Rethinking board composition: Balancing competence and compatibility in director selection

Board composition is critical to board effectiveness. Shaping an effective board begins with the selection of directors. While much attention has been paid to the skills and qualifications directors require, there has been less focus on the necessity for board members to interact and work well together. This exploratory study offers insights into what qualities directors look for when selecting new members and the approach adopted to identify and select them. The findings of 10 in-depth interviews with Australian directors suggest new members are selected both on competencies and compatibility. Yet not all selection approaches adequately assess candidates for these two criteria. As a result many appointments fail to realise the selection criteria reducing capacity to reach its full potential.

Searching for semantic person queries using channel representations

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to relate and easy to understand. However such queries are not easily utilised within intelligent surveillance systems as they are difficult to transform into a representation that can be searched for automatically in large camera networks. In this paper we propose a novel approach that transforms such a semantic query into an avatar that is searchable within a video stream, and demonstrate state-of-the-art performance for locating a subject in video based on a description.

The mechanical and inflammatory low back pain (MIL) index: development and validation

Abstract Background The purpose of this study was the development of a valid and reliable “Mechanical and Inflammatory Low Back Pain Index” (MIL) for assessment of non-specific low back pain (NSLBP). This 7-item tool assists practitioners in determining whether symptoms are predominantly mechanical or inflammatory. Methods Participants (n = 170, 96 females, age = 38 ± 14 years-old) with NSLP were referred to two Spanish physiotherapy clinics and completed the MIL and the following measures: the Roland Morris Questionnaire (RMQ), SF-12 and “Backache Index” (BAI) physical assessment test. For test-retest reliability, 37 consecutive patients were assessed at baseline and three days later during a non-treatment period. Face and content validity, practical characteristics, factor analysis, internal consistency, discriminant validity and convergent validity were assessed from the full sample. Results A total of 27 potential items that had been identified for inclusion were subsequently reduced to 11 by an expert panel. Four items were then removed due to cross-loading under confirmatory factor analysis where a two-factor model yielded a good fit to the data (χ2 = 14.80, df = 13, p = 0.37, CFI = 0.98, and RMSEA = 0.029). The internal consistency was moderate (α = 0.68 for MLBP; 0.72 for ILBP), test-retest reliability high (ICC = 0.91; 95%CI = 0.88-0.93) and discriminant validity good for either MLBP (AUC = 0.74) and ILBP (AUC = 0.92). Convergent validity was demonstrated through similar but weak correlations between the ILBP and both the RMQ and BAI (r = 0.34, p < 0.001) and the MLBP and BAI (r = 0.38, p < 0.001). Conclusions The MIL is a valid and reliable clinical tool for patients with NSLBP that discriminates between mechanical and inflammatory LBP. Keywords: Low back pain; Psychometrics properties; Pain measurement; Screening tool; Inflammatory; Mechanical

Arabic translation, adaptation and modification of the dialysis symptom index for chronic kidney disease stages four and five

Background Symptom burden in chronic kidney disease (CKD) is poorly understood. To date, the majority of research focuses on single symptoms and there is a lack of suitable multidimensional symptom measures. The purpose of this study was to modify, translate, cross-culturally adapt and psychometrically analyse the Dialysis Symptom Index (DSI). Methods The study methods involved four phases: modification, translation, pilot-testing with a bilingual non-CKD sample and then psychometric testing with the target population. Content validity was assessed using an expert panel. Inter-rater agreement, test-retest reliability and Cronbach’s alpha coefficient were calculated to demonstrate reliability of the modified DSI. Discriminative and convergent validity were assessed to demonstrate construct validity. Results Content validity index during translation was 0.98. In the pilot study with 25 bilingual students a moderate to perfect agreement (Kappa statistic = 0.60-1.00) was found between English and Arabic versions of the modified DSI. The main study recruited 433 patients CKD with stages 4 and 5. The modified DSI was able to discriminate between non-dialysis and dialysis groups (p < 0.001) and demonstrated convergent validity with domains of the Kidney Disease Quality of Life short form. Excellent test-retest and internal consistency (Cronbach’s α = 0.91) reliability were also demonstrated. Conclusion The Arabic version of the modified DSI demonstrated good psychometric properties, measures the multidimensional nature of symptoms and can be used to assess symptom burden at different stages of CKD. The modified instrument, renamed the CKD Symptom Burden Index (CKD-SBI), should encourage greater clinical and research attention to symptom burden in CKD.

