Adolescent Drug Abuse Diagnosis (ADAD) vs. Health of Nation Outcome Scale for Children and Adolescents (HoNOSCA) in clinical outcome measurement.

BACKGROUND: The Adolescent Drug Abuse Diagnosis (ADAD) and Health of Nation Outcome Scales for Children and Adolescents (HoNOSCA) are both measures of outcome for adolescent mental health services. AIMS: To compare the ADAD with HoNOSCA; to examine their clinical usefulness. METHODS: Comparison of the ADAD and HoNOSCA outcome measures of 20 adolescents attending a psychiatric day care unit. RESULTS: ADAD change was positively correlated with HoNOSCA change. HoNOSCA assesses the clinic's day-care programme more positively than the ADAD. The ADAD detects a group for which the mean score remains unchanged whereas HoNOSCA does not. CONCLUSIONS: A good convergent validity emerges between the two assessment tools. The ADAD allows an evidence-based assessment and generally enables a better subject discrimination than HoNOSCA. HoNOSCA gives a less refined evaluation but is more economic in time and possibly more sensitive to change. Both assessment tools give useful information and enabled the Day-care Unit for Adolescents to rethink the process of care and of outcome, which benefited both the institution and the patients.

Quantitative Ultrasound of the Heel and Fracture Risk Assessment: an Updated Meta-Analysis

Objectives: Quantitative ultrasound (QUS) is an attractive method for assessing fracture risk because it is portable, inexpensive, without ionizing radiation, and available in areas of the world where DXA is not readily accessible or affordable. However, the diversity of QUS scanners and variability of fracture outcomes measured in different studies is an important obstacle to widespread utilisation of QUS for fracture risk assessment. We aimed in this review to assess the predictive power of heel QUS for fractures considering different characteristics of the association (QUS parameters and fracture outcomes measured, QUS devices, study populations, and independence from DXA-measured bone density).Materials/Methods : We conducted an inverse-variance randomeffects meta-analysis of prospective studies with heel QUS measures at baseline and fracture outcomes in their follow-up. Relative risks (RR) per standard deviation (SD) of different QUS parameters (broadband ultrasound attenuation [BUA], speed of sound &SOS;, stiffness index &SI;, and quantitative ultrasound index [QUI]) for various fracture outcomes (hip, vertebral, any clinical, any osteoporotic, and major osteoporotic fractures) were reported based on study questions.Results : 21 studies including 55,164 women and 13,742 men were included with a total follow-up of 279,124 person-years. All four QUS parameters were associated with risk of different fractures. For instance, RR of hip fracture for 1 SD decrease of BUA was 1.69 (95% CI 1.43-2.00), SOS was 1.96 (95% CI 1.64-2.34), SI was 2.26 (95%CI 1.71-2.99), and QUI was 1.99 (95% CI 1.49-2.67). Validated devices from different manufacturers predicted fracture risks with a similar performance (meta-regression p-values>0.05 for difference of devices). There was no sign of publication bias among the studies. QUS measures predicted fracture with a similar performance in men and women. Meta-analysis of studies with QUS measures adjusted for hip DXA showed a significant and independent association with fracture risk (RR/SD for BUA =1.34 [95%CI 1.22-1.49]).Conclusions : This study confirms that QUS of the heel using validated devices predicts risk of different fracture outcomes in elderly men and women. Further research and international collaborations are needed for standardisation of QUS parameters across various manufacturers and inclusion of QUS in fracture risk assessment tools. Disclosure of Interest : None declared.

Clinical methods for quantifying body segment posture: a literature review

Purpose. Clinicians commonly assess posture in persons with musculoskeletal disorders and tend to do so subjectively. Evidence-based practice requires the use of valid, reliable and sensitive tools to monitor treatment effectiveness. The purpose of this article was to determine which methods were used to assess posture quantitatively in a clinical setting and to identify psychometric properties of posture indices measured from these methods or tools. Methods. We conducted a comprehensive literature review. Pertinent databases were used to search for articles on quantitative clinical assessment of posture. Searching keywords were related to posture and assessment, scoliosis, back pain, reliability, validity and different body segments. Results. We identified 65 articles with angle and distance posture indices that corresponded to our search criteria. Several studies showed good intra- and inter-rater reliability for measurements taken directly on the persons (e.g., goniometer, inclinometer, flexible curve and tape measurement) or from photographs, but the validity of these measurements was not always demonstrated. Conclusion. Taking measurements of all body angles directly on the person is a lengthy process and may affect the reliability of the measurements. Measurement of body angles from photographs may be the most accurate and rapid way to assess global posture quantitatively in a clinical setting.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Sleep quality, the neglected outcome variable in clinical studies focusing on locomotor system; a construct validation study

