Survey of general practitioners' awareness, practice and perception of social prescribing across Europe

BACKGROUND

Social prescribing (SP) is a patient pathway by which healthcare professionals connect patients with other sources of support, groups, or activities within their community. The awareness, practice, and perception of SP among GPs across Europe remains unclear.

OBJECTIVES

To explore the awareness, practice, and perception of GPs on SP in the WONCA Europe region.

METHODS

An anonymous, cross-sectional online survey was distributed through a snowballing system, mailing lists, and at three international conferences in 2022/2023 to explore GPs' awareness, practice, and perception of SP. The questionnaire in English contained 21 open and closed questions.

RESULTS

Of the 208 participating GPs from 33 countries, 116 (56%) previously heard of 'social prescribing' and 66 (32%) regularly referred patients to community activities through a formal system. These 66 GPs reported different funding sources and varied activities, with an average of four activities and physical exercise being the most prevalent. Among them, 25 (38%) knew about national or local SP awareness campaigns. Of these 25, 17 (68%) agreed that SP increases their job satisfaction and 21 (84%) agreed that it has a positive impact on their patients. Variations in SP awareness and referral practice were evident across and within countries.

CONCLUSION

Despite disparities in awareness and referral practice as well as a diversity of activities and funding sources, most GPs who actively referred patients and were informed about SP campaigns agreed that SP positively impacts them and their patients.

[Teleconsultation: finding its place in primary care]

Teleconsultation is a remote health consultation using information and communication technologies. There are different modalities and specific practical and communication skills are required. Notwithstanding its prominence in Spain, there is little evidence on teleconsultation. This article explores the applicability, barriers, facilitators and future challenges of teleconsultation. While it has the potential to improve access to healthcare, as well as save time and costs for both patients and healthcare professionals, it faces a number of challenges such as the digital divide and resistance to change. To address new challenges and overcome obstacles, it is crucial to gain the trust of patients and professionals. Improving training in the skills required to optimize their use is also essential. Future research should aim to provide robust evidence regarding safety and cost-effectiveness to ensure successful implementation.

[Analysis of the interruptions generated by the use of smartphones among Primary Care Health professionals]

OBJECTIVE

To analyze the particular use of smartphones among Primary Care Health professionals during the care act and its consequences.

DESIGN

Multicenter, cross-sectional study in a primary care setting, carried out in 3phases: survey of professionals, checklist of professionals and survey of patients.

PARTICIPANTS

Primary Care Health professionals from the Territorial Primary Care Management of Barcelona (online survey) and health professionals (checklist) and patients (patient survey) from 2primary care teams in Barcelona city.

MAIN MEASUREMENTS

Bivariate descriptive analysis of the variables from the different surveys. Use of the mobile phone in the consultation, time, reason, type of use and perception of appropriateness. Characteristics of interruptions.

RESULTS

In relation to patients, 31% consider that the health professional should only consult the mobile phone if it is to resolve some aspect of their reason for consultation and 10% consider it a lack of respect. Eighteen percent of patients describe interruptions, the majority lasting between 10 and 30s and considering them mostly avoidable. In relation to professionals, the majority (96%) claim to have their mobile phone in the consultation and on mute (77%), with only 2% recognizing its use in the presence of the patient, which is in line with what the patients describe. Furthermore, 80% of professionals say they ask permission to use it, contrasting with what patients report (50%). Eighty-five percent of professionals consider its use appropriate.

CONCLUSIONS

The use of mobile phones is perceived by patients as an interruption that can affect the care act, generating dissatisfaction, which must be taken into account by health professionals. Healthcare organizations should establish recommendations regarding the use of mobile phones in consultations.

Impact of COVID-19 on the Pediatric Primary Care Model in Catalonia: Analysis of Changes in the Number and Type of Face-to-Face and Remote Visits

Background

The outbreak of COVID-19 has turned the care model of health systems around the world upside down. The health care crisis has led to opportunities for digital health to deliver quality care, and the system has been redirected toward telemedicine. In Catalonia, Spain, as of March 2020, the pattern of visits in primary care pediatric consultations changed, such that face-to-face visits decreased in favor of non-face-to-face visits.

Objective

This study aimed to analyze variations in the types of pediatric visits in primary care centers in Catalonia before and after the onset of COVID-19.

Methods

This was a descriptive observational study based on administrative data. The number and type of visits to primary care pediatric services in Catalonia between January 2019 and December 2022 were studied.

Results

A drop of more than 80% in face-to-face visits and an increase of up to 15 times in remote visits were observed as of March 2020 compared to the previous year. Subsequently, the face-to-face attendance rate began to recover, although it did not reach the same rate as before COVID-19. Non-face-to-face visits were maintained, representing more than 20% of the total after more than 2 years of the pandemic.

Conclusions

COVID-19 has been the trigger for a transition in the types of visits to primary care pediatric services. The COVID-19 pandemic was a clear catalyst for the integration of telemedicine in Catalan pediatric health care. In this context, although face-to-face consultations have recovered in absolute numbers, after the pandemic period, the weight of telemedicine has increased.

Correction: Feasibility of a Pediatric Acute Video Consultation Process Among Health Care Professionals in Primary Care in a Rural Setting: Protocol for a Prospective Validation Study

[This corrects the article DOI: 10.2196/52946.].

Real-world testing of an artificial intelligence algorithm for the analysis of chest X-rays in primary care settings

Interpreting chest X-rays is a complex task, and artificial intelligence algorithms for this purpose are currently being developed. It is important to perform external validations of these algorithms in order to implement them. This study therefore aims to externally validate an AI algorithm's diagnoses in real clinical practice, comparing them to a radiologist's diagnoses. The aim is also to identify diagnoses the algorithm may not have been trained for. A prospective observational study for the external validation of the AI algorithm in a region of Catalonia, comparing the AI algorithm's diagnosis with that of the reference radiologist, considered the gold standard. The external validation was performed with a sample of 278 images and reports, 51.8% of which showed no radiological abnormalities according to the radiologist's report. Analysing the validity of the AI algorithm, the average accuracy was 0.95 (95% CI 0.92; 0.98), the sensitivity was 0.48 (95% CI 0.30; 0.66) and the specificity was 0.98 (95% CI 0.97; 0.99). The conditions where the algorithm was most sensitive were external, upper abdominal and cardiac and/or valvular implants. On the other hand, the conditions where the algorithm was less sensitive were in the mediastinum, vessels and bone. The algorithm has been validated in the primary care setting and has proven to be useful when identifying images with or without conditions. However, in order to be a valuable tool to help and support experts, it requires additional real-world training to enhance its diagnostic capabilities for some of the conditions analysed. Our study emphasizes the need for continuous improvement to ensure the algorithm's effectiveness in primary care.

[Improving quality of life in older adults with the decline syndrome: The role of occupational therapy in primary care]

OBJECTIVE

To evaluate the effect of an occupational therapy intervention in users recently diagnosed with the decline syndrome, who have experienced a decrease in the Barthel and/or Lawton index in the last month and susceptible to improvement based on medical opinion.

DESIGN

Non-controlled, quasi-experimental longitudinal study. A pre-post intervention.

LOCATION

Sant Hipòlit de Voltregà health centre. Osona, Barcelona.

PARTICIPANTS

Patients referred by the centre's primary care nursing, social work or medical staff with a recent diagnosis of decline syndrome who may benefit from the intervention of an occupational therapy professional.

INTERVENTION

Following the initial assessment visit, four training sessions were conducted to improve functional independence, mobility and adaptation of the home environment, providing training to primary caregivers.

MAIN MEASUREMENTS

Patient autonomy was assessed using the Barthel and Lawton scales, quality of life using the EuroQol questionnaire (EQ-5D) and home suitability using the home suitability assessment questionnaire.

RESULTS

Improvements were observed in autonomy in activities of daily living (p=0.003), mobility (p=0.001) and housing adaptation (p<0.001). The level of anxiety/depression was reduced (p=0.028), and the mean health status score increased markedly (p<0.001).

CONCLUSIONS

This study highlights the improvement in the quality of life and autonomy in the basic activities of daily living for individuals receiving occupational therapy, emphasizing the need for home adaptation and family support.