Medical semantic similarity with a neural language model

Advances in neural network language models have demonstrated that these models can effectively learn representations of words meaning. In this paper, we explore a variation of neural language models that can learn on concepts taken from structured ontologies and extracted from free-text, rather than directly from terms in free-text. This model is employed for the task of measuring semantic similarity between medical concepts, a task that is central to a number of techniques in medical informatics and information retrieval. The model is built with two medical corpora (journal abstracts and patient records) and empirically validated on two ground-truth datasets of human-judged concept pairs assessed by medical professionals. Empirically, our approach correlates closely with expert human assessors ($\approx$ 0.9) and outperforms a number of state-of-the-art benchmarks for medical semantic similarity. The demonstrated superiority of this model for providing an effective semantic similarity measure is promising in that this may translate into effectiveness gains for techniques in medical information retrieval and medical informatics (e.g., query expansion and literature-based discovery).

Development of a hybrid pollution index for heavy metals in marine and estuarine sediments

Heavy metal pollution of sediments is a growing concern in most parts of the world, and numerous studies focussed on identifying contaminated sediments by using a range of digestion methods and pollution indices to estimate sediment contamination have been described in the literature. The current work provides a critical review of the more commonly used sediment digestion methods and identifies that weak acid digestion is more likely to provide guidance on elements that are likely to be bioavailable than other traditional methods of digestion. This work also reviews common pollution indices and identifies the Nemerow Pollution Index as the most appropriate method for establishing overall sediment quality. Consequently, a modified Pollution Index that can lead to a more reliable understanding of whole sediment quality is proposed. This modified pollution index is then tested against a number of existing studies and demonstrated to give a reliable and rapid estimate of sediment contamination and quality.

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

Exploiting inference from semantic annotations for information retrieval

The increasing amount of information that is annotated against standardised semantic resources offers opportunities to incorporate sophisticated levels of reasoning, or inference, into the retrieval process. In this position paper, we reflect on the need to incorporate semantic inference into retrieval (in particular for medical information retrieval) as well as previous attempts that have been made so far with mixed success. Medical information retrieval is a fertile ground for testing inference mechanisms to augment retrieval. The medical domain offers a plethora of carefully curated, structured, semantic resources, along with well established entity extraction and linking tools, and search topics that intuitively require a number of different inferential processes (e.g., conceptual similarity, conceptual implication, etc.). We argue that integrating semantic inference in information retrieval has the potential to uncover a large amount of information that otherwise would be inaccessible; but inference is also risky and, if not used cautiously, can harm retrieval.

Cross-cultural adaptation, reliability and validity of the Turkish version of the spine functional index

Background The Spine Functional Index (SFI) is a patient reported outcome measure with sound clinimetric properties and clinical viability for the determination of whole-spine impairment. To date, no validated Turkish version is available. The purpose of this study is to cross-culturally adapted the SFI for Turkish-speaking patients (SFI-Tk) and determine the psychometric properties of reliability, validity and factor structure in a Turkish population with spine musculoskeletal disorders. Methods The SFI English version was culturally adapted and translated into Turkish using a double forward and backward method according to established guidelines. Patients (n = 285, cervical = l29, lumbar = 151, cervical and lumbar region = 5, 73% female, age 45 ± 1) with spine musculoskeletal disorders completed the SFI-Tk at baseline and after a seven day period for test-retest reliability. For criterion validity the Turkish version of the Functional Rating Index (FRI) was used plus the Neck Disability Index (NDI) for cervical patients and the Oswestry Disability Index (ODI) for back patients. Additional psychometric properties were determined for internal consistency (Chronbach’s α), criterion validity and factor structure. Results There was a high degree of internal consistency (α = 0.85, item range 0.80-0.88) and test-retest reliability (r = 0.93, item range = 0.75-0.95). The factor analysis demonstrated a one-factor solution explaining 24.2% of total variance. Criterion validity with the ODI was high (r = 0.71, p < 0.001) while the FRI and NDI were fair (r = 0.52 and r = 0.58, respectively). The SFI-Tk showed no missing responses with the ‘half-mark’ option used in 11.75% of total responses by 77.9% of participants. Measurement error from SEM and MDC90 were respectively 2.96% and 7.12%. Conclusions The SFI-Tk demonstrated a one-factor solution and is a reliable and valid instrument. The SFI-Tk consists of simple and easily understood wording and may be used to assess spine region musculoskeletal disorders in Turkish speaking patients.