In addition to general health and pain, sleep is highly relevant to judging the well-being of an individual. Of these three important outcome variables, however, sleep is neglected in most outcome studies.Sleep is a very important resource for recovery from daily stresses and strains, and any alteration of sleep will likely affect mental and physical health, especially during disease. Sleep assessment therefore should be standard in all population-based or clinical studies focusing on the locomotor system. Yet current sleep assessment tools are either too long or too specific for general use.

A methodologic study of pain assessment in Anglo and Hispanic children with cancer

There is growing clinical evidence that even young children experience pain and accompanying anxiety. Few instruments have been validated to assess pain characteristics in children. The study of related demographic, illness, psychologic and parental factors in children has also been limited. This study examines the reliability and validity of pain assessment tools in an outpatient pediatric cancer population. A total of 78 children from three to fifteen years of age were observed and interviewed about the pain of invasive procedures. The effect of cultural factors and the stress of acculturation were examined by comparing data from two cultural groups, Anglo and Hispanic.^ Spielberger State-Trait Anxiety Scales were administered to children and parents prior to an invasive procedure. The Procedure Behavioral Checklist (PBCL) was used for observation of the child's response during the procedure. The Children's Procedural Interview (CPI) which contains items on the PBCL and visual analogues (scales of faces indicating varying degrees of pain and anxiety) was administered following the procedure.^ Reliability coefficients for Anglos were.78 on the PBCL,.79 on the CPI and.85 on the visual analogue scales. For Hispanics, the reliability for the PBCL was.54, while the CPI had a reliability of.72 and the visual analogue scales,.87. Construct validity was demonstrated by high correlations between the PBCL and CPI scores for both ethnic groups (.66 for Anglos and.64 for Hispanics) and by the significant correlation of State anxiety scores with both PBCL and CPI scores. Age was inversely correlated with PBCL and CPI scores for both ethnic groups. Hispanic parents' anxiety scores were higher than Anglo parents, but were not highly correlated with their child's PBCL, CPI or State-Trait anxiety scores. Caregivers' ratings were correlated with the PBCL scores for Anglos but not for Hispanics.^ The findings of this study indicate that pain responses may be reliably assessed using both observational and self-report methods in children, though differences in Anglo and Hispanic cultures exist. Differences in pain symptomatology and assessment in the two cultural groups warrant further study. ^

Patient-oriented computerized clinical guidelines for mobile decision support in gestational diabetes

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients’ self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient’s access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients’ personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients’ acceptance of the whole system.

Robotic Outcome Assessment in a Non-Human Primate Model of Middle Cerebral Artery Stroke

Stroke is a prevalent disorder with immense socioeconomic impact. A variety of chronic neurological deficits result from stroke. In particular, sensorimotor deficits are a significant barrier to achieving post-stroke independence. Unfortunately, the majority of pre-clinical studies that show improved outcomes in animal stroke models have failed in clinical trials. Pre-clinical studies using non-human primate (NHP) stroke models prior to initiating human trials are a potential step to improving translation from animal studies to clinical trials. Robotic assessment tools represent a quantitative, reliable, and reproducible means to assess reaching behaviour following stroke in both humans and NHPs. We investigated the use of robotic technology to assess sensorimotor impairments in NHPs following middle cerebral artery occlusion (MCAO). Two cynomolgus macaques underwent transient MCAO for 90 minutes. Approximately 1.5 years following the procedure these NHPs and two non-stroke control monkeys were trained in a reaching task with both arms in the KINARM exoskeleton. This robot permits elbow and shoulder movements in the horizontal plane. The task required NHPs to make reaching movements from a centrally positioned start target to 1 of 8 peripheral targets uniformly distributed around the first target. We analyzed four movement parameters: reaction time, movement time (MT), initial direction error (IDE), and number of speed maxima to characterize sensorimotor deficiencies. We hypothesized reduced performance in these attributes during a neurobehavioural task with the paretic limb of NHPs following MCAO compared to controls. Reaching movements in the non-affected limbs of control and experimental NHPs showed bell-shaped velocity profiles. In contrast, the reaching movements with the affected limbs were highly variable. We found distinctive patterns in MT, IDE, and number of speed peaks between control and experimental monkeys and between limbs of NHPs with MCAO. NHPs with MCAO demonstrated more speed peaks, longer MTs, and greater IDE in their paretic limb compared to controls. These initial results qualitatively match human stroke subjects’ performance, suggesting that robotic neurobehavioural assessment in NHPs with stroke is feasible and could have translational relevance in subsequent human studies. Further studies will be necessary to replicate and expand on these preliminary findings.

