School Counseling in West Virginia: An Examination of School Counselors and Implementation of WV Policy 2315

Since the inception of the profession of school counseling there has been confusion and inconsistency about what the appropriate role of the school counselor should be. Beginning in 2002, the State of West Virginia followed a nationwide movement to attempt to clarify the role of the school counselor by implementing Policy 2315, West Virginia\u27s policy on Comprehensive Guidance and Counseling. However, since the creation of the policy, no statewide study has been conducted to determine if West Virginia school counselors are fully implementing the policy which is based on the American School Counselor Association‟s National Model for school counseling programs. This study found that there remains a great deal of inconsistency and confusion regarding the appropriate role and function of the school counselor in West Virginia. Additionally, this study provides a glimpse into the activities that school counselors in the state find important as well as the frequency with which they work with students on the outcomes in the American School Counselor Association‟s National Standards. The results lay the groundwork for improved professional development and improved higher education training for West Virginia school counselors who work every day to improve the lives of the students with whom they come in contact

Neurologic phenotypes associated with COL4A1/2 mutations

Objective: To characterize the neurologic phenotypes associated with COL4A1/2 mutations and to seek genotype–phenotype correlation. Methods: We analyzed clinical, EEG, and neuroimaging data of 44 new and 55 previously reported patients with COL4A1/COL4A2 mutations. Results: Childhood-onset focal seizures, frequently complicated by status epilepticus and resistance to antiepileptic drugs, was the most common phenotype. EEG typically showed focal epileptiform discharges in the context of other abnormalities, including generalized sharp waves or slowing. In 46.4% of new patients with focal seizures, porencephalic cysts on brain MRI colocalized with the area of the focal epileptiform discharges. In patients with porencephalic cysts, brain MRI frequently also showed extensive white matter abnormalities, consistent with the finding of diffuse cerebral disturbance on EEG. Notably, we also identified a subgroup of patients with epilepsy as their main clinical feature, in which brain MRI showed nonspecific findings, in particular periventricular leukoencephalopathy and ventricular asymmetry. Analysis of 15 pedigrees suggested a worsening of the severity of clinical phenotype in succeeding generations, particularly when maternally inherited. Mutations associated with epilepsy were spread across COL4A1 and a clear genotype–phenotype correlation did not emerge. Conclusion: COL4A1/COL4A2 mutations typically cause a severe neurologic condition and a broader spectrum of milder phenotypes, in which epilepsy is the predominant feature. Early identification of patients carrying COL4A1/COL4A2 mutations may have important clinical consequences, while for research efforts, omission from large-scale epilepsy sequencing studies of individuals with abnormalities on brain MRI may generate misleading estimates of the genetic contribution to the epilepsies overall

Group Counseling : Strategies and Skills

xvi, 480 p.; ill.; 23 cm

Certification of Reference Materials for Detection of the Human Prothrombin Gene G20210A Sequence Variant

There is a need for reference materials in the field of genetic testing for verification of tests results obtained in patients and probands. New types of certified reference materials (CRMs) for genetic testing of the human prothrombin gene G20210A mutation are available. Homogeneity, stability and fitness for the purpose of the plasmids could be demonstrated and no evidence was found that they would not work with other methods as long as these are targeting the whole or parts of the prothrombin gene fragment inserted into the plasmids. The described CRMs support the efforts of the international community in development, validation and harmonisation of tests for molecular genetic testingJRC.D.2-Reference material

Distinct Worst Pain Profiles in Oncology Outpatients Undergoing Chemotherapy

BackgroundWhile pain is a significant problem for oncology patients, little is known about interindividual variability in pain characteristics.ObjectiveThe aims of this study were to identify subgroups of patients with distinct worst pain severity profiles and evaluate for differences among these subgroups in demographic, clinical, and pain characteristics and stress and symptom scores.MethodsPatients (n = 934) completed questionnaires 6 times over 2 chemotherapy cycles. Worst pain intensity was assessed using a 0- to 10-point numeric rating scale. Brief Pain Inventory was used to assess various pain characteristics. Latent profile analysis was used to identify subgroups of patients with distinct pain profiles.ResultsThree worst pain profiles were identified (low [17.5%], moderate [39.9%], severe [42.6%]). Compared with the other 2 classes, severe class was more likely to be single and unemployed and had a lower annual household income, a higher body mass index, a higher level of comorbidity, and a poorer functional status. Severe class was more likely to have both cancer and noncancer pain, a higher number of pain locations, higher frequency and duration of pain, worse pain quality scores, and higher pain interference scores. Compared with the other 2 classes, severe class reported lower satisfaction with pain management and higher global, disease-specific, and cumulative life stress, as well as higher anxiety, depression, fatigue, sleep disturbance, and cognitive dysfunction scores.ConclusionsUnrelieved pain is a significant problem for more than 80% of outpatients.Implications for practiceClinicians need to perform comprehensive pain assessments; prescribe pharmacologic and nonpharmacologic interventions; and initiate referrals for pain management and psychological services