The artificial intelligence revolution in primary care: Challenges, dilemmas and opportunities

Artificial intelligence (AI) can be a valuable tool for primary care (PC), as, among other things, it can help healthcare professionals improve diagnostic accuracy, chronic disease management and the overall efficiency of the care they provide. It is important to emphasise that AI should not be seen as a replacement tool, but as an aid to PC professionals. Although AI is capable of processing large amounts of data and generating accurate predictions, it cannot replace the skill and expertise of professionals in clinical decision making. AI still requires the interpretation and clinical judgement of a trained healthcare professional and cannot provide the empathy and emotional support often required in healthcare.

Feasibility of a Pediatric Acute Video Consultation Process Among Health Care Professionals in Primary Care in a Rural Setting: Protocol for a Prospective Validation Study

BACKGROUND

For years, in Catalonia and in the rest of Spain, there has been a deficit and an unequal geographical distribution of health professionals specializing in pediatrics, especially in rural areas. Among the proposals to improve this situation is the promotion of the use of information and communication technologies (ICT) among users and professionals. Moreover, with the outbreak of COVID-19, the use of telehealth has become an essential tool, with an overall increase in non-face-to-face visits, including in primary care pediatrics. In this context, telemedicine, when used in primary care pediatrics, can be an effective means of improving families' access to medical care. Currently, in Catalonia, telemedicine involving patients and health professionals is used in pediatric primary care through telephone consultation and asynchronous teleconsultation (eConsulta). Video consultation is in practice not used, although it could have different applications.

OBJECTIVE

The aim of this study is to evaluate the feasibility of a video consultation process with physical examination in acute pediatric pathology in rural areas among primary care professionals. In addition, the level of satisfaction with these remote consultations will be assessed from the perspective of both the users and the health care professionals.

METHODS

We will conduct a prospective experimental study to analyze the possibility of using video consultation in pediatric acute care in primary care in central Catalonia (Spain). A minimum of 170 children aged between 0 and 14 years attending the primary care center (PCC) for acute illness for a period of 1 year will be included in the study. Initially, the telemetric visit, including a physical examination, will include a nurse at the patient and family's side and a pediatrician who will participate remotely. Subsequently, the pediatrician will visit the patient in person and the physical examination and diagnosis made during the remote visit will be compared with the physical examination and diagnosis of the face-to-face visit, which is considered the gold standard.

RESULTS

Recruitment was planned to begin in the second half of 2023 and continue for at least 1 year. It is anticipated to be a good resource for a variety of acute pediatric conditions in primary care. The evaluation will focus on the feasibility of performing live remote visits and comparing their diagnostic accuracy with that of face-to-face visits.

CONCLUSIONS

We believe that this study could provide evidence on the feasibility and diagnostic accuracy of video consultation in pediatric acute primary care in a rural setting, as well as on satisfaction with video consultations among both users and professionals. If proven useful in addressing the acute needs of children in a variety of situations, it could become a digital health tool that improves the overall pediatric primary care service in rural areas, for both families and professionals.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/52946.

A Sex- and Gender-Based Approach to Chronic Conditions in Central Catalonia (Spain): A Descriptive Cross-Sectional Study

The growth of chronic conditions worldwide poses a challenge for both health systems and the quality of life of people with these conditions. However, sex- and gender-based approaches are scarce in this field. Adopting this perspective, this study aims to describe the prevalence of chronic conditions in the Bages-Moianès region (Catalonia, Spain), and analyse the associations of chronic conditions with sex and age. This cross-sectional study used data from the population assigned to the Catalan Health Institute primary care settings in this area between 2018 and 2021 (n = 163,024). A total of 26 chronic conditions (grouped into 7 typologies), sex and age were the analysis variables. A total of 75,936 individuals presented at least one chronic condition, representing 46.6% of the analysed population. The prevalence was higher among women and older individuals. Being male was associated with a greater probability of presenting cardiovascular diseases, neurodevelopmental disorders and metabolic diseases and a lower probability of presenting neurodegenerative diseases, chronic pain and mental health disorders. Adjusting by sex, a positive age gradient was observed in most groups, except for respiratory diseases and mental health disorders. Chronic conditions have a high prevalence in the Bages-Moianès region, showing differences in typology, sex and age. Adopting gender perspectives (both in health systems and future research) is crucial when dealing with chronic conditions in order to take into account their differential impact.

eHealth in the Management of Depressive Episodes in Catalonia's Primary Care From 2017 to 2022: Retrospective Observational Study

BACKGROUND

The reasons for mental health consultations are becoming increasingly relevant in primary care. The Catalan health care system is undergoing a process of digital transformation, where eHealth is becoming increasingly relevant in routine clinical practice.

OBJECTIVE

This study aimed to analyze the approach to depressive episodes and the role of eHealth in the Catalan health care system from 2017 to 2022.

METHODS

A retrospective observational study was conducted on diagnostic codes related to depressive episodes and mood disorders between 2017 and 2022 using data from the Catalan Institute of Health. The sociodemographic evolution and prevalence of depression and mood disorders in Catalonia were analyzed between 2017 and 2022. Sociodemographic variables were analyzed using absolute frequency and percentage. The prevalence of depressive episodes was calculated, highlighting the year-to-year changes. The use of eHealth for related consultations was assessed by comparing the percentages of eHealth and face-to-face consultations. A comparison of sociodemographic variables based on attendance type was conducted. Additionally, a logistic regression model was used to explore factors influencing face-to-face attendance. The analysis used R software (version 4.2.1), with all differences examined using 95% CIs.

RESULTS

From 2017 to 2022, there was an 86.6% increase in the prevalence of depression and mood disorders, with women consistently more affected (20,950/31,197, 67.2% in 2017 and 22,078/33,169, 66.6% in 2022). In 2022, a significant rise in depression diagnoses was observed in rural areas (difference 0.71%, 95% CI 0.04%-1.43%), contrasting with a significant decrease in urban settings (difference -0.7%, 95% CI -1.35% to -0.05%). There was a significant increase in antidepressant use in 2022 compared to 2017 (difference 2.4%, 95% CI 1.87%-3.06%) and the proportion of eHealth visits rose from 4.34% (1240/28,561) in 2017 to 26.3% (8501/32,267) in 2022. Logistic regression analysis indicated that men (odds ratio [OR] 1.06, 95% CI 1.04-1.09) and younger individuals had a higher likelihood of eHealth consultations in 2022. Furthermore, individuals using eHealth consultations were more likely to use antidepressants (OR 1.54, 95% CI 1.50-1.57) and anxiolytics (OR 1.06, 95% CI 1.03-1.09).

CONCLUSIONS

The prevalence of depression in Catalonia has significantly increased in the last 6 years, likely influenced by the COVID-19 pandemic. Despite ongoing digital transformation since 2011, eHealth usage remained limited as of 2017. During the lockdown period, eHealth accounted for nearly half of all health care consultations, representing a quarter of consultations by 2022. In the immediate aftermath of the COVID-19 pandemic, emerging evidence suggests a significant role of eHealth in managing depression-related consultations, along with an apparent likelihood of patients being prescribed antidepressants and anxiolytics. Further research is needed to understand the long-term impact of eHealth on diagnostic practices and medication use.

Corrigendum: Feasibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen self-testing in school and summer camp attendees

[This corrects the article DOI: 10.3389/fped.2022.975454.].

Knowledge and Perception of the Use of AI and its Implementation in the Field of Radiology: Cross-Sectional Study

BACKGROUND

Artificial Intelligence (AI) has been developing for decades, but in recent years its use in the field of health care has experienced an exponential increase. Currently, there is little doubt that these tools have transformed clinical practice. Therefore, it is important to know how the population perceives its implementation to be able to propose strategies for acceptance and implementation and to improve or prevent problems arising from future applications.

OBJECTIVE

This study aims to describe the population's perception and knowledge of the use of AI as a health support tool and its application to radiology through a validated questionnaire, in order to develop strategies aimed at increasing acceptance of AI use, reducing possible resistance to change and identifying possible sociodemographic factors related to perception and knowledge.

