Scoping review of adherence promotion theories in pelvic floor muscle training : 2011 ics state-of-the-science seminar research paper I of IV

Aims This paper, the first of four emanating from the International Continence Society's 2011 State-of-the-Science Seminar on pelvic-floor-muscle training (PFMT) adherence, aimed to summarize the literature on theoretical models to promote PFMT adherence, as identified in the research, or suggested by the seminar's expert panel, and recommends future directions for clinical practice and research. Methods Existing literature on theories of health behavior were identified through a conventional subject search of electronic databases, reference-list checking, and input from the expert panel. A core eligibility criterion was that the study included a theoretical model to underpin adherence strategies used in an intervention to promote PFM training/exercise. Results A brief critique of 12 theoretical models/theories is provided and, were appropriate, their use in PFMT adherence strategies identified or examples of possible uses in future studies outlined. Conclusion A better theoretical-based understanding of interventions to promote PFMT adherence through changes in health behaviors is required. The results of this scoping review and expert opinions identified several promising models. Future research should explicitly map the theories behind interventions that are thought to improve adherence in various populations (e.g., perinatal women to prevent or lessen urinary incontinence). In addition, identified behavioral theories applied to PFMT require a process whereby their impact can be evaluated.

Health professionals’ and patients’ perspectives on pelvic floor muscle training adherence : 2011 ICS State-of-the-Science Seminar research paper IV of IV

Aims There is scant information on pelvic floor muscle training (PFMT) adherence barriers and facilitators. A web-based survey was conducted (1) to investigate whether responses from health professionals and the public broadly reflected findings in the literature, (2) if responses differed between the two groups, and (3) to identify new research directions. Methods Health professional and public surveys were posted on the ICS website. PFMT adherence barriers and facilitators were divided into four categories: physical/condition, patient, therapy, and social-economic. Responses were analyzed using descriptive statistics from quantitative data and thematic data analysis for qualitative data. Results Five hundred and fifteen health professionals and 51 public respondents participated. Both cohorts felt “patient-related factors” constituted the most important adherence barrier, but differed in their rankings of short- and long-term barriers. Health professionals rated “patient-related” and the public “therapy-related” factors as the most important adherence facilitator. Both ranked “perception of PFMT benefit” as the most important long-term facilitator. Contrary to published findings, symptom severity was not ranked highly. Neither cohort felt the barriers nor facilitators differed according to PFM condition (urinary/faecal incontinence, pelvic organ prolapse, pelvic pain); however, a large number of health professionals felt differences existed across age, gender, and ethnicity. Half of respondents in both cohorts felt research barriers and facilitators differed from those in clinical practice. Conclusions An emphasis on “patient-related” factors, ahead of “condition-specific” and “therapy-related,” affecting PFMT adherence barriers was evident. Health professionals need to be aware of the importance of long-term patient perception of PFMT benefits and consider enabling strategies.

School-based first aid training and the implications for traffic injury prevention : a randomised controlled trial

Adolescent injury remains a significant public health concern and is often the result of at-risk transport related behaviours. When a person is injured actions taken by bystanders are of crucial importance and timely first aid appears to reduce the severity of some injuries (Hussain & Redmond, 1994). Accordingly, researchers have suggested that first aid training should be more widely available as a potential strategy to reduce injury (Lynch et al., 2006). Further research has identified schools as an ideal setting for learning first aid skills as a means of injury prevention (Maitra, 1997). The current research examines the implications of school based first aid training for young adolescents on injury prevention, particularly relating to transport injuries. First aid training was integrated with peer protection and school connectedness within the Skills for Preventing Injury in Youth (SPIY) program (Buckley & Sheehan, 2009) and evaluated to determine if there was a reduction in the likelihood of transport related injuries at six months post-intervention. In Queensland, Australia, 35 high schools were recruited and randomly assigned to intervention and control conditions in early April 2012. A total of 2,000 Year nine students (mean age 13.5 years, 39% male) completed surveys six months post-intervention in November 2012. Analyses will compare the intervention students with control group students who self-reported i) first aid training with a teacher, professional or other adult and ii) no first aid in the preceding six months. Using the Extended Adolescent Injury Checklist (E-AIC) (Chapman, Buckley & Sheehan, 2011) the transport related injury experiences included being injured while “riding as a passenger in a car”, “driving a car off road” and “riding a bicycle”. It is expected that students taught first aid within SPIY will report significantly fewer transport related injuries in the previous three months, compared to the control groups described above. Analyses will be conducted separately for sex and socio-economic class of schools. Findings from this study will provide insight into the value of first aid in adolescent injury prevention and provide evidence as to whether teaching first aid skills within a school based health education curriculum has traffic safety implications.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