Robotic Outcome Assessment in a Non-Human Primate Model of Middle Cerebral Artery Stroke

Stroke is a prevalent disorder with immense socioeconomic impact. A variety of chronic neurological deficits result from stroke. In particular, sensorimotor deficits are a significant barrier to achieving post-stroke independence. Unfortunately, the majority of pre-clinical studies that show improved outcomes in animal stroke models have failed in clinical trials. Pre-clinical studies using non-human primate (NHP) stroke models prior to initiating human trials are a potential step to improving translation from animal studies to clinical trials. Robotic assessment tools represent a quantitative, reliable, and reproducible means to assess reaching behaviour following stroke in both humans and NHPs. We investigated the use of robotic technology to assess sensorimotor impairments in NHPs following middle cerebral artery occlusion (MCAO). Two cynomolgus macaques underwent transient MCAO for 90 minutes. Approximately 1.5 years following the procedure these NHPs and two non-stroke control monkeys were trained in a reaching task with both arms in the KINARM exoskeleton. This robot permits elbow and shoulder movements in the horizontal plane. The task required NHPs to make reaching movements from a centrally positioned start target to 1 of 8 peripheral targets uniformly distributed around the first target. We analyzed four movement parameters: reaction time, movement time (MT), initial direction error (IDE), and number of speed maxima to characterize sensorimotor deficiencies. We hypothesized reduced performance in these attributes during a neurobehavioural task with the paretic limb of NHPs following MCAO compared to controls. Reaching movements in the non-affected limbs of control and experimental NHPs showed bell-shaped velocity profiles. In contrast, the reaching movements with the affected limbs were highly variable. We found distinctive patterns in MT, IDE, and number of speed peaks between control and experimental monkeys and between limbs of NHPs with MCAO. NHPs with MCAO demonstrated more speed peaks, longer MTs, and greater IDE in their paretic limb compared to controls. These initial results qualitatively match human stroke subjects’ performance, suggesting that robotic neurobehavioural assessment in NHPs with stroke is feasible and could have translational relevance in subsequent human studies. Further studies will be necessary to replicate and expand on these preliminary findings.

Testing the psychometric properties of two self-report clinical competence scales for nursing students.

Background: It is important to assess the clinical competence of nursing students to gauge their educational needs. Competence can be measured by self-assessment tools; however, Anema and McCoy (2010) contend that currently available measures should be further psychometrically tested.
Aim: To test the psychometric properties of Nursing Competencies Questionnaire (NCQ) and Self-Efficacy in Clinical Performance (SECP) clinical competence scales.
Method: A non-randomly selected sample of n=248 2nd year nursing students completed NCQ, SECP and demographic questionnaires (June and September 2013). Mokken Scaling Analysis (MSA) was used to investigate structural validity and scale properties; convergent and discriminant validity and reliability were also tested for each scale.
Results: MSA analysis identified that the NCQ is a unidimensional scale with strong scale scalability coefficients Hs =0.581; but limited item rankability HT =0.367. The SECP scale MSA suggested that the scale could be potentially split into two unidimensional scales (SECP28 and SECP7), each with good/reasonable scalablity psychometric properties as summed scales but negligible/very limited scale rankability (SECP28: Hs = 0.55, HT=0.211; SECP7: Hs = 0.61, HT=0.049). Analysis of between cohort differences and NCQ/SECP scores produced evidence of discriminant and convergent validity; good internal reliability was also found: NCQ α = 0.93, SECP28 α = 0.96 and SECP7 α=0.89.

Discussion: In line with previous research further evidence of the NCQ’s reliability and validity was demonstrated. However, as the SECP findings are new and the sample small with reference to Straat and colleagues (2014), the SECP results should be interpreted with caution and verified on a second sample.
Conclusions: Measurement of perceived self-competence could start early in a nursing programme to support students’ development of clinical competence. Further testing of the SECP scale with larger nursing student samples from different programme years is indicated.

