal pain, specifically CLBP and OA. Methods: A two-phase search strategy of electronic databases was used to identify systematic reviews and studies relevant to this area. Articles were coded for their use of behaviour change theory, and the number of behaviour change techniques (BCTs) was identified using a 93-item taxonomy, Taxonomy (v1). Results: 25 articles of 22 studies met the inclusion criteria, of which only three reported having based their intervention on theory, and all used Social Cognitive Theory. A total of 33 BCTs were coded across all articles with the most commonly identified techniques being '. instruction on how to perform the behaviour', '. demonstration of the behaviour', '. behavioural practice', '. credible source', '. graded tasks' and '. body changes'. Conclusion: Results demonstrate that theoretically driven research within group based self-management programmes for chronic musculoskeletal pain is lacking, or is poorly reported. Future research that follows recommended guidelines regarding the use of theory in study design and reporting is warranted.

Reading for Academic Purposes: Techniques and Strategies to help Angolan ELT Students at ISCED-Benguela enhance their Reading Skills

This paper examines academic reading difficulties Angolan second year ELT students have at ISCED (Instituto Superior de Ciências da Educação) in Benguela and focuses on a variety of reading strategies and techniques as well as models for reading materials to help improve academic reading skills. Finally, it recommends the use of appropriate reading strategies and techniques, materials, and the adoption of a more student-centred approach in teaching reading to encourage the development of a reading culture for academic purposes.

Emotional intelligence and enterprise handbook : tools and techniques to help students succeed in life and work.

Manual diseñado para que profesores de enseñanza secundaria ayuden y apoyen el desarrollo de la inteligencia emocional, que abarca la conciencia y la responsabilidad, la actitud positiva y apreciativa, la empatía y el respeto, la motivación y la persistencia. Las actividades para nueve sesiones desarrollan la inteligencia con respecto a uno mismo, otras personas, el empleo y el futuro.

Filtering techniques in self-tuning

In the last few years a state-space formulation has been introduced into self-tuning control. This has not only allowed for a wider choice of possible control actions, but has also provided an insight into the theory underlying—and hidden by—that used in the polynomial description. This paper considers many of the self-tuning algorithms, both state-space and polynomial, presently in use, and by starting from first principles develops the observers which are, effectively, used in each case. At any specific time instant the state estimator can be regarded as taking one of two forms. In the first case the most recently available output measurement is excluded, and here an optimal and conditionally stable observer is obtained. In the second case the present output signal is included, and here it is shown that although the observer is once again conditionally stable, it is no longer optimal. This result is of significance, as many of the popular self-tuning controllers lie in the second, rather than first, category.

Cursor relocation techniques to help older adults find 'lost' cursors

Older adult computer users often lose track of the mouse cursor and so resort to methods such as mouse shaking or searching the screen to find the cursor again. Hence, this paper describes how a standard optical mouse was modified to include a touch sensor, activated by releasing and touching the mouse, which automatically centers the mouse cursor to the screen, potentially making it easier to find a 'lost' cursor. Six older adult computer users and six younger computer users were asked to compare the touch sensitive mouse with cursor centering with two alternative techniques for locating the mouse cursor: manually shaking the mouse and using the Windows sonar facility. The time taken to click on a target following a distractor task was recorded, and results show that centering the mouse was the fastest to use, with a 35% improvement over shaking the mouse. Five out of six older participants ranked the touch sensitive mouse with cursor centering as the easiest to use.

Cursor relocation techniques to help older adults find ‘lost’ cursors

Older adult computer users often lose track of the mouse cursor and so resort to methods such as shaking the mouse or searching the entire screen to find the cursor again. Hence, this paper describes how a standard optical mouse was modified to include a touch sensor, activated by releasing and touching the mouse, which automatically centers the mouse cursor to the screen, potentially making it easier to find a ‘lost’ cursor. Six older adult computer users and six younger computer users were asked to compare the touch sensitive mouse with cursor centering with two alternative techniques for locating the mouse cursor: manually shaking the mouse and using the Windows sonar facility. The time taken to click on a target after a distractor task was recorded, and results show that centering the mouse was the fastest to use, with a 35% improvement over shaking the mouse. Five out of six older participants ranked the touch sensitive mouse with cursor centering as the easiest to use.

Self-reported attenuated psychotic-like experiences in help-seeking adolescents and their association with age, functioning and psychopathology

OBJECTIVE Self-rated attenuated psychotic-like experiences (APLEs) are increasingly used to screen for ultra-high-risk (UHR) across all ages. However, self-rated psychotic-like experiences (PLEs), in particular perception-related ones, were more frequent in children and adolescents, in which they possessed less clinical significance. We therefore explored the prevalence of different factors of APLEs in help-seeking adolescents, and their relationship with age, functioning and psychopathology METHOD As a part of the "Liberiamo il Futuro" project, help-seeking adolescents (N=171; 11-18years, 53% male) were screened with the 92-item Prodromal Questionnaire (PQ-92). A factor analysis was performed on the PQ-92 positive items (i.e., APLEs) to identify different APLE-factors. These were assessed for their association with age, functioning and psychopathology using regression analyses. RESULTS APLEs were very common in help-seeking adolescents, and formed four factors: "Conceptual Disorganization and Suspiciousness", "Perceptual Abnormalities", "Bizarre Experiences", and "Magical Ideation". Associations with age and functioning but not psychopathology were found for "Perceptual Abnormalities" that was significantly more severe in 11-12-year-olds, while "Conceptual Disorganization and Suspiciousness" was significantly related to psychopathology. CONCLUSION In line with findings on PLEs, prevalence and clinical significance of APLEs, especially perception-related ones, might depend on age and thus neurodevelopmental stage, and may fall within the normal spectrum of experience during childhood. This should be considered when screening for UHR status in younger age groups

Understanding treatment-related symptoms, symptom management techniques, and symptom management self-efficacy in a sample of non-muscle invasive bladder cancer patients

The current literature available on bladder cancer symptom management from the perspective of the patients themselves is limited. There is also limited psychosocial research specific to bladder cancer patients and no previous studies have developed and validated measures for bladder cancer patients’ symptom management self-efficacy. The purpose of this study was to investigate non-muscle invasive bladder cancer patients’ health related quality of life through two main study objectives: (1) to describe the treatment related symptoms, reported effectiveness of symptom-management techniques, and the advice a sample of non-muscle invasive bladder cancer patients would convey to physicians and future patients; and (2) to evaluate Lepore’s symptom management self-efficacy measure on a sample of non-muscle invasive bladder cancer patients. Methods. A total of twelve (n=12) non-muscle invasive bladder cancer patients participated in an in-depth interview and a sample of 46 (n=4) non-muscle invasive bladder cancer patients participated in the symptom-management self-efficacy survey. Results. A total of five symptom categories emerged for the participants’ 59 reported symptoms. Four symptom management categories emerged out of the 71 reported techniques. A total of 62% of the participants’ treatment related symptom-management techniques were reported as effective in managing their treatment-related symptoms. Five advice categories emerged out of the in-depth interviews: service delivery; medical advice; physician-patient communication; encouragement; and no advice. An exploratory factor analysis indicated a single-factor structure for the total population and a multiple factor structure for three subgroups: all males, married males, and all married participants. Conclusion. These findings can inform physicians and patients of effective symptom-management techniques thus improving patients’ health-related quality of life. The advice these patients’ impart can improve service-delivery and patient education.^

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.