Mindfulness-meditation on the move : implementation of an ACT-based mindfulness practice intervention and training within a University Dance program

As part of the introduction of a broader dance medicine and science related health and wellbeing program, a 9 week mindfulness-meditation ACT-based program was delivered to all students undertaking full-time University dance training (N = 106). The aim of the program was to assist students in the further development of performance psychology skills that could be applied in both performance and non-performance settings. Participant groups were comprised of both male (N = 12) and female (N = 94) students from across all three year levels of two undergraduate dance courses, divided into three groups by mixed year levels due to timetable scheduling requirements. Pre- and post-testing was undertaken utilising the Mindful Attention Awareness Scale (MAAS-15), a uni-dimensional measure of mindfulness, in addition to qualitative questions checking the current level of awareness and understanding of mindfulness practice and its application. Weekly sessions were conducted by qualified sport and exercise psychologists and covered key practices such as: Mindfulness of Body, Mindfulness of Breathing, Mindfulness of Sounds, ACT-based and general Imagery exercises, Developing Open Awareness, Mindfulness of Emotions, and Developing Inner Stillness. Students were required to maintain a reflective journal that was utilised at the end of each weekly session, in addition to completion of a mid-Semester reflective debrief. Teaching staff additionally attended the weekly sessions and linked the mindfulness practice learnings into the student’s practical dance and academic classes where appropriate. Anecdotal feedback indicates that participation in the mindfulness-meditation sessions and the development of these mental skills has resulted in positive performance and personal outcomes. Observations collated from staff and students, results from the data collection phases and recommendations regarding future applications within dance training settings will be discussed within the presentation.

The protective mechanisms of first aid training within a school-based program for early adolescents

This thesis was concerned with the protective mechanisms of first aid training in the context of peer support. Using a randomised control trial design the current program of research explores first aid training in the school setting and identifies the key components of effective school-based first aid training programs. In particular, examining whether first aid training and associated knowledge could be protective for early adolescents. This broader framing considered whether first aid impacted on increasing behaviour and attitudes towards helping an injured friend, and reducing personal risk taking and related injury.

Functional Imagery Training to reduce snacking: Testing a novel motivational intervention based on Elaborated Intrusion theory

Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

A Training-Based Iterative Detection/Channel Estimation Scheme for Large Non-Orthogonal STBC MIMO Systems

In this paper, we propose a training-based channel estimation scheme for large non-orthogonal space-time block coded (STBC) MIMO systems.The proposed scheme employs a block transmission strategy where an N-t x N-t pilot matrix is sent (for training purposes) followed by several N-t x N-t square data STBC matrices, where Nt is the number of transmit antennas. At the receiver, we iterate between channel estimation (using an MMSE estimator) and detection (using a low-complexity likelihood ascent search (LAS) detector) till convergence or for a fixed number of iterations. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed scheme at low complexities. The fact that we could show such good results for large STBCs (e.g., 16 x 16 STBC from cyclic division algebras) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot-based channel estimation and turbo coding) establishes the effectiveness of the proposed scheme.

On the improvement of diversity-multiplexing gain tradeoff in a training based TDD-simo system

This paper investigates the diversity-multiplexing gain tradeoff (DMT) of a time-division duplex (TDD) single-input multiple-output (SIMO) system with perfect channel state information (CSI) at the receiver (CSIR) and partial CSI at the transmitter (CSIT). The partial CSIT is acquired through a training sequence from the receiver to the transmitter. The training sequence is chosen in an intelligent manner based on the CSIR, to reduce the training length by a factor of r, the number of receive antennas. We show that, for the proposed training scheme and a given channel coherence time, the diversity order increases linearly with r for nonzero multiplexing gain. This is a significant improvement over conventional orthogonal training schemes.

A neural network based power system stabilizer suitable for on-line training-a practical case study for EGAT system

This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS

Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.