Sleep disturbance is associated with perturbations in immune-inflammatory pathways in oncology outpatients undergoing chemotherapy

Objective/backgroundSleep disturbance is a common problem in patients receiving chemotherapy. Purpose was to evaluate for perturbations in immune-inflammatory pathways between oncology patients with low versus very high levels of sleep disturbance.Patients/methodsSleep disturbance was evaluated using the General Sleep Disturbance Scale six times over two cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct sleep disturbance profiles. Pathway impact analyses were performed in two independent samples using gene expression data obtained from RNA sequencing (n = 198) and microarray (n = 162) technologies. Fisher's combined probability test was used to identify significantly perturbed pathways between Low versus Very High sleep disturbance classes.ResultsIn the RNA sequencing and microarray samples, 59.1% and 51.9% of patients were in the Very High sleep disturbance class, respectively. Thirteen perturbed pathways were related to immune-inflammatory mechanisms (i.e., endocytosis, phagosome, antigen processing and presentation, natural killer cell mediated cytotoxicity, cytokine-cytokine receptor interaction, apoptosis, neutrophil extracellular trap formation, nucleotide-binding and oligomerization domain-like receptor signaling, Th17 cell differentiation, intestinal immune network for immunoglobulin A production, T-cell receptor signaling, complement and coagulation cascades, and tumor necrosis factor signaling).ConclusionsFirst study to identify perturbations in immune-inflammatory pathways associated with very high levels of sleep disturbance in oncology outpatients. Findings suggest that complex immune-inflammatory interactions underlie sleep disturbance

Oncology Outpatients With Worse Anxiety and Sleep Disturbance Profiles Are at Increased Risk for a Higher Symptom Burden and Poorer Quality of Life

BackgroundAnxiety and sleep disturbance are frequent symptoms during chemotherapy.ObjectivesPurposes were to identify subgroups of oncology outpatients with distinct joint anxiety and sleep disturbance profiles, as well as evaluate for differences in demographic and clinical characteristics, sleep disturbance characteristics, severity of common symptoms, and quality-of-life outcomes among these subgroups.MethodsOncology outpatients (n = 1331) completed self-report measures of anxiety and sleep disturbance 6 times over 2 chemotherapy cycles. Latent profile analysis was done to identify subgroups of patients with distinct joint anxiety and sleep disturbance profiles.ResultsThree profiles were identified (ie, no anxiety and low sleep disturbance (59.7%), moderate anxiety and high sleep disturbance (32.5%), high anxiety and very high sleep disturbance (7.8%)). Compared with the no anxiety and low sleep disturbance class, the other 2 classes were younger; less likely to be married; had a lower annual household income; and had childcare responsibilities. Patients in the 2 worse profiles had problems with both sleep initiation and maintenance. These patients reported higher levels of depressive symptoms, trait and state anxiety, and evening fatigue, as well as lower levels of morning and evening energy, cognitive function, and poorer quality of life.ConclusionsMore than 40% of patients had moderate or high levels of anxiety and high or very high levels of sleep disturbance. Modifiable risk factors associated with these profiles may be used to develop targeted interventions for 1 or both symptoms.Implications for practiceClinicians need to assess for the co-occurrence of anxiety and sleep disturbance

Figure 5

Figure 5. Family pedigrees from published cases. Fig.5a. COL4A2 c. 2399 G>A; p. G800E. Ref. Ha et al., 2016. Fig.5b. COL4A2 c. 3455 G>A; p. G1152D. Ref. Yoneda et al., 2012. Fig.5c. COL4A1 c. 1249G>C; p.G417R. Ref. Giorgio et al., 2015. Fig.5d. COL4A1 c.3796G>C; p.G1266R. Ref. Shah et al., 2012. Fig.5e: COL4A1 c.2662G>C; p.G888R. Ref. Giorgio et al., 2015. Fig.5f: COL4A1 p.G562E. Ref. Vahedi et al., 2003 and Vahedi et al., 2007. Fig.5g.: COL4A1 p. G749S. Ref. Gasparini et al., 2006. Fig.5h: COL4A1 c.3389G>A; p.G1130D. Ref. Breedved et al. 2006 Fig.5i: COL4A1 c.2159G>A. Ref. Tonduti et al., 2012. Fig.5j: COL4A1 c.3715G>A; p.G1239R. Ref. Takenouchi et al., 2015. Fig.5k: COL4A1 c. 2645G>A. Ref. Shah et al., 2012. Fig.5l: COL4A1 c.1973 G>A. Ref. Livingston et al., 2011. Fig.5m: COL4A1 c.4031G>C; p.G1344A. Ref. Leung et al., 2012. Fig.5n: COL4A2 c.3455G>A; p.G1152D. Ref. Yoneda et al., 2012. Fig.5o: COL4A1 c.2085del; p. G696fs. Ref. Lemmens et al., 2013. wt/m: wild-type/mutated