Online journal of public health informatics最新文献

Unlabelled: This viewpoint highlights the critical need for proactive and strategic integration of digital health tools into heat-health action plans (HHAPs) across Europe. Drawing insights from the digital health surge during the COVID-19 pandemic and recent heat-related health impacts, we identify response gaps and suggest specific strategies to strengthen current plans. Key recommendations include leveraging mobile health communication, expanding telemedicine usage, adopting wearable health monitoring devices, and using advanced data analytics to improve responsiveness and equity. This perspective aims to guide policymakers, health authorities, and health care providers in systematically enhancing heat-health preparedness through digital health innovation.

Background: Threats to data integrity have always existed in online human subjects research, but it appears these threats have become more common and more advanced in recent years. Researchers have proposed various techniques to address satisficers, repeat participants, bots, and fraudulent participants; yet, no synthesis of this literature has been conducted.

Objective: This study undertakes a scoping review of recent methods and ethical considerations for addressing threats to data integrity in online research.

Methods: A PubMed search was used to identify 90 articles published from 2020 to 2024 that were written in English, that discussed online human subjects research, and that had at least one paragraph dedicated to discussing threats to online data integrity.

Results: We cataloged 16 types of techniques for addressing threats to online data integrity. Techniques to authenticate personal information (eg, videoconferencing and mailing incentives to a physical address) appear to be very effective at deterring or identifying fraudulent participants. Yet such techniques also come with ethical considerations, including participant burden and increased threats to privacy. Other techniques, such as Completely Automated Public Turing test to tell Computers and Humans Apart (reCAPTCHA; Google LLC), scores, and checking IP addresses, although very common, were also deemed by several researchers as no longer sufficient protections against advanced threats to data integrity.

Conclusions: Overall, this review demonstrates the importance of shifting online research protocols as bots and fraudulent participants become more sophisticated.

Background: Nigeria has made significant investments in client-level electronic health systems, including the Nigeria Medical Record System (NMRS) and the National Data Repository (NDR), with funding from the US President's Emergency Plan for AIDS Relief through the US Centers for Disease Control and Prevention (US CDC). A biometric system was used across the US CDC-supported program in Nigeria to consistently track and monitor service uptake by people living with HIV during this period. The system was used to conduct deduplication analysis with the goal of preventing double counting and improving data integrity across all the US CDC-supported treatment sites (health facilities and community sites).

Objective: We describe the fingerprint biometric system in Nigeria and the process used for deduplicating health records of people living with HIV, including preliminary results.

Methods: The fingerprint biometric system leveraged the availability of the electronic NMRS at health facilities and the NDR. The integration of the fingerprint biometric module into the NMRS enabled fingerprints capture using SecuGen devices. Stakeholder engagement and capacity building were conducted with people living with HIV and health facility staff for fingerprint capture, storage, and transmission of the fingerprint templates to the NDR. Deduplication of the fingerprint templates was conducted in the automated biometric information system that is integrated with the NDR.

Results: We implemented fingerprint capture for 1,538,971 people living with HIV to deduplicate records from 1,141 treatment sites to improve the reliability and uniqueness of the system of records. Preliminary data showed that of the 1,538,971 records assessed by 30th June 2024, 1,520,187 of the active records (98.78%) had valid fingerprints, and 1,264,299 (83.17%) of the records with valid fingerprints were unique.

Conclusions: The implementation of a biometric system using fingerprint data allowed the identification of potentially duplicate records for resolution, thereby improving the quality of HIV treatment data for HIV program planning.

Background: The COVID-19 pandemic continues to offer valuable insights into crisis management and risk communication, particularly through retrospective analyses that allow a more comprehensive understanding. Emotional responses played a crucial role in shaping how individuals processed information and built trust in different objects in the early stages of the COVID-19 pandemic.

Objective: This study aimed to investigate how negative emotions influence online information engagement and trust in 4 distinct entities: government, scientists, health care providers, and other people (relatives, friends, family, and strangers).

Methods: A nationwide survey was conducted in China from January 31 to February 9, 2020, involving 1568 adult participants. The data collection was particularly valuable due to the limited access to national samples in China during the early stages of the public health crisis. Participants were asked questions related to negative emotions, engagement with online information, and their trust in 4 different entities (government, scientists, other people, and health care providers) during the pandemic. Mediation analyses were performed to test the associations between the examined variables. A 95% bootstrap CI approach was used to estimate the mediation effects.

Results: This study reveals that negative emotions not only had a direct effect on trust but also indirectly fostered trust in the government and scientists through increased information engagement. There was a positive association (B=0.219, SE 0.023; P<.001) between negative emotions and information engagement. In addition, individuals experiencing more negative emotions tended to trust more in the government (B=0.191, SE 0.022; P<.001) and scientists (B=0.184, SE 0.017; P<.001). However, this effect did not extend to trust in health care providers or interpersonal trust.

Conclusions: The research findings reveal that while negative emotions directly and indirectly enhanced trust in the government and scientists through increased information engagement, they did not significantly impact trust in health care providers or interpersonal relationships in the Chinese context. These findings highlight the different pathways through which emotions and information behaviors affect trust during public health crises, offering critical lessons for future public health emergencies and risk communication.

Background: Neonatal disease and its outcomes are important indicators for a responsive health care system and encompass the effects of socioeconomic and environmental factors on new-borns and mothers. Ethiopia is working to achieve the Sustainable Development Goal target for the reduction of 12 or less per 1000 birth by 2030 and 21 per 1000 livebirths by 2025 as part of the second Ethiopian Health Sector Transformation Plan.