References:
Anema, M., G and McCoy, JK. (2010) Competency-Based Nursing Education: Guide to Achieving Outstanding Learner Outcomes. New York: Springer.
Straat, JH., van der Ark, LA and Sijtsma, K. (2014) Minimum Sample Size Requirements for Mokken Scale Analysis Educational and Psychological Measurement 74 (5), 809-822.

French good practice guidelines for management of the risk of low back pain among workers exposed to manual material handling: Hierarchical strategy of risk assessment of work situations

International audience

Adaptação de um instrumento de rastreio cognitivo, o MoCA (Montreal Cognitive Assessment) para população cabo-verdiana

Dissertação de Mestrado, Neurociências Cognitivas e Neuropsicologia, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2016

[In search of] Digital biomarkers for objective pain assessment

Pain is a highly complex phenomenon involving intricate neural systems, whose interactions with other physiological mechanisms are not fully understood. Standard pain assessment methods, relying on verbal communication, often fail to provide reliable and accurate information, which poses a critical challenge in the clinical context. In the era of ubiquitous and inexpensive physiological monitoring, coupled with the advancement of artificial intelligence, these new tools appear as the natural candidates to be tested to address such a challenge. This thesis aims to conduct experimental research to develop digital biomarkers for pain assessment. After providing an overview of the state-of-the-art regarding pain neurophysiology and assessment tools, methods for appropriately conditioning physiological signals and controlling confounding factors are presented. The thesis focuses on three different pain conditions: cancer pain, chronic low back pain, and pain experienced by patients undergoing neurorehabilitation. The approach presented in this thesis has shown promise, but further studies are needed to confirm and strengthen these results. Prior to developing any models, a preliminary signal quality check is essential, along with the inclusion of personal and health information in the models to limit their confounding effects. A multimodal approach is preferred for better performance, although unimodal analysis has revealed interesting aspects of the pain experience. This approach can enrich the routine clinical pain assessment procedure by enabling pain to be monitored when and where it is actually experienced, and without the involvement of explicit communication,. This would improve the characterization of the pain experience, aid in antalgic therapy personalization, and bring timely relief, with the ultimate goal of improving the quality of life of patients suffering from pain.

The Clinical Impact Of Cerebellar Grey Matter Pathology In Multiple Sclerosis.

The cerebellum is an important site for cortical demyelination in multiple sclerosis, but the functional significance of this finding is not fully understood. To evaluate the clinical and cognitive impact of cerebellar grey-matter pathology in multiple sclerosis patients. Forty-two relapsing-remitting multiple sclerosis patients and 30 controls underwent clinical assessment including the Multiple Sclerosis Functional Composite, Expanded Disability Status Scale (EDSS) and cerebellar functional system (FS) score, and cognitive evaluation, including the Paced Auditory Serial Addition Test (PASAT) and the Symbol-Digit Modalities Test (SDMT). Magnetic resonance imaging was performed with a 3T scanner and variables of interest were: brain white-matter and cortical lesion load, cerebellar intracortical and leukocortical lesion volumes, and brain cortical and cerebellar white-matter and grey-matter volumes. After multivariate analysis high burden of cerebellar intracortical lesions was the only predictor for the EDSS (p<0.001), cerebellar FS (p = 0.002), arm function (p = 0.049), and for leg function (p<0.001). Patients with high burden of cerebellar leukocortical lesions had lower PASAT scores (p = 0.013), while patients with greater volumes of cerebellar intracortical lesions had worse SDMT scores (p = 0.015). Cerebellar grey-matter pathology is widely present and contributes to clinical dysfunction in relapsing-remitting multiple sclerosis patients, independently of brain grey-matter damage.

Concepts and tools for comprehensive sustainability assessments for tourism destinations: a comparative review

This paper reviews a wide range of tools for comprehensive sustainability assessments at whole tourism destinations, covering socio-cultural, economic and environmental issues. It considers their strengths, weaknesses and site specific applicability. It is intended to facilitate their selection (and combination where necessary). Tools covered include Sustainability Indicators, Environmental Impact Assessment, Life Cycle Assessment, Environmental Audits, Ecological Footprints, Multi-Criteria Analysis and Adaptive Environmental Assessment. Guidelines for evaluating their suitability for specific sites and situations are given as well as examples of their use.