Work engagement, job design and the role of the social context at work: Exploring antecedents from a relational perspective

Relational resources are now recognised as significant factors in workplaces and increasing attention is being given to the motivational impact of giving in addition to receiving social support. Our study builds on this work to determine the role of such relational mechanisms in work engagement, a concept that simultaneously captures drive and well-being. Data from 182 midwives from two maternity hospitals revealed a best-fit model where perceived supervisor support, social support from peers, prosocial impact on others and autonomy explained 52% of variance in work engagement. Perceived prosocial impact acted as a significant partial mediator between autonomy and work engagement. This study provides evidence for the importance of perceived prosocial impact and the role of immediate supervisors in facilitating work engagement in midwifery. Results highlight the value of relational resources and suggest their explicit inclusion in current models of work engagement

Living environment and self assessed morbidity: a questionnaire-based survey

<p>Abstract</p> <p>Background</p> <p>Health complaints have been reported to be higher among the industrial area residents when compared with reference community.</p> <p>Methods</p> <p>Such reports being only a few, a questionnaire survey was conducted in three different areas (Industrial, Residential, Commercial) of Ahmedabad city of India to determine the pattern of morbidity and to do a comparative analysis of different areas within the city.</p> <p>Results</p> <p>A total of 679 families (243 from commercial, 199 from residential and 237 from industrial area) were included in this study. This study revealed that apart from presence of industry in close proximity to residence (99.2%), industrial area residents are having many other disadvantages from the point of view of public health like waste water stagnation (87.4%), problem of cooking smoke (33.2%) and presence of garbage dumps near residence (72.8%). Consequently, problems like coughing, wheezing, eye irritation, skin irritation, jaundice, asthma, and dental caries have been observed to be more common in industrial area. Comparative risk calculated in terms of odds ratio for different such problems have ranged from 1.83 to 6.2 when industrial area was compared with commercial area. Similarly on comparison of industrial area with residential area, odds ratio for different problems have ranged from 1.82 to 11.5.</p> <p>Conclusion</p> <p>This study has pointed out the need of separate planning and implementation of specific upliftment programs for addressing the environmental as well as public health issues of industrial localities.</p

lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers

We assume data sampled from a mixture of d-dimensional linear subspaces with spherically symmetric distributions within each subspace and an additional outlier component with spherically symmetric distribution within the ambient space (for simplicity we may assume that all distributions are uniform on their corresponding unit spheres). We also assume mixture weights for the different components. We say that one of the underlying subspaces of the model is most significant if its mixture weight is higher than the sum of the mixture weights of all other subspaces. We study the recovery of the most significant subspace by minimizing the lp-averaged distances of data points from d-dimensional subspaces, where p>0. Unlike other lp minimization problems, this minimization is non-convex for all p>0 and thus requires different methods for its analysis. We show that if 0<p<=1, then for any fraction of outliers the most significant subspace can be recovered by lp minimization with overwhelming probability (which depends on the generating distribution and its parameters). We show that when adding small noise around the underlying subspaces the most significant subspace can be nearly recovered by lp minimization for any 0<p<=1 with an error proportional to the noise level. On the other hand, if p>1 and there is more than one underlying subspace, then with overwhelming probability the most significant subspace cannot be recovered or nearly recovered. This last result does not require spherically symmetric outliers.Comment: This is a revised version of the part of 1002.1994 that deals with single subspace recovery. V3: Improved estimates (in particular for Lemma 3.1 and for estimates relying on it), asymptotic dependence of probabilities and constants on D and d and further clarifications; for simplicity it assumes uniform distributions on spheres. V4: minor revision for the published versio

Efficient Online Timed Pattern Matching by Automata-Based Skipping

The timed pattern matching problem is an actively studied topic because of its relevance in monitoring of real-time systems. There one is given a log $w$ and a specification $\mathcal{A}$ (given by a timed word and a timed automaton in this paper), and one wishes to return the set of intervals for which the log $w$, when restricted to the interval, satisfies the specification $\mathcal{A}$. In our previous work we presented an efficient timed pattern matching algorithm: it adopts a skipping mechanism inspired by the classic Boyer--Moore (BM) string matching algorithm. In this work we tackle the problem of online timed pattern matching, towards embedded applications where it is vital to process a vast amount of incoming data in a timely manner. Specifically, we start with the Franek-Jennings-Smyth (FJS) string matching algorithm---a recent variant of the BM algorithm---and extend it to timed pattern matching. Our experiments indicate the efficiency of our FJS-type algorithm in online and offline timed pattern matching

Capacity development for health research in Africa: experiences managing the African Doctoral Dissertation Research Fellowship Program

