154 research outputs found

    Morphological characterization of the AlphaA- and AlphaB-crystallin double knockout mouse lens

    Get PDF
    BACKGROUND: One approach to resolving some of the in vivo functions of alpha-crystallin is to generate animal models where one or both of the alpha-crystallin gene products have been eliminated. In the single alpha-crystallin knockout mice, the remaining alpha-crystallin may fully or partially compensate for some of the functions of the missing protein, especially in the lens, where both alphaA and alphaB are normally expressed at high levels. The purpose of this study was to characterize gross lenticular morphology in normal mice and mice with the targeted disruption of alphaA- and alphaB-crystallin genes (alphaA/BKO). METHODS: Lenses from 129SvEvTac mice and alphaA/BKO mice were examined by standard scanning electron microscopy and confocal microscopy methodologies. RESULTS: Equatorial and axial (sagittal) dimensions of lenses for alphaA/BKO mice were significantly smaller than age-matched wild type lenses. No posterior sutures or fiber cells extending to the posterior capsule of the lens were found in alphaA/BKO lenses. Ectopical nucleic acid staining was observed in the posterior subcapsular region of 5 wk and anterior subcapsular cortex of 54 wk alphaA/BKO lenses. Gross morphological differences were also observed in the equatorial/bow, posterior and anterior regions of lenses from alphaA/BKO mice as compared to wild mice. CONCLUSION: These results indicated that both alphaA- and alphaB-crystallin are necessary for proper fiber cell formation, and that the absence of alpha-crystallin can lead to cataract formation

    The Effect of a School-Based Intervention on Physical Activity and Well-Being: a Non-Randomised Controlled Trial with Children of Low Socio-Economic Status

    Get PDF
    Abstract Background Self-determination theory (SDT) has been used to predict children’s physical activity and well-being. However, few school-based SDT intervention studies have been conducted, and no research exists with children of low socio-economic status (SES). Therefore, SDT-derived needs-supportive teaching techniques informed the design and analyses of the Healthy Choices Programme (HCP). The aim was to determine if the HCP could enhance moderate-to-vigorous physical activity (MVPA) and well-being among children of low SES through increasing autonomy-support, needs satisfaction and intrinsic motivation. Method A mixed factorial two (group) × two (time) wait-list controlled trial was conducted and reported using the TREND guidelines. A total of 155 children (56% females; intervention n = 84, control n = 71) took part and completed measures at baseline (week 0) and post-intervention (week 11). The effect of the intervention on MVPA (model 1) and well-being (model 2) was tested through serial mediation models with three mediators (i.e. autonomy-support, needs satisfaction and intrinsic motivation). Results In comparison to the control group, the intervention was related to increases in MVPA (ÎČ = .45) and autonomy-support (ÎČ = .17). In model 1, analyses revealed partial mediation of the MVPA change through autonomy-support (ÎČ = .14), intrinsic motivation (ÎČ = .51) and all three SDT mediators in sequence (total r 2  = .34). In model 2, well-being was indirectly enhanced through autonomy-support (ÎČ = .38) and autonomy-support and needs satisfaction in sequence (total r 2  = .21). Conclusions The HCP enhanced MVPA and well-being by engendering a needs-supportive physical activity environment. The scientific and practical contribution of this study was the application of SDT in all aspects of the HCP intervention’s design and analyses. Practitioners may consider integrating SDT principles, as implemented in the HCP, for health promotion. Trial Registration This study is registered on Research Registry (number researchregistry2852)

    Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology

    Get PDF
    Contains fulltext : 97171.pdf (postprint version ) (Open Access)BACKGROUND: Current human resources planning models in nursing are unreliable and ineffective as they consider volumes, but ignore effects on quality in patient care. The project RN4CAST aims innovative forecasting methods by addressing not only volumes, but quality of nursing staff as well as quality of patient care. METHODS/DESIGN: A multi-country, multilevel cross-sectional design is used to obtain important unmeasured factors in forecasting models including how features of hospital work environments impact on nurse recruitment, retention and patient outcomes. In each of the 12 participating European countries, at least 30 general acute hospitals were sampled. Data are gathered via four data sources (nurse, patient and organizational surveys and via routinely collected hospital discharge data). All staff nurses of a random selection of medical and surgical units (at least 2 per hospital) were surveyed. The nurse survey has the purpose to measure the experiences of nurses on their job (e.g. job satisfaction, burnout) as well as to allow the creation of aggregated hospital level measures of staffing and working conditions. The patient survey is organized in a sub-sample of countries and hospitals using a one-day census approach to measure the patient experiences with medical and nursing care. In addition to conducting a patient survey, hospital discharge abstract datasets will be used to calculate additional patient outcomes like in-hospital mortality and failure-to-rescue. Via the organizational survey, information about the organizational profile (e.g. bed size, types of technology available, teaching status) is collected to control the analyses for institutional differences.This information will be linked via common identifiers and the relationships between different aspects of the nursing work environment and patient and nurse outcomes will be studied by using multilevel regression type analyses. These results will be used to simulate the impact of changing different aspects of the nursing work environment on quality of care and satisfaction of the nursing workforce. DISCUSSION: RN4CAST is one of the largest nurse workforce studies ever conducted in Europe, will add to accuracy of forecasting models and generate new approaches to more effective management of nursing resources in Europe

