In this paper, we investigate how crude oil price and volume traded affected the profitability of oil and gas companies in the United Kingdom (UK) since the financial crisis started in 2008. The study benefit from insights of the financial statements, to develop a model that focuses on how changes in oil price impact corporate performance. In order to observe the financial indicators that influence the performance, as well as the effects that changes in oil prices and demand of crude oil have on the profitability of oil and gas companies, we apply comparative regression analysis, including the generalised method of moments estimation technique for panel data set. The sample is consisting of 31 oil and gas companies in the UK, and the period analysed is 2006–2014. Results show that profitable oil and gas companies managed to face the drop in oil price and recover, characterized by significant cash flows and stock turnover, efficient use of assets, and high solvency rates. Although the oil price and volume traded do not significantly affect profitability and other financial ratios, if the oil price continues to decrease, it would permanently alter both the UK economy and oil and gas companies. In order to survive, companies make drastic cuts and defer essential investments, often at the long-term expense of asset performance. This study is important in a world where the energy consumption steadily grew over time. However, the renewable energy is cheaper and more environmentally friendly, and thus, countries where oil and gas industry is one of the most popular sectors face an economic decline. These results could be useful for investors, managers or decision makers, reclaiming strategic decisions in the current uncertain and volatile environment. This paper intends to investigate the relationship between oil price and corporate performance in a European country where the energy industry is one of the essential components of the economy. The UK offshore oil and gas industry used to contribute to 2.5% of GDP before 2010, but in 2015 it only counted for 0.8%. Fiscal revenues declined from approximately £7 billion before 2010 to 2 billion in 2015 and to almost zero in 2016. Also, jobs continue to be made redundant, leaving a high unemployment rate. Although it is intuitive for the performance of oil and gas companies to be strongly related to oil prices, there are few papers to study this relationship, while many focused on the impact of oil price shocks on a macroeconomic level. This paper aims to observe to what extent were the oil and gas companies affected after the financial crisis began, and since the oil price dropped, to review corporate performance in times of high volatility and increased financial risks.st century and accounted for approximately 60% of the world’s growth in oil consumption over the last decade. The European Union is situated between the US and China in the list of countries by oil consumption, relying on net imports for 89% of the oil products consumed. The major producer of crude oil in the EU is the United Kingdom, followed by Denmark, Italy, and Romania . The financial markets developed over the oil-related funds all over the world and thus many investors pay great attention to oil price fluctuations, while oil and gas companies increased the number of mutual and exchange-traded funds.The world is dependent on energy, and thus consumption steadily grew over the last decades. Large economies such as the United States and China became the most significant oil consumers. China doubled its energy consumption over the first decade of the 21Nowadays, even the most profitable and stable companies suffer from the crisis threatening the oil and gas industry. After an extended period of high oil prices, the industry is now facing an extended period of low prices, amplified by a decrease in the operational efficiency of oil and gas companies due to higher extraction costs. On the contrary, economical fossil fuels allow higher standards of living for the population and thus, economic growth on this side, but significant costs regarding pollution or oil spills.The oil and gas industry was always volatile, facing boom-and-boost cycles. Thereby, companies tend to invest in assets and raise employees number in order to grow during prosperous periods, while making drastic cuts and dropping profitable projects, to minimize costs during downturns.Economic factors also put pressure on this industry, while digital technologies offer new tools that simplify operational processes and increase production. However, these are costly and require intelligent investing. Therefore, oil and gas companies are forced to create strategies for sustainable change, bringing stability, improving the primary performance metrics and operational excellence through booms and busts.The main contribution of this paper comes from the analysis perspective, including besides the financial information, data reflecting the dynamics of the oil industry to observe the corporate performance, which is not only critical to companies operating in this field, but also to oil-dependent countries such as the UK. This research was undertaken to analyse the profitability of oil and gas companies in the UK, where unemployment rate and losses steadily grew over the last years due to the decrease in oil price, affecting the economy at different levels. The profitability is analysed based on assets efficiency, liquidity, and solvency, concerning crude oil prices. As the literature was primarily focused on the relationship between oil prices and stock markets, our study analyses the performance of oil and gas companies over the financial crisis and the periods of falling oil prices, reviewing their operational activity, and their ability to generate profits. Therefore, we seek to fill the gap in the present literature, developing the research into adjacent points of interest that have not been debated recently. In addition, the study is generalised to the corporate performance in the oil and gas industry, in the UK, while previous studies focused on the effects that oil prices have on individual companies.The following section reviews the literature related to oil and gas industry performance over time. The third section presents the data used and the methodology. Section 4 describes the empirical results obtained through different stages of analysis. Firstly, correlations between all variables are discussed, followed by a presentation of the baseline regression results. Secondly, a non-linear analysis has been employed in order to capture the structural breaks in oil and gas companies performance, financial ratios, and crude oil prices. These various stages of the study were also intended to test the results robustness. Section 5 concludes.The financial crisis represented a turning point for some major national oil companies around the world. For example, although the competition for resources increased, in China, it was discovered that some of the world’s biggest oil companies became the most efficient regarding production, mostly based on investment opportunities, expansions, and international cooperation agreements. National Chinese oil companies were also an advantage because of the production scale, and due to domestic macroeconomic regulations focused on protecting the monopolistic organisations and based on the gradual increase in the domestic oil demand. However, it was admitted that there is an unobserved heterogeneity with parameters related to the centrally planned economy or institutional environment, which may influence the analysis and cause unbiased results in oil companies efficiency on the subject of production . These mStudies also proved that corporate governance has an essential impact on oil companies’ profitability and performance. Besides, ownership concentration also has a strong influence on firm performance, showing a nonlinear relationship. Studies prove the fact that, on a risk-adjusted basis, companies with strong shareholders rights outperform, proving that good governance has a positive impact on corporate performance ,4. FurthThe fact that changes in oil price have a positive effect on stock returns, and an increase in oil prices does not depress the demand of oil to a large extent, shows that oil and gas companies easily pass oil price increases on to customers. Depending on the corporate culture, managers and shareholders are focused on maximising companies’ operational efficiency over long-term through constant returns and gradual growth. Oil companies should also have an increased level of control and transparency in order to safeguard investor’s interests and bank officials offering resources for new investments . MoreoveThe liberalization of capital flows increased the competition in globalized markets, although the EU members tried to reduce the disparities between the integrated European areas. In the recent context, companies reach competitiveness through innovation and research, focusing on increasing productivity, but also supporting sustainable economic growth and citizens’ quality of life . ResearcIn developed countries, oil and gas companies have robust command-and-control regulations, while the lack of control, corruption and weak enforcement of legislation penalise returns and productivity in developing economies. This is a strong reason for companies to use their know-how and resources to change the situation in developing countries and in economically disadvantaged communities, where selling off natural resources causes poverty and low wages ,16. AlthThe aim of this study contributes significantly to this field of research as it focuses on the question related to what extent the oil price may drop until it would permanently affect oil and gas companies performance and the UK economy. Considering that the relationship between the stock prices and oil price was analysed over time, our study will focus more on companies’ financial performance rather than on shareholders’ returns, reviewing their operational activity as well as the level of the taxes paid, based on oil consumption and its prices. The period analysed is suitable to reveal if there is an effect over the short or long-term period, and the sample is adequate to consider the results specific to the oil and gas industry in the UK. Therefore, the study is more general than previous works that considered influences on individual companies, and thus a limited number of companies.This study evaluates the profitability of oil and gas companies in the UK, based on different financial indicators, but also trying to capture to what extent profitability was affected by the changes in crude oil prices. To obtain more information on the profitability of oil and gas companies, the analysis will include besides the evidence on oil prices and corporate performance, financial information related to the companies, such as assets efficiency, liquidity, solvency or the level of taxes paid. Considering the recent steady period of low oil prices, and the switch towards renewable energies, it is expected for oil and gas companies profitability to drop. Therefore, it is essential to overview how efficiently they operate and