Adjusted versus Targeted Fortification in Extremely Low Birth Weight Preterm Infants: Fortin Study-A Randomized Clinical Trial.

Fortified human milk is the first choice for preterm infants. Although individualized fortification is recommended, the optimal method for this population remains uncertain. We conducted a comparative study assessing the growth effects of adjusted (AF) and targeted fortification (TF) in extremely low birth weight (ELBW) infants. This single-center, randomized, controlled clinical trial was conducted at a tertiary neonatal unit in Spain. Eligible participants were premature infants with a birthweight of <1000 g exclusively fed with human milk. A total of 38 patients were enrolled, 15 of them randomized to AF group and 23 to TF group. AF was based on blood urea nitrogen (BUN) concentration and TF on human milk analysis. The primary outcome was weight gain velocity (g/kg/day). No significant differences were found in weight gain velocity at 28 days, at 36 weeks of postmenstrual age, at discharge, nor during the intervention. Protein intake was significantly higher in the AF group (5.02 g/kg/day vs. 4.48 g/kg/day, p = 0.001). No differences were found in the lipid, carbohydrate, and energy intake; in the weight z score change between the different time points; nor in the length and head circumference growth. Both AF and TF are comparable methods of fortification and provide the appropriate growth rate in ELBW infants.

Lindernia dubia (L.) Pennel as an Alien Weed in Central Spain: A Case Study.

Lindernia dubia (L.) Pennell is a species with invasive behavior outside of its native range of distribution (America), linked mainly to aquatic habitats. This annual species has been acknowledged as a weed in rice paddies in Europe and Asia. Due to the impacts of this invasive plant, some authors have even listed this species as a global invader. The present work focused on spontaneous plant species occurring in seedlings of Typha domingensis Pers. grown in central Spain for the establishment of constructed wetlands. Weed inventory revealed the presence of L. dubia as a dominant spontaneous species in this crop environment. A suite of mesocosm experiments were designed to study the population density of L. dubia versus that of the other dominant plant species, and to determine traits associated with its weedy potential. The results showed that L. dubia presents competitive attributes such as morphological variability, early flowering, long seeding time, short growth cycle, small and light seeds and a high seed production and germination rate (25 °C), meaning a high reproductive capacity in a cycle of about three months for plant growth in non-limiting conditions. The data obtained from this work provide a basis for understanding the weedy potential of L. dubia, and for management decisions of a potentially invasive species, which has been little investigated in Europe.

How to Design Successful Participatory Design Workshops for Digital Health Solutions?

Participatory design (PD) is increasingly used to support design and development of digital health solutions. The involves representatives of future user groups and experts to collect their needs and preferences and ensure easy to use and useful solutions. However, reflections and experiences with PD in designing digital health solutions are rarely reported. The objective of this paper is to collect those experiences including lessons learnt and moderator experiences, and to identify challenges. For this purpose, we conducted a multiple case study to explore the skill development process required to successfully design a solution in the three cases. From the results, we derived good practice guidelines to support designing successful PD workshops. They include adapting the workshop activities and material to the vulnerable participant group and considering their environment and previous experiences, planning sufficient time for preparation and supporting the activities with appropriate material. We conclude that PD workshop results are perceived as useful for designing digital health solutions, but careful design is very relevant.

Assessment of distance to primary percutaneous coronary intervention centres in ST-segment elevation myocardial infarction: Overcoming inequalities with process mining tools.