METHODS

A cross-sectional observational study was conducted using an anonymous and voluntarily validated questionnaire aimed at the entire population of Catalonia aged 18 years or older. The survey addresses 4 dimensions defined to describe users' perception of the use of AI in radiology, (1) "distrust and accountability," (2) "personal interaction," (3) "efficiency," and (4) "being informed," all with questions in a Likert scale format. Results closer to 5 refer to a negative perception of the use of AI, while results closer to 1 express a positive perception. Univariate and bivariate analyses were performed to assess possible associations between the 4 dimensions and sociodemographic characteristics.

RESULTS

A total of 379 users responded to the survey, with an average age of 43.9 (SD 17.52) years and 59.8% (n=226) of them identified as female. In addition, 89.8% (n=335) of respondents indicated that they understood the concept of AI. Of the 4 dimensions analyzed, "distrust and accountability" obtained a mean score of 3.37 (SD 0.53), "personal interaction" obtained a mean score of 4.37 (SD 0.60), "efficiency" obtained a mean score of 3.06 (SD 0.73) and "being informed" obtained a mean score of 3.67 (SD 0.57). In relation to the "distrust and accountability" dimension, women, people older than 65 years, the group with university studies, and the population that indicated not understanding the AI concept had significantly more distrust in the use of AI. On the dimension of "being informed," it was observed that the group with university studies rated access to information more positively and those who indicated not understanding the concept of AI rated it more negatively.

CONCLUSIONS

The majority of the sample investigated reported being familiar with the concept of AI, with varying degrees of acceptance of its implementation in radiology. It is clear that the most conflictive dimension is "personal interaction," whereas "efficiency" is where there is the greatest acceptance, being the dimension in which there are the best expectations for the implementation of AI in radiology.

Efficacy, Safety, and Evaluation Criteria of mHealth Interventions for Depression: Systematic Review

BACKGROUND

Depression is a significant public health issue that can lead to considerable disability and reduced quality of life. With the rise of technology, mobile health (mHealth) interventions, particularly smartphone apps, are emerging as a promising approach for addressing depression. However, the lack of standardized evaluation tools and evidence-based principles for these interventions remains a concern.

OBJECTIVE

In this systematic review and meta-analysis, we aimed to evaluate the efficacy and safety of mHealth interventions for depression and identify the criteria and evaluation tools used for their assessment.

METHODS

A systematic review and meta-analysis of the literature was carried out following the recommendations of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. Studies that recruited adult patients exhibiting elevated depressive symptoms or those diagnosed with depressive disorders and aimed to assess the effectiveness or safety of mHealth interventions were eligible for consideration. The primary outcome of interest was the reduction of depressive symptoms, and only randomized controlled trials (RCTs) were included in the analysis. The risk of bias in the original RCTs was assessed using version 2 of the Cochrane risk-of-bias tool for randomized trials.

RESULTS

A total of 29 RCTs were included in the analysis after a comprehensive search of electronic databases and manual searches. The efficacy of mHealth interventions in reducing depressive symptoms was assessed using a random effects meta-analysis. In total, 20 RCTs had an unclear risk of bias and 9 were assessed as having a high risk of bias. The most common element in mHealth interventions was psychoeducation, followed by goal setting and gamification strategies. The meta-analysis revealed a significant effect for mHealth interventions in reducing depressive symptoms compared with nonactive control (Hedges g=-0.62, 95% CI -0.87 to -0.37, I2=87%). Hybrid interventions that combined mHealth with face-to-face sessions were found to be the most effective. Three studies compared mHealth interventions with active controls and reported overall positive results. Safety analyses showed that most studies did not report any study-related adverse events.

CONCLUSIONS

This review suggests that mHealth interventions can be effective in reducing depressive symptoms, with hybrid interventions achieving the best results. However, the high level of heterogeneity in the characteristics and components of mHealth interventions indicates the need for personalized approaches that consider individual differences, preferences, and needs. It is also important to prioritize evidence-based principles and standardized evaluation tools for mHealth interventions to ensure their efficacy and safety in the treatment of depression. Overall, the findings of this study support the use of mHealth interventions as a viable method for delivering mental health care.

TRIAL REGISTRATION

PROSPERO CRD42022304684; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=304684.

Factors associated with the attraction and retention of family and community medicine and nursing residents in rural settings: a qualitative study

BACKGROUND

The current shortage of primary care doctors and nurses is causing difficulties in replacement, and this shortage is expected to increase. This situation is more pronounced in rural environments than in urban ones. Family and community care specialty training is a key component of both the transition to clinical practice and the retention of new professionals. The aim of this study is to explore the attitudes and perceptions of internal medicine residents and internal nurse residents trained in a rural teaching unit on factors associated with recruitment and retention, including the role of the specialty training programme.

METHODS

A qualitative study was conducted. Purposive sampling was used, and thirteen residents from the central Catalonia teaching unit who were in their final year of training participated in semistructured interviews. The data were collected during 2022 and were subsequently analysed with thematic analysis. The study is reported using the COREQ checklist.

RESULTS

Six themes emerged from data related to perceptions and attitudes about the factors associated with recruitment and retention: training programme, characteristics of the family and community specialty, concept of rural life, family and relational factors, economic and resource factors, and recruitment and job opportunities.

CONCLUSIONS

Family and community medicine and nursing residents trained in rural settings expressed satisfaction with the specialty programme and most features of primary care, but they experienced a wide range of uncertainties in deciding on their professional future in terms of living in rural areas, family support, financial support and recruitment. This study identifies individual and structural factors that could be of great use to retain doctors and nurses in rural areas.

[Approach to digital transformation in healthcare to reduce the digital divide]

Digital transformation involves the integration of technology into all areas of an organization and a change in the way of operating and providing value. In the healthcare sector, digital transformation should focus on improving health for all by accelerating the development and adoption of digital solutions. The WHO considers digital health as a key factor in ensuring universal health coverage, protection against health emergencies, and better well-being for one billion people worldwide. Digital transformation in healthcare should include digital determinants of health as new factors of inequality alongside classic social determinants. Addressing digital determinants of health and the digital divide is essential to ensure that all people have access to the benefits of digital technology for their health and well-being.

Creation of a Laboratory for Statistics and Analysis of Dependence and Chronic Conditions: Protocol for the Bages Territorial Specialization and Competitiveness Project (PECT BAGESS)

BACKGROUND

With the increasing prevalence of chronic diseases, partly due to the increase in life expectancy and the aging of the population, the complexity of the approach faced by the structures, dynamics, and actors that are part of the current care and attention systems is evident. The territory of Bages (Catalonia, Spain) presents characteristics of a highly complex ecosystem where there is a need to develop new, more dynamic structures for the various actors in the health and social systems, aimed at incorporating new actors in the technological and business field that would allow innovation in the management of this context. Within the framework of the Bages Territorial Specialization and Competitiveness Project (PECT BAGESS), the aim is to address these challenges through various entities that will develop 7 interrelated operations. Of these, the operation of the IDIAP Jordi Gol-Catalan Health Institute focuses on the creation of a Laboratory for Statistics and Analysis of Dependence and Chronic Conditions in the Bages region, in the form of a database that will collect the most relevant information from the different environments that affect the management of chronic conditions and dependence: health, social, economic, and environment.

OBJECTIVE

This study aims to create a laboratory for statistical, dependence, and chronic condition analysis in the Bages region, to determine the chronic conditions and conditions that generate dependence in the Bages area, in order to propose products and services that respond to the needs of people in these situations.

METHODS

PECT BAGESS originated from the Shared Agenda initiative, which was established in the Bages region with the goal of enhancing the quality of life and fostering social inclusion for individuals with chronic diseases. This study presents part of this broader project, consisting of the creation of a database. Data from chronic conditions and dependence service providers will be combined, using a unique identifier for the different sources of information. A thorough legal analysis was conducted to establish a secure data sharing mechanism among the entities participating in the project.

RESULTS

The laboratory will be a key piece in the structure generated in the environment of the PECT BAGESS, which will allow relevant information to be passed on from the different sectors involved to respond to the needs of people with chronic conditions and dependence, as well as to generate opportunities for products and services.

CONCLUSIONS

The emerging organizational dynamics and structures are expected to demonstrate a health and social management model that may have a remarkable impact on these sectors. Products and services developed may be very useful for generating synergies and facilitating the living conditions of people who can benefit from all these services. However, secure data sharing circuits must be considered.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/46542.

