Development of a tool for palliative care needs assessment and intervention: mixed methods research at a Swiss tertiary oncology clinic.

BACKGROUND Palliative care interventions improve quality-of-life for advanced cancer patients and their caregivers. The frequency and quality of service provision could be improved by a clinical tool that helps oncology professionals to assess unmet needs for palliative care interventions and to structure the interventions delivered. This paper aims to answer the following research question: what do oncology professionals and cancer patients view as important elements in a clinical tool for assessing unmet palliative care needs? Based on the feedback from professionals and patients, we developed and refined an intervention-focused clinical tool for use in cancer care. METHODS This study used a prospective convergent mixed methods design and was carried out at a single tertiary hospital in Switzerland. Healthcare professionals participated in focus groups (n=29) and a Delphi survey (n=73). Patients receiving palliative care were interviewed (n=17). Purposive sampling was used to achieve maximal variation in participant response. Inductive content analysis and descriptive statistics were used to analyze focus group discussions, open-ended survey questions and interview data. Descriptive statistics were used for analyzing quantitative survey items and interviewee characteristics. RESULTS Focus groups and Delphi surveys showed that seven key palliative care interventions were important to oncology professionals. They also valued a tool that could be used by doctors, nurses, or other professionals. Participants did not agree about the best timepoint for assessment. Two versions of a pilot clinical tool were tested in patient interviews. Interviews highlighted the divergent patient needs that must be accommodated in clinical practice. Patients provided confirmation that a clinical tool would be helpful to them. CONCLUSIONS This paper reports on research carried out to understand what elements are most important in a tool that helps oncology professionals to identify patients' unmet needs and provide tailored palliative care interventions. This study demonstrated that professionals and patients alike are interested in a clinical tool. Responses from oncology healthcare professionals helped to identify relevant palliative care interventions, and patients provided constructive input used in designing a tool for use in clinical interactions

Development of a tool for palliative care needs assessment and intervention: mixed methods research at a Swiss tertiary oncology clinic

BACKGROUND Palliative care interventions improve quality-of-life for advanced cancer patients and their caregivers. The frequency and quality of service provision could be improved by a clinical tool that helps oncology professionals to assess unmet needs for palliative care interventions and to structure the interventions delivered. This paper aims to answer the following research question: what do oncology professionals and cancer patients view as important elements in a clinical tool for assessing unmet palliative care needs? Based on the feedback from professionals and patients, we developed and refined an intervention-focused clinical tool for use in cancer care. METHODS This study used a prospective convergent mixed methods design and was carried out at a single tertiary hospital in Switzerland. Healthcare professionals participated in focus groups (n=29) and a Delphi survey (n=73). Patients receiving palliative care were interviewed (n=17). Purposive sampling was used to achieve maximal variation in participant response. Inductive content analysis and descriptive statistics were used to analyze focus group discussions, open-ended survey questions and interview data. Descriptive statistics were used for analyzing quantitative survey items and interviewee characteristics. RESULTS Focus groups and Delphi surveys showed that seven key palliative care interventions were important to oncology professionals. They also valued a tool that could be used by doctors, nurses, or other professionals. Participants did not agree about the best timepoint for assessment. Two versions of a pilot clinical tool were tested in patient interviews. Interviews highlighted the divergent patient needs that must be accommodated in clinical practice. Patients provided confirmation that a clinical tool would be helpful to them. CONCLUSIONS This paper reports on research carried out to understand what elements are most important in a tool that helps oncology professionals to identify patients' unmet needs and provide tailored palliative care interventions. This study demonstrated that professionals and patients alike are interested in a clinical tool. Responses from oncology healthcare professionals helped to identify relevant palliative care interventions, and patients provided constructive input used in designing a tool for use in clinical interactions

Recent advances in modeling and analysis of bioelectric and biomagnetic sources

Determining the centers of electrical activity in the human body and the connectivity between different centers of activity in the brain is an active area of research. To understand brain function and the nature of cardiovascular diseases requires sophisticated methods applicable to non-invasively measured bioelectric and biomagnetic data. As it is difficult to solve for all unknown parameters at once, several strains of data analysis have been developed, each trying to solve a different part of the problem and each requiring a different set of assumptions. Current trends and results from major topics of electro- and magnetoencephalographic data analysis are presented here together with the aim of stimulating research into the unification of the different approaches. The following topics are discussed: source reconstruction using detailed finite element modeling to locate sources deep in cthe brain; connectivity analysis for the quantification of strength and direction of information flow between activity centers, preferably incorporating an inverse solution; the conflict between the statistical independence assumption of sources and a possible connectivity; the verification and validation of results derived from non-invasively measured data through animal studies and phantom measurements. This list already indicates the benefits of a unified view