Objectives: In ST-segment elevation myocardial infarction (STEMI), time delay between symptom onset and treatment is critical to improve outcome. The expected transport delay between patient location and percutaneous coronary intervention (PCI) centre is paramount for choosing the adequate reperfusion therapy. The "Centro" region of Portugal has heterogeneity in PCI assess due to geographical reasons. We aimed to explore time delays between regions using process mining tools. Methods: Retrospective observational analysis of patients with STEMI from the Portuguese Registry of Acute Coronary Syndromes. We collected information on geographical area of symptom onset, reperfusion option, and in-hospital mortality. We built a national and a regional patient's flow models by using a process mining methodology based on parallel activity-based log inference algorithm. Results: Totally, 8956 patients (75% male, 48% from 51 to 70 years) were included in the national model. Most patients (73%) had primary PCI, with the median time between admission and treatment <120 minutes in every region; "Centro" had the longest delay. In the regional model corresponding to the "Centro" region of Portugal divided by districts, only 61% had primary PCI, with "Guarda" (05:04) and "Castelo Branco" (06:50) showing longer delays between diagnosis and reperfusion than "Coimbra" (01:19). For both models, in-hospital mortality was higher for those without reperfusion therapy compared to PCI and fibrinolysis. Conclusion: Process mining tools help to understand referencing networks visually, easily highlighting its inefficiencies and potential needs for improvement. A new PCI centre in the "Centro" region is critical to offer timely first-line treatment to their population.

Geostatistical analysis from the clinical laboratory in cardiovascular prevention for primary care. / Análisis geoestadístico desde el laboratorio clínico en prevención cardiovascular para atención primaria.

INTRODUCTION AND OBJECTIVES: Cardiovascular diseases continue to lead the ranking of mortality in Spain. The implementation of geostatistical analysis techniques in the clinical laboratory are innovative tools that allow the design of new strategies in primary prevention of cardiovascular disease. The aim of this study was to study the prevalence and geolocation of severe dyslipidemia in the health areas under study in order to implement prevention strategies in primary care. A retrospective cohort study of low-density protein-bound cholesterol, triglyceride and lipoprotein (a) levels in the years 2019 and 2020 were carried out. In addition, a geostatistical analysis was performed including representation in choropleth maps and the detection of clustering clusters, using geographic information in zip code format included in the demographic data of each analytic. RESULTS: The analytical data included in the study were triglycerides (n=365,384), low density protein-bound cholesterol (n=289,594) and lipoprotein to lipoprotein (a) (n=502). Areas with the highest and lowest percentage of cases were identified for the established cut-off points of LDL-C>190mg/dL and TG>150mg/dL. Two clustering clusters with statistical significance were detected for cLDL>190mg/dL and a total of 6 clusters for TG values>150mg/dL. CONCLUSIONS: The detection of clusters, as well as the representation of choropleth maps, can be of great help in detecting geographic areas that require greater attention to intervene and improve cardiovascular risk.

Application of Machine Learning Techniques to Help in the Feature Selection Related to Hospital Readmissions of Suicidal Behavior.

Suicide was the main source of death from external causes in Spain in 2020, with 3,941 cases. The importance of identifying those mental disorders that influenced hospital readmissions will allow us to manage the health care of suicidal behavior. The feature selection of each hospital in this region was carried out by applying Machine learning (ML) and traditional statistical methods. The results of the characteristics that best explain the readmissions of each hospital after assessment by the psychiatry specialist are presented. Adjustment disorder, alcohol abuse, depressive syndrome, personality disorder, and dysthymic disorder were selected for this region. The most influential methods or characteristics associated with suicide were benzodiazepine poisoning, suicidal ideation, medication poisoning, antipsychotic poisoning, and suicide and/or self-harm by jumping. Suicidal behavior is a concern in our society, so the results are relevant for hospital management and decision-making for its prevention.

Process mining for healthcare: Characteristics and challenges.

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

Online Mindfulness Experience for Emotional Support to Healthcare staff in times of Covid-19.