Impact of the COVID-19 pandemic on diagnosis of respiratory diseases in the Northern Metropolitan Area in Barcelona (Spain)

Objective

The COVID-19 pandemic has had a great effect on the management of chronic diseases, by limiting the access to primary care and to diagnostic procedures, causing a decline in the incidence of most diseases. Our aim was to analyze the impact of the pandemic on primary care new diagnoses of respiratory diseases.

Methods

Observational retrospective study performed to describe the effect of COVID-19 pandemic on the incidence of respiratory diseases according to primary care codification. Incidence rate ratio between pre-pandemic and pandemic period was calculated.

Results

We found a decrease in the incidence of respiratory conditions (IRR 0.65) during the pandemic period. When we compared the different groups of diseases according to ICD-10, we found a significant decrease in the number of new cases during the pandemic period, except in the case of pulmonary tuberculosis, abscesses or necrosis of the lungs and other respiratory complications (J95). Instead, we found increases in flu and pneumonia (IRR 2.17) and respiratory interstitial diseases (IRR 1.41).

Conclusion

There has been a decrease in new diagnosis of most respiratory diseases during the COVID-19 pandemic.

Prevalence of Respiratory Infections during the 2018-2020 Period in the Paediatric Population of Primary Care Centres in Central Catalonia

Following the COVID-19 pandemic, policies such as social distancing, hand washing, and the use of masks were implemented, which could play an important role in the reduction of infectious diseases. An observational, descriptive, cross-sectional study was conducted to observe the prevalence of respiratory infections in children under 15 years of age during the 2018-2020 period in Primary Care centres in Central Catalonia. In 2020, there was a 44.3% decrease in total consultations for respiratory infections compared to 2019. All respiratory infections exhibited a significant decrease except flu-like syndrome; children between the ages of 6 and 12 had the highest prevalence of flu-like syndrome (87.6%), and the SARS-CoV-2-19 infection was most frequent (4%) among those between the ages of 12 and 15. Compared to urban centres, rural centres presented a higher prevalence of all infections except flu-like syndrome and SARS-CoV-2. In conclusion, the COVID-19 pandemic caused a significant decrease in the number of consultations for respiratory infections in the paediatric population, except for flu-like syndrome, which increased in cases in January, February, and March 2020. No differences were found between sexes, although differences were found in the distribution of the different age groups.

European Perspective on How Social Prescribing Can Facilitate Health and Social Integrated Care in the Community

Social Prescribing is a mechanism by which primary care team members can refer patients to community groups to improve their health and well-being. It integrates health, social care, and community, allowing patients to actively improve their health and well-being by participating in community initiatives and activities. These activities have traditionally been part of community life in European countries, and the benefits need to be consistently recognized.

Analysing Twitter's Role in Combating the Magnetic Vaccine Conspiracy Theory Using Social Network Analysis

BACKGROUND

The popularity of the magnetic vaccine conspiracy theory, and others of a similar nature, creates challenges to promoting vaccines and disseminating accurate health information.

OBJECTIVE

Health conspiracy theories are gaining in popularity. The study's objective was to evaluate the Twitter social media network related to the magnetic vaccination conspiracy theory and to apply social capital theory to analyse the unique social structures of influential users. As a strategy for online public health surveillance, we employ social network analysis to identify the important opinion leaders sharing the conspiracy, the key websites, and the narratives.

METHODS

A total of 18,706 tweets were retrieved and analysed using social network analysis. Data were retrieved from June 01 to June 13 (2021) using the keyword 'vaccine magnetic'. Tweets were retrieved via a dedicated Twitter Application Programming Interface (API). More specifically, the Academic Track API was used, and the data were analysed using NodeXL Pro and Gephi.

RESULTS

There were a total of 22,762 connections between Twitter users within the dataset. The study found that the most influential user within the network consisted of a news account that was reporting on the conspiracy. There were also several other users that became influential such as an epidemiologist, a health economist, and a retired sports athlete who exerted their social capital within the network.

CONCLUSIONS

Our study finds that influential users were effective broadcasters against the conspiracy, and their reach extended beyond their own network of Twitter followers. We emphasise the need for trust in contact with influential users concerning health information, particularly in the context of widespread social uncertainty resulting from the pandemic, when public sentiment on social media may be unpredictable. The study highlights the potential of influential users to disrupt information flows of conspiracy theories due to their unique social capital.

CLINICALTRIAL

CauRuler: Causal irredundant association rule miner for complex patient trajectory modelling

BACKGROUND AND OBJECTIVES

Discovering causal associations between variables is one of the main goals of clinical trials, with the ultimate aim of identifying the causes of specific health status. Prior knowledge of causal paths could help ensure patients do not develop the resultant conditions. In recent years, thanks to the enormous amount of health data stored with the support of digital tools, attempts have been made to employ Machine Learning to infer causality. Those methodologies suffer from some deficiencies in controlling cofounders when analysing causality, as well as providing causal rules general enough to be useful in healthcare practice. Conversely, this work presents and evaluates CauRuler, a new approach to deal with causality from association rules. The proposed approach uses a pruning strategy to reduce the association rule set, which does not compromise the causality learning capability of the algorithm. This behaviour makes the algorithm suitable for exploiting large health databases with thousands of patients and medical instances. CauRuler can control a larger number of confounders than other proposals, bringing robustness to causal analysis and avoiding the identification of spurious associations. Additionally, the method generalizes causality using anti-monotone properties to obtain complex and general causal paths. The method can target correct causal associations in complex medical databases with retrospective data.

METHOD

CauRuler extends association rule mining with an irredundancy property so that the set of rules learnt is reduced in size and generalized. General association rules, conformed by fewer items, enable controlling more confounding variables to verify, with more statistical evidence on available data, if they represent causal paths in patient disease trajectories.

RESULTS

CauRuler has been tested on a complex real medical database (3,5 M visits to the primary care services between 2019 and 2020, and controlling over 15.000 different variables including diagnoses and demographic and other clinical patient data). The reduction of the rule set achieved by the pruning strategy goes from 7.732 to 2.240 rules, from which 46 have been found to have causality relationships in the patient trajectories, and generalized to 14 rules tested as true causal relationships thanks to the confounding analysis. These rules have been validated by clinicians with the support of a graphical map. The obtained causal paths control in average of 906 confounder variables, retrieving robust results.

CONCLUSIONS

Causal relationships enable predicting causal paths between health conditions according to patient trajectories. Knowing these causal paths is crucial for understanding and preventing the appearance or worsening of diseases in patients. CauRuler, with high demanding thresholds, has proven its efficiency and effectiveness in targeting previously known causal associations between diagnoses, reaching consensus in the medical community. Softening these thresholds should help target interesting general causal paths.

Subcutaneous anti-COVID-19 hyperimmune immunoglobulin for prevention of disease in asymptomatic individuals with SARS-CoV-2 infection: a double-blind, placebo-controlled, randomised clinical trial

BACKGROUND

Anti-COVID-19 hyperimmune immunoglobulin (hIG) can provide standardized and controlled antibody content. Data from controlled clinical trials using hIG for the prevention or treatment of COVID-19 outpatients have not been reported. We assessed the safety and efficacy of subcutaneous anti-COVID-19 hyperimmune immunoglobulin 20% (C19-IG20%) compared to placebo in preventing development of symptomatic COVID-19 in asymptomatic individuals with SARS-CoV-2 infection.

METHODS

We did a multicentre, randomized, double-blind, placebo-controlled trial, in asymptomatic unvaccinated adults (≥18 years of age) with confirmed SARS-CoV-2 infection within 5 days between April 28 and December 27, 2021. Participants were randomly assigned (1:1:1) to receive a blinded subcutaneous infusion of 10 mL with 1 g or 2 g of C19-IG20%, or an equivalent volume of saline as placebo. The primary endpoint was the proportion of participants who remained asymptomatic through day 14 after infusion. Secondary endpoints included the proportion of individuals who required oxygen supplementation, any medically attended visit, hospitalisation, or ICU, and viral load reduction and viral clearance in nasopharyngeal swabs. Safety was assessed as the proportion of patients with adverse events. The trial was terminated early due to a lack of potential benefit in the target population in a planned interim analysis conducted in December 2021. ClinicalTrials.gov registry: NCT04847141.

