Using automated active infrared counters to estimate footfall on urban park footpaths: behavioural stability and validity testing.

BACKGROUND: Using infrared counters is a promising unobtrusive method of assessing footfall in urban parks. However, infrared counters are susceptible to reliability and validity issues, and there is limited guidance for their use. The aims of this study were to (1) determine how many weeks of automated active infrared count data would provide behaviourally stable estimates of urban park footfall for each meteorological season, and (2) determine the validity of automated active infrared count estimates of footfall in comparison to direct manual observation counts. METHODS: Three automated active infrared counters collected daily footfall counts for 365 days on three footpaths in an urban park within Northampton, England, between May 2021 - May 2022. Intraclass correlation coefficients were used to compare the behavioural stability of abbreviated data collection schedules with total median footfall within each meteorological season (Spring, Summer, Autumn, Winter). Public holidays, events, and extreme outliers were removed. Ten one-hour manual observations were conducted at the site of an infrared counter to determine the validity of the infrared counter. RESULTS: At least four-weeks (28 days) of infrared counts are required to provide 'good' to 'excellent' (Intraclass correlation > 0.75, > 0.9, respectively) estimates of median daily footfall per meteorological season in an urban park. Infrared counters had, on average, -4.65 counts per hour (95% LoA -12.4, 3.14; Mean absolute percentage error 13.7%) lower counts compared to manual observation counts during one-hour observation periods (23.2 ± 15.6, 27.9 ± 18.9 counts per hour, respectively). Infrared counts explained 98% of the variance in manual observation counts. The number of groups during an observation period explained 78% of the variance in the difference between infrared and manual counts. CONCLUSIONS: Abbreviated data collection schedules can still obtain estimates of urban park footfall. Automated active infrared counts are strongly associated with manual counts; however, they tend to underestimate footfall, often due to people in groups. Methodological and practical recommendations are provided.

Survey mode and nonresponse bias: A meta-analysis based on the data from the international social survey programme waves 1996-2018 and the European social survey rounds 1 to 9.

The constant increase in survey nonresponse and fieldwork costs are the reality of survey research. Together with other unpredictable events occurring in the world today, this increase poses a challenge: the necessity to accelerate a switch from face-to-face data collection to different modes, that have usually been considered to result in lower response rates. However, recent research has established that the simple response rate is a feeble measure of study quality. Therefore, this article aims to analyze the effect of survey characteristics, especially the survey mode, on the nonresponse bias. The bias measure used is the internal criteria first proposed by Sodeur and first applied by Kohler. The analysis is based on the survey documentation and results from the International Social Survey Programme waves 1996-2018 and the European Social Survey rounds 1 to 9. Random-effects three-level meta-regression models, based on data from countries from each inhabited continent, were created in order to estimate the impact of the survey mode or modes, sampling design, fieldwork experience, year of data collection, and response rate on the nonresponse bias indicator. Several ways of nesting observations within clusters were also proposed. The results suggest that using mail and some types of mixed-mode surveys were connected to lower nonresponse bias than using face-to-face mode surveys.

Managing the elephant in the room: responding to COVID-19's impact on data collection.

BACKGROUND: The global COVID-19 pandemic has affected data collection for many researchers, in particular research that involves face-to-face interviews. AIM: To share learning about the challenges encountered when face-to-face interviews could not continue as planned in a study and how to adapt data collection so that it can continue despite severe disruption. DISCUSSION: This article examines the considerations and actions taken by the authors to ensure the continuity of data collection. The research aimed to use narrative inquiry to understand the experiences of significant others supporting people in intensive care units with severe burn injuries. But the pandemic meant the researchers could not meet face-to-face with participants as originally intended and so they had to consider new ways to approach data collection. The authors explore the process of adapting the interviews to video conferencing and telephone use while preserving the study's person-centred focus to remain coherent with narrative methodology. CONCLUSION: Adapting data collection is valuable in ensuring the continuity of research. Careful consideration and planning are required to ensure the research remains robust and ethically sound. IMPLICATIONS FOR PRACTICE: Adapting data collection methods can allow for greater flexibility when participants cannot attend face-to-face interviews.

