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Chronic tinnitus, the perception of a phantom sound in the absence of corresponding stimulus, is a condition known to affect patients&rsquo, quality of life. Recent advances in mHealth have enabled patients to maintain a &lsquo, disease journal&rsquo, of ecologically-valid momentary assessments, improving patients&rsquo, own awareness of their disease while also providing clinicians valuable data for research. In this study, we investigate the effect of non-personalised tips on patients&rsquo, perception of tinnitus, and on their continued use of the application. The data collected from the study involved three groups of patients that used the app for 16 weeks. Groups A &amp, Y were exposed to feedback from the start of the study, while group B only received tips for the second half of the study. Groups A and Y were run by different supervisors and also differed in the number of hospital visits during the study. Users of Group A and B underwent assessment at baseline, mid-study, post-study and follow-up, while users of group Y were only assessed at baseline and post-study. It is seen that the users in group B use the app for longer, and also more often during the day. The answers of the users to the Ecological Momentary Assessments are seen to form clusters where the degree to which the tinnitus distress depends on tinnitus loudness varies. Additionally, cluster-level models were able to predict new unseen data with better accuracy than a single global model. This strengthens the argument that the discovered clusters really do reflect underlying patterns in disease expression.

The utilization of mobile technology in the field of medicine and healthcare has become a decisive aspect. The entire field is denoted as mobile health (mHealth). For mHealth, the development and use of mobile applications are crucial. The purposes and goals of mHealth apps, in turn, are manifold. As a consequence, a plethora of mHealth apps can be found in the app stores. Interestingly, for patients, users, and health care providers that consider to use mHealth apps one aspect has been less pursued so far: Systematic and standardized ways that help about the quality of an app or its medical evidence are mainly missing. The Mobile App Rating Scale (MARS) is a standardized instrument that aims at the systematic and comparable evaluation of the quality of mobile health apps as well as categorizing their goals and functions. It comprises 23 items, which are utilized to calculate a rating scale. Having MARS in mind, a database was developed that is called Mobile Health App Database (MHAD). The latter offers technical features to systematically utilize the MARS for researchers as well as clinicians and end-users that (i) want to evaluate apps as well as (ii) want an interactive and easy-to-use web interface that shows the results of the rating procedure. MHAD comprises a rating platform that supports the conduction of MARS ratings and their release process. With the information platform, a web application was developed that prepares the data stored in the rating platform for being freely viewed and studied by users, patients, and health care providers. The goal of MHAD constitutes to be an open science repository that encourages researchers to release their MARS ratings to a broader audience. Such repositories become more and more important in many fields, especially in the field of mHealth.

Tinnitus is a condition associated with a continuous noise in the ears or head and can arise from many different medical disorders. The perception of tinnitus can vary within and between days. In the recent years, Ecological Momentary Assessments of tinnitus have been used to investigate these tinnitus variations during the daily life of the patients. In the last five years, several independent studies have used Ecological Momentary Assessment to assess tinnitus. With this chapter, we want to review the current state of this research. All the EMA studies revealed a considerable variability of tinnitus loudness and tinnitus distress. It has been found that emotional states and emotional dynamics, the subjectively perceived stress level and the time of the day exert influence on the tinnitus variability. In summary, the EMA method revealed a good potential to improve our scientific understanding of tinnitus. Furthermore, it also showed that it can be used to understand the individual differences of tinnitus—and may even be used as a tool for individualized diagnostic and treatment. We conclude, that the results of the EMA studies can lead to improvements of existing research methods in the field of tinnitus.

This paper uses a large panel database to investigate the determinants of forest clearing in Indonesian kabupatens since 2005. Our study incorporates short-run changes in prices and demands for palm oil and wood products, as well as the exchange rate, the real interest rate, land-use zoning, forest protection, the estimated opportunity cost of forested land, the quality of local governance, the poverty rate, population density, the availability of communications infrastructure, transport cost, local rainfall and terrain slope. The econometric results highlight the role of dynamic economic factors in forest clearing: significant roles for lagged changes in all the short-run economic variables—product prices, demands, the exchange rate and the real interest rate—as well as communications infrastructure, some types of commercial zoning, rainfall and terrain slope. We find no significance for the other variables, although our measure of protected-area status is too general for strong conclusions to be drawn about the empirical relationship between forest clearing and protection. It is also possible that the insignificance of transport cost in our results is due to collinearity with our proxy for communications cost, and/or the offsetting effects of transport cost on the direct profitability of forest clearing (negative) and the effectiveness of local forest regulation (positive). Our results strongly support a model of forest clearing as an investment that is highly sensitive to expectations about future forest product prices and demands, as well as changes in the cost of capital (indexed by the real interest rate), the relative cost of local inputs (indexed by the exchange rate), and the cost of land clearing (indexed by local precipitation). By implication, the opportunity cost of forested land fluctuates widely with changes in international markets and decisions by Indonesia's financial authorities about the exchange and interest rates. Our results suggest that forest conservation programs are unlikely to succeed if they ignore such powerful forces.

Conservation of habitats is critical for survival of endangered tigers. This paper develops a resource allocation model for tiger habitat protection incorporating information about threats to particular tiger subspecies, the quality of remaining habitat areas, the observed effectiveness of habitat protection by country, and the potential costs of protection projects for 74 habitats in Asia. Implementation of the model moves through two stages. The first stage employs user-specified weights to combine numerous subindices into composite indices of species threat, habitat quality, potential project costs and protection effectiveness. The second stage employs additional user-specified weights to combine the composite indices into priority scores and potential project budget shares for all 74 habitat areas. Exploration of model results suggests that changes in user-specified weights can have very significant consequences for habitat priority scores. Illustrative scenarios indicate that no single priority ordering can be prescribed in such a diverse setting, and actual priorities will depend on the preferences of decision-makers, as revealed in the weights assigned to species threats, habitat quality, cost elements, and effective protection. At the same time, the model can make a useful contribution by identifying priority orderings that are consistent with different sets of preferences. And it can inform policy discussions by allowing for extended exploration of alternative strategies, along with providing feedback to decision makers about the implicit preferences associated with their resource allocation decisions.

In this paper, we develop and illustrate a prototype incentive system for promoting rapid reduction of forest clearing in tropical countries. Our proposed Tropical Forest Protection Fund (TFPF) is a cash-on-delivery system that rewards independently monitored performance without formal contracts. The system responds to forest tenure problems in many countries by dividing incentive payments between national governments, which command the greatest number of instruments that affect forest clearing, and indigenous communities, which often have tenure rights in forested lands. The TFPF incorporates both monetary and reputational incentives, which are calculated quarterly. The monetary incentives are unconditional cash transfers based on measured performance, while the reputational incentives are publicly disclosed, color-coded performance ratings for each country. The incentives include rewards for: (1) exceeding long-run expectations, given a country’s forest clearing history and development status; (2) meeting or exceeding global REDD goals; and (3) achieving an immediate reduction in forest clearing. Drawing on monthly forest clearing indicators from the new FORMA (Forest Monitoring for Action) database, we illustrate a prototype TFPF for eight East Asian countries: Cambodia, China, Indonesia, Lao PDR, Malaysia, Myanmar, Thailand, and Vietnam. A system with identical design principles could be implemented by single or multiple donors for individual or multiple forest proprietors within one or more countries, as well as national or local governments in individual countries, tropical regions, or the global pan-tropics. Our results demonstrate the importance of financial flexibility in the design of the proposed TFPF. Its incentives are calculated to induce a massive, rapid reduction of tropical forest clearing. If that occurs, a TFPF for East Asia will need standby authority for disbursements that may total $10–14 billion annually for the next two decades. This financial burden will not persist, however, because the TFPF is designed to self-liquidate once all recipient countries have achieved clearly specified benchmarks. We estimate that the TFPF can be closed by 2070, with its major financial responsibility discharged by 2040.

A stream of users' interactions with an mHealth app can be seen as the result of a stochastic process that can be captured by an algorithm that learns over the whole stream. But is it only one process? We investigate to what extend learning for each user separately delivers better predictions than learning one model over the whole stream. Our application scenario is the prediction of Ecological Momentary Assessments (EMA) for an mHealth app (TinnitusTipps) on tinnitus. The data were recorded as part of a pilot study, in which one group of users received non-personalized suggestions (tips) throughout the study, while the other group received tips only during the second half of the study. Our method encompasses user-centric and global stream learning for EMA prediction, combined under a Contextual Multi-Armed Bandit (CMAB) that captures the context of each user group and incorporates the prediction quality of each learner into the reward function. We show that user-centric learning is beneficial for users who contribute many EMA, while a learner over the whole stream is better for users with few EMA.