During the first confinement in Spain, between the months of March to June 2020, Information and Communication Technologies strategies were implemented in order to support health workers in the Wellbeing of Mental Health. Faced with so much uncertainty about the pandemic, an Online Mindfulness course. The objective of the course was to support healthcare professionals in Castilla y León in managing stress, anxiety and other emotional disturbances generated by coping with a situation as uncertain and unexpected as a pandemic, in order to manage emotions and thoughts that can lead to suicidal ideation. The motivations for the demand, reasons or motivations in which the health professionals of Castilla y León decided to participate in the mindfulness course in the first wave of Covid-19 in Spain are described. The descriptive and inferential statistical analysis of the customer satisfaction survey applied at the end of the mindfulness course, to the health professionals who participated in a satisfaction survey (CSQ-8: Client Satisfaction Questionnaire). Professional were asked to complete a survey based on (CSQ-8: Client Satisfaction Questionnaire) whose Cronbach's alpha = 0.917 is why the instrument used with N = 130 participants has high reliability. The 66% answered with a highly satisfied that they would return to the mindfulness online course. The 93% of the people who answered the satisfaction survey were women, of which they are professionals in the nursing area, with a participation of around 62%. In relation to the online system used in the Mindfulness intervention, 74% expressed that they fully agreed that it has been easy to use the online system for the mindfulness intervention. Health Professionals responded with 58% high satisfaction and 36% satisfaction, making a total of 94% on the help received in the online mindfulness courses to solve their problems. There is no difference between the age groups of the professionals who have preferred the Mindfulness online course (p = 0.672).

Systemic epigallocatechin gallate protects against retinal degeneration and hepatic oxidative stress in the P23H-1 rat.

Retinitis pigmentosa (RP) is a group of inherited retinal disorders that lead to photoreceptor loss. RP has been reported to be related to oxidative stress, autophagy, and inflammation. (-)-Epigallocatechin gallate (EGCG), the most abundant catechin-based flavonoid in green tea leaves, has significant antioxidant, anti-carcinogenic, antimicrobial, and neuroprotective properties. EGCG, given its low molecular weight and hydrophilic properties, can cross the blood-retinal barrier and is able to reach different ocular tissues such as the lens, cornea, and retina. EGCG has been shown to provide retinal protection against ischemia; sodium nitroprusside-, N-methyl-D-aspartate-, lipopolysaccharide-, light-, sodium iodate-, or H2O2-induced damage and diabetic retinopathy. This suggests that systemic EGCG administration has the potential to protect against retinal degenerative or neurodegenerative diseases such as RP. The aim of this work was to investigate whether EGCG can protect against RP progression in the animal P23H line 1, the model of RP. Albino P23H rats were crossed with pigmented Long Evans rats to produce offspring exhibiting the clinical features of RP. Pigmented P23H rats were treated via intraperitoneal injection with saline or EGCG at a dose of 25 mg/kg every week from P100 to P160 and then compared to wild-type Long Evans rats. Rats treated with EGCG showed better visual and retinal electrical function with increased contrast sensitivity and b-wave values compared with those observed in P23H rats treated with vehicle. EGCG reduced lipid peroxidation and increased total antioxidant capacity and catalase and superoxide dismutase activities. No differences were observed in visual acuity, nitrate levels, nitrite levels or glutathione S-transferase activity. In conclusion, EGCG not only reduced the loss of visual function in P23H rats but also improved the levels of antioxidant enzymes and reduced oxidative damage. This study was approved by the Institutional Animal Care and Use Committee (CEICA) from the University of Zaragoza under project license PI12/14 on July 11, 2014.

Effect of the Implementation of a Surgical Care Bundle in the Incidence of Surgical Site Infection in Spine Surgery: A Quasi-Experimental Study.

STUDY DESIGN: Quasi-experimental intervention study. OBJECTIVE: To assess the effect of a clinical safety and quality improvement plan for patients undergoing spinal fusion surgery on the incidence of surgical site infection (SSI). SUMMARY OF BACKGROUND DATA: In recent years, infection surveillance and control programs based on care bundles have been included in surgical protocols. These have proven to be essential tools for the prevention and control of SSI, providing indicators for improvement and allowing the characterization of related risk factors. METHODS: A quasi-experimental study was carried out with analysis before and after the introduction of a preventive care bundle (clinical safety and quality improvement plan). Patients who underwent spinal fusion surgery were included. The incidence of SSI up to 90 days after surgery (maximum incubation period) was assessed. The effect of the intervention was evaluated with the adjusted odds ratio (oR) using a logistic regression model. RESULTS: A total of 1554 patients were included, 690 in the period 2007 to 2011 (before) and 864 during 2012 to 2018 (after). SSI incidence decreased from 4.2% to 1.9% after the plan (OR: 0.43; 95% confidence interval: 0.23-0.80; P  = 0.006). There was also an improvement in the adequacy of antibiotic prophylaxis, preoperative preparation, and hair removal procedure after the introduction of the care bundle. CONCLUSION: After implementation of the care bundle, the incidence of SSI in spine fusion surgery decreased significantly. Multivariate analysis showed that the care bundle was an independent protective factor. The implementation of these measures should be reinforced on the routine medical practice to reduce the SSI incidence.Level of Evidence: 3.