    Selection for environmental variance of litter size in rabbits

    Get PDF
    [EN] Background: In recent years, there has been an increasing interest in the genetic determination of environmental variance. In the case of litter size, environmental variance can be related to the capacity of animals to adapt to new environmental conditions, which can improve animal welfare. Results: We developed a ten-generation divergent selection experiment on environmental variance. We selected one line of rabbits for litter size homogeneity and one line for litter size heterogeneity by measuring intra-doe phenotypic variance. We proved that environmental variance of litter size is genetically determined and can be modified by selection. Response to selection was 4.5% of the original environmental variance per generation. Litter size was consistently higher in the Low line than in the High line during the entire experiment. Conclusions: We conclude that environmental variance of litter size is genetically determined based on the results of our divergent selection experiment. This has implications for animal welfare, since animals that cope better with their environment have better welfare than more sensitive animals. We also conclude that selection for reduced environmental variance of litter size does not depress litter size.This research was funded by the Ministerio de EconomĂ­a y Competitividad (Spain), Projects AGL2014-55921, C2-1-P and C2-2-P. Marina MartĂ­nez-Alvaro has a Grant from the same funding source, BES-2012-052655.Blasco Mateu, A.; MartĂ­nez Álvaro, M.; GarcĂ­a Pardo, MDLL.; Ibåñez Escriche, N.; Argente, MJ. (2017). Selection for environmental variance of litter size in rabbits. Genetics Selection Evolution. 49(48):1-8. https://doi.org/10.1186/s12711-017-0323-4S184948Morgante F, SĂžrensen P, Sorensen DA, Maltecca C, Mackay TFC. Genetic architecture of micro-environmental plasticity in Drosophila melanogaster. Sci Rep. 2015;5:9785.SĂžrensen P, de los Campos G, Morgante F, Mackay TFC, Sorensen D. Genetic control of environmental variation of two quantitative traits of Drosophila melanogaster revealed by whole-genome sequencing. Genetics. 2015;201:487–97.Zhang XS, Hill WG. Evolution of the environmental component of the phenotypic variance: stabilizing selection in changing environments and the homogeneity cost. Evolution. 2005;59:1237–44.Mulder HA, Bijma P, Hill WG. Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance. Genet Sel Evol. 2008;40:37–59.Bodin L, Bolet G, Garcia M, Garreau H, Larzul C, David I. Robustesse et canalisation, vision de gĂ©nĂ©ticiens. INRA Prod Anim. 2010;23:11–22.GarcĂ­a ML, Argente MJ, Muelas R, Birlanga V, Blasco A. Effect of divergent selection for residual variance of litter size on health status and welfare. In: Proceedings of the 10th World Rabbit Congress. Sharm El-Sheikh; 2012. p. 103–6.Argente MJ, GarcĂ­a ML, Zbynovska K, Petruska P, Capcarova M, Blasco A. Effect of selection for residual variance of litter size on hematology parameters as immunology indicators in rabbits. In: Proceedings of the 10th World Congress on genetics applied to livestock production. Vancouver; 2014.GarcĂ­a ML, Zbynovska K, Petruska P, BovdisovĂĄ I, KalafovĂĄ A, Capcarova M, et al. Effect of selection for residual variance of litter size on biochemical parameters in rabbits. In: Proceedings of the 67th annual meeting of the European Federation of Animal Science. Belfast; 2016.Broom DM. Welfare assessment and relevant ethical decisions: key concepts. Annu Rev Biomed Sci. 2008;20:79–90.SanCristobal-Gaudy M, Bodin L, Elsen JM, Chevalet C. Genetic components of litter size variability in sheep. Genet Sel Evol. 2001;33:249–71.Sorensen D, Waagepetersen R. Normal linear models with genetically structured residual variance heterogeneity: a case study. Genet Res. 2003;82:207–22.Mulder HA, Hill WG, Knol EF. Heritable environmental variance causes nonlinear relationships between traits: application to birth weight and stillbirth of pigs. Genetics. 2015;199:1255–69.Ros M, Sorensen D, Waagepetersen R, Dupont-Nivet M, San Cristobal M, Bonnet JC. Evidence for genetic control of adult weight plasticity in the snail Helix aspersa. Genetics. 2004;168:2089–97.GutiĂ©rrez JP, Nieto B, Piqueras P, Ibåñez N, Salgado C. Genetic parameters for components analysis of litter size and litter weight traits at birth in mice. Genet Sel Evol. 2006;38:445–62.Ibåñez-Escriche N, Sorensen D, Waagepetersen R, Blasco A. Selection for environmental variation: a statistical analysis and power calculations to detect response. Genetics. 