the financial risks undertaken.The analysis is based on annual data, over the period 2006–2014. The following financial indicators and ratios used in this study were collected from Amadeus database, which offers financial information on companies across Europe: return on equity (ROE), cash flow over operating revenue (CF/OpRev), current ratio (CurrRat), Asset turnover (AssTn), solvency ratio (SolvRat), stock turnover (StockTn), and finally, taxation, computed as the natural logarithm of the value paid by companies every year as taxes (lTax). The data related to the oil industry  was obtained from the website Investing UK. It was then used to compute three control variables, with identical annual values regardless of the company considered: OilPrice, as the annual average of the crude oil price, OilVolume, as the annual average amount of oil traded, and a dummy variable (dummyOilPrice) which takes the value 1 when the annual average oil price drops compared to the previous year’s average, or 0 if it increases.In order to obtain robust results, we collected data for a limited sample of 31 oil and gas companies, due to the fact that many companies in this industry had missing data from their balance sheets, profit and loss accounts, and global ratios over the period considered. The data collected were analysed with STATA, a statistical software package commonly used in the economics field, to observe statistical analysis, graphics and regressions. All the results further presented and those from the “Results and analysis” section represent authors’ computations in STATA.Return on equity is on average 27.67%, which indicates high profitability of oil and gas companies in relation to the book value of shareholders’ equity. The cash flow over operating revenue ratio also proves that oil and gas companies are profitable, showing investors and shareholders that most oil and gas companies can generate consistent cash from their sales. With an average current ratio of 2.5, companies analysed can pay off their short-term liabilities based on their current assets, which is another proof that they are financially stable. Based on the average asset turnover of 1.45, the oil and gas companies are efficient regarding their assets, as they are generating sufficient sales revenue. The average solvency ratio of 46.7, the companies observed also prove that they can meet their long-term obligations, sustaining their operations indefinitely. The stock turnover is very high, approximately 45, showing that the oil and gas companies’ inventory is used or sold quickly.Tax variable shows an average of approximately $150 million  paid annually by the oil and gas companies in the UK. For this variable, some data is missing as companies rarely registered negative values on Taxation, and therefore these values could not be computed based on the logarithm.Over the period analysed, from 2006 to 2014, the average price of the crude oil was $84.92, while the volume of the oil traded was of approximately 5 barrels/month, increasing very much from the first year until the last ones.Profitability will be considered as a function of multiple indicators, some internal and other exogenous to the companies, as presented in the following equation:In order to test the results robustness, another model will be tested, based on the previous equation where the three control variables, related to the oil price and volume traded, are added:i represents the unknown intercept of each of the 31 companies included in the sample (i = 1…31), t is the year analysed (t = 2006…2014), the coefficients associated to each explanatory variable are the βs, and the error term is εit.The linear model of the profitability function can be expressed by the following two equations:The relationship between oil price and returns was mostly studied through vector autoregressive—VAR or structural vector autoregressive models—SVAR ,7. WithiFirst of all, this analysis reveals, through descriptive statistics, the dynamics of the variables observed, capturing their primary influences over profitability. In order to test whether or not the explanatory variables have a significant impact on return on equity, a comparison between different regression models will be realised: the first one considered is Pooled Ordinary Least Square (OLS) model, followed by Fixed Effect (FE) and Random Effect (RE) models. All will be regressed on the overall panel of oil and gas companies, for the nine-year period. One of the advantages of panel data analysis is accounting for individual heterogeneity while controlling for unobserved differences in corporate practices through time. The Hausman Test will be used to reflect the accuracy of fixed effect and random effect models. Therefore, if there are specific companies characteristics which would influence other variables, the fixed effect model is more appropriate. On the contrary, the random effect model is useful for samples in which variation across entities are random and uncorrelated with explanatory variables.The sample is subject to the inverse causality of the explanatory variables towards the dependent one. Under these conditions, methods such as OLS, FE, and RE may return inaccurate estimates, using linear regression techniques. The generalised method of moments (GMM), or instrumental variable panel VAR, may be used to resolve issues such as simultaneity bias, reverse causality or omitted variables. Therefore, GMM is employed as a final stage in the comparative regression analysis, being a dynamic model, which uses a series of instrumental variables, generated from lagged dependent variables.After testing the linear relationships between variables, revealing the most influential factors for profitability, a new stage of the analysis will be employed, using quadratic regression analysis. The stage actually means that the regression models previously used will be retested adding for every explanatory variable its quadratic form. This will indicate if there is a non-linear effect on the performance of oil and gas companies rather than a straight influence from the variables used to explain changes in ROE.The matrix presented in It seems that the cash flow over operating revenue ratio, the asset turnover, and stock turnover positively influence the profitability indicator. Moreover, the solvency ratio and oil price also appear to be statistically significant factors, with a negative influence on ROE. The other variables, current ratio, the level of taxation and the volume of oil traded also restrict the return on equity, but their correlation coefficients are small and are not statistically significant, indicating very low to no impact.The rest of the variables present various significant correlations between each other, but they do not present substantial coefficients, which means that they can be included in the same regression model without implying autocorrelation issues related to independent variables.Overall, the cash flow over operating revenue ratio is in a direct relationship with the current and solvency ratios, and in a negative relationship with the asset turnover and the level of taxes paid. Moreover, the ability to pay off short-term liabilities with current assets should increase along with the solvency ratio and stock turnover, being affected, by great asset turnover and substantial levels of taxes paid. Results also reveal an indirect relationship between asset turnover and solvency ratio, indicating reduced asset efficiency when oil and gas companies have high debt ratios. Lower taxes are associated with higher solvency ratios, based on lower profits and interest deductibility. Finally, the volume of the oil traded seems to be dependent only on the oil price, following the same trend.The comparative regression models were computed, and the main results were included in From all the explanatory variables, results show that asset turnover and cash flow over operating revenue have the highest regression coefficients. Based on their values, a unit change in the asset turnover ratio will bring more than five units change in the same direction of the ROE, while one unit change in the cash-flow ratio induces a similar change in ROE. Although the asset turnover coefficient is the highest, the impact on ROE is at a lower level because the average value of the asset turnover (1.45) is 20 times lower than the average ROE (22.67). Along with these two variables, stock turnover also has a significant direct impact on ROE. Based on these positive coefficients, statistically significant, we can say that the profitability of oil and gas companies increases with the level of cash generated and the efficient usage of assets, as well as based on the number of times the inventory is sold or used over a year.Solvency ratio is also an influential variable, having a negative influence on ROE. This indicates that oil and gas companies in the UK perform better when they dispose of more liabilities (registering a higher degree of solvency). Also, the current ratio also has an indirect impact on profitability, but this is not statistically significant in any of the regression models used. This might also be related to the level of short-term debt, which may affect the general profitability when it increases.The level of taxation also has a positive effect on ROE, with statistically significant coefficients in all the models besides OLS and GMM. Considering that the taxation variable includes logarithm values of the taxes paid annually by the oil and gas companies, having an average of 11.89 (compared to 27.67 for average ROE), based on the statistically significant regression coefficients of approximately 7, we can can assume that a high level of taxes paid does not affect the oil and gas companies profitability, as they do not face high tax burdens.The Pooled OLS model applied on return on equity, shows that 31% of the variation in ROE is explained by the independent variables used. The fixed effects (FE), followed by random effects (RE) models, return higher R squared values, indicating that these are better models for the profitability indicator studied. The Hausman test suggests that there are specific characteristics in oil and gas companies, which influence the relationships between variables. There is enough reason for computing a corrected fixed-effect model (denoted “FE (corr.)”), adjusting for time fixed effects and heteroskedasticity to return reliable results.The final model employed was the Generalized Method of Moments using the lagged dependent variable. It is more performant regarding simultaneity bias, reverse causality, and omitted variables, and thus its results should be the most reliable in this type of analysis. They are also robust, due to the fact that they are similar to the results returned by the static models used. In addition, the profitability variable indicates a dependence on the previous years ROE levels. The Sargan test validates the over-identifying restrictions, with a substantial probability of 81%, while the Arrelano Bond test for serial correlation in the first-differenced errors also validates the GMM models results.In order to test the robustness again, we include in the model the three control variables related to oil price and volume traded over the period analysed. The comparative regressions results are included in Slight changes appear only in term of the coefficient values, which are a little higher for most variables. However, the statistically significant regression coefficients have the same signs and indicate the same independent variables with a positive influence on ROE regardless of the model used, cash flow/operating revenue, asset turnover, stock turnover, and negative influence from the solvency ratio. The taxation variable returns a significant direct impact only from the fixed and random effect models.Regarding the control variables, all regression coefficients show a negative impact on ROE. While the results show that oil and gas companies tend to be more profitable when oil price and the volume of the oil traded decrease, this would not be the logic effect. However, we can assume that in the first part of the period analysed, when the crude oil price and volume traded were reduced, the oil and gas companies from the UK were more profitable. As long as the regression coefficients of the control variables are not statistically significant, it means that this assumption cannot be confirmed. However, the GMM results indicate a negative relationship between the dummy and ROE. As the dummy was computed in order to capture the oil price drop , this coefficient suggests that over the nine years period, a decrease in oil prices did affect the profitability of oil and gas companies.The goodness of fit indicator for these models show again a 32% of the variation in ROE explained through the Pooled Ordinary Least Square regression model, and 40% of the variation explained by the fixed effects and random effects models. The Hausman test suggests that in this case, random effects are more appropriate for the oil and gas companies database, indicating that the specific company characteristics do not affect the results. Therefore, a new random effect model corrected for heteroskedasticity was tested. The GMM model shows similar results, including the fact that profitability is directly dependent on the previous years levels, with a Sargan test which validates the over-identifying restrictions with a probability of 89%. The Arellano Bond test for serial correlation in the first-differenced errors also confirms the GMM models results.The cash flow over operating revenue ratio is a complex indicator as it refers to more than company sales of goods and services. This ratio offers an overview of the financial health of the company, the sales effectiveness, its liquidity and cash management. Therefore, higher ratios reflect companies’ ability to generate cash from its sales. For the oil and gas companies in the UK, it appears that the return on equity increases along with the cash flows from operating activities, but for a ratio up to 50%. The figure below  indicateFor the companies analysed, there are minor differences between the current ratio and liquidity ratio. Therefore we chose the first, used to measure the firm’s ability to pay off its short-term liabilities with its current assets. As observed in As seen in The stock turnover, reflecting the number of times the inventory is sold or used over a period of one year, is very high for the UK oil and gas companies, indicating operational efficiency in the asset management department. For the oil and gas companies analysed, more than 50% pay taxes higher than 100 million Euros per year. Over the period analysed, the oil price had an average price ranging from 64 $/barrel to a little below 100 $/barrel. The first part of the period indicated lower prices, with the peak in 2008 (98.58 $/barrel), while from 2011 the price oscillated above 90 $/barrel. Considering this information, it can be presumed from the graph illustrated in Observing from the descriptive analysis that the independent variables, except the solvency ratio, have a non-linear relationship with companies profitability, we decided to retest the regression model, including quadratic variables as well. We assume that the relationships discovered through linear regression analysis are the main ones, and the different influences occur in exceptional cases, associated with the squared variables. Results are presented in the following table .Results show that cash flow over operating revenue has a positive influence on ROE, but from a certain point (from a ratio of 50 as suggested in The current ratio indicates a positive influence and a negative one from the squared ratio. The graph presented in Asset turnover coefficients follow the trend reflected in Solvency ratio only has a statistically significant indirect impact on ROE, as shown in The stock turnover confirms the inverted U-shape presented in Taxation variables also follow the trend presented in the descriptive analysis: for taxes up to 160 millions of Euros (see comments on This quadratic regression model indicates higher goodness of fit indicators. The Pooled Ordinary Least Square regression model surprises 52% of the variation in ROE, increasing to 55% of the variation explained through the fixed effects model. The Hausman test suggests that this is more appropriate for the oil and gas companies’ database, as specific company characteristics affect the results. The GMM model is the best employed so far, with a Sargan test validating the over-identifying restrictions with a probability of 99%, and the serial correlation in the first-differenced errors confirming the GMM results.Considering that the oil price and oil volume variables also revealed a non-linear relationship with ROE, we retested the quadratic regression model, including the three control variables, even with the squared variables of oil price and oil volume. There are no significant changes in the results , provingThe control variables do not reveal statistically significant regression coefficients, except in the GMM case, where the basic variables of the oil price have a negative influence on ROE, showing that lower prices of crude oil are associated to higher profitability over the period analysed.The goodness of fit indicators for this updated quadratic regression model are slightly higher than the rest, showing that the Pooled Ordinary Least Square regression model surprises 53% of the variation in ROE, increasing to 56% of the variation explained through the fixed effects model. The Hausman test suggests again that company characteristics affect the results and the fixed effects model is more appropriate. In addition, Sargan test attributed to the GMM validates the over-identifying restrictions with a probability of 99.95%.According to the homogeneous values of the data analysed, the profitability of oil and gas companies increases with the level of cash generated and the efficient usage of assets, as well as based on the number of times the inventory is sold or used over a year. These show a productive operational activity for oil and gas companies in the UK. Correspondingly, these tend to perform better when they dispose of more liabilities. While the oil price changes and oil volume traded does not seem to have a substantial impact on the analysed companies, results suggest that a decrease in oil prices affects their profitability. Although it seems that companies easily pass the oil price increases on to customers, if the oil price continues to drop, it would permanently affect both the oil and gas companies and the economy, as long as oil and gas industry is still an important pillar for the UK economy, bringing significant tax revenues.As national strategic resources, the North Sea oil and gas is essential to the economy and development of the United Kingdom. With large energy companies operating, two of the six supermajor oil and gas companies have their headquarters in the UK: BP and Royal Dutch Shell. However, since the financial crisis started, due to the oil price volatility, the employment in the UK offshore oil and gas industry was reduced with 25% over the last five years, while oil and gas companies reduced their activity.Although lately, they faced the challenges of a volatile environment with a reduction in production, oil and gas companies managed to recover and continue to register large profit margins and returns. The high-performance organisation is obtainable through operational efficiency in the asset management department, efficiently use of assets in generating sales, and ability to permanently generate cash from sales. Oil and gas companies seem to be performant in the use of liabilities, with significant levels of solvency, and the higher the amount of taxes paid are, the more profitable regarding shareholders’ equity they tend to be. It also shows that the oil and gas industry continues to be an essential pillar in the UK economy, providing substantial fiscal revenues based on profitable oil and gas companies.The latest dropout in oil price and volume traded affected the return on equity, as oil and gas companies indicated higher profitability at the beginning of the period analysed when, although the oil price and volume traded were at their minimum over the nine years observed, the companies registered the highest returns and profit margins. If the oil price reduction continues, this will continue to affect oil and gas companies performance, along with the UK economy, through increased unemployment and reduced taxes paid to the government, towards a permanent decrease in GDP.and, results indicate that there is unobserved heterogeneity in the sample consisting of 31 oil companies, and therefore, estimation techniques employed may produce biased efficiency estimates. On the other hand, results demonstrated their robustness through different regression models and techniques, proving the consistency of this research.Problems related to various impacts of the global financial crisis permanently challenge the oil and gas companies, to cope with the decrease in oil price and the changes in production and revenues. Therefore, the influence of unobserved heterogeneity in the parameters used in this paper, and the ways to conduct quantitative analysis to observe these influential factors were exemplified in different stages of the analysis. On the one hNowadays, the largest oil and gas companies seem to take the climate commitment very seriously and pledge to reduce the net carbon emission in the following decades. The latest requirements demand that companies disclose the climate change risks on their business, so the shareholders understand the implications of company activities. Although their shareholders, as well as consumers, approve the change from fossil fuels, oil and gas companies seem to undertake small investments in renewable energy compared to their overall revenues. Overall, considering the importance of renewable energy stocks in the future, we realise that increased oil prices and high prices for other types of fossil fuels will just increase the demand for clean energy products. Even though oil and gas companies seem to have steady profits and returns, over the long-term, the only solution for them to keep their high-performance is switching towards eco-friendly policies.


This data paper presents a reconstruction of historical ports and coastal routes in England and Wales during the age of the sailing ship, ending at the beginning of the twentieth century. The dataset was created by an amalgamation of twenty different sources, including geographical data, primary sources and secondary literature. Ports found in historical documents were listed by year of appearance and georeferenced. Ports that appear in multiple sources were listed only once. Coastal routes between ports were drawn based on navigation charts and bathymetry data, distinguishing five categories with different characteristics. Visibility from the coast was deduced from elevation rasters and lighthouse locations. Subsequently both ports and coastal routes were checked using topological rules to ensure the connectivity of the network. The data is provided in shapefile format with all the attributes and can be analysed using Geographical Information Systems (GIS) for different types of geographical and historical studies. The aimThe data can be used to better understand long-term effects of transport infrastructure on social and economic history – specifically from maritime trade 21.1Drawing on eleven different sources, we created a list of ports and other smaller places where coasting vessels regularly landed to load and discharge goods. The existing literature provides convenient lists of the most important ports. However, coasting vessels called at a much larger range of landing locations than these suggest – including beaches, natural bays, etc. To locate and record more places we drew on new sources that provided us with an array of landing locations at different benchmark dates.3The Atlas of Industrialising Britain4Digitising port information from secondary sources was relatively easy. What was more difficult was gathering port data from the port book and crew list coastal shipping data. Both sources give the movements of coasting ships and, as a result, also record myriad landing locations and ports that often do not appear in the secondary sources. These ports were included in the port data presented here.The British government's board of trade collected thousands of crew lists from ships to keep track of mariners, and between 1830 and 1844, their lists also recorded ship movements. The lists survive in good numbers, so we were able to sample randomly from this source.From 1565 to 1790, customs officials at regional ‘head ports’ documented ship movements in their domicile port and in smaller local creeks and havens using the standardised port book volumes. Over twenty thousand port books created by this early modern fiscal system survive. Yet, it is difficult – perhaps impossible – to undertake national level random sampling due to patchy survival rates and the current removal of most books to the conservation department at the National Archives, Kew. Therefore, we drew on a non-random sample of port books from the seventeenth century. We collected all useable data from a port book set originally created during the Cromwellian or Interregnum period, 1649–1660 (E122). This set includes numerous ports located on the West, South and East coasts of England and Wales. It comes from the records of 13 customs ports. However, the thousands of coastal voyages these volumes recorded include detail for a much larger set of places because officials also recorded the varied and numerous destinations and ports of origin of coasters. Later, to strengthen our sample of eastern and western ports, we added sets from the port books of King's Lynn and Barnstable to 1683, this time taken from port books still available in the main E190 port book series.Because of geographical sampling limitations, the port book data we found cover coastal trades that varied in type and by region. Our sample cuts across several different trades with different characteristics. Riverine trade of small vessels of around 15 tons, for instance, are common in Gloucester's port book data 6In the nineteenth century, the number of reported ports of all kinds increased compared with the sixteenth century due to better information in the sources, but also because of the overall expansion of the network of coastal ports. According to earlier sources, 'ports' included harbours, small creeks or just beaches. These were overseen by larger ports with customs houses. 71.2In the sailing era, natural conditions constrained operations, especially storms, tides and waves, but also low light, and clearly these all had adverse effects. In terms of navigation, instruments used at the time allowed travel only under certain circumstances, and good visibility was necessary for safe passage. Knowledge of bathymetry was key to avoiding damage by grounding on sandbanks or rocks. Navigational charts reported the depth of water at certain locations, but for these to be of any use it was crucial to know the exact position of the ship. Mariners used landmarks to track their position, often using triangulation, and it was thus normal to sail in sight of the coast. During the night, or in poor visibility, navigation became difficult. Beacons, lighthouses and light-vessels etc. served as an alternative to landmarks where available, but their presence on the coast was very limited at the beginning of our period of study.We used an amalgamation of different sources to identify coastal routes mariners most likely followed. Specifically, we relied on historical coastal charts, bathymetric depth rasters, topographic elevation rasters, and parliamentary reports to create our database.Great Britain's CoastingPilot, first published in 1693 The main primary sources used to determine coastal routes were navigation charts included in Captain Collins' publication, Bathymetry data was used to distinguish those areas with sandbanks or submerged rocks. Although we understand the position of sands changed over time, we assume there was historical stability in other parts of the coast that were less affected by tides and oceanic currents. We relied on the EMODnet Bathymetry data for the Atlantic Ocean, published by the European Marine Observation and Data Network in 2016 8Topographical data were gathered from the NASA Shuttle Radar Topography Mission (SRTM). Our raster, however, was a processed version offered by the International Centre for Tropical Agriculture (CIAT); in particular, we worked with its version 4.1 CoastingPilotLight-Houses of the British Islands in two editions, one published in 1832 and the other in 1851 Finally, we also used five sources to obtain the location and visibility range of lighthouses, beacons2Using all these sources, we created two databases covering all of England and Wales. The database of ports was designed as a shapefile with georeferenced points and temporal data. When we compiled the port data, we maintained full linkage between ports and all sources so users can view ports by specific source dating from chosen period. This allows the ports database to be used in time-dynamic analyses because ports that were in operation at given periods of time between the mid-sixteenth to the early-twentieth centuries can be isolated from those that were not. The shapefile of coastal routes interconnects the elements of the previous database, distinguishing each segment by category. We also introduced time dynamic data for lighthouses to show building date and changes to their characteristics like light visibility range. This gave us a more precise account of a key change in navigational visibility over this period.In geographical terms, both shapefiles were created using the coordinates system of the British National Grid projected into Transverse Mercator with datum ODGB 1936 of the Ordnance Survey National Grid.2.1The shapefile of ports includes precise information to locate each element geographically and temporally. FID and Shape were automatically generated by the software. The first indicates the order in which each element was recorded. The second indicates the type of element, in this case, points.Fields Name was created as a unique identifier. It allows the linking of each element, often named differently across different sources, with the same register of all the other sources contained in our database.Field The following variables contain information on the presence of each element in every source. In each column we used a binary variable, identifying those elements that were listed in that source  and those that were not .Point_X and Point_Y include geographical coordinates of each element based on the British National Grid. Please note that the geolocation of each point was done manually and with maximum precision given the available information. In many cases, we had to rely on current maps, such as ESRI's World Imagery system or Google Earth to find and locate named places. This should not pose a problem since we do not expect any significant variation in their location over the period of study.Finally, fields 2.1.1In summary, our ports database includes 479 different places. Only 13 ports came up in all 11 sources.Note the relative stability of the number of appearances, except for the long tail of ports with only one, two, or three observations. These include smaller ports that go unreported in published sources, but that were nonetheless visited by real coasting ships.2.1.2In our work, we use data from many different sources, and each source has its own temporal coverage. Some sources, for instance, list ports in operation at specific dates. In others, data was compiled at some point from a specific archive over a longer period. In these cases, the presence of a specific port on the list does not imply that port was in operation for the whole period, but just for the time it was recorded. Observing the chart, one can see that the sources pertain to different periods. Aggregate lists of ports dating from before the eighteenth century do not exist to our knowledge. For later periods, comprehensive lists of ports for specific periods are available. In these cases, the sources provide more precision; however, diversity and coverage are limited by a focus on larger ports often with specific infrastructure or facilities.2.1.3Wet docks did not exist in England and Wales in 1660, and only a handful of harbours had been built by this time. Many ports, however, were greatly improved by the beginning of the twentieth century. It is estimated there were 391 acres of wet dock space and 50 harbours in 1830 Bogart and Richardson 2.2The database of coastal routes was designed to interconnect the database of historical ports. We opted not to draw direct connections between individual ports, but rather to introduce interconnected segments with different characteristics through which all connections could be made. The structure of the attribute table is summarised in FID and Shape. The first records the order in which each element was added. The second indicates the type of element, in this case, polylines.The software automatically generated fields Type indicates the category of each polyline. It allows the classification of the routes by their nature. We opted for five different levels of classification, as seen in Field Level 1: Coastal routes based on maritime navigational charts.The charts detailed coastal landmarks which mariners could use to determine their geographical position. The inclusion of landmarks aided the description of coastal routes, such as that between London and Newcastle. Directions should not be understood as being precise, but more like broad corridors ships could use to navigate safely between geographical points. Nautical charts also estimated distances between landmarks, which enabled navigators to plan their route and to calculate travel times using the point-to-point distances provided on pages of text interspersed between the bound maps.We were able to recreate the primary coastal routes described in this source in ArcGIS by geolocating landmarks and plotting routes between them according to the various given orientations, and by comparing them with the distances quoted in the source. Furthermore, we ensured all the connections were within the visibility range from the coast in good weather and in daylight.Level 2: 10m depth bathymetry isolines.Assuming ships could become grounded when the depth of the water was less than the draught of the ship itself, nautical charts tended to report accurate bathymetry data. It allowed ship masters to circumvent those areas with greater ruggedness and to avoid danger. In this sense, the distance from the coast became an issue for navigation. Visibility of the coast, especially in poor weather, required proximity to the shore. However, the depth of the seabed near the coast was a clear constraint. Mariners had to remain close enough to shore to see landmarks and sufficiently far out to avoid grounding.To incorporate this issue into our GIS model, we drew a continuous line around the coast of England and Wales at a 10m constant depth. To do so, we relied on the EMODnet bathymetry raster This line represents the closest a ship could navigate to the coast in order to avoid sandbanks and underwater rocks. Ships may have had draughts of less than 10m, but given the limited precision of the bathymetry raster employed, we believe this value is a safe threshold estimation.Level 3: Penetration routes to port.As described in the previous category, in order to avoid running aground, navigation in shallow waters was not recommended, but ships had to access and depart from ports located on the coast. In many cases, the average depth of the seabed around ports was much lower than 10m and the route to enter them was riddled with obstacles.To solve this problem, we drew penetration lines connecting ports with those routes rounding the coastline. These lines were meant to maximise the depth of the seabed from the port to the 10m isolines and the coastal routes, as described above, for which we used Level 4: Inland waterways.Some of the ports recorded were not located on the coast, but on inland waterways. We cannot assume, based on our data, that these ports were accessible from the coast without transferring goods to smaller riverboats, yet we know there were regular coastal trading connections with river ports. At this stage, this allows for a basic overview of the extensive interconnection of inland waterways and coastal routes for transportation.For this exercise, we plotted those rivers, lakes, and sea-lanes required to guarantee connection to all our ports and landing locations. Note that the set of these lines was not conceived to include all inland waterways, but just those needed to ensure the interconnection of our coastal network as it is detailed by the sources used Level 5: Open water routes.Some routes described in our sources exceeded the ranges of visibility from the English and Welsh coasts . For those cases, and because lines categorised in Level 1 were restricted to be within the daylight visibility range from the coast, we drew additional lines representing these connections.The following three fields give information on the visibility of the coast from each route. The first field corresponds to daylight visibility, while the later ones refer to night visibility in the late-seventeenth and mid-nineteenth century.The last field of this database contains the length of each polyline in metres. This field was automatically estimated using GIS software and its use is merely analytical.Continuity across successive editions of Collins’ charts suggest the routes he originally detailed did not change significantly over the period covered by this data. This was a respected source of navigational guidance that was widely used.2.2.1Ships for the most part circumnavigated England and Wales when travelling between ports. They followed routes that, in the main, curved around the country. Navigators depended on the sight of landmarks when coasting, and consequently, these normally had to be visible from sea. This fact allowed us to pinpoint precisely the maximum distance coastal landmarks could be identified from ships everywhere on the coast, which in turn indicates how far away from the shore coasters would normally have sailed. Using GIS, we plotted the maximum distance it was possible to sail from the land before sight of the coastline was lost entirely. We did this by using mathematical principles of earth curvature and sight of horizon from ships. We also introduced night visibility variables based on the location of lighthouses and beacons. This created a realistic outer boundary for the open water routes.1 and a landmark with height h2 located on the coast at an elevation z2.Visibility in daylight and good weather conditions was estimated geometrically based on the Earth's curvature. We assumed an observer located in the mast of a conventional ship at a height hE, the radius of the Earth), the horizon line and the two elements described above (observer and landmark), we obtain the following equations:Applying the Pythagorean Theorem from the core of the Earth  was equal to zero, the elevation of terrain on the coast (z2) was equal to zero, and the height of the observer (h2) was equal to 2 m, we obtain a visibility range of 4.7 km, i.e. around 3 miles. This limit closely matches the historic three-mile territorial waters limit that was also (probably) determined by the distance ships could be realistically seen from the shore To estimate visibility at night-time, the procedure was rather different for the initial and for the final period of study.For the first period, we proceeded to identify all the lighthouses and beacons recorded by .Given the technological limits of lighthouses and beacons at this time, and a lack of consistent information now about those that existed, we opted to digitise all lighthouses and beacons charted by 16].16 ColliLight-Houses of the British Islands, published in 1832 and 1851 by the UK Hydrographic Office To estimate night visibility in the second period we opted for a different strategy. The In order to determine the visibility area for lights in the later period, we opted to digitise and geolocate every light type listed and to add a buffer around each to visualise the radius of light visibility detailed by this source. For those elements where authors provided no information, we used the average visibility range of all lights: 21 km.2.3Once the databases were completed, we proceeded to validate them in GIS using a set of topological rules. The aim of the exercise was to ensure coastal routes connected to points representing ports. In other words, each pair of ports was connected by at least one route. In doing so, we designed the database so other researchers can perform spatial and network analysis by modelling least cost routes through the network.Database validation required the cleaning of spatially coincident places with different names, as determined by their x and y coordinates. Ports with the same or very close geographical coordinates were removed. Besides which, all landing places had to be connected by a coastal route segment.•Must be disjointed•Must be covered by an endpointThe topological rules we used in ArcGIS to do so were the following:•Must be single-part•Must not intersect•Must not overlap•Must not self-intersect•Must not self-overlap•Must not intersect or touch the interiorRegarding coastal routes, we opted for a network composed of individual route segments without intersections or overlap between each. In this case we used the following topological rules in GIS to ensure the validity of the network:


The high prevalence of skin diseases in resource-poor settings, where health workers with sufficient knowledge of skin diseases are scarce, calls for innovative measures. Timely diagnosis and treatment of skin diseases, especially neglected tropical diseases (NTDs) that manifest with skin lesions, such as leprosy, is crucial to prevent disabilities as well as psychological and socioeconomic problems. Innovative technological methods like telemedicine and mobile health  can help to bridge the gap between the burden of skin diseases and the lack of capable staff in resource-poor settings by bringing essential health services from central level closer to peripheral levels. Netherlands Leprosy Relief (NLR) has developed a mobile phone application called the ‘SkinApp’, which aims to support peripheral health workers to recognize the early signs and symptoms of skin diseases, including skin NTDs, and to start treatment promptly or refer for more advanced diagnostic testing or disease management when needed. Further research is needed to determine how greatly mHealth in general and the SkinApp in particular can contribute to improved health outcomes, efficiency, and cost-effectiveness. This article is written as a short communication, describing the ongoing development process of a mobile phone application that supports peripheral health workers in diagnosing and treating skin diseases in resource-poor settings.It is known that skin diseases are highly prevalent, particularly in resource-poor areas, where children are disproportionally affected—though there is a lack of systematically-collected data supporting this ,2. The eNeglected topical diseases (NTDs) that manifest in skin lesions like leprosy and lymphatic filariasis see  are amonSkin conditions are usually not fatal, but it is important to recognize those that may be, such as blistering diseases. They can also be a sign of an underlying medical condition that might be life-threatening, such as HIV/AIDS. In view of the HIV/AIDS epidemic, the importance of dermatology cannot be underestimated, as 90% of HIV/AIDS patients develop a skin problem see  during tPhysical problems caused by skin conditions can lead to deterioration of the quality of life. Additionally, skin diseases often cause psychological problems such as anxiety, depression, and exclusion. A study in Colombia to determine the impact of skin diseases on the quality of life found that even the most localized or asymptomatic skin lesion leads to a disruption at some level of patient wellness . The higStudies have shown that a minimum of 10% of the consultations at peripheral healthcare level relates to common skin diseases ,10. UnfoThere are various innovative ways to enhance the quality of peripheral dermatology care. These include, but are not limited to, technological methods such as telemedicine, artificial intelligence, and mobile health . In teledermatology, telecommunication technologies are used to exchange information regarding skin conditions over distances that a patient would otherwise have to travel . The twoArtificial intelligence can be used to make a computer-based algorithm that is able to make diagnostic decisions regarding skin conditions to a good degree of accuracy . HowevermHealth refers to the use of mobile communication devices to support health system needs. It can be made available by and for resource managers and health workers, as well as community members, patients, and their caregivers. It can also be used for management purposes, data collection and reporting, decision support, training, emergency referrals, alerts, and supervision ,16. In Lhttps://www.dermassistance.es/). There is also a variety of disease-specific applications available. In the field of leprosy, for example, there is an initiative aimed at the early recognition of leprosy using image recognition through neural network technology by the Vellore Institute of Technology (http://preleprosy.com/), but this is still in development. There are many mobile phone applications concerning skin diseases. As of August 2017, more than 520 dermatology-related mobile phone applications are available in the Google Play Store and the Apple App Store . The majTo increase the capability of peripheral health workers in resource-poor settings to diagnose and treat skin diseases and thus strengthen the health system, the Netherlands Leprosy Relief (NLR) developed an application suitable for Android and Apple devices. To our knowledge, no other similar mobile phone application is available. The aim was not only to support health workers to better serve a large proportion of their patients with common skin diseases, but also to enhance the detection and treatment of less common skin diseases, such as leprosy. Knowing that correct diagnosis and timely treatment help to prevent disabilities, the use of the SkinApp can contribute to reduced suffering caused by dermatological conditions.The SkinApp uses an algorithm to support the process of diagnosis. It was inspired by the algorithm developed by Mahé for the management of common skin diseases at the primary healthcare level ,23. It cThe development of the NLR SkinApp went through three stages: (1) a pilot project using a paper-based algorithm in Nigeria ; (2) a pThe study in Nigeria was a prospective pilot study to assess the performance of first-line healthcare providers using a paper-based algorithm to support their diagnosis and treatment of seven skin diseases. In this study, 19 patent medicine vendors and 12 traditional healers assessed a total of 4147 patients with skin lesions, and their diagnoses and treatment choices were validated by two independent dermatologists. Overall, the first-line healthcare providers using the algorithm correctly diagnosed and treated or referred 82% of patients presenting with skin lesions. Adding pictorial images of signs and symptoms was believed to further improve the algorithm . On the In the first version of the SkinApp, which was tested in Zambezia Province, in Mozambique, 21 diseases were included in the algorithm: eight common skin diseases, six NTDs that manifest in skin lesions, and seven HIV/AIDS-related skin diseases see . The pilBased on the results of the pilot and advancing insight, a second version of the SkinApp was developed. While the first version presented possible diagnoses with a description of signs, symptoms, and treatment advice, the second version aligned much better with the clinical validation of a patient with a skin disease. This was achieved by integrating an improved algorithm that starts with signs and symptoms and their location on a body map, and leads to the most likely diagnosis and treatment advice. In the second version, a number of diseases and supporting photos were added. A feedback button was inserted, which could be developed into a teledermatology function if required. The second version of the SkinApp was implemented in Nampula Province in 2017–2018. A WhatsApp group was formed for SkinApp users to meet the need for a teledermatology option. This enabled them to consult with an experienced Mozambican dermatologist, if needed, though an internet connection is required. Findings from the implementation project confirmed that the SkinApp is more easily accessible than literature and books, and that it is easy to operate. The narrative and illustrative content were considered clear. However, a glossary explaining dermatological terminology would help to improve intelligibility. Adding a reporting option was also mentioned as a possible improvement. These findings helped to further improve the user-friendliness of the SkinApp, but these pilots did not address the performance of the SkinApp as a diagnostic tool.On the basis of the experiences with the SkinApp in Mozambique and the feedback received from involved dermatologists, a third version has since been developed. Its performance is currently being validated. The third version contains a total number of 29 skin diseases see , an imprThe second version of the NLR SkinApp is currently available in English and Portuguese for mobile devices with Android as well as iOS operating systems through the Google Play Store (SkinApp) and the Apple App Store (as Skin_App) respectively, free of charge. Once downloaded, the SkinApp can be used offline.The third version will be released once the current validation study is completed. The validation study is done in clinical settings under appropriate ethical and statistical guidelines. It encompasses concordance testing of the photos used in the application. The accuracy of the SkinApp will be assessed by comparing the diagnosis made by peripheral health workers using the SkinApp, to the diagnosis made by experienced dermatologists. Further evaluation of the use of the third version is planned for in several African countries. The capacity of the health workers to diagnose and treat skin diseases at baseline will be compared to their capacity two years after the introduction of the use of the SkinApp. Furthermore, a comparison will be made between the detection and treatment of skin diseases—specifically neglected tropical diseases—before and after the introduction of the SkinApp.Once validated, the NLR SkinApp will be made available for use in other countries, where it can be modified to the context by changing the language, adapting the included skin diseases to those prevalent in the area, and using country-specific photos and treatment advices.Agarwal et al. conducted a systematic review entitled ‘Evidence on feasibility and effective use of mHealth strategies by frontline health workers in developing countries’ . They foOne of the success factors for the adoption of mobile tools identified by Agarwal et al. was the involvement of the health workers throughout the development and implementation process . The SkiThere is a clear need to address the mismatch between the burden of skin diseases at the community level in resource-poor areas and the capability of peripheral health workers to diagnose, treat, and refer people with skin diseases, including skin NTDs. mHealth in general and the NLR SkinApp in particular can help to bridge this gap. The technical requirements and costs to ensure the sustainability of these innovative approaches are likely to increase, especially upon usage in different countries, which requires context-specific adaptation such as the use of the local language and alignment with the epidemiological situation. Therefore, more research is needed to gather evidence on the health outcomes and (cost-) effectiveness of mHealth for skin diseases, including skin NTDs, to ensure a wider use in support of peripheral health workers.


Among the variables associated with occupational stress, two of the most studied are the adverse perceptions of psychosocial risk factors in the workplace and burnout. With the rise of positive psychology, other variables of the individual type, such as hardy personality have also been the subject of study. No studies have been found that jointly examine these variables related to mental health in police officers. The aim of this research was to analyze which variables were associated with mental health in police officers. A total of 223 policemen (202 men and 21 women) participated in a cross-sectional study. Of all the variables, emotional exhaustion and perception of problems as challenges were the only factors introduced in the regression model. These factors must be considered to improve both human resource interventions and occupational health practices in this professional group. Police officers are highly likely to suffer from work-related stress due to the obligations and tasks of their work, such as providing help, mediating conflicts between citizens, organizing traffic or reporting offenses. These tasks imply that the police officers are exposed to traumatic situations , and thaThe following concepts are explained below: psychosocial risk factors, burnout, and hardy personality.The lack of social support within the organization is one of the variables that has best explained stress in police officers. The feeling of perceived support from peers and superiors is crucial for these professionals . In addiHypothesis 1: Psychosocial risk factors will predict psychological health in police officers.The term “burnout” refers to a situation of chronic work stress with negative affective connotations that makes it difficult for workers to perform their work and maintain their relationships that are established among them. It is a psychological syndrome whose main dimensions are emotional exhaustion, depersonalization, and feeling of lack of personal accomplishment . SchaufeHypothesis 2: The three dimensions of burnout  will predict psychological health in police officers.Hardy personality is the set of attitudes and strategies that establishes the motivation to perceive stressful working circumstances as opportunities of development or growth. It is a variable or personal resource used to alleviate or minimize the negative effects of stressful events on health, especially to protect against occupational stress . This coHypothesis 3: Hardy personality factors  will predict mental health in police officers.As mentioned earlier, we have found no previous studies on the prediction of police officers that comprise psychological health that simultaneously consider predictor variables such as perception of psychosocial risk factors, burnout dimensions, and hardy personality. The earlier mentioned hypotheses can be summed up in a single one:Hypothesis: Adverse perception of psychosocial risk factors , burnout dimensions , and hardy personality factors  will predict mental health.SD = 7.52). The average seniority in the job was 14 years (SD = 13.90). The average number of hours worked per week was 38 h (SD = 8.87).In this research, a non experimental, cross-sectional design was used. Cross-sectional studies are defined at a specific point in time and their purpose is to establish associations between variables and evaluate prevalence issues, not to seek cause-and-effect relationships . Non proIn order to evaluate the perceived state of health, the Spanish adaptation of the General Health Questionnaire – GHQ-28 –  was usedThe DECORE-21  was applThe Spanish adaptation of the Maslach Burnout Inventory–Human Services Survey – MBI–HSS –  was usedThe Occupational Resilience Questionnaire was used . It consThe research exceeded all the parameters of the Deontology Commission of the Faculty of Psychology of the Complutense University of Madrid, obtaining a favorable report. The collaboration between the university and the police became effective after the signing of an agreement between both institutions. We were able to collaborate after different negotiations with the police management, since it is difficult to access this professional group to deal with work-related stress issues. The agreement emphasized on the preservation of the anonymity of the police officers and the purpose of the university to use the data for a purely scientific and research aim, without damage to the participating policemen or the organization. The battery of questionnaires was prepared, and the police officers were given an open envelope with an information sheet, informed consent, and questionnaires to be completed. All informed consents of each participant were obtained. Once the participants had completed the questionnaires and checked that all items had been rated, the researcher double-checked, and the envelope was closed, with a previous review by the participant and the researcher of the answer of all items, in order to ensure that no questions were left blank. Completion of the questionnaires lasted approximately 40 min per evaluation shift. At all times, at least three researchers were present to clarify any type of doubt regarding the items.k regression analysis blocks, each with one or more variables that precede it. In each phase, the increase in R2 is observed, produced by the introduction of a new block taking into account the variables introduced in the previous sequence. This change in R2 acquires relevance in this procedure, since an increase in it represents what each new block brings over the previous one or can eliminate the effect of what was explained by the previous blocks .r = 0.50, p < 0.01). About the anxiety and insomnia scale, positive and significant correlations were found between this scale and the organizational support factor  and the overall risk index of DECORE . The anxiety and insomnia scale also correlated positively and significantly with the emotional exhaustion dimension  and with the depersonalization factor . The severe depression scale correlated positively and significantly with the emotional exhaustion dimension . With respect to the overall GHQ score, we found positive and significant associations in organizational support . As for burnout dimensions, this overall score correlated positively and significantly with emotional exhaustion and depersonalization . Regarding the control scale of DECORE, positive and significant correlations between control and emotional exhaustion and depersonalization scales were obtained . The score on the organizational support scale correlated positively and significantly with scores on the emotional exhaustion  and depersonalization  scales. As for the relationship between psychosocial risk factors and hardy personality, the highest correlation occurred between organizational support and commitment, which was negative and significant . Besides, the GRI correlated positively and significantly with the scores obtained in emotional exhaustion and depersonalization . Finally, we found correlations between personal accomplishment and the following factors: challenge , commitment , and global hardy personality score .Regarding the correlations made, the following were noteworthy: a positive and significant association was found between the somatic symptoms scale and the emotional exhaustion dimension  and in the GHQ-total dimension . The direct score of the questionnaire for each subscale is 21 and for the total score 84; as a result, in general, the police officers evaluated perceived a low frequency of symptoms associated with worse mental health. Regarding the perception of psychosocial risk factors, the highest scores  are those obtained in the cognitive demands and rewards factors (397 and 343). These scores indicate that police officers perceive excessive cognitive demands and scarce rewards. Likewise, although the scores are lower than the previous ones, they perceive scarce control and little organizational support. In relation to burnout, the police officers evaluated obtained the highest scores in the dimension emotional exhaustion. In the rest of the burnout factors, the values did not exceed the average score of the scale; only in personal accomplishment factor higher scores were obtained. Finally, with respect to the hardy personality, the total number of police officers obtained scores close to 4, the control and commitment being factors in which the police officers obtained the highest scores . In this questionnaire, scores close to 4 indicate higher levels of hardy personality.Regarding the average scores and standard deviations obtained from the police officers of the study, in relation to the perceived psychological health, the results showed that the highest scores  appear in the scale of social dysfunction ; the dimensions of burnout; and the factors of the hardy personality are presented in R2 of 0.27 from model 2 to model 3.Considering the GHQ-total score as criterion variable, the sequential or hierarchical regression analysis showed that model 3 included the variables, challenge and emotional exhaustion, accounting for 39% of the total variance of GHQ-total. When emotional exhaustion was introduced, the organizational support of model 3, which did appear in model 2, was eliminated. There was a variation in ΔIn this study, we examined which of the factors relating to work stress, such as perception of psychosocial risk factors, burnout, and hardy personality, predicted mental health in police officers. The descriptive data indicated that the police officers perceived excessive cognitive demands and few rewards in their work. In addition, they presented moderate values of burnout and high levels of hardy personality. Among the correlations made, it was pointed out that at a higher frequency of somatic symptoms and symptoms related to anxiety, insomnia, and depression experienced, higher levels of emotional exhaustion were found in the police officers evaluated. It is noteworthy that there was a positive and significant correlation between the perception of worse mental health and higher levels of emotional exhaustion and depersonalization. It was also interesting to know that the perception of poor support at work was significantly associated with high levels of emotional tiredness. In general, the adverse perceptions of psychosocial risk factors was associated with high levels of emotional exhaustion and depersonalization. Among the perception of the psychosocial risk factors, the results found agree that other studies that suggest that police officers feel stressed and they perceived excessive demands in their work . The facRegarding the prediction of psychological health from the indicated variables using the hierarchical regression analysis, the results showed that only the challenge and emotional exhaustion factors explained 39% of the total variance of the variable psychological health evaluated using the GHQ-total score. The inclusion of the emotional exhaustion dimension caused the organizational support factor is not included within the model. In relation to psychosocial risk factors as health predictors, the results of this research are not in line with those other studies that suggest that lack of support from peers and supervisors is one of the specific stressors that has been most associated with stress in police officers and is considered one of the best health predictors in these professionals . The perSpecifically, in line with the psychosocial risk factors involved in the demand–control–social–support and effort–rewards Imbalance models , the results found in different studies reveal that demands and control factors are related to cardiovascular disease . These iRegarding the dimensions of the burnout construct, it was the emotional exhaustion factor that appeared as a predictor of psychological health. Considering this, it is necessary to mention that other studies have also indicated similar results in police officers . RegardiAs for the strengths of this research, it offers results on both of the organizational and personal variables, which have been jointly taken into account for the purpose of identifying which of these factors predicted a higher frequency of symptoms related to perception of worse mental health in police officers. On the contrary, the results presented serve to improve intervention practices for work-related stress in police officers. It has been observed in this study that the perception of problems and difficult situations as challenges or emotionally exhausting factors predict mental health; therefore, interventions for occupational stress to improve psychological health in these professionals should be addressed to those factors. The results of this research are somehow expected, since a main role has always been given to the variable – control over work – and, in this case, it does not appear as a predictor of mental health. In the same way, it is necessary to mention the different limitations of this research. In the first place, this is a cross-sectional design, which makes it impossible to obtain causal relations. On the contrary, the difficulty to access this sample, in many cases prevents longitudinal studies that provide information obtained over time .In future studies, it would be advisable to increase the size of the sample in order to perform other analyses, for example, to establish differences in work stress according to sex or occupational rank that could not be carried out in this research. Some studies have shown that there are differences in police stress according to these variables . In a stThis study was carried out in accordance with the written informed consent obtained from all participants. The protocol was approved by the Deontology Commission of the Faculty of Psychology of the Complutense University of Madrid, obtaining a favorable report.BT-V, LL-M, and JM-G contributed to the conception and design of the study. YG-A organized the database. BT-V and LL-M performed the statistical analysis. BT-V, JM-G, and YG-A wrote the first draft of the manuscript. BT-V and LL-M revised the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background: Urinary incontinence (UI) represents a complex problem which commonly affects women and influences their physical, mental, and social wellbeing. The objective of this study was to explore the experiences of a group of women with urinary incontinence. Methods: A qualitative exploratory study. Purposeful sampling was used. Recruited patients were females aged >18 years old with positive symptoms, signs of urinary incontinence, and attending a specialized urinary incontinence center for the first time. We collected data using interviews and participants’ personal letters. A thematic analysis was performed. Results: 18 women participated with a mean age of 47.32 years. Four themes emerged: (a) Experiencing uncontrolled urinary leakage, (b) Information based on beliefs and myths regarding UI, (c) Adapting to change and developing strategies, (d) The role of education. Women’s experiences were accompanied by feelings of stress and shame. A lack of information regarding UI was found, together with numerous misconceptions. Urinary incontinence triggers many changes in women. Some women may develop feelings of rejection towards their own body. Family involvement during these times is essential for education and promoting healthy sexual practices. Conclusions: This study highlights the importance of developing educational programs that focus on women’s information and education regarding triggering factors and coping strategies. Urinary incontinence (UI) or involuntary leakage of urine  is a disUrinary incontinence is associated with increased rates and severity of female sexual dysfunction, such as: impaired body image, fear of coital UI, avoidance of sex, decreased desire, lubrication, and satisfaction, as well as increased pain . MoreoveStigma enhances the formation of negative attitudes towards seeking professional help for urinary incontinence through the effect of internalized shame ,16,17. OLikewise, Norton et al.  pointed The present study forms part of a larger research project which objective was to study new pelvic floor rehabilitation therapies, and the impact of urinary incontinence in the women´s life. In the first quantitative research phase, previously published, we used a non-randomized clinical trial involving 60 women >18 years of age, both with and without urinary incontinence . The objA qualitative exploratory and descriptive study ,27 was cPrior to the study, the position of the researchers was established according to their previous experience . Four reThe setting for this study was a specialized UI center in Madrid (Spain) performing assessments, treatments, follow-up, and specialized care of women with PFD. The center’s professional team was formed by gynecologists, nurses, midwives, and physiotherapists who are experts in PFD and urinary incontinence. The pelvic floor assessment was carried out based on both a physical and an electromyographic (EMG) examination. The center was fully equipped with technical equipment, such as the Verity Medical Neurotrac®  , which wPatients with UI who attended the specialized UI center  for the first time were enrolled in the study between June 2015 and June 2017. Purposeful sampling methods were employed based on the relevance to the research question . All patients were recruited during their first visit to the clinic to ensure that none had experienced a significant improvement at the time of the study. The recruitment took place when the women initially visited the clinic. If they met the inclusion criteria and agreed to participate, then they were included in the research project. During this first visit, they were given information on the study and participation in the study was confirmed two weeks later by telephone. The recruitment was performed by MZPD. The women who agreed to participate were consecutively enrolled in the study. The interviews were scheduled during the following two weeks. The sampling process continued until the researcher achieved information redundancy , at whicThe subjects included in the study were: (a) females aged >18 years old; (b) who attended the center due to an involuntary loss of urine; (c) with UI symptoms and signs according to the American Urological Association and Society of Urodynamics, Female Pelvic Medicine guidelines , for exaPrior to data collection, two briefing sessions were conducted to determine the data collection procedure , and to confirm that the process of data collection was known by the entire research team. First-person data collection tools (in-depth interviews and participants’ letters) were used. Subsequently, researcher field notes were obtained . Open-enThe women participating in the study were asked to write personal letters, which were used as part of the analyzed data, bringing the task of data collection into the respondents’ everyday world . These lThe field notes were collected during the interviews with the aim of noting participants’ gestures and non-verbal language (for example: nervousness or discomfort). The researcher also collected descriptions of the place where the interviews were held, comments on methodological aspects and descriptions of any event (for example: interruptions during the interview) taking place during data collection.All the interviews were digitally audio recorded and transcribed verbatim . In total, 1450 min of interviews were recorded and the average time of each interview was 80.55 minutes. The full literal transcription of each of the interviews, the women’s letters and the researchers’ field notes were all collated in order to perform a qualitative analysis. A thematic analysis was performed, which began by analyzing the most descriptive content in order to reach meaningful units. This then went into further depth to produce thematic code groups . To identify the relevant content, researchers read and reread the data at three different levels: literally, interpretively, and reflexively . In thisSubsequently, meetings were held to identify and compare the results obtained. The final outcome was the identification of themes that represented the women’s experiences with UI who sought care for first time. No qualitative software was used to analyze the data. Data was classified, categorized, and organized using Microsoft Excel.The guidelines for conducting qualitative studies established by the Consolidated Criteria for Reporting Qualitative Research (COREQ)  and the The study was approved, and all procedures were followed in accordance with the ethical standards of the Ethics Committee of the University Rey Juan Carlos, Spain (code: 20/2015). Informed consent and permission to record the interviews was obtained from all participants included in the study.Eighteen females with SUI (61.11%), UUI (22.22%), and MUI (16.66%) were enrolled in this study, and the mean age of participants was 47.32 years. Upon analysis of the data collected, four specific themes emerged which described the experiences of the women with UI and can be used to help women seek specialized help for the first time: (a) Experiencing uncontrolled urinary leakage, (b) Information based on beliefs and myths regarding UI, (c) Adapting to change and developing strategies, and (d) The role of education. In order to facilitate the traceability and identification of the results obtained, these are accompanied below by excerpts of transcripts.All the participants acknowledged that the negative experiences derived from the loss of urine had forced them to seek help at a specialized urinary incontinence center. The women described the leakage of urine as being uncomfortable, unpleasant, and stressful. Most participants described how UI made them feel unclean. Furthermore, UI triggered feelings of shame, uneasiness, insecurity, suffering, lack of control, blame and low self-esteem. Some women described feeling like they had a “defect” or “fault” making them feel less of a person, to the point of feeling guilty for having UI. Many women were also afraid that the leakage of urine would cause their clothes to smell, so they were continuously checking whether they smelled of urine or if there was a disagreeable odor. All the women who participated in the study complained about the overall lack of information and about how the little information was available to them was unclear. Many had not heard of UI before suffering the initial symptoms and were unaware of where to go to receive treatment. Furthermore, for many participants, their knowledge of UI was based on a series of beliefs or myths. For example, there was a belief that urinary leakage was a ‘normal’ occurrence which, sooner or later, would affect all women. Another belief was that it worsened with age and that women should resign themselves to having to live with the condition. Another common myth was that UI happened to all women after childbirth, therefore relating urinary leakage to the process of reproduction . Most participants confirmed how this idea was reinforced by their close friends and family and even by some health professionals. Other participants believed that UI was something they had inherited, as there were previous cases in the family. Finally, all the participants expressed how the lack of credible information caused them to have doubts, until they eventually decided to seek help in order to receive trustworthy information. Before seeking help, the participants described feeling forced to modify their habits and routines, and how this negatively affected their daily life, for example, by influencing the way they dressed or their social life. Women described feeling forced to develop strategies to manage the urinary leaks and avoid so-called ‘accidents’. One of the participants spoke of having to carefully choose the places she went to and the necessity of always locating the bathroom when she visited new places. Another strategy was to avoid traveling, or limiting any social life in fear of having a urinary leak. Even the use of public transport was seen as a challenge and cause of insecurity. All participants agreed that the most common strategy was to use incontinence pads. Women viewed these as something that gave them a sense of security, ensuring that their clothes would stay dry yet discreet enough to make others unaware of any leakage. Furthermore, some participants said that they wore pads, despite not having heavy leakage, but as a means of protection. Another strategy was the use of fragrances and perfumes, sprayed onto the body and clothes, to avoid any urine smell that may otherwise be filtered through the sanitary pads and/or diapers. Finally, our participants acknowledged that, over time, they felt unable to continue with these strategies and therefore decided to seek help to control and/or treat their UI. The participants emphasized how the education that they had received at home or the fact of living in a rigid and restrictive social environment had conditioned their experience of UI and how they sought UI care. Family education was seen as being key for the acceptance and recognition of UI and for acquiring healthy hygiene and urinary habits, as well for the development of a healthy sexuality. Sexual education within the family is essential for helping women develop their sexuality. For some women, this experience was natural and positive because there was freedom to discuss and pose questions about the urogenital area and sex within the family. In contrast, others acknowledged feelings of rejection towards the urogenital area, sex, and their sexuality due to the fact that, during their adolescence, their education was driven by fear, thus conditioning their sexual relationships. As such, the social environment of women can clearly shape their experience. Thus, some women spoke about how living in a restrictive, chauvinistic, and paternalistic environment from an early age had influenced them in how they perceived and experienced matters related to their pelvic and genital region, highlighting connotations of sin, guilt, and danger. These areas were perceived as being taboo, associated with many misconceptions, and a considerable emotional burden. After attending a specialized center, the women experienced a change in how they perceived this region. Some women felt that their urogenital region defined them as a woman, playing an important role in their personal story. Other women felt they had rediscovered their intimate body parts through the exercises and techniques that they had learned at the specialized center. Our results illustrate how UI is experienced with feelings of unpleasantness, shame, insecurity, and guilt. There is a lack of information on UI, and the information available is unclear. Furthermore, there are many false beliefs surrounding this issue. Urinary incontinence triggers changes which force women to develop certain strategies in their daily life. Some women have a negative perception of the pelvic region. Finally, education on behalf of the family and their social environment is necessary in order to acquire healthy hygienic and urinary habits. For women, UI was unpleasant, stressful, and traumatic; it led to feelings of shame, insecurity, suffering and guilt, to the extent that some participants described feeling ‘dirty’. Previous research ,40 has rThe lack of information on UI and pelvic floor dysfunctions has led to many myths and misconceptions which have strengthened the taboo of UI . This isPrevious research ,11,13 haOur findings highlight how women who have had negative experiences with their pelvic region describe rediscovering their body when seeking for help and initiating physiotherapy treatment. Kao et al.  noted thFinally, our findings highlight how the family and the surrounding context condition a woman’s experience of UI and sexuality. Previous authors ,12 agreeThis study has some limitations concerning generalizability that limit the extrapolation of our results to the whole population with UI. It is important to consider a possible Spanish cultural influence to the themes generated by this research. In this sense, Siddiqui et al.  reportedAdditionally, this study was performed on women attending a specialized UI center for the first time; therefore, our findings do not extend to patients with UI who have not visited a UI clinic or specialist. Lastly, the findings of this qualitative descriptive study have been organized to display the experience of the participants, rather than the phenomenon of UI. The findings could have therefore been presented in a different manner. The choice of how to present and order research findings facilitates the understanding of the participants’ experiences and is typical of qualitative exploratory studies . This study provides insight on how UI is experienced by a group of Spanish women who are seeking care at a specialized UI center for first time. Our findings shed light on how UI influences the lives of female patients and triggers the visit to a specialized center for the first time. Our participants’ experiences of living with UI revealed the following: (a) a lack of control over their bodies and uncontrolled and unscheduled urine losses, (b) most of the information on urine loss available is based on myths and beliefs, which raises concerns over the credibility and veracity of the information that the woman with UI receives, (c) the strategies that the women use for the management of urine loss over time are insufficient, so that UI still has a negative impact on their lives, and (d) the women experience a lack of education concerning the urogenital region and on related aspects such as hygiene and sexuality.Women should receive accurate information regarding UI and the urogenital region from healthcare professionals in order to change false beliefs. Furthermore, women should receive support in order to be able to anatomically recognize their pelvic and urogenital regions. Healthcare professionals can help women to recognize and accept their body. This implies the implementation of educational and training programs on coping and managing urinary incontinence by interdisciplinary teams led by healthcare professionals in different contexts, such as the community, health centers, and UI associations. Similarly, work teams should be formed between healthcare professionals working in the community and education professionals to develop programs in schools and high schools on the promotion of regional urogenital health in girls and adolescents. Furthermore, providers of women’s healthcare services have an important role in the education of women during routine health visits. As such, routine health visits represent an ideal opportunity to provide a unified education, shared by all women’s health care providers  by providing truthful information on the woman’s body, dispelling myths and false beliefs on UI, clarifying any questions on pelvic and urogenital regions, and promoting healthy hygiene habits. Our study also provides grounds to guide healthcare professionals to further research the quality of life of women with UI. Concretely, it would be interesting to analyze the experience of women who have undergone specific treatments for UI in their own contexts, and to identify the factors that helped facilitate the same or that represented barriers for seeking care.