FINDINGS

461 individuals (mean age 39.6 years [SD 12.8]) were randomized and received the intervention within a mean of 3.1 (SD 1.27) days from a positive SARS-CoV-2 test. In the prespecified modified intention-to-treat analysis that included only participants who received a subcutaneous infusion, the primary outcome occurred in 59.9% (91/152) of participants receiving 1 g C19-IG20%, 64.7% (99/153) receiving 2 g, and 63.5% (99/156) receiving placebo (difference in proportions 1 g C19-IG20% vs. placebo, -3.6%; 95% CI -14.6% to 7.3%, p = 0.53; 2 g C19-IG20% vs placebo, 1.1%; -9.6% to 11.9%, p = 0.85). None of the secondary clinical efficacy endpoints or virological endpoints were significantly different between study groups. Adverse event rate was similar between groups, and no severe or life-threatening adverse events related to investigational product infusion were reported.

INTERPRETATION

Our findings suggested that administration of subcutaneous human hyperimmune immunoglobulin C19-IG20% to asymptomatic individuals with SARS-CoV-2 infection was safe but did not prevent development of symptomatic COVID-19.

FUNDING

Grifols.

Translation, Cross-Cultural Adaptation, and Psychometric Validation of the Positive Body Image among Adolescents Scale (PBIAS) into Spanish and Catalan

The Positive Body Image among Adolescents Scale (PBIAS) explores the factors that bolster and interfere with developing and maintaining a positive body image during adolescence. The aim of this study was to translate, adapt, and validate the PBIAS into Spanish and Catalan. A cross-sectional study was conducted for the instrument's translation, cross-cultural adaptation, and psychometric validation. A process of translation, back-translation, expert consultation, and piloting was followed. The reliability and statistical validity were evaluated. The Cronbach's alpha was 0.95 in both the Spanish and Catalan versions. Pearson's correlation coefficients were statistically significant (r > 0.087) for all items analyzed. The resulting values of the Spanish and Catalan versions indicate a good level of concordance (p < 0.001) with the original questionnaire, the comparative fit index being 0.914 and 0.913, the Tucker-Lewis index being 0.893 and 0.892, the root mean square error of approximation being 1.31 and 1.28, and the standardized root mean square residual being 0.051 and 0.060, respectively. The instrument presents a good level of internal consistency, a high level of reliability, and statistical validity compared to the original instrument. The PBIAS in Spanish and Catalan can be a useful assessment instrument for educators and health professionals in the context of adolescent mental health literacy. This work contributes to the Sustainable Development Goals (Goal 3) of the United Nations 2030 Agenda.

Gender, Mental Health and Socioeconomic Differences in Fibromyalgia: A Retrospective Cohort Study Using Real-World Data from Catalonia

The main objective of our study was to assess the associated risk between fibromyalgia (FM) and the incidence of the diagnosis of anxiety and depression in the general population during the years 2010-2017 in Catalonia.

METHOD

A retrospective cohort study was designed using the Information System for Research Development in Primary Care database. All patients with FM were included (n = 56,098) and matched to the control group in a 1:2 pairing ratio (n = 112,196). The demographic variables studied were sex, age and socio-economic status.

RESULTS

Patients with FM have a lower survival rate if they are also diagnosed with anxiety and depression during the entire study period, with the rate being 26.6% lower in FM patients at an 8-year follow-up (0.58, 95%CI: 0.57-0.59 vs. 0.79, 95%CI: 0.78-0.79). There is a 58% reduction in the risk of developing anxiety and/or depression in the control group vs. the FM group (p-value < 0.05), and by 45% in male vs. female sex (p-value < 0.05).

CONCLUSIONS

FM is a disease that is associated with anxiety and depression, and men are at lower risk of anxiety and depression after FM diagnosis.

Use of virtual reality compared to the role-playing methodology in basic life support training: a two-arm pilot community-based randomised trial

INTRODUCTION

Virtual reality (VR) is a technology that allows us to replace our real environment with one created with digital media. This technology is increasingly used in the training of healthcare professionals, and previous studies show that the involvement and motivation of students who participate in activities that use VR increases compared to those who undergo training with the traditional methodology. The main aim of the study is to evaluate the learning curve of the students using a VR environment, to evaluate the satisfaction with the training activity and the cost, and to compare them with training that uses role-playing methodology.

METHODOLOGY

Two-arm community-based randomised trial. The control arm will base the training on the usual role-playing methodology. The second arm or intervention arm will base the Basic Life Support (BLS) training on a VR programme.

RESULTS

Statistically significant differences are observed in the percentage of correct answers in favour of the group that used VR as a learning methodology in the test taken at the end of the course. These differences disappear when comparing the results of the test performed at six months. The satisfaction rating of the role-playing training activity has a score of 9.37 out of a total of 10 and satisfaction with the VR methodology has a score of 9.72. The cost analysis shows that the cost of training a student by role-playing is 32.5 euros and, if trained by VR, it is 41.6 euros.

CONCLUSIONS

VR is a tool that allows the consolidation of a greater amount of knowledge in the short term and can be used for situations such as pandemics, where traditional formats are not available. In relation to student satisfaction with the training activity, the rating in both groups is very high and the differences are minimal. The results will be directly applicable to the decision making of BLS training in Central Catalonia in relation to the scheduling of training activities that use the VR methodology in an uncertain environment.

Impact of the COVID-19 pandemic on diagnosis of respiratory diseases in the Northern Metropolitan Area in Barcelona (Spain)

OBJECTIVE

The COVID-19 pandemic has had a great effect on the management of chronic diseases, by limiting the access to primary care and to diagnostic procedures, causing a decline in the incidence of most diseases. Our aim was to analyze the impact of the pandemic on primary care new diagnoses of respiratory diseases.

METHODS

Observational retrospective study performed to describe the effect of COVID-19 pandemic on the incidence of respiratory diseases according to primary care codification. Incidence rate ratio between pre-pandemic and pandemic period was calculated.

RESULTS

We found a decrease in the incidence of respiratory conditions (IRR 0.65) during the pandemic period. When we compared the different groups of diseases according to ICD-10, we found a significant decrease in the number of new cases during the pandemic period, except in the case of pulmonary tuberculosis, abscesses or necrosis of the lungs and other respiratory complications (J95). Instead, we found increases in flu and pneumonia (IRR 2.17) and respiratory interstitial diseases (IRR 1.41).

CONCLUSION

There has been a decrease in new diagnosis of most respiratory diseases during the COVID-19 pandemic.

Feasibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen self-testing in school and summer camp attendees

Background

SARS-CoV-2 screening is one of the pillars of non-pharmaceutical preventive strategies to early identify and isolate infected individuals and therefore decrease community incidence.

Methods

We assessed the feasibility of severe acute respiratory syndrome coronavirus 2 self-testing with antigen-detecting rapid diagnostic tests in attendees of educational settings.

Results

A total of 305 students (88.15%) and 41 staff (11.85%) from 9 to 56 years old participated in the self-testing procedure and answered the survey at the end of the study. 91.3% (n = 313) did not need help, 96.1% of participants reported the same outcome as the healthcare workers. 94.5% strongly or slightly agree with the statement "I would repeat the experience".

Conclusion

The study demonstrates that self-testing is acceptable and usable in children, adolescents and adults when the epidemiological situation may require a systematic screening of these populations, although supervision by health care or previously trained personnel is recommended for younger age groups.

Analyzing Discussions Around Rural Health on Twitter During the COVID-19 Pandemic: Social Network Analysis of Twitter Data

Background

Individuals from rural areas are increasingly using social media as a means of communication, receiving information, or actively complaining of inequalities and injustices.

Objective

The aim of our study is to analyze conversations about rural health taking place on Twitter during a particular phase of the COVID-19 pandemic.

Methods

This study captured 57 days' worth of Twitter data related to rural health from June to August 2021, using English-language keywords. The study used social network analysis and natural language processing to analyze the data.

Results

It was found that Twitter served as a fruitful platform to raise awareness of problems faced by users living in rural areas. Overall, Twitter was used in rural areas to express complaints, debate, and share information.