2008;180:2209–26.Wolc A, White IM, Avendano S, Hill WG. Genetic variability in residual variation of body weight and conformation scores in broiler chickens. Poult Sci. 2009;88:1156–61.Fina M, Ibåñez-Escriche N, Piedrafita J, Casellas J. Canalization analysis of birth weight in Bruna dels Pirineus beef cattle. J Anim Sci. 2013;91:3070–8.Mulder HA, RönnegĂ„rd L, Fikse WF, Veerkamp RF, Strandberg E. Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models. Genet Sel Evol. 2013;45:23.Janhunen M, Kause A, VehvilĂ€inen H, JĂ€rvisalom O. Genetics of microenvironmental sensitivity of body weight in rainbow trout (Oncorhynchus mykiss) selected for improved growth. PLoS One. 2012;7:e38766.Sonesson AK, ØdegĂ„rd J, RönnegĂ„rd L. Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar). Genet Sel Evol. 2013;45:41.Garreau H, Bolet G, Larzul C, Robert-Granie C, Saleil G, SanCristobal M, et al. Results of four generations of a canalising selection for rabbit birth weight. Livest Sci. 2008;119:55–62.Pun A, Cervantes I, Nieto B, Salgado C, PĂ©rez-Cabal MA, Ibåñez-Escriche N, et al. Genetic parameters for birth weight environmental variability in mice. J Anim Breed Genet. 2012;130:404–14.Hill WG, Mulder HA. Genetic analysis of environmental variation. Genet Res (Camb). 2010;92:381–95.Yang Y, Christensen OF, Sorensen D. Analysis of a genetically structured variance heterogeneity model using the Box–Cox transformation. Genet Res (Camb). 2011;93:33–46.Piles M, Garcia ML, Rafel O, Ramon J, Baselga M. Genetics of litter size in three maternal lines of rabbits: repeatability versus multiple-trait models. J Anim Sci. 2006;84:2309–15.Estany J, Baselga M, Blasco A, Camacho J. Mixed model methodology for the estimation of genetic response to selection in litter size of rabbits. Livest Prod Sci. 1989;21:67–75.Box GEP, Tiao GC. Bayesian inference in statistical analysis. New York: Wiley; 1973.Searle SR. Matrix algebra useful for statistics. Toronto: Wiley; 1982.Sorensen D, Gianola D. Likelihood, Bayesian and MCMC methods in quantitative genetics. New York: Springer; 2002.Geyer CM. Practical Markov chain Monte Carlo (with discussion). Stat Sci. 1992;7:467–511.Legarra A. TM threshold model. 2008. http://genoweb.toulouse.inra.fr/~alegarra/tm_folder/ . Accessed 02 May 2017.Blasco A. Bayesian data analysis for animal scientists. New York: Springer; 2017.RönnegĂ„rd L, Felleki M, Fikse F, Mulder HA, Strandberg E. Genetic heterogeneity of residual variance—estimation of variance components using double hierarchical generalized linear models. Genet Sel Evol. 2010;42:8.Felleki M, Lee D, Lee Y, Gilmour AR, RönnegĂ„rd L. Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models. Genet Res (Camb). 2012;94:307–17.Thompson R. Estimation of realized heritability in a selected population using mixed model methods. Genet Sel Evol. 1986;18:475–84.Sorensen DA, Johansson K. Estimation of direct and correlated responses to selection using univariate animal models. J Anim Sci. 1992;70:2038–44.Popper K. The logic of scientific discovery. London: Hutchinson & Co; 1959.Falconer DS, MacKay TFC. An introduction to quantitative genetics. 4th ed. Harlow: Longman Group Ltd; 1996.Formoso-Rafferty N, Cervantes I, Ibåñez-Escriche N, GutiĂ©rrez JP. Correlated genetic trends for production and welfare traits in a mouse population divergently selected for birth weight environmental variability. Animal. 2016;10:1770–7.Ibåñez-Escriche N, Moreno A, Nieto B, Piqueras P, Salgado C, GutiĂ©rrez JP. Genetic parameters related to environmental variability of weight traits in a selection experiment for weight gain in mice; signs of correlated canalised response. Genet Sel Evol. 2008;40:279–93.Mulder HA, Hill WG, Vereijken A, Veerkamp RF. Estimation of genetic variation in residual variance in female and male broiler chickens. Animal. 2009;3:1673–80.Ibåñez-Escriche N, Varona L, Sorensen D, Noguera JL. A study of heterogeneity of environmental variance for slaughter weight in pigs. Animal. 2008;2:19–26.Bolet G, Garreau H, Hurtaud J, Saleil G, EsparbiĂ© J, Falieres J. Canalising selection on within litter variability of birth weight in rabbits: responses to selection and characteristics of the uterus of the does. In: Proceedings of the 9th World Rabbit Congress. Verona; 2008. p. 51–6.San Cristobal-Gaudy M, Elsen JM, Bodin L, Chevalet C. Prediction of the response to a selection for canalisation of a continuous trait in animal breeding. Genet Sel Evol. 1998;30:423–51.Argente MJ, Santacreu MA, Climent A, Blasco A. Genetic correlations between litter size and uterine capacity. In: Proceeding of the 8th World Rabbit Congress. Valencia; 2000. p. 333–38.Rauw WM. Immune response from a resource allocation perspective. Front Genet. 2012;3:267

    Assessing the organizational context for EBP implementation: the development and validity testing of the Implementation Climate Scale (ICS)

    Get PDF
    BACKGROUND: Although the importance of the organizational environment for implementing evidence-based practices (EBP) has been widely recognized, there are limited options for measuring implementation climate in public sector health settings. The goal of this research was to develop and test a measure of EBP implementation climate that would both capture a broad range of issues important for effective EBP implementation and be of practical use to researchers and managers seeking to understand and improve the implementation of EBPs. METHODS: Participants were 630 clinicians working in 128 work groups in 32 US-based mental health agencies. Items to measure climate for EBP implementation were developed based on past literature on implementation climate and other strategic climates and in consultation with experts on the implementation of EBPs in mental health settings. The sample was randomly split at the work group level of analysis; half of the sample was used for exploratory factor analysis (EFA), and the other half was used for confirmatory factor analysis (CFA). The entire sample was utilized for additional analyses assessing the reliability, support for level of aggregation, and construct-based evidence of validity. RESULTS: The EFA resulted in a final factor structure of six dimensions for the Implementation Climate Scale (ICS): 1) focus on EBP, 2) educational support for EBP, 3) recognition for EBP, 4) rewards for EBP, 5) selection for EBP, and 6) selection for openness. This structure was supported in the other half of the sample using CFA. Additional analyses supported the reliability and construct-based evidence of validity for the ICS, as well as the aggregation of the measure to the work group level. CONCLUSIONS: The ICS is a very brief (18 item) and pragmatic measure of a strategic climate for EBP implementation. It captures six dimensions of the organizational context that indicate to employees the extent to which their organization prioritizes and values the successful implementation of EBPs. The ICS can be used by researchers to better understand the role of the organizational context on implementation outcomes and by organizations to evaluate their current climate as they consider how to improve the likelihood of implementation success. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13012-014-0157-1) contains supplementary material, which is available to authorized users

    Naturopathic Care for Anxiety: A Randomized Controlled Trial ISRCTN78958974

    Get PDF
    BACKGROUND: Anxiety is a serious personal health condition and represents a substantial burden to overall quality of life. Additionally anxiety disorders represent a significant cost to the health care system as well as employers through benefits coverage and days missed due to incapacity. This study sought to explore the effectiveness of naturopathic care on anxiety symptoms using a randomized trial. METHODS: Employees with moderate to severe anxiety of longer than 6 weeks duration were randomized based on age and gender to receive naturopathic care (NC) (n = 41) or standardized psychotherapy intervention (PT) (n = 40) over a period of 12 weeks. Blinding of investigators and participants during randomization and allocation was maintained. Participants in the NC group received dietary counseling, deep breathing relaxation techniques, a standard multi-vitamin, and the herbal medicine, ashwagandha (Withania somnifera) (300 mg b.i.d. standardized to 1.5% with anolides, prepared from root). The PT intervention received psychotherapy, and matched deep breathing relaxation techniques, and placebo. The primary outcome measure was the Beck Anxiety Inventory (BAI) and secondary outcome measures included the Short Form 36 (SF-36), Fatigue Symptom Inventory (FSI), and Measure Yourself Medical Outcomes Profile (MY-MOP) to measure anxiety, mental health, and quality of life respectively. Participants were blinded to the placebo-controlled intervention. RESULTS: Seventy-five participants (93%) were followed for 8 or more weeks on the trial. Final BAI scores decreased by 56.5% (p<0.0001) in the NC group and 30.5% (p<0.0001) in the PT group. BAI group scores were significantly decreased in the NC group compared to PT group (p = 0.003). Significant differences between groups were also observed in mental health, concentration, fatigue, social functioning, vitality, and overall quality of life with the NC group exhibiting greater clinical benefit. No serious adverse reactions were observed in either group. RELEVANCE: Many patients seek alternatives and/or complementary care to conventional anxiety treatments. To date, no study has evaluated the potential of a naturopathic treatment protocol to effectively treat anxiety. Knowledge of the efficacy, safety or risk of natural health products, and naturopathic treatments is important for physicians and the public in order to make informed decisions. INTERPRETATION: Both NC and PT led to significant improvements in patients' anxiety. Group comparison demonstrated a significant decrease in anxiety levels in the NC group over the PT group. Significant improvements in secondary quality of life measures were also observed in the NC group as compared to PT. The whole system of naturopathic care for anxiety needs to be investigated further including a closer examination of the individual components within the context of their additive effect. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN78958974

    A Longitudinal Test of the Demand–Control Model Using Specific Job Demands and Specific Job Control

    Get PDF
    # The Author(s) 2010. This article is published with open access at Springerlink.com Background Supportive studies of the demand–control (DC) model were more likely to measure specific demands combined with a corresponding aspect of control. Purpose A longitudinal test of Karasek’s (Adm Sci Q. 24:285–308, 1) job strain hypothesis including specific measures of job demands and job control, and both selfreport and objectively recorded well-being. Method Job strain hypothesis was tested among 267 health care employees from a two-wave Dutch panel survey with a 2-year time lag. Results Significant demand/control interactions were found for mental and emotional demands, but not for physical demands. The association between job demands and job satisfaction was positive in case of high job control, whereas this association was negative in case of low job control. In addition, the relation between job demands and J. de Jonge (*

    Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers.

    Get PDF
    Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10(-8)). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34(+) stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal.This research uses resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute of Allergy and Infectious Diseases (NIAID), the National Human Genome Research Institute (NHGRI), the National Institute of Child Health and Human Development (NICHD) and JDRF and supported by grant U01 DK062418 from the US National Institutes of Health. Further support was provided by grants from the NIDDK (DK046635 and DK085678) to P.C. and by a joint JDRF and Wellcome Trust grant (WT061858/09115) to the Diabetes and Inflammation Laboratory at Cambridge University, which also received support from the NIHR Cambridge Biomedical Research Centre. ImmunoBase receives support from Eli Lilly and Company. C.W. and H.G. are funded by the Wellcome Trust (089989). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140). We gratefully acknowledge the following groups and individuals who provided biological samples or data for this study. We obtained DNA samples from the British 1958 Birth Cohort collection, funded by the UK Medical Research Council and the Wellcome Trust. We acknowledge use of DNA samples from the NIHR Cambridge BioResource. We thank volunteers for their support and participation in the Cambridge BioResource and members of the Cambridge BioResource Scientific Advisory Board (SAB) and Management Committee for their support of our study. We acknowledge the NIHR Cambridge Biomedical Research Centre for funding. Access to Cambridge BioResource volunteers and to their data and samples are governed by the Cambridge BioResource SAB. Documents describing access arrangements and contact details are available at http://www.cambridgebioresource.org.uk/. We thank the Avon Longitudinal Study of Parents and Children laboratory in Bristol, UK, and the British 1958 Birth Cohort team, including S. Ring, R. Jones, M. Pembrey, W. McArdle, D. Strachan and P. Burton, for preparing and providing the control DNA samples. This study makes use of data generated by the Wellcome Trust Case Control Consortium, funded by Wellcome Trust award 076113; a full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk/.This is the author accepted manuscript. The final version is available via NPG at http://www.nature.com/ng/journal/v47/n4/full/ng.3245.html

    Tracking of an electron beam through the solar corona with LOFAR

    Get PDF
    © ESO 2018. The Sun's activity leads to bursts of radio emission, among other phenomena. An example is type-III radio bursts. They occur frequently and appear as short-lived structures rapidly drifting from high to low frequencies in dynamic radio spectra. They are usually interpreted as signatures of beams of energetic electrons propagating along coronal magnetic field lines. Here we present novel interferometric LOFAR (LOw Frequency ARray) observations of three solar type-III radio bursts and their reverse bursts with high spectral, spatial, and temporal resolution. They are consistent with a propagation of the radio sources along the coronal magnetic field lines with nonuniform speed. Hence, the type-III radio bursts cannot be generated by a monoenergetic electron beam, but by an ensemble of energetic electrons with a spread distribution in velocity and energy. Additionally, the density profile along the propagation path is derived in the corona. It agrees well with three-fold coronal density model by (1961, ApJ, 133, 983)

    Meta Modeling for Business Process Improvement

    Get PDF
    Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated
    • 

    corecore