Africa's progress depends on her capacity to generate, adapt, and use scientific knowledge to meet regional health and development needs. Yet, Africa's higher education institutions that are mandated to foster this capacity lack adequate resources to generate and apply knowledge, raising the need for innovative approaches to enhance research capacity. In this paper, we describe a newly-developed program to support PhD research in health and population sciences at African universities, the African Doctoral Dissertation Research Fellowship (ADDRF) Program. We also share our experiences implementing the program. As health research capacity-strengthening in Africa continues to attract attention and as the need for such programs to be African-led is emphasized, our experiences in developing and implementing the ADDRF offer invaluable lessons to other institutions undertaking similar initiatives

Non-Redundant Spectral Dimensionality Reduction

Spectral dimensionality reduction algorithms are widely used in numerous domains, including for recognition, segmentation, tracking and visualization. However, despite their popularity, these algorithms suffer from a major limitation known as the "repeated Eigen-directions" phenomenon. That is, many of the embedding coordinates they produce typically capture the same direction along the data manifold. This leads to redundant and inefficient representations that do not reveal the true intrinsic dimensionality of the data. In this paper, we propose a general method for avoiding redundancy in spectral algorithms. Our approach relies on replacing the orthogonality constraints underlying those methods by unpredictability constraints. Specifically, we require that each embedding coordinate be unpredictable (in the statistical sense) from all previous ones. We prove that these constraints necessarily prevent redundancy, and provide a simple technique to incorporate them into existing methods. As we illustrate on challenging high-dimensional scenarios, our approach produces significantly more informative and compact representations, which improve visualization and classification tasks

The Social context of motorcycle riding and the key determinants influencing rider behavior: A qualitative investigation

Objective: Given the increasing popularity of motorcycle riding and heightened risk of injury or death associated with being a rider, this study explored rider behaviour as a determinant of rider safety and, in particular, key beliefs and motivations which influence such behaviour. To enhance the effectiveness of future education and training interventions, it is important to understand riders’ own views about what influences how they ride. Specifically, this study sought to identify key determinants of riders’ behaviour in relation to the social context of riding including social and identity-related influences relating to the group (group norms and group identity) as well as the self (moral/personal norm and self-identity). ----- ----- Method: Qualitative research was undertaken via group discussions with motorcycle riders (n = 41). Results: The findings revealed that those in the group with which one rides represent an important source of social influence. Also, the motorcyclist (group) identity was associated with a range of beliefs, expectations, and behaviours considered to be normative. Exploration of the construct of personal norm revealed that riders were most cognizant of the “wrong things to do” when riding; among those issues raised was the importance of protective clothing (albeit for the protection of others and, in particular, pillion passengers). Finally, self-identity as a motorcyclist appeared to be important to a rider’s self-concept and was likely to influence their on-road behaviour. ----- ----- Conclusion: Overall, the insight provided by the current study may facilitate the development of interventions including rider training as well as public education and mass media messages. The findings suggest that these interventions should incorporate factors associated with the social nature of riding in order to best align it with some of the key beliefs and motivations underpinning riders’ on-road behaviours

The accuracy of diagnostic indicators for coeliac disease: A systematic review and meta-analysis

Background: The prevalence of coeliac disease (CD) is around 1%, but diagnosis is challenged by varied presentation and non-specific symptoms and signs. This study aimed to identify diagnostic indicators that may help identify patients at a higher risk of CD in whom further testing is warranted. // Methods: International guidance for systematic review methods were followed and the review was registered at PROSPERO (CRD42020170766). Six databases were searched until April 2021. Studies investigating diagnostic indicators, such as symptoms or risk conditions, in people with and without CD were eligible for inclusion. Risk of bias was assessed using the QUADAS-2 tool. Summary sensitivity, specificity, and positive predictive values were estimated for each diagnostic indicator by fitting bivariate random effects meta-analyses. // Findings: 191 studies reporting on 26 diagnostic indicators were included in the meta-analyses. We found large variation in diagnostic accuracy estimates between studies and most studies were at high risk of bias. We found strong evidence that people with dermatitis herpetiformis, migraine, family history of CD, HLA DQ2/8 risk genotype, anaemia, type 1 diabetes, osteoporosis, or chronic liver disease are more likely than the general population to have CD. Symptoms, psoriasis, epilepsy, inflammatory bowel disease, systemic lupus erythematosus, fractures, type 2 diabetes, and multiple sclerosis showed poor diagnostic ability. A sensitivity analysis revealed a 3-fold higher risk of CD in first-degree relatives of CD patients. // Conclusions: Targeted testing of individuals with dermatitis herpetiformis, migraine, family history of CD, HLA DQ2/8 risk genotype, anaemia, type 1 diabetes, osteoporosis, or chronic liver disease could improve case-finding for CD, therefore expediting appropriate treatment and reducing adverse consequences. Migraine and chronic liver disease are not yet included as a risk factor in all CD guidelines, but it may be appropriate for these to be added. Future research should establish the diagnostic value of combining indicators

Tuning of Human Modulation Filters Is Carrier-Frequency Dependent

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