Searching for people using semantic soft biometric descriptions

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to communicate and easy to understand. However such queries are not easily utilised within intelligent video surveillance systems, as they are difficult to transform into a representation that can be utilised by computer vision algorithms. In this paper we propose a novel approach that transforms such a semantic query into an avatar in the form of a channel representation that is searchable within a video stream. We show how spatial, colour and prior information (person shape) can be incorporated into the channel representation to locate a target using a particle-filter like approach. We demonstrate state-of-the-art performance for locating a subject in video based on a description, achieving a relative performance improvement of 46.7% over the baseline. We also apply this approach to person re-detection, and show that the approach can be used to re-detect a person in a video steam without the use of person detection.

Confirmatory factory analysis of the Neck Disability Index in a general problematic neck population indicates a one-factor model

BACKGROUND CONTEXT: The Neck Disability Index frequently is used to measure outcomes of the neck. The statistical rigor of the Neck Disability Index has been assessed with conflicting outcomes. To date, Confirmatory Factor Analysis of the Neck Disability Index has not been reported for a suitably large population study. Because the Neck Disability Index is not a condition-specific measure of neck function, initial Confirmatory Factor Analysis should consider problematic neck patients as a homogenous group. PURPOSE: We sought to analyze the factor structure of the Neck Disability Index through Confirmatory Factor Analysis in a symptomatic, homogeneous, neck population, with respect to pooled populations and gender subgroups. STUDY DESIGN: This was a secondary analysis of pooled data. PATIENT SAMPLE: A total of 1,278 symptomatic neck patients (67.5% female, median age 41 years), 803 nonspecific and 475 with whiplash-associated disorder. OUTCOME MEASURES: The Neck Disability Index was used to measure outcomes. METHODS: We analyzed pooled baseline data from six independent studies of patients with neck problems who completed Neck Disability Index questionnaires at baseline. The Confirmatory Factor Analysis was considered in three scenarios: the full sample and separate sexes. Models were compared empirically for best fit. RESULTS: Two-factor models have good psychometric properties across both the pooled and sex subgroups. However, according to these analyses, the one-factor solution is preferable from both a statistical perspective and parsimony. The two-factor model was close to significant for the male subgroup (p<.07) where questions separated into constructs of mental function (pain, reading headaches and concentration) and physical function (personal care, lifting, work, driving, sleep, and recreation). CONCLUSIONS: The Neck Disability Index demonstrated a one-factor structure when analyzed by Confirmatory Factor Analysis in a pooled, homogenous sample of neck problem patients. However, a two-factor model did approach significance for male subjects where questions separated into constructs of mental and physical function. Further investigations in different conditions, subgroup and sex-specific populations are warranted.

Cross-cultural adaptation and validation of the Foot Function Index to Spanish

Background The purpose of this study was to adapt and validate the Foot Function Index to the Spanish (FFI-Sp) following the guidelines of the American Academy of Orthopaedic Surgeons. Methods A cross-sectional study 80 participants with some foot pathology. A statistical analysis was made, including a correlation study with other questionnaires (the Foot Health Status Questionnaire, EuroQol 5-D, Visual Analogue Pain Scale, and the Short Form SF-12 Health Survey). Data analysis included reliability, construct and criterion-related validity and factor analyses. Results The principal components analysis with varimax rotation produced 3 principal factors that explained 80% of the variance. The confirmatory factor analysis showed an acceptable fit with a comparative fit index of 0.78. The FFI-Sp demonstrated excellent internal consistency on the three subscales: pain 0.95; disability 0.96; and activity limitation 0.69, the subscale that scored lowest. The correlation between the FFI-Sp and the other questionnaires was high to moderate. Conclusions The Spanish version of the Foot Function Index (FFI-Sp) is a tool that is a valid and reliable tool with a very good internal consistency for use in the assessment of pain, disability and limitation of the function of the foot, for use both in clinic and research.