Conclusions

Twitter could be leveraged as a powerful social listening tool for individuals and organizations that want to gain insight into popular narratives around rural health.

Knowledge and perception of primary care healthcare professionals on the use of artificial intelligence as a healthcare tool

Objective

The rapid digitisation of healthcare data and the sheer volume being generated means that artificial intelligence (AI) is becoming a new reality in the practice of medicine. For this reason, describing the perception of primary care (PC) healthcare professionals on the use of AI as a healthcare tool and its impact in radiology is crucial to ensure its successful implementation.

Methods

Observational cross-sectional study, using the validated Shinners Artificial Intelligence Perception survey, aimed at all PC medical and nursing professionals in the health region of Central Catalonia.

Results

The survey was sent to 1068 health professionals, of whom 301 responded. And 85.7% indicated that they understood the concept of AI but there were discrepancies in the use of this tool; 65.8% indicated that they had not received any AI training and 91.4% that they would like to receive training. The mean score for the professional impact of AI was 3.62 points out of 5 (standard deviation (SD)  =  0.72), with a higher score among practitioners who had some prior knowledge of and interest in AI. The mean score for preparedness for AI was 2.76 points out of 5 (SD  =  0.70), with higher scores for nursing and those who use or do not know if they use AI.

Conclusions

The results of this study show that the majority of professionals understood the concept of AI, perceived its impact positively, and felt prepared for its implementation. In addition, despite being limited to a diagnostic aid, the implementation of AI in radiology was a high priority for these professionals.

Eleven-month longitudinal study of antibodies in SARS-CoV-2 exposed and naïve primary health care workers upon COVID-19 vaccination

We evaluated the kinetics of antibody responses to Two years into the COVID-19 pandemic and 1 year after the start of vaccination rollout, the world faced a peak of cases associated with the highly contagious Omicron variant of concern (VoC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) and nucleocapsid (N) antigens over five cross-sectional visits (January-November 2021), and the determinants of pre-booster immunoglobulin levels, in a prospective cohort of vaccinated primary health care workers in Catalonia, Spain. Antibodies against S antigens after a full primary vaccination course, mostly with BNT162b2, decreased steadily over time and were higher in pre-exposed (n = 247) than naïve (n = 200) individuals, but seropositivity was maintained at 100% (100% IgG, 95.5% IgA, 30.6% IgM) up to 319 days after the first dose. Antibody binding to variants of concern was highly maintained for IgG compared to wild type but significantly reduced for IgA and IgM, particularly for Beta and Gamma. Factors significantly associated with longer-term antibodies included age, sex, occupation, smoking, adverse reaction to vaccination, levels of pre-vaccination SARS-CoV-2 antibodies, interval between disease onset and vaccination, hospitalization, oxygen supply, post COVID and symptomatology. Earlier morning vaccination hours were associated with higher IgG responses in pre-exposed participants. Symptomatic breakthroughs occurred in 9/447 (2.01%) individuals, all among naïve (9/200, 4.5%) and generally boosted antibody responses. Additionally, an increase in IgA and/or IgM seropositivity to variants, and N seroconversion at later time points (6.54%), indicated asymptomatic breakthrough infections, even among pre-exposed. Seropositivity remained highly stable over almost a year after vaccination. However, gradually waning of anti-S IgGs that correlate with neutralizing activity, coupled to evidence of an increase in breakthrough infections during the Delta and Omicron predominance, provides a rationale for booster immunization.

Effects of Physical Activity Interventions in the Elderly with Anxiety, Depression, and Low Social Support: A Clinical Multicentre Randomised Trial

The percentage of older people is increasing worldwide. Loneliness and anxious−depressive states are emerging health conditions in this population group, and these conditions give rise to higher morbidity and mortality. Physical activity (PA) and social relationships have been linked to physical and mental health. The objective of this study was to evaluate whether a 4-month programme of moderate PA in a group would improve the emotional state, levels of social support, and quality of life in a sample of individuals >64 years of age. A multicentre randomised clinical trial was designed in primary care. Ninety (90) participants were selected. After the intervention, there were positive differences between the groups, with significant improvements in the intervention group (IG) in depression, anxiety, health status perception, and social support. Walking in a group two days per week for 4 months reduced clinical depression and anxiety by 59% and 45%, respectively. The level of satisfaction was very high, and adherence was high. In conclusion, the moderate group PA programme improved clinical anxiety, depression, social support, and perceptions of health status in the patients studied.

The #VaccinesWork Hashtag on Twitter in the Context of the COVID-19 Pandemic: Network Analysis

Background

Vaccination is one of the most successful public health interventions for the prevention of COVID-19. Toward the end of April 2021, UNICEF (United Nations International Children’s Emergency Fund), alongside other organizations, were promoting the hashtag #VaccinesWork.

Objective

The aim of this paper is to analyze the #VaccinesWork hashtag on Twitter in the context of the COVID-19 pandemic, analyzing the main messages shared and the organizations involved.

Methods

The data set used in this study consists of 11,085 tweets containing the #VaccinesWork hashtag from the 29th to the 30th of April 2021. The data set includes tweets that may not have the hashtag but were replies or mentions in those tweets. The data were retrieved using NodeXL, and the network graph was laid out using the Harel-Koren fast multiscale layout algorithm.

Results

The study found that organizations such as the World Health Organization, UNICEF, and Gavi were the key opinion leaders and had a big influence on the spread of information among users. Furthermore, the most shared URLs belonged to academic journals with a high impact factor. Provaccination users had other vaccination-promoting hashtags in common, not only in the COVID-19 scenario.

Conclusions

This study investigated the discussions surrounding the #VaccinesWork hashtag. Social media networks containing conspiracy theories tend to contain dubious accounts leading the discussions and are often linked to unverified information. This kind of analysis can be useful to detect the optimal moment for launching health campaigns on Twitter.

Sustained seropositivity up to 20.5 months after COVID-19

This study evaluated the persistence of IgM, IgA, and IgG to SARS-CoV-2 spike and nucleocapsid antigens up to 616 days since the onset of symptoms in a longitudinal cohort of 247 primary health care workers from Barcelona, Spain, followed up since the start of the pandemic. The study also assesses factors affecting antibody levels, including comorbidities and the responses to variants of concern as well as the frequency of reinfections. Despite a gradual and significant decline in antibody levels with time, seropositivity to five SARS-CoV-2 antigens combined was always higher than 90% over the whole study period. In a subset of 23 participants who had not yet been vaccinated by November 2021, seropositivity remained at 95.65% (47.83% IgM, 95.65% IgA, 95.65% IgG). IgG seropositivity against Alpha and Delta predominant variants was comparable to that against the Wuhan variant, while it was lower for Gamma and Beta (minority) variants and for IgA and IgM. Antibody levels at the time point closest to infection were associated with age, smoking, obesity, hospitalization, fever, anosmia/hypogeusia, chest pain, and hypertension in multivariable regression models. Up to 1 year later, just before the massive roll out of vaccination, antibody levels were associated with age, occupation, hospitalization, duration of symptoms, anosmia/hypogeusia, fever, and headache. In addition, tachycardia and cutaneous symptoms associated with slower antibody decay, and oxygen supply with faster antibody decay. Eight reinfections (3.23%) were detected in low responders, which is consistent with a sustained protective role for anti-spike naturally acquired antibodies. Stable persistence of IgG and IgA responses and cross-recognition of the predominant variants circulating in the 2020-2021 period indicate long-lasting and largely variant-transcending humoral immunity in the initial 20.5 months of the pandemic, in the absence of vaccination.

Using Artificial Intelligence as a Diagnostic Decision Support Tool in Skin Disease: Protocol for an Observational Prospective Cohort Study

BACKGROUND

Dermatological conditions are a relevant health problem. Each person has an average of 1.6 skin diseases per year, and consultations for skin pathology represent 20% of the total annual visits to primary care and around 35% are referred to a dermatology specialist. Machine learning (ML) models can be a good tool to help primary care professionals, as it can analyze and optimize complex sets of data. In addition, ML models are increasingly being applied to dermatology as a diagnostic decision support tool using image analysis, especially for skin cancer detection and classification.