Effects of Daily Melatonin Supplementation on Visual Loss, Circadian Rhythms, and Hepatic Oxidative Damage in a Rodent Model of Retinitis Pigmentosa.

Retinitis pigmentosa (RP) is a group of inherited neurodegenerative diseases characterized by a progressive loss of visual function that primarily affect photoreceptors, resulting in the complete disorganization and remodeling of the retina. Progression of the disease is enhanced by increased oxidative stress in the retina, aqueous humor, plasma, and liver of RP animal models and patients. Melatonin has beneficial effects against age-related macular degeneration, glaucoma, and diabetic retinopathy, in which oxidative stress plays a key role. In the present study, we used the P23HxLE rat as an animal model of RP. Melatonin treatment (10 mg/kg b.w. daily in drinking water for 6 months) improved the parameters of visual function and decreased the rate of desynchronization of the circadian rhythm, both in P23HxLE and wild-type rats. Melatonin reduced oxidative stress and increased antioxidant defenses in P23HxLE animals. In wild-type animals, melatonin did not modify any of the oxidative stress markers analyzed and reduced the levels of total antioxidant defenses. Treatment with melatonin improved visual function, circadian synchronization, and hepatic oxidative stress in P23HxLE rats, an RP model, and had beneficial effects against age-related visual damage in wild-type rats.

Distinctive Traits for Drought and Salt Stress Tolerance in Melon (Cucumis melo L.).

Melon (Cucumis melo L.) is a crop with important agronomic interest worldwide. Because of the increase of drought and salinity in many cultivation areas as a result of anthropogenic global warming, the obtention of varieties tolerant to these conditions is a major objective for agronomical improvement. The identification of the limiting factors for stress tolerance could help to define the objectives and the traits which could be improved by classical breeding or other techniques. With this objective, we have characterized, at the physiological and biochemical levels, two different cultivars (sensitive or tolerant) of two different melon varieties (Galia and Piel de Sapo) under controlled drought or salt stress. We have performed physiological measurements, a complete amino acid profile and we have determined the sodium, potassium and hormone concentrations. This has allowed us to determine that the distinctive general trait for salt tolerance in melon are the levels of phenylalanine, histidine, proline and the Na+/K+ ratio, while the distinctive traits for drought tolerance are the hydric potential, isoleucine, glycine, phenylalanine, tryptophan, serine, and asparagine. These could be useful markers for breeding strategies or to predict which varieties are likely perform better under drought or salt stress. Our study has also allowed us to identify which metabolites and physiological traits are differentially regulated upon salt and drought stress between different varieties.

Sentiment Analysis Techniques Applied to Raw-Text Data from a Csq-8 Questionnaire about Mindfulness in Times of COVID-19 to Improve Strategy Generation.

The use of artificial intelligence in health care has grown quickly. In this sense, we present our work related to the application of Natural Language Processing techniques, as a tool to analyze the sentiment perception of users who answered two questions from the CSQ-8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in daily life. As such, we proposed an online course where this method was applied in order to improve the quality of life of health care professionals in COVID 19 pandemic times. We also carried out an evaluation of the satisfaction level of the participants involved, with a view to establishing strategies to improve future experiences. To automatically perform this task, we used Natural Language Processing (NLP) models such as swivel embedding, neural networks, and transfer learning, so as to classify the inputs into the following three categories: negative, neutral, and positive. Due to the limited amount of data available-86 registers for the first and 68 for the second-transfer learning techniques were required. The length of the text had no limit from the user's standpoint, and our approach attained a maximum accuracy of 93.02% and 90.53%, respectively, based on ground truth labeled by three experts. Finally, we proposed a complementary analysis, using computer graphic text representation based on word frequency, to help researchers identify relevant information about the opinions with an objective approach to sentiment. The main conclusion drawn from this work is that the application of NLP techniques in small amounts of data using transfer learning is able to obtain enough accuracy in sentiment analysis and text classification stages.