Challenges in developmental psychology research during the COVID-19 pandemic / Desafios da pesquisa em psicologia do desenvolvimento durante a pandemia da COVID-19 / Desafíos de la investigación en psicología del desarrollo durante la pandemia de COVID-19

The COVID-19 pandemic brought a series of restructurings necessary for research in Developmental Psychology. The aim of the manuscript is to discuss adaptations we made in our research in this context during the COVID-19 pandemic and to present strategies to adequate research protocols originally designed to occur in person. Although some contexts do not allow the continuity of studies, research at this time can bring essential contributions in this extreme period. This article explores the strategies for adapting recruitment procedures, suggesting dissemination platforms, and using social networks for this purpose. Guidelines are suggested for conducting non-face-to-face interviews with caregivers, ways of assessing the interaction of the mother-child pairs, and problematizing ethical issues. The procedures for returning the results, an ethical researcher commitment, may be improved by resources such as automatic reports. Besides, strategies for better dissemination of the results for the participants are suggested. (AU)

A pandemia COVID-19 trouxe uma série de reestruturações necessárias à pesquisa em Psicologia do Desenvolvimento. O objetivo deste artigo é discutir as adaptações que realizamos em pesquisas neste contexto durante a pandemia de COVID-19 e apresentar estratégias para adequação de protocolos de pesquisa originalmente planejados para ocorrer de forma presencial. Embora alguns contextos não permitam a continuidade dos estudos, pesquisas nesse momento podem trazer importantes contribuições sobre este período ímpar. No presente artigo são exploradas estratégias de adaptação dos procedimentos de recrutamento, sugeridas plataformas de divulgação e como melhor usar as redes sociais para esse fim. Também são descritos procedimentos para realização de entrevistas não presenciais com responsáveis, formas de avaliação da interação das duplas mãe-criança e problematizadas questões éticas. Os procedimentos de devolução dos resultados, um compromisso ético dos pesquisadores, podem ser facilitados por recursos como relatórios automáticos. Além disso, sugerimos estratégias para melhor divulgação dos resultados ao público participante. (AU)

La pandemia del COVID-19 trajo una serie de reestructuraciones necesarias para la investigación en Psicología del Desarrollo. El objetivo de este artículo es discutir las adaptaciones realizadas en las investigaciones en este contexto durante la pandemia de COVID-19 y presentar algunas estrategias para la adaptación de los protocolos de investigación originalmente planeados para ser presenciales. Si bien algunos contextos no permitan la continuidad de los estudios, la investigación en este momento puede aportar importantes avances sobre estos tiempos de crisis. Este artículo explora las estrategias para adaptar los procedimientos de contratación, sugiriendo algunas plataformas de difusión y la mejor manera de utilizar las redes sociales para este fin. También se describen los procedimientos para la realización de entrevistas no presenciales con padres o tutores legales, las formas de evaluar la interacción madre-hijo y las cuestiones éticas. Los procedimientos para la devolución de los resultados, un compromiso ético de los investigadores, pueden verse facilitados por funciones como informes automáticos. Además, se recomienda estrategias para una mejor difusión de los resultados al público participante. (AU)

Identifying Patients With Inflammatory Bowel Disease on Twitter and Learning From Their Personal Experience: Retrospective Cohort Study.

BACKGROUND: Patients use social media as an alternative information source, where they share information and provide social support. Although large amounts of health-related data are posted on Twitter and other social networking platforms each day, research using social media data to understand chronic conditions and patients' lifestyles is limited. OBJECTIVE: In this study, we contributed to closing this gap by providing a framework for identifying patients with inflammatory bowel disease (IBD) on Twitter and learning from their personal experiences. We enabled the analysis of patients' tweets by building a classifier of Twitter users that distinguishes patients from other entities. This study aimed to uncover the potential of using Twitter data to promote the well-being of patients with IBD by relying on the wisdom of the crowd to identify healthy lifestyles. We sought to leverage posts describing patients' daily activities and their influence on their well-being to characterize lifestyle-related treatments. METHODS: In the first stage of the study, a machine learning method combining social network analysis and natural language processing was used to automatically classify users as patients or not. We considered 3 types of features: the user's behavior on Twitter, the content of the user's tweets, and the social structure of the user's network. We compared the performances of several classification algorithms within 2 classification approaches. One classified each tweet and deduced the user's class from their tweet-level classification. The other aggregated tweet-level features to user-level features and classified the users themselves. Different classification algorithms were examined and compared using 4 measures: precision, recall, F1 score, and the area under the receiver operating characteristic curve. In the second stage, a classifier from the first stage was used to collect patients' tweets describing the different lifestyles patients adopt to deal with their disease. Using IBM Watson Service for entity sentiment analysis, we calculated the average sentiment of 420 lifestyle-related words that patients with IBD use when describing their daily routine. RESULTS: Both classification approaches showed promising results. Although the precision rates were slightly higher for the tweet-level approach, the recall and area under the receiver operating characteristic curve of the user-level approach were significantly better. Sentiment analysis of tweets written by patients with IBD identified frequently mentioned lifestyles and their influence on patients' well-being. The findings reinforced what is known about suitable nutrition for IBD as several foods known to cause inflammation were pointed out in negative sentiment, whereas relaxing activities and anti-inflammatory foods surfaced in a positive context. CONCLUSIONS: This study suggests a pipeline for identifying patients with IBD on Twitter and collecting their tweets to analyze the experimental knowledge they share. These methods can be adapted to other diseases and enhance medical research on chronic conditions.