Objective: This study aimed to compare the performance of classical time-series models with that of deep learning models and to forecast the neonatal mortality rate in Ethiopia to verify whether Ethiopia will achieve national and international targets.

Methods: Data were extracted from the official World Bank database. Classical time-series models, such as autoregressive integrated moving average (ARIMA) and double exponential smoothing, and neural network-based models, such as multilayer perceptron, convolutional neural network, and long short-term memory, have been applied to forecast neonatal mortality rates from 2021 to 2030 in Ethiopia. During model building, the first 21 years of data (from 1990 to 2010) were used for training, and the remaining 10 years of data were used to test model performance. Model performance was evaluated using R², mean absolute percentage error (MAPE), and root mean squared error (RMSE). Finally, the best model was used to forecast the neonatal mortality rate over the next 10 years from 2021 to 2030, with a 95% prediction interval (PI).

Results: The results showed that the double exponential smoothing model was the best, with a maximum R2 of 99.94% and minimum MAPE and RMSE of 0.002 and 0.0748, respectively. The worst performing among the 5 models was the CNN, with an R2 of 93.71% and a maximum RMSE of 0.79. Neonatal mortality in Ethiopia is forecasted to be 23.20 (PI 22.20-24.40) per 1000 live births in 2025 and 19.80 (PI 17.10-22.80) per 1000 live births in 2030.

Conclusions: This study revealed that national and international targets for neonatal mortality cannot be realized if the current trend continues. This highlights the need for urgent interventions to strengthen the health system to fasten the decline rate of neonatal mortality and collaborative effort with concerned stakeholders for improved and responsive neonatal and child health services in order to achieve these targets.

Unlabelled: The COVID-19 pandemic accelerated the adoption of remote consultations across health care, requiring rapid adjustments in service delivery. Consequently, there is an urgent need to understand the impact of remote consultations on health pathways. This viewpoint paper explores key challenges in data sources in England that hinder research on the impact of remote consultations on health outcomes. Based on our experience conducting research on this topic, we present variations in observational study findings and their validity, considering differences in population characteristics and data sources. We provide recommendations to enhance data quality for future research, including improvements in data recording platforms and strengthened structures for linking primary and secondary care electronic health records.

Background: Emotional health plays a fundamental role in quality of life, particularly after the COVID-19 pandemic, which has increased stress and anxiety, especially among children and young people.

Objective: This study aimed to focus on the early identification of emotional processes that affect individuals' well-being and their effective management.

Methods: The open-source web app HealthTest was developed to help users understand and manage their emotions through tests focused on aspects such as stress, anxiety, and depression. The Open Source Scrum (OSCRUM) framework was used to optimize collaboration and effectively achieve objectives.

Results: HealthTest has established itself as a valuable tool for mental health professionals by gathering data from seventh-semester software engineering students and external users. It identifies trends in stress, anxiety, and depression through user self-assessments. In addition, it provides meditation and relaxation resources designed to support users in managing their emotional well-being.

Conclusions: This study promotes accessibility to self-care and health care tools. HealthTest reaffirms its commitment to benefiting both mental health professionals and patients, providing an effective avenue for controlling and improving emotional well-being.

Background: Socioeconomic and environmental factors influence youth mental well-being. Promoting mental well-being is essential to support youths' development toward adulthood with good mental health. Different Stockholm municipalities have adopted strategies to promote youth well-being. However, contextualizing and perceiving goals and mechanisms at the local municipal level is difficult. Thus, comparing or tracking their conception, purpose, and characteristics has been challenging.

Objective: We aimed to use data visualizations developed from a fusion of data sources to facilitate stakeholder conversations on promoting youth mental well-being within a municipality. We strive to demonstrate our methodology of using data visualizations as "boundary objects," which are cognitive artifacts that bridge knowledge from various domains to elicit understanding from specialized and siloed parts of a health delivery system.

Methods: Stakeholders from the municipalities of Lidingö and Nynäshamn participated in the study. A total of 15 workshops were conducted: 6 with only Lidingö participants, 6 with only Nynäshamn participants, and 3 with mixed participants. The sessions were conducted via Microsoft Teams or as physical sessions in Swedish and lasted between 60 and 90 minutes. Interactions were recorded with consent from participants. Recordings were transcribed using Amberscript software. We used matrix factorization with Kullback-Leibler divergence to extract 1000 features and created 10 topic clusters with 20 top words. We used the identified words and phrases to backtrack within the transcripts and to identify dialogues where they were used. We summarized participants' interactions across all the workshops to identify factors or strategies discussed for youth well-being.

Results: Participants noted that these sessions allowed them to contextualize their local observations from municipalities relative to the status of other municipalities in the national statistics. They indicated that they conceptualized well-being differently in their respective municipalities and between different professional backgrounds, and the sources of stress for youth differed. They noted the differences in the strategy and data collected for tracking youth well-being. Promotion of sports was a common strategy, while options for leisure activities differed between municipalities and professions.

Conclusions: Based on our observations and analysis of the transcripts from participatory workshops, we observed that the data-driven visualizations helped stakeholders from different departments of Lidingö and Nynäshamn municipalities to identify and bridge knowledge gaps caused by data silos. Participants noted proposals to modify future surveys and identified that this approach to visualizations would help them to share knowledge and maintain a long-term and sustainable