Modeling the ongoing dynamics of short and long-range temporal correlations in broadband EEG during movement

Electroencephalogram (EEG) undergoes complex temporal and spectral changes during voluntary movement intention. Characterization of such changes has focused mostly on narrowband spectral processes such as Event-Related Desynchronization (ERD) in the sensorimotor rhythms because EEG is mostly considered as emerging from oscillations of the neuronal populations. However, the changes in the temporal dynamics, especially in the broadband arrhythmic EEG have not been investigated for movement intention detection. The Long-Range Temporal Correlations (LRTC) are ubiquitously present in several neuronal processes, typically requiring longer timescales to detect. In this paper, we study the ongoing changes in the dynamics of long- as well as short-range temporal dependencies in the single trial broadband EEG during movement intention. We obtained LRTC in 2 s windows of broadband EEG and modeled it using the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model which allowed simultaneous modeling of short- and long-range temporal correlations. There were significant (p < 0.05) changes in both broadband long- and short-range temporal correlations during movement intention and execution. We discovered that the broadband LRTC and narrowband ERD are complementary processes providing distinct information about movement because eliminating LRTC from the signal did not affect the ERD and conversely, eliminating ERD from the signal did not affect LRTC. Exploring the possibility of applications in Brain Computer Interfaces (BCI), we used hybrid features with combinations of LRTC, ARFIMA, and ERD to detect movement intention. A significantly higher (p < 0.05) classification accuracy of 88.3 ± 4.2% was obtained using the combination of ARFIMA and ERD features together, which also predicted the earliest movement at 1 s before its onset. The ongoing changes in the long- and short-range temporal correlations in broadband EEG contribute to effectively capturing the motor command generation and can be used to detect movement successfully. These temporal dependencies provide different and additional information about the movement

Novel MEMS Sensor for Detecting Magnetic Particles in Liquids

We present a novel MEMS sensor for the detection of magnetic particles in liquids, which consists of a microcantilever excited piezoelectrically in resonance and having an integrated planar coil on its free end. Due to the latter component, magnetic particles are attracted and accumulate on the sensor surface. The additional mass introduced by the particles changes the resonance frequency of the microcantilever serving as measured quantity. To evaluate our design, we dispersed 250 nm iron-oxide particles in de-ionized water and monitored the resonance frequency during particle accumulation. 100 min after measurement start, a total resonance frequency shift of 6 kHz was found, which can easily be measured and shows the high potential of the proposed sensor design

Cross-Linking and Evaluation of the Thermo-Mechanical Behavior of Epoxy Based Poly(ionic Liquid) Thermosets

Poly(ionic liquids) (PILs) and ionenes are polymers containing ionic groups in their repeating units. The unique properties of these polymers render them as interesting candidates for a variety of applications, such as gas separation membranes and polyelectrolytes. Due to the vast number of possible structures, numerous synthesis protocols to produce monomers with different functional groups for task-specific PILs are reported in literature. A difunctional epoxy-IL resin was synthesized and cured with multifunctional amine and anhydride hardeners and the thermal and thermomechanical properties of the networks were assessed via differential scanning calorimetry and dynamic mechanical analysis. By the selection of suitable hardeners, the glass transition onset temperature (Tg,onset) of the resulting networks was varied between 18 °C and 99 °C. Copolymerization of epoxy-IL with diglycidyl ether of bisphenol A (DGEBA) led to a further increase of the Tg,onset. The results demonstrate the potential of epoxy chemistry for tailorable PIL networks, where the hardener takes the place of the ligands without requiring an additional synthesis step and can be chosen from a broad range of commercially available compounds

Cross-Linking and Evaluation of the Thermo-Mechanical Behavior of Epoxy Based Poly(ionic Liquid) Thermosets

Poly(ionic liquids) (PILs) and ionenes are polymers containing ionic groups in their repeating units. The unique properties of these polymers render them as interesting candidates for a variety of applications, such as gas separation membranes and polyelectrolytes. Due to the vast number of possible structures, numerous synthesis protocols to produce monomers with different functional groups for task-specific PILs are reported in literature. A difunctional epoxy-IL resin was synthesized and cured with multifunctional amine and anhydride hardeners and the thermal and thermomechanical properties of the networks were assessed via differential scanning calorimetry and dynamic mechanical analysis. By the selection of suitable hardeners, the glass transition onset temperature (Tg,onset) of the resulting networks was varied between 18 °C and 99 °C. Copolymerization of epoxy-IL with diglycidyl ether of bisphenol A (DGEBA) led to a further increase of the Tg,onset. The results demonstrate the potential of epoxy chemistry for tailorable PIL networks, where the hardener takes the place of the ligands without requiring an additional synthesis step and can be chosen from a broad range of commercially available compounds