Phenomenological interview of older adults through virtual media: an experience report.

OBJECTIVES: to report the experience of conducting phenomenological interviews through virtual means in a group of older adults during the COVID-19 pandemic. METHODS: an experience report on the main aspects that the researchers experienced in the virtual phenomenological interview process as an alternative to face-to-face interviews with older adults during social isolation due to the COVID-19 pandemic. RESULTS: the experience of conducting phenomenological interviews by videoconference was useful, enriching and satisfying. The difficulties that arose were smaller in relation to the benefits of the technique. FINAL CONSIDERATIONS: the use of technology to optimize qualitative data collection is a recommended strategy that can be adopted by nursing whenever the research objectives allow.

Crowdsourcing the identification of studies for COVID-19-related Cochrane Rapid Reviews.

BACKGROUND: Utilisation of crowdsourcing within evidence synthesis has increased over the last decade. Crowdsourcing platform Cochrane Crowd has engaged a global community of 22,000 people from 170 countries. The COVID-19 pandemic presented an opportunity to engage the community and keep up with the exponential output of COVID-19 research. AIMS: To test whether a crowd could accurately assess study eligibility for reviews under time constraints. OUTCOME MEASURES: time taken to complete each task, time to produce required training modules, crowd sensitivity, specificity and crowd consensus. METHODS: We created four crowd tasks, corresponding to four Cochrane COVID-19 Rapid Reviews. The search results of each were uploaded and an interactive training module was developed for each task. Contributors who had participated in another COVID-19 task were invited to participate. Each task was live for 48-h. The final inclusion and exclusion decisions made by the core author team were used as the reference standard. RESULTS: Across all four reviews 14,299 records were screened by 101 crowd contributors. The crowd completed each screening task within 48-h for three reviews and in 52 h for one. Sensitivity ranged from 94% to 100%. Four studies, out of a total of 109, were incorrectly rejected by the crowd. However, their absence ultimately would not have altered the conclusions of the reviews. Crowd consensus ranged from 71% to 92% across the four reviews. CONCLUSION: Crowdsourcing can play a valuable role in study identification and offers willing contributors the opportunity to help identify COVID-19 research for rapid evidence syntheses.

National Health Interview Survey, COVID-19, and Online Data Collection Platforms: Adaptations, Tradeoffs, and New Directions.

High-quality data are accurate, relevant, and timely. Large national health surveys have always balanced the implementation of these quality dimensions to meet the needs of diverse users. The COVID-19 pandemic shifted these balances, with both disrupted survey operations and a critical need for relevant and timely health data for decision-making. The National Health Interview Survey (NHIS) responded to these challenges with several operational changes to continue production in 2020. However, data files from the 2020 NHIS were not expected to be publicly available until fall 2021. To fill the gap, the National Center for Health Statistics (NCHS) turned to 2 online data collection platforms-the Census Bureau's Household Pulse Survey (HPS) and the NCHS Research and Development Survey (RANDS)-to collect COVID-19‒related data more quickly. This article describes the adaptations of NHIS and the use of HPS and RANDS during the pandemic in the context of the recently released Framework for Data Quality from the Federal Committee on Statistical Methodology. (Am J Public Health. 2021;111(12):2167-2175. https://doi.org/10.2105/AJPH.2021.306516).

Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data.

OBJECTIVE: Robust disease and syndromic surveillance tools are underdeveloped in the United States, as evidenced by limitations and heterogeneity in sociodemographic data collection throughout the COVID-19 pandemic. To monitor the COVID-19 pandemic in Minnesota, we developed a federated data network in March 2020 using electronic health record (EHR) data from 8 multispecialty health systems. MATERIALS AND METHODS: In this serial cross-sectional study, we examined patients of all ages who received a COVID-19 polymerase chain reaction test, had symptoms of a viral illness, or received an influenza test from January 3, 2016, through November 7, 2020. We evaluated COVID-19 testing rates among patients with symptoms of viral illness and percentage positivity among all patients tested, in aggregate and by zip code. We stratified results by patient and area-level characteristics. RESULTS: Cumulative COVID-19 positivity rates were similar for people aged 12-64 years (range, 15.1%-17.6%) but lower for adults aged ≥65 years (range, 9.3%-10.7%). We found notable racial and ethnic disparities in positivity rates early in the pandemic, whereas COVID-19 positivity was similarly elevated across most racial and ethnic groups by the end of 2020. Positivity rates remained substantially higher among Hispanic patients compared with other racial and ethnic groups throughout the study period. We found similar trends across area-level income and rurality, with disparities early in the pandemic converging over time. PRACTICE IMPLICATIONS: We rapidly developed a distributed data network across Minnesota to monitor the COVID-19 pandemic. Our findings highlight the utility of using EHR data to monitor the current pandemic as well as future public health priorities. Building partnerships with public health agencies can help ensure data streams are flexible and tailored to meet the changing needs of decision makers.