Incorporation of biochemical parameters and diagnostic algorithms in the laboratory computer system for the early detection of lipid abnormalities from the lipid units. / Incorporación de parámetros bioquímicos y algoritmos diagnósticos en el sistema informático de laboratorio para la detección precoz de alteraciones lipídicas desde las unidades de lípidos.

INTRODUCTION: The combination of biochemical markers, together with the design and implementation of diagnostic algorithms in laboratory computer systems could become very powerful tools in the stratification of cardiovascular risk. OBJECTIVES: To implement new biochemical markers and diagnostic algorithms not yet available, in order to provide an estimation of cardiovascular risk and the diagnostic orientation of lipid alterations. MATERIAL AND METHODS: Study of the implementation of apolipoprotein B and lipoprotein (a), as well as the inclusion of different diagnostic algorithms. This was carried out jointly by the different Lipid Units of the Spanish Society of Atherosclerosis, Hospital Virgen Macarena in Seville, Hospital Juan Ramón Jiménez, Hospital Infanta Elena, and Hospital de Río Tinto during 2018 and 2019. RESULTS: The 4diagnostic algorithms entered into the Laboratory Information System, showed a total of 9,985 patients with c-LDL>200mg/dl. The diagnostic algorithm was extended to include Apo B, with 8,182 determinations showing an apolipoprotein B>100mg/dl). A total of 747 lipoprotein (a) were determined, of which 30.65% were> 50mg/dl. More than 2/3 (71.80%) showed results compatible with small and dense LDL particles. CONCLUSIONS: The implementation of new analytical parameters and algorithms in Primary Care laboratory results can identify a considerable number of patients with different alterations in lipid metabolism. This, together with the classic risk factors, could contribute to a correct risk stratification in preventing the progression of cardiovascular disease.

Prevalence of severe hypercholesterolemia observed in different hospitals in Andalusia and Ceuta. / Prevalencia de hipercolesterolemias severas observadas en los distintos hospitales de Andalucía y Ceuta.

Severe hypercholesterolaemia is a major cardiovascular risk factor. Early detection and treatment can reduce the incidence of cardiovascular disease. Given the high prevalence of hypercholesterolaemia in Andalusia, the development of a screening strategy for its detection in Primary Care may be an efficient measure. OBJECTIVE: To identify patients in Primary Care with severe hypercholesterolaemia that may increase their cardiovascular risk by reviewing LDL-cholesterol results in computerised laboratory systems. MATERIAL AND METHODS: Observational, retrospective, multi-centre study in 16 hospitals in Andalusia and Ceuta. Anonymous analytical data were acquired from the different laboratory computer systems for the year 2018, and exclusively from Macarena Hospital for the year 2019. RESULTS: From a total of 1,969,035 determinations on≥18 years old, 2,791 patients (0.14%) were detected with LDL-cholesterol>250mg/dl and from a total of 2.327.211 determinations studied in children under 18 years old, 3,804 patients (0.16%) were detected with LDL-cholesterol>135mg/dL. The highest incidence of possible genetic hypercholesterolaemia in adults corresponded to the province of Seville with 23.6 cases/1,000 determinations, while in minors, the highest incidence corresponded to the province of Cadiz with 75 possible cases/1,000 determinations. A geographical triangle of greater prevalence is observed between the provinces of Seville, Huelva and Cadiz. CONCLUSIONS: The development of a screening strategy using a computerised review of LDL-cholesterol in Primary Care detects a large number of subjects with severe hypercholesterolaemia that could benefit from an early intervention.

Choroidal Thickness and Volume Modifications Induced by Aerobic Exercise in Healthy Young Adults.

INTRODUCTION: Our aim was to evaluate the changes in choroidal thickness (CT) and volume (CV) following aerobic physical exercise in healthy young adults. METHODS: This study included 72 eyes from healthy volunteers between 22 and 37 years old. Using the International Physical Activity Questionnaire, total physical activity was computed. Measurements using an autorefractometer, ocular biometry, and spectral-domain optical coherence tomography using the Enhanced Depth Imaging protocol were taken. OCT was performed as a baseline measurement and after performing 10 min of dynamic physical exercise (3 and 10 min post-exercise). The choroidal layer was manually segmented, and the CT and CV in different areas from the Early Treatment Diabetic Retinopathy Study grid were obtained. RESULTS: In healthy adults, at 3 min post-exercise, CT was higher in the subfoveal, the 3-mm nasal, and the 6-mm superior areas. Between 3 and 10 min post-exercise, the CT was reduced in all areas, and in some areas, the values were even smaller than the baseline measurements. The CV values showed changes after exercise similar to those of thickness. The total CV recovery after exercise was related to sex and physical activity level. CONCLUSION: Individuals with higher physical activity habits had greater CV at rest than those with lower physical activity levels. During exercise, healthy young people adjust CT and CV. At 3 min post-exercise, CT and CV increase. Women and individuals with greater physical activity levels reduce their total CV more than others during recovery.

Skin manifestations during the COVID-19 pandemic in the pediatric emergency department.

BACKGROUND: The role of SARS-CoV-2 as the cause of chilblains in children remains a matter of debate but it is important to elucidate it for patient isolation and contact tracing. We sought to define the etiology, clinical presentation, time course, and outcomes of children presenting to the emergency department (ED) with cutaneous manifestations shortly after the first pandemic peak of COVID-19 in Spain. METHODS: A prospective, observational study in children <15 years of age evaluated for skin lesions in the EDs of three pediatric hospitals. Children underwent a comprehensive work-up including tests for SARS-CoV-2 antibodies and polymerase chain reaction (PCR), and serology and PCR tests for other viruses and bacteria. A 1 month follow-up visit was conducted. RESULTS: From April 14 through May 8, 2020, we enrolled 62 children. Of those, 34 had acro-ischemic skin lesions and 28 had a variety of skin rashes. Overall, 40% of children had mild systemic symptoms. Children with chilblains were older, had pain more frequently and a more prolonged duration of skin lesions, while those with non-specific rashes had fever more frequently. Lesions were resolved in 75% of children at follow up. Five patients demonstrated SARS-CoV-2 antibodies, and none tested positive with PCR. Three additional patients tested positive with PCR for rhinovirus, Mycoplasma pneumoniae and Chlamydia pneumoniae. CONCLUSIONS: The number of ED visits for chilblains, which are rare in pediatrics, was high soon after the first peak of COVID-19 in Spain. The disease course was self-limited, outcomes were favorable, and the possibility of viral transmission was negligible as all patients tested negative for SARS-CoV-2 by PCR.

Liver-lung interactions in acute respiratory distress syndrome.

Patients with liver diseases are at high risk for the development of acute respiratory distress syndrome (ARDS). The liver is an important organ that regulates a complex network of mediators and modulates organ interactions during inflammatory disorders. Liver function is increasingly recognized as a critical determinant of the pathogenesis and resolution of ARDS, significantly influencing the prognosis of these patients. The liver plays a central role in the synthesis of proteins, metabolism of toxins and drugs, and in the modulation of immunity and host defense. However, the tools for assessing liver function are limited in the clinical setting, and patients with liver diseases are frequently excluded from clinical studies of ARDS. Therefore, the mechanisms by which the liver participates in the pathogenesis of acute lung injury are not totally understood. Several functions of the liver, including endotoxin and bacterial clearance, release and clearance of pro-inflammatory cytokines and eicosanoids, and synthesis of acute-phase proteins can modulate lung injury in the setting of sepsis and other severe inflammatory diseases. In this review, we summarized clinical and experimental support for the notion that the liver critically regulates systemic and pulmonary responses following inflammatory insults. Although promoting inflammation can be detrimental in the context of acute lung injury, the liver response to an inflammatory insult is also pro-defense and pro-survival. A better understanding of the liver-lung axis will provide valuable insights into new diagnostic targets and therapeutic strategies for clinical intervention in patients with or at risk for ARDS.

Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review.

According to the World Health Organization (WHO) report in 2016, around 800,000 of individuals have committed suicide. Moreover, suicide is the second cause of unnatural death in people between 15 and 29 years. This paper reviews state of the art on the literature concerning the use of machine learning methods for suicide detection on social networks. Consequently, the objectives, data collection techniques, development process and the validation metrics used for suicide detection on social networks are analyzed. The authors conducted a scoping review using the methodology proposed by Arksey and O'Malley et al. and the PRISMA protocol was adopted to select the relevant studies. This scoping review aims to identify the machine learning techniques used to predict suicide risk based on information posted on social networks. The databases used are PubMed, Science Direct, IEEE Xplore and Web of Science. In total, 50% of the included studies (8/16) report explicitly the use of data mining techniques for feature extraction, feature detection or entity identification. The most commonly reported method was the Linguistic Inquiry and Word Count (4/8, 50%), followed by Latent Dirichlet Analysis, Latent Semantic Analysis, and Word2vec (2/8, 25%). Non-negative Matrix Factorization and Principal Component Analysis were used only in one of the included studies (12.5%). In total, 3 out of 8 research papers (37.5%) combined more than one of those techniques. Supported Vector Machine was implemented in 10 out of the 16 included studies (62.5%). Finally, 75% of the analyzed studies implement machine learning-based models using Python.

Users' Experiences of a Mobile Health Self-Management Approach for the Treatment of Cystic Fibrosis: Mixed Methods Study.

BACKGROUND: Despite a large number of clinical trials aiming at evaluating the digital self-management of chronic diseases, there is little discussion about users' experiences with digital approaches. However, a good user experience is a critical factor for technology adoption. Understanding users' experiences can inform the design of approaches toward increased motivation for digital self-management. OBJECTIVE: This study aimed to evaluate the self-management of cystic fibrosis (CF) with a focus on gastrointestinal concerns and the care of young patients. Following a user-centered design approach, we developed a self-management app for patients and parents and a web tool for health care professionals (HCPs). To evaluate the proposed solutions, a 6-month clinical trial was conducted in 6 European CF competence centers. This paper analyzes the user acceptance of the technology and the benefits and disadvantages perceived by the trial participants. METHODS: A mixed methods approach was applied. Data were collected through 41 semistructured qualitative interviews of patients, parents, and HCPs involved in the clinical trial. In addition, data were collected through questionnaires embedded in the self-management app. RESULTS: Support for enzyme dose calculation and nutrition management was found to be particularly useful. Patients and parents rapidly strengthened their knowledge about the treatment and increased their self-efficacy. Reported benefits include reduced occurrence of symptoms and enhanced quality of life. Patients and parents had different skills, requiring follow-up by HCPs in an introductory phase. HCPs valued obtaining precise information about the patients, allowing for more personalized advice. However, the tight follow-up of several patients led to an increased workload. Over time, as patient self-efficacy increased, patient motivation for using the app decreased and the quality of the reported data was reduced. CONCLUSIONS: Self-management enfolds a collaboration between patients and HCPs. To be successful, a self-management approach should be accepted by both parties. Through understanding behaviors and experiences, this study defines recommendations for a complex case-the demanding treatment of CF. We identify target patient groups and situations for which the app is most beneficial and suggest focusing on these rather than motivating for regular app usage over a long time. We also advise the personalized supervision of patients during the introduction of the approach. Finally, we propose to develop guidance for HCPs to facilitate changes in practice. As personalization and technology literacy are factors found to influence the acceptance of digital self-management of other chronic diseases, it is relevant to consider the proposed recommendations beyond the case of CF.