Multiple family groups for adult cancer survivors and their families: a 1-day workshop model

With marked advances in early detection and aggressive multimodality treatment, many adult cancers are now associated with good prognoses for disease-free survival. A burgeoning literature examining posttreatment quality-of-life issues has highlighted the numerous challenges experienced by patients and families in the aftermath of cancer treatment, further underscoring a need for new family-based psychosocial support interventions for cancer survivors and their families. This paper describes the clinical protocol for one such intervention, a 1-day "workshop" version of a multiple family group (MFG) for head and neck cancer survivors and their families. Data are reported from our experiences in running five 1-day workshops. Families uniformly reported that they were highly satisfied with their MFG participation, leading us to conclude that the abbreviated 1-day MFG model we are advocating is a promising family-focused support intervention for cancer survivors and their families.     

Crossed-categorization, evaluation, and face recognition

We investigated the relationship between evaluative intergroup bias and biased errors in intergroup face recognition after crossed-categorization (the combination of two social categories in defining a target of perception). Although evaluative bias and recognition bias often operate in parallel, we draw on two previously unconnected literatures to predict a divergence between these two processes after crossed-categorization. We tested this hypothesis by assessing participants’ evaluations of and recognition of targets who shared two ingroups with participants, targets who shared only one ingroup with participants, and targets who shared neither ingroup. Consistent with predictions, targets’ shared and unshared group memberships combined additively to affect evaluation, but targets who shared two ingroup memberships were better recognized than all other category combinations. These results document the relationship between evaluative bias and recognition bias after crossed-categorization and indicate that crossed-categorization affects evaluative bias and recognition bias in different ways.     

Seven-month-olds detect ordinal numerical relationships within temporal sequences

Previous evidence has shown that 11-month-olds represent ordinal relations between purely numerical values, whereas younger infants require a confluence of numerical and non-numerical cues. In this study, we show that when multiple featural cues (i.e., color and shape) are provided, 7-month-olds detect reversals in the ordinal direction of numerical sequences relying solely on number when non-numerical quantitative cues are controlled. These results provide evidence for the influence of featural information and multiple cue integration on infants’ proneness to detect ordinal numerical information.     

A Longitudinal Study of Coping Strategies and Quality of Life Among People with Multiple Sclerosis

The current study was designed to examine the role of coping strategies on quality of life (QOL) of people with multiple sclerosis (MS) over a period of 12 months. Respondents were 321 people with MS and 239 people from the general population who completed measures of QOL on two occasions, 12 months apart. People with MS also completed measures of how they coped with their illness. The results demonstrated that people with MS experienced lower levels of QOL at both points in time. For people with MS, QOL domains strongly predicted other QOL domains at both time 1 and time 2. The coping strategies of social support, focusing on the positive and wishful thinking were consistent predictors of physical QOL, psychological QOL, social QOL and environmental QOL. These findings indicate that coping strategies play an important role in predicting the QOL of people with MS.     

Alternative Multiple Imputation Inference for Categorical Structural Equation Modeling

The use of item responses from questionnaire data is ubiquitous in social science research. One side effect of using such data is that researchers must often account for item level missingness. Multiple imputation is one of the most widely used missing data handling techniques. The traditional multiple imputation approach in structural equation modeling has a number of limitations. Motivated by Lee and Cai’s approach, we propose an alternative method for conducting statistical inference from multiple imputation in categorical structural equation modeling. We examine the performance of our proposed method via a simulation study and illustrate it with one empirical data set.     

Altered visual and somatosensory feedback affects gait stability in persons with multiple sclerosis

Persons with multiple sclerosis (PwMS) often report problems due to sensory loss and have an inability to appropriately reweight sensory information. Both of these issues can affect individual’s ability to maintain stability when walking under challenging conditions. The purpose of the current study was to determine how gait stability is adapted when walking under challenging sensory conditions where vision and somatosensation at the feet is manipulated. 25 healthy adults and 40 PwMS (15 fallers, 25 non-fallers) walked on a treadmill at their preferred normal walking speed under 3 conditions: normal walking, altered vision using goggles that shifted visual field laterally, and altered somatosensation using shoes with compliant foam soles. Inertial measurement united recorded acceleration at the lumbar and right ankle, and acceleration variability measures were calculated including root mean square (RMS), range, sample entropy (SaEn), and Lyapunov exponents (LyE). A gait stability index (GSI) was calculated using each of the four variability measures as the ratio of lumbar acceleration variability divided by foot acceleration variability in the frontal and sagittal planes. The sagittal and frontal GSI_RMS were larger in the somatosensory condition compared to the normal and visual conditions (p < 0.001). The frontal GSI_SaEn was greater in the visual condition compared to the somatosensory condition (p = 0.021). The frontal and sagittal GSI_LyE was greater in the somatosensory condition compared to the normal and visual conditions (p < 0.002). The current study showed that HC, MS non-fallers and MS fallers largely adapted to altered sensory feedback during walking in a similar manner. However, MS faller subjects may be more reliant on visual feedback compared to MS non-fallers and HC subjects.     

Multiple causal pathways in attention-deficit/hyperactivity disorder – Do emerging executive and motivational deviations precede symptom development?

The multiple causal pathways model on the etiology of attention-deficit/hyperactivity disorder (ADHD) is well established. However, developmental implications of the model are not yet sufficiently analyzed. The model implies that critical neural and neuropsychological deviations from normative development precede secondarily developing ADHD symptoms. Cognitive, “cool” inhibitory control (CIC) and reward-related, “hot” functions (RRF) are regarded as neuropsychological basic deficits that indicate independent causal pathways. Both functions involve top-down control networks that undergo major normative developmental changes in the preschool period. We formalized the following assumptions in a path model: (a) CIC and RRF predict change in ADHD symptoms in the preschool period, (b) the reverse is not true, and (c) CIC and RRF independently contribute to this prediction. A community-based sample of 125 (71 boys) preschoolers was assessed at at age 4 and 5 years. At each assessment wave, CIC and RRF were measured by a battery of age-appropriate valid tasks. ADHD symptoms were measured by a clinical parent interview. Evaluation of model fit using manifest maximum likelihood parameter estimation clearly supported the hypothesized path model while controlling for gender of child and maternal education level. Thus, regarding the basic deficits of CIC and RRF, the results add evidence on the developmental implications of the multiple causal pathways model. Our findings point to the potential significance of these early emerging characteristics as indicators of risk and as targets for preventive interventions.     

Semantic segmentation via highly fused convolutional network with multiple soft cost functions

Semantic image segmentation is one of the most challenging tasks in computer vision. In this paper, we propose a highly fused convolutional network, which consists of three parts: downsampling, fused upsampling and multiple predictions. We adopt a VGG-net based downsampling structure, followed by multiple steps of upsampling. Feature maps in each pair of corresponding pooling layers and unpooling layers are combined. We also bring out multiple pre-outputs, each is generated from an unpooling layer by a one-step upsampling operation. Finally, we concatenate these pre-outputs to get the final output. As a result, our proposed network makes high use of the feature information by fusing and reusing features in low layers. In addition, when training our model, we add multiple soft cost functions on pre-outputs and the final output. In this way, we can reduce the loss reduction in backpropagation. We evaluate our model on three public segmentation datasets: CamVid, PASCAL VOC, and ADE20K. We achieve considerable segmentation performance on PASCAL VOC dataset and ADE20K dataset. Especially on CamVid dataset, we achieve state-of-the-art performance.     

Modeling behavioral recovery following lesion induction in the rat dentate gyrus

Unilateral entorhinal lesions have enjoyed immense popularity as a model of recovery from damage. In part, the popularity has been supported the laminar organization of the hippocampal formation, which allows for the dissection of the contribution of individual afferent pathways to the recovery process. The commissural/associational pathway is of particular interest, since electrophysiological and gross anatomical data, although limited, have correlated sprouting in this pathway with behavioral recovery. Unfortunately, information relating recovery to synaptic structure is lacking. Addressing this issue, two analyses were conducted. Initially, a quantitative review of the literature reporting behavioral recovery following this type of lesion was conducted using meta-analytic techniques. Using this detailed information across decades of research, multiple linear regression analysis was conducted to address whether the morphological correlates of recovery could predict behavioral recovery. This resulted in an equation relating morphology and recovery that stood up well to several diagnostic tests. Moreover, this model suggests that synapse structure (in particular, synapse size and curvature, as well as terminal compartmentalization and the density of multi-synaptic terminals) holds a greater potential to predict behavioral recovery than increases in synapse number, which is typically seen as the optimal anatomical measure of recovery. This initial attempt to identify, quantify, and validate a model of lesion recovery is an important initial step in understanding how synaptic morphology may help mediate recovery of function.