Accuracy of Dental Photography: Professional vs. Smartphone's Camera.

There is a scant literature on the accuracy of dental photographs captured by Digital Single-Lens Reflex (DSLR) and smartphone cameras. The aim was to compare linear measurements of plaster models photographed with DSLR and smartphone's camera with digital models. Thirty maxillary casts were prepared. Vertical and horizontal reference lines were marked on each tooth, with exception to molars. Then, models were scanned with the TRIOS 3 Basic intraoral dental scanner (control). Six photographs were captured for each model: one using DSLR camera (Canon EOS 700D) and five with smartphone (iPhone X) (distance range 16-32 cm). Teeth heights and widths were measured on scans and photographs. The following conclusions could be drawn: (1) the measurements of teeth by means of DSLR and smartphone cameras (at distances of at least 24 cm) and scan did not differ. (2) The measurements of anterior teeth by means of DSLR and smartphone cameras (at all distances tested) and scan exhibited no difference. For documentational purposes, the distortion is negligeable, and both camera devices can be applied. Dentists can rely on DSLR and smartphone cameras (at distances of at least 24 cm) for smile designs providing comparable and reliable linear measurements.

Efficiency and Quality of Data Collection Among Public Mental Health Surveys Conducted During the COVID-19 Pandemic: Systematic Review.

BACKGROUND: The World Health Organization has recognized the importance of assessing population-level mental health during the COVID-19 pandemic. During a global crisis such as the COVID-19 pandemic, a timely surveillance method is urgently needed to track the impact on public mental health. OBJECTIVE: This brief systematic review focused on the efficiency and quality of data collection of studies conducted during the COVID-19 pandemic. METHODS: We searched the PubMed database using the following search strings: ((COVID-19) OR (SARS-CoV-2)) AND ((Mental health) OR (psychological) OR (psychiatry)). We screened the titles, abstracts, and texts of the published papers to exclude irrelevant studies. We used the Newcastle-Ottawa Scale to evaluate the quality of each research paper. RESULTS: Our search yielded 37 relevant mental health surveys of the general public that were conducted during the COVID-19 pandemic, as of July 10, 2020. All these public mental health surveys were cross-sectional in design, and the journals efficiently made these articles available online in an average of 18.7 (range 1-64) days from the date they were received. The average duration of recruitment periods was 9.2 (range 2-35) days, and the average sample size was 5137 (range 100-56,679). However, 73% (27/37) of the selected studies had Newcastle-Ottawa Scale scores of <3 points, which suggests that these studies are of very low quality for inclusion in a meta-analysis. CONCLUSIONS: The studies examined in this systematic review used an efficient data collection method, but there was a high risk of bias, in general, among the existing public mental health surveys. Therefore, following recommendations to avoid selection bias, or employing novel methodologies considering both a longitudinal design and high temporal resolution, would help provide a strong basis for the formation of national mental health policies.

Considerations for Improving Reporting and Analysis of Date-Based COVID-19 Surveillance Data by Public Health Agencies.

More than a year after the first domestic COVID-19 cases, the United States does not have national standards for COVID-19 surveillance data analysis and public reporting. This has led to dramatic variations in surveillance practices among public health agencies, which analyze and present newly confirmed cases by a wide variety of dates. The choice of which date to use should be guided by a balance between interpretability and epidemiological relevance. Report date is easily interpretable, generally representative of outbreak trends, and available in surveillance data sets. These features make it a preferred date for public reporting and visualization of surveillance data, although it is not appropriate for epidemiological analyses of outbreak dynamics. Symptom onset date is better suited for such analyses because of its clinical and epidemiological relevance. However, using symptom onset for public reporting of new confirmed cases can cause confusion because reporting lags result in an artificial decline in recent cases. We hope this discussion is a starting point toward a more standardized approach to date-based surveillance. Such standardization could improve public comprehension, policymaking, and outbreak response. (Am J Public Health. 2021;111(12):2127-2132. https://doi.org/10.2105/AJPH.2021.306520).

COVID-19 Pandