Duration of untreated psychosis: Impact of the definition of treatment onset on its predictive value over three years of treatment.

BACKGROUND: While reduction of DUP (Duration of Untreated Psychosis) is a key goal in early intervention strategies, the predictive value of DUP on outcome has been questioned. We planned this study in order to explore the impact of three different definition of "treatment initiation" on the predictive value of DUP on outcome in an early psychosis sample. METHODS: 221 early psychosis patients aged 18-35 were followed-up prospectively over 36 months. DUP was measured using three definitions for treatment onset: Initiation of antipsychotic medication (DUP1); engagement in a specialized programme (DUP2) and combination of engagement in a specialized programme and adherence to medication (DUP3). RESULTS: 10% of patients never reached criteria for DUP3 and therefore were never adequately treated over the 36-month period of care. While DUP1 and DUP2 had a limited predictive value on outcome, DUP3, based on a more restrictive definition for treatment onset, was a better predictor of positive and negative symptoms, as well as functional outcome at 12, 24 and 36 months. Globally, DUP3 explained 2 to 5 times more of the variance than DUP1 and DUP2, with effect sizes falling in the medium range according to Cohen. CONCLUSIONS: The limited predictive value of DUP on outcome in previous studies may be linked to problems of definitions that do not take adherence to treatment into account. While they need replication, our results suggest effort to reduce DUP should continue and aim both at early detection and development of engagement strategies.

Prognostic value of baseline total metabolic tumor volume (TMTV0) measured on FDG-PET/CT in patients with peripheral T-cell lymphoma (PTCL).

BACKGROUND: Most peripheral T-cell lymphoma (PTCL) patients have a poor outcome and the identification of prognostic factors at diagnosis is needed. PATIENTS AND METHODS: The prognostic impact of total metabolic tumor volume (TMTV0), measured on baseline [(18)F]2-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography, was evaluated in a retrospective study including 108 PTCL patients (27 PTCL not otherwise specified, 43 angioimmunoblastic T-cell lymphomas and 38 anaplastic large-cell lymphomas). All received anthracycline-based chemotherapy. TMTV0 was computed with the 41% maximum standardized uptake value threshold method and an optimal cut-off point for binary outcomes was determined and compared with others prognostic factors. RESULTS: With a median follow-up of 23 months, 2-year progression-free survival (PFS) was 49% and 2-year overall survival (OS) was 67%. High TMTV0 was significantly associated with a worse prognosis. At 2 years, PFS was 26% in patients with a high TMTV0 (>230 cm(3), n = 53) versus 71% for those with a low TMTV0, [P < 0.0001, hazard ratio (HR) = 4], whereas OS was 50% versus 80%, respectively, (P = 0.0005, HR = 3.1). In multivariate analysis, TMTV0 was the only significant independent parameter for both PFS and OS. TMTV0, combined with PIT, discriminated even better than TMTV0 alone, patients with an adverse outcome (TMTV0 >230 cm(3) and PIT >1, n = 33,) from those with good prognosis (TMTV0 ≤230 cm(3) and PIT ≤1, n = 40): 19% versus 73% 2-year PFS (P < 0.0001) and 43% versus 81% 2-year OS, respectively (P = 0.0002). Thirty-one patients (other TMTV0-PIT combinations) had an intermediate outcome, 50% 2-year PFS and 68% 2-year OS. CONCLUSION: TMTV0 appears as an independent predictor of PTCL outcome. Combined with PIT, it could identify different risk categories at diagnosis and warrants further validation as a prognostic marker.

Condition-dependence, pleiotropy and the handicap principle of sexual selection in melanin-based colouration.

The signalling function of melanin-based colouration is debated. Sexual selection theory states that ornaments should be costly to produce, maintain, wear or display to signal quality honestly to potential mates or competitors. An increasing number of studies supports the hypothesis that the degree of melanism covaries with aspects of body condition (e.g. body mass or immunity), which has contributed to change the initial perception that melanin-based colour ornaments entail no costs. Indeed, the expression of many (but not all) melanin-based colour traits is weakly sensitive to the environment but strongly heritable suggesting that these colour traits are relatively cheap to produce and maintain, thus raising the question of how such colour traits could signal quality honestly. Here I review the production, maintenance and wearing/displaying costs that can generate a correlation between melanin-based colouration and body condition, and consider other evolutionary mechanisms that can also lead to covariation between colour and body condition. Because genes controlling melanic traits can affect numerous phenotypic traits, pleiotropy could also explain a linkage between body condition and colouration. Pleiotropy may result in differently coloured individuals signalling different aspects of quality that are maintained by frequency-dependent selection or local adaptation. Colouration may therefore not signal absolute quality to potential mates or competitors (e.g. dark males may not achieve a higher fitness than pale males); otherwise genetic variation would be rapidly depleted by directional selection. As a consequence, selection on heritable melanin-based colouration may not always be directional, but mate choice may be conditional to environmental conditions (i.e. context-dependent sexual selection). Despite the interest of evolutionary biologists in the adaptive value of melanin-based colouration, its actual role in sexual selection is still poorly understood.

Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches

We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.

Little evidence for association between the TGFBR1*6A variant and colorectal cancer: a family-based association study on non-syndromic family members from Australia and Spain.

Genome-wide linkage studies have identified the 9q22 chromosomal region as linked with colorectal cancer (CRC) predisposition. A candidate gene in this region is transforming growth factor beta receptor 1 (TGFBR1). Investigation of TGFBR1 has focused on the common genetic variant rs11466445, a short exonic deletion of nine base pairs which results in truncation of a stretch of nine alanine residues to six alanine residues in the gene product. While the six alanine (*6A) allele has been reported to be associated with increased risk of CRC in some population based study groups this association remains the subject of robust debate. To date, reports have been limited to population-based case-control association studies, or case-control studies of CRC families selecting one affected individual per family. No study has yet taken advantage of all the genetic information provided by multiplex CRC families. Methods: We have tested for an association between rs11466445 and risk of CRC using several family-based statistical tests in a new study group comprising members of non-syndromic high risk CRC families sourced from three familial cancer centres, two in Australia and one in Spain. Results: We report a finding of a nominally significant result using the pedigree-based association test approach (PBAT; p = 0.028), while other family-based tests were non-significant, but with a p-value < 0.10 in each instance. These other tests included the Generalised Disequilibrium Test (GDT; p = 0.085), parent of origin GDT Generalised Disequilibrium Test (GDT-PO; p = 0.081) and empirical Family-Based Association Test (FBAT; p = 0.096, additive model). Related-person case-control testing using the 'More Powerful' Quasi-Likelihood Score Test did not provide any evidence for association (M-QL5; p = 0.41). Conclusions: After conservatively taking into account considerations for multiple hypothesis testing, we find little evidence for an association between the TGFBR1*6A allele and CRC risk in these families. The weak support for an increase in risk in CRC predisposed families is in agreement with recent meta-analyses of case-control studies, which estimate only a modest increase in sporadic CRC risk among 6*A allele carriers.

Drivers and Barriers of Collaboration in the Value Chain of Paperboard-Packed Consumer Goods

Value chain collaboration has been a prevailing topic for research, and there is a constantly growing interest in developing collaborative models for improved efficiency in logistics. One area of collaboration is demand information management, which enables improved visibility and decrease of inventories in the value chain. Outsourcing of non-core competencies has changed the nature of collaboration from intra-enterprise to cross-enterprise activity, and this together with increasing competition in the globalizing markets have created a need for methods and tools for collaborative work. The retailer part in the value chain of consumer packaged goods (CPG) has been studied relatively widely, proven models have been defined, and there exist several best practice collaboration cases. The information and communications technology has developed rapidly, offering efficient solutions and applications to exchange information between value chain partners. However, the majority of CPG industry still works with traditional business models and practices. This concerns especially companies operating in the upstream of the CPG value chain. Demand information for consumer packaged goods originates at retailers' counters, based on consumers' buying decisions. As this information does not get transferred along the value chain towards the upstream parties, each player needs to optimize their part, causing safety margins for inventories and speculation in purchasing decisions. The safety margins increase with each player, resulting in a phenomenon known as the bullwhip effect. The further the company is from the original demand information source, the more distorted the information is. This thesis concentrates on the upstream parts of the value chain of consumer packaged goods, and more precisely the packaging value chain. Packaging is becoming a part of the product with informative and interactive features, and therefore is not just a cost item needed to protect the product. The upstream part of the CPG value chain is distinctive, as the product changes after each involved party, and therefore the original demand information from the retailers cannot be utilized as such – even if it were transferred seamlessly. The objective of this thesis is to examine the main drivers for collaboration, and barriers causing the moderate adaptation level of collaborative models. Another objective is to define a collaborative demand information management model and test it in a pilot business situation in order to see if the barriers can be eliminated. The empirical part of this thesis contains three parts, all related to the research objective, but involving different target groups, viewpoints and research approaches. The study shows evidence that the main barriers for collaboration are very similar to the barriers in the lower part of the same value chain; lack of trust, lack of business case and lack of senior management commitment. Eliminating one of them – the lack of business case – is not enough to eliminate the two other barriers, as the operational model in this thesis shows. The uncertainty of the future, fear of losing an independent position in purchasing decision making and lack of commitment remain strong enough barriers to prevent the implementation of the proposed collaborative business model. The study proposes a new way of defining the value chain processes: it divides the contracting and planning process into two processes, one managing the commercial parts and the other managing the quantity and specification related issues. This model can reduce the resistance to collaboration, as the commercial part of the contracting process would remain the same as in the traditional model. The quantity/specification-related issues would be managed by the parties with the best capabilities and resources, as well as access to the original demand information. The parties in between would be involved in the planning process as well, as their impact for the next party upstream is significant. The study also highlights the future challenges for companies operating in the CPG value chain. The markets are becoming global, with toughening competition. Also, the technology development will most likely continue with a speed exceeding the adaptation capabilities of the industry. Value chains are also becoming increasingly dynamic, which means shorter and more agile business relationships, and at the same time the predictability of consumer demand is getting more difficult due to shorter product life cycles and trends. These changes will certainly have an effect on companies' operational models, but it is very difficult to estimate when and how the proven methods will gain wide enough adaptation to become standards.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Theoretical background for market emergence framework : Case: Electricity Distribution Industry

Both the competitive environment and the internal structure of an industrial organization are typically included in the processes which describe the strategic management processes of the firm, but less attention has been paid to the interdependence between these views. Therefore, this research focuses on explaining the particular conditions of an industry change, which lead managers to realign the firm in respect of its environment for generating competitive advantage. The research question that directs the development of the theoretical framework is: Why do firms outsource some of their functions? The three general stages of the analysis are related to the following research topics: (i) understanding forces that shape the industry, (ii) estimating the impacts of transforming customer preferences, rivalry, and changing capability bases on the relevance of existing assets and activities, and emergence of new business models, and (iii) developing optional structures for future value chains and understanding general boundaries for market emergence. The defined research setting contributes to the managerial research questions “Why do firms reorganize their value chains?”, “Why and how are decisions made?” Combining Transaction Cost Economics (TCE) and Resource-Based View (RBV) within an integrated framework makes it possible to evaluate the two dimensions of a company’s resources, namely the strategic value and transferability. The final decision of restructuring will be made based on an analysis of the actual business potential of the outsourcing, where benefits and risks are evaluated. The firm focuses on the risk of opportunism, hold-up problems, pricing, and opportunities to reach a complete contract, and finally on the direct benefits and risks for financial performance. The supplier analyzes the business potential of an activity outside the specific customer, the amount of customer-specific investments, the service provider’s competitive position, abilities to revenue gains in generic segments, and long-term dependence on the customer.

On Value Creation at an Industrial Intersection – Bioenergy in the Forest and Energy Sectors

The traditional forest industry is a good example of the changing nature of the competitive environment in many industries. Faced with drastic challenges forestindustry companies are forced to search for new value-creating strategies in order to create competitive advantage. The emerging bioenergy business is now offering promising avenues for value creation for both the forest and energy sectors because of their complementary resources and knowledge with respect to bioenergy production from forest-based biomass. The key objective of this dissertation is to examine the sources of sustainable competitive advantage and the value-creation opportunities that are emerging at the intersection between the forest and energy industries. The research topic is considered from different perspectives in order to provide a comprehensive view of the phenomenon. The study discusses the business opportunities that are related to producing bioenergy from forest-based biomass, and sheds light on the greatest challenges and threats influencing the success of collaboration between the forest and energy sectors. In addition, it identifies existing and potential bioenergy actors, and considers the resources and capabilities needed in order to prosper in the bioenergy field. The value-creation perspective is founded on strategic management accounting, the theoretical frameworks are adopted from the field of strategic management, and the future aspect is taken into account through the application of futures studies research methodology. This thesis consists of two parts. The first part provides a synthesis of the overall dissertation, and the second part comprises four complementary research papers. There search setting is explorative in nature, and both qualitative and quantitative research methods are used. As a result, the thesis lays the foundation for non-technological studies on bioenergy. It gives an example of how to study new value-creation opportunities at an industrial intersection, and discusses the main determinants affecting the value-creation process. In order to accomplish these objectives the phenomenon of value creation at the intersection between the forest and energy industries is theorized and connected with the dynamic resource-based view of the firm.

Coopetitive advantage – How firms create and appropriate value by collaborating with their competitors