OBJECTIVE

This study aims to perform a prospective validation of an image analysis ML model as a diagnostic decision support tool for the diagnosis of dermatological conditions.

METHODS

In this prospective study, 100 consecutive patients who visit a participant general practitioner (GP) with a skin problem in central Catalonia were recruited. Data collection was planned to last 7 months. Anonymized pictures of skin diseases were taken and introduced to the ML model interface (capable of screening for 44 different skin diseases), which returned the top 5 diagnoses by probability. The same image was also sent as a teledermatology consultation following the current stablished workflow. The GP, ML model, and dermatologist's assessments will be compared to calculate the precision, sensitivity, specificity, and accuracy of the ML model. The results will be represented globally and individually for each skin disease class using a confusion matrix and one-versus-all methodology. The time taken to make the diagnosis will also be taken into consideration.

RESULTS

Patient recruitment began in June 2021 and lasted for 5 months. Currently, all patients have been recruited and the images have been shown to the GPs and dermatologists. The analysis of the results has already started.

CONCLUSIONS

This study will provide information about ML models' effectiveness and limitations. External testing is essential for regulating these diagnostic systems to deploy ML models in a primary care practice setting.

An AI-driven Digital Health solution to support clinical management of long COVID patients: prospective multicenter observational study

Background

COVID-19 pandemic has revealed the weaknesses of most health systems around the world, collapsing them and depleting their available health care resources. Fortunately, the development and enforcement of specific public health policies, such as vaccination, mask wearing, and social distancing, among others, has reduced the prevalence and complications associated with COVID-19 in its acute phase. However, the aftermath of the global pandemic has called for an efficient approach to manage patients with long COVID-19. This is a great opportunity to leverage on innovative digital health solutions to provide exhausted health care systems with the most cost-effective and efficient tools available to support the clinical management of this population. In this context, the SENSING-AI project is focused on the research toward the implementation of an artificial intelligence–driven digital health solution that supports both the adaptive self-management of people living with long COVID-19 and the health care staff in charge of the management and follow-up of this population.

Objective

The objective of this protocol is the prospective collection of psychometric and biometric data from 10 patients for training algorithms and prediction models to complement the SENSING-AI cohort.

Methods

Publicly available health and lifestyle data registries will be consulted and complemented with a retrospective cohort of anonymized data collected from clinical information of patients diagnosed with long COVID-19. Furthermore, a prospective patient-generated data set will be captured using wearable devices and validated patient-reported outcomes questionnaires to complement the retrospective cohort. Finally, the ‘Findability, Accessibility, Interoperability, and Reuse’ guiding principles for scientific data management and stewardship will be applied to the resulting data set to encourage the continuous process of discovery, evaluation, and reuse of information for the research community at large.

Results

The SENSING-AI cohort is expected to be completed during 2022. It is expected that sufficient data will be obtained to generate artificial intelligence models based on behavior change and mental well-being techniques to improve patients’ self-management, while providing useful and timely clinical decision support services to health care professionals based on risk stratification models and early detection of exacerbations.

Conclusions

SENSING-AI focuses on obtaining high-quality data of patients with long COVID-19 during their daily life. Supporting these patients is of paramount importance in the current pandemic situation, including supporting their health care professionals in a cost-effective and efficient management of long COVID-19.

Trial Registration

Clinicaltrials.gov NCT05204615; https://clinicaltrials.gov/ct2/show/NCT05204615

International Registered Report Identifier (IRRID)

DERR1-10.2196/37704

Influenza vaccination in coronavirus times: Primary Care professionals' intention to get vaccinated in Central Catalonia (VAGCOVID). A cross sectional study

Influenza vaccination is the main measure of prevention against epidemic flu. Although recommended, vaccination coverage remains low. The lack of knowledge about the evolution of influenza in the context of the SARS-CoV-2 coronavirus pandemic led to the recommendation of influenza vaccination to people at risk and professionals to avoid a greater burden than the one already posed by SARS-CoV-2. The aim of the study is to determine health professionals' intention to vaccinate against seasonal flu in the 2020-2021 campaign, in the context of the SARS-CoV-2 pandemic, and to analyse the factors that influence it. Cross-sectional study through a structured survey aimed at Primary Care professionals in Central Catalonia. A total of 610 participants responded to the survey, 65.7% of whom intended to get vaccinated against influenza in this campaign, and 11.1% did not know or did not answer. The intention to get vaccinated is associated with the professional category and the number of years of professional practice. The profile of the professionals who intend to get vaccinated against flu includes professionals with a history of vaccination, who participate in on-call duties and perceive that their dependents were at risk of becoming ill. During the SARS-CoV-2 pandemic, although almost two-thirds of the respondents showed a clear intention to get vaccinated against influenza, 11% were doubtful. To improve influenza vaccination uptake among health professionals, strategies need to be devised to target those professionals who are hesitant or reluctant to vaccinate.

Applicability of information and communication technologies in a secondary hospital pelvic floor service

Information and Communication Technologies increase healthcare education. Since the COVID-19 pandemic outbreak, they have been gaining importance. Our aim was to assess the effects of a web-based questionnaire used in a pelvic floor consultation. We performed a prospective intervention study analysing the use of a web-based questionnaire prior to a first appointment. Fifty-two women used the questionnaire and 52 did not. All patients filled in a paper-based survey relating to satisfaction and pelvic floor knowledge after the appointment. Women in the intervention group showed better knowledge. They had 11% more correct answers for organ prolapse definition [CI 95% (-0.30 to 0.07)], 25% more correct answers for incontinence definition [CI 95% (-0.41 to -0.08)] and 23% better incontinence classification [CI 95% (-0.34 to 0.09]. More patients in the web-questionnaire group started primary therapy in the first consultation (38% versus 16%). Measurements of the total mean time in the consultation room revealed no statistically significant differences [19.36 (SD 4.96) and 21.19 (SD 4.62) minutes, respectively; p = .05] and satisfaction levels were similar.After using our web-based questionnaire, the time for medical histories reduced and patient knowledge increased without changing satisfaction levels. Impact statementWeb-based questionnaires (WBQ) and information web links may help to reduce time of history taking while time for physical examination, counselling and treatment discussion increases. Also, patient knowledge improves.What is already known on this subject? There are reviews showing how Information and Communication Technologies (ICT) can improve health quality and sanitary education. Since the Covid-19 pandemic started, ICT use has been accelerated and traineeship and learning has been enforced. However, there is not extensive research on its use in gynaecological consultations.What do the results of this study add? We have proved that the use of a WBQ and information web links before face-to-face first visit in a pelvic floor service improves patient knowledge. We have also worked to provide scientific evidence to an ICT tool.What are the implications of these findings for clinical practice and/or further research? The most important implications for clinical practice are the improvement of patient-provider communication, the time reduction for history taking in contrast to time increase for physical examination, counselling and treatment discussion.Apart from that, WBQ may help to measure qualitative information, because it is registered and can be used as patient reported outcomes (PRO) to increase quality of care. Further research should focus on other benefits of WBQ such as achieving better patient satisfaction.

Descriptive study of a telemedicine program in palpebral pathology for primary care (tele-eyelid)

BACKGROUND AND OBJECTIVE

In 2013 we implemented an asynchronous telemedicine circuit for the diagnosis of eyelid diseases (tele-eyelid), connecting the outpatient primary healthcare with the hospital's specialists. The purpose of this study is to assess the use of telemedicine in the diagnosis of eyelid diseases by primary care teams, to evaluate its usefulness and to analyse the epidemiology of the pathological conditions referred to the tertiary level hospital, as well as the need for surgery.

MATERIALS AND METHODS

This study was carried out in the Spanish public health system, in a mainly rural area assisted by the Institut Català de la Salut (ICS) and Althaia Xarxa Assistencial Universitària de Manresa. This is a retrospective, descriptive analysis of the telematic consultations undertaken between 2013 and 2019. The consultations between 2018 and 2019 underwent a further descriptive retrospective-prospective analysis to assess the conditions referred to the hospital.

RESULTS

Unnecessary referrals were avoided in 72% of telematic consultations. More than 50% of primary care practitioners used tele-eyelid. Up to 68% of the referrals were due to eyelid tumours, 50% needed surgery and 18%, a biopsy. Moreover, we found a high reliability between telematic and face-to-face diagnosis.

CONCLUSIONS

Teleophthalmology applied to eyelid pathology is a useful tool to improve access to specialized care and helps solving pathological conditions. It avoids unnecessary consultations and increases efficiency, both in primary and hospital care.

The experiences of patients with diabetes and strategies for their management during the first COVID-19 lockdown: a qualitative study

BACKGROUND

During the pandemic, primary care systems prioritised attention to COVID-19 patients; chronically ill patients, such as people with Type 2 Diabetes were obliged to take more responsibility for their own care. We aimed to analyse the experiences of patients with Type 2 Diabetes Mellitus during the stay-at-home order that was in place during the first wave of the COVID-19 pandemic and identify the strategies and resources used in managing their care.

METHOD

We conducted a qualitative descriptive study. The participants were ten patients with type 2 Diabetes Mellitus who experienced strict lockdown during the first wave of the COVID-19 pandemic in Catalonia, Spain, selected using intentional sampling. We recorded semi-structured interviews with the participants and conducted thematic analysis.

RESULTS

We identified 14 subthemes, which we then grouped into three overarching themes: 1) anxiety, fear, and vulnerability (anxiety, fear, vulnerability, rethinking life, loneliness, sadness), 2) insufficient diabetes monitoring by the health system (health care received, glycaemic control, view of treatment by health providers) and proactive self-care (changes in daily routine, diet, physical activity, medication, personal protective equipment & social distancing).

CONCLUSION

Despite the exceptional nature of the situation and the stress, worry, and changes in their daily lives, many respondents reported that they had successfully modified their lifestyles. Self-care was effective during confinement and was based on a process of adaptation using the resources available, without face-to-face contact with primary care health staff.

RELEVANCE TO CLINICAL PRACTICE

These results can help to guide the design and implementation of self-care-focused strategies and also to explore new ways of empowering patients without access to health care personnel.

A Social Network Analysis of Twitter Data Related to Blood Clots and Vaccines

After the first weeks of vaccination against SARS-CoV-2, several cases of acute thrombosis were reported. These news reports began to be shared frequently across social media platforms. The aim of this study was to conduct an analysis of Twitter data related to the overall discussion. The data were retrieved from 14 March to 14 April 2021 using the keyword 'blood clots'. A dataset with n = 266,677 tweets was retrieved, and a systematic random sample of 5% of tweets (n = 13,334) was entered into NodeXL for further analysis. Social network analysis was used to analyse the data by drawing upon the Clauset-Newman-Moore algorithm. Influential users were identified by drawing upon the betweenness centrality measure. Text analysis was applied to identify the key hashtags and websites used at this time. More than half of the network comprised retweets, and the largest groups within the network were broadcast clusters in which a number of key users were retweeted. The most popular narratives involved highlighting the low risk of obtaining a blood clot from a vaccine and highlighting that a number of commonly consumed medicine have higher blood clot risks. A wide variety of users drove the discussion on Twitter, including writers, physicians, the general public, academics, celebrities, and journalists. Twitter was used to highlight the low potential of developing a blood clot from vaccines, and users on Twitter encouraged vaccinations among the public.

Using artificial intelligence as a diagnostic decision support tool in skin disease: observational prospective cohort study (Preprint)

Background

Dermatological conditions are a relevant health problem. Each person has an average of 1.6 skin diseases per year, and consultations for skin pathology represent 20% of the total annual visits to primary care and around 35% are referred to a dermatology specialist. Machine learning (ML) models can be a good tool to help primary care professionals, as it can analyze and optimize complex sets of data. In addition, ML models are increasingly being applied to dermatology as a diagnostic decision support tool using image analysis, especially for skin cancer detection and classification.

Objective

This study aims to perform a prospective validation of an image analysis ML model as a diagnostic decision support tool for the diagnosis of dermatological conditions.

Methods

In this prospective study, 100 consecutive patients who visit a participant general practitioner (GP) with a skin problem in central Catalonia were recruited. Data collection was planned to last 7 months. Anonymized pictures of skin diseases were taken and introduced to the ML model interface (capable of screening for 44 different skin diseases), which returned the top 5 diagnoses by probability. The same image was also sent as a teledermatology consultation following the current stablished workflow. The GP, ML model, and dermatologist’s assessments will be compared to calculate the precision, sensitivity, specificity, and accuracy of the ML model. The results will be represented globally and individually for each skin disease class using a confusion matrix and one-versus-all methodology. The time taken to make the diagnosis will also be taken into consideration.

Results

Patient recruitment began in June 2021 and lasted for 5 months. Currently, all patients have been recruited and the images have been shown to the GPs and dermatologists. The analysis of the results has already started.

Conclusions

This study will provide information about ML models’ effectiveness and limitations. External testing is essential for regulating these diagnostic systems to deploy ML models in a primary care practice setting.

Mobile Applications in Mood Disorders and Mental Health: Systematic Search in Apple App Store and Google Play Store and Review of the Literature

OBJECTIVES

The main objective of this work was to explore and characterize the current landscape of mobile applications available to treat mood disorders such as depression, bipolar disorder, and dysthymia.

METHODS

We developed a tool that makes both the Apple App Store and the Google Play Store searchable using keywords and that facilitates the extraction of basic app information of the search results. All app results were filtered using various inclusion and exclusion criteria. We characterized all resultant applications according to their technical details. Furthermore, we searched for scientific publications on each app's website and PubMed, to understand whether any of the apps were supported by any type of scientific evidence on their acceptability, validation, use, effectiveness, etc. Results: Thirty apps were identified that fit the inclusion and exclusion criteria. The literature search yielded 27 publications related to the apps. However, these did not exclusively concern mood disorders. 6 were randomized studies and the rest included a protocol, pilot-, feasibility, case-, or qualitative studies, among others. The majority of studies were conducted on relatively small scales and 9 of the 27 studies did not explicitly study the effects of mobile application use on mental wellbeing.

CONCLUSION

While there exists a wealth of mobile applications aimed at the treatment of mental health disorders, including mood disorders, this study showed that only a handful of these are backed by robust scientific evidence. This result uncovers a need for further clinically oriented and systematic validation and testing of such apps.

Spike-based COVID-19 immunization increases antibodies to nucleocapsid antigen

Antibodies to the nucleocapsid (N) antigen are suggested to be used to monitor infections after COVID-19 vaccination, as first generation subunit vaccines are based on the spike (S) protein. We used multiplex immunoassays to simultaneously measure antibody responses to different fragments of the SARS-CoV-2 S and N antigens for evaluating the immunogenicity of the mRNA-1273 (Spykevax) and the BNT162b2 (Comirnaty) vaccines in 445 health care workers. We report a >4-fold increase post-vaccination of IgG levels to the full length (N FL) and C-terminus of N (N CT) in 5.2% and 18.0% of individuals, respectively, and of IgA in 3.6% (N FL) and 9.0% (N CT) of them. The increase in IgG levels and avidity was more pronounced after Spykevax than Comirnaty vaccination (36.2% vs 13.1% for N CT, and 10.6% vs 3.7% for N FL). Data suggest the induction of cross-reactive antibodies against the N CT region after administering these S-based vaccines, and this should be taken into account when using N seropositivity to detect breakthroughs.

Comparing the Clinical Characteristics and Mortality of Residential and Non-Residential Older People with COVID-19: Retrospective Observational Study

Nursing homes have accounted for a significant part of SARS-CoV-2 mortality, causing great social alarm. Using data collected from electronic medical records of 1,319,839 institutionalised and non-institutionalised persons ≥ 65 years, the present study investigated the epidemiology and differential characteristics between these two population groups. Our results showed that the form of presentation of the epidemic outbreak, as well as some risk factors, are different among the elderly institutionalised population with respect to those who are not. In addition to a twenty-fold increase in the rate of adjusted mortality among institutionalised individuals, the peak incidence was delayed by approximately three weeks. Having dementia was shown to be a risk factor for death, and, unlike the non-institutionalised group, neither obesity nor age were shown to be significantly associated with the risk of death among the institutionalised. These differential characteristics should be able to guide the actions to be taken by the health administration in the event of a similar infectious situation among institutionalised elderly people.