Collaboration between competing firms (coopetition) has emerged as an important issue forn business practice in many industries. Extant literature has examined coopetition on many levels of analysis, but lacks clarity in distinguishing it explicitly from cooperation between noncompeting organizations. Because of this, the performance implications of coopetition from the perspective of an individual firm are still ambiguous – some research suggests positive results whereas other studies suggest detrimental outcomes. The aim in this dissertation is to narrow these gaps by exploring how firms create and appropriate value through collaboration with their competitors. The dissertation is divided into two parts. The first part comprises an overview of the relevant literature, as well as the conclusions of the whole study, and the second part includes six research publications. Both qualitative and quantitative methodologies are utilized. The results suggest that coopetition embodies the distinctive logic of value creation and appropriation from the perspective of an individual firm, and thus differs in terms of performance implications from cooperation between non-competitors. The distinction comes from the fact that competitors have somewhat similar understanding, capabilities and interest related to certain markets, which is potentially both challenging and beneficial in terms of the individual firm’s competitiveness. It appears from the findings that there are distinctive firm-external and firm-specific factors affecting the success of a coopetition strategy. This study makes three main contributions. First, on the conceptual level it shows the distinction between coopetition and cooperation between non-rivals as a collaborative inter-organizational relationship. Secondly, it sets out a framework and propositions that enhance understanding of how value is created and appropriated in coopetition from the perspective of an individual firm. Thirdly, it offers empirical evidence of how coopetition affects firms’ innovation and market performance, and identifies the focal internal and external factors involved. In general terms, the thesis adds to our knowledge of how a firm can successfully utilize a coopetition strategy in its pursuit of improved performance.

The role of power relations in strategic supply management – A value net approach

Supplier relationships are key elements of supply management and thus have attracted substantial research interest among academics and practitioners. The collaborative nature of relationships has been the focus of the mainstream research, and limited interest has been channelled towards power in buyer–supplier relationships. However, power is one of the key factors determining the outcomes in many business relations. Hence, one of the main objectives of this dissertation is to clarify how power may influence the nature of buyer–supplier relationships and, moreover, the depth of collaboration. Another main objective is to clarify the role of power relations in strategic supply management. Given the different nature of relationships, the firm needs divergent strategies in its supply management in order to handle them efficiently. Power has been identified as one of the factors that affect the nature of buyer–supplier relationships, and firms should thus develop strategies for handling power relations. Three research questions are addressed in pursuit of these objectives, the aim being to clarify the sources of power, the influence of power on collaboration, and the role of buyer–supplier relationships in the firm’s supply strategy. This dissertation has two parts. The first part provides a synthesis of the overall dissertation, and the second part comprises five complementary research papers. The qualitative research method is applied in an empirical case study from the Finnish food industry. The main contribution of this dissertation is that it clarifies the role of power relations in strategic supply management in value nets, and discloses the nature of power as an influencing factor in supplier relationships. It extends the discussion on power in buyer– supplier relationships in highlighting the context of networks and raising the question of network effects on power relations. It also illustrates how power positions and power relations in value nets can be determined based on the sources of power of the network actors, and shows their influence on collaboration.

Virtual Professional Network as a Value Creator in the Dental Business

The research of virtual professional networks has been enormous but the lack of research in the dental field was obvious. This study focuses on those uses and gratifications, and motives of participants that a virtual pro-fessional network should fulfil. The aim of this study is to understand the factors behind the successful virtual professional network, and motives of participants that support a particular business network’s building up for contributing its further success. In this study the focus is on particular mo-tives, needs and benefits of participants that are significant for the net-work’s further development. The study will explore relevant scientific research and theory that is char-acteristic in networking, and theories of user’s needs and motives. Empiri-cal data was collected from dental professionals by net based question-naire that was sent by e-mail. Data analysis was done by quantitative fac-tor analysis. The findings of this study were obvious that virtual knowledge of implantology is inadequate and knowledge is rather difficult to find in the Internet. Sharing of virtual knowledge, net-learning and communication were seen to improve the quality of impolantological professionalism and also the development of these areas was experienced essential. On the grounds of this study a host of a virtual professional network can focus on those aspects that serve the users at best, can develop professionalism in implantology and can profit in its own business operations.

Customer Driven Service Development – Technology-based Care and Services for the Elderly

The objective of this master’s thesis was to examine technology-based smart home devices and services. Topic was approached through basic theories, transaction cost theory and resource-based view in order to build basis for this thesis. Conceptual framework was discussed by means of networks, value networks and service systems which provide a useful framework for service development. The needs of the elderly living at home were discussed in order to find out which technology-based services could be used to satisfy the needs. Segmentation and need data collected previously during proactive home visits was exploited and additionally a survey targeted to experts and professionals of social and health care sector was done to verify the needs. Finally, the results of the survey were analyzed using quality function deployment method to figure out the most important and suitable service offerings for the elderly. As a conclusion of analysis, social media and monitoring services are the most useful technology-based services. However, traditional home services will still maintain their necessity too.

Components of customer value in nurse call solutions

This study aimed to identify the value components of nurse call solutions. The value creation of such systems was analyzed by using a framework that was created based on the existing customer value literature. The empirical part of the study was conducted as a multiple-case study by using qualitative research methods. The data for the analysis was gathered through structured interviews in ten Finnish eldercare centers. The results indicate that a nurse call solution creates value for eldercare centers by increasing the safety of the residents, and by improving the efficiency of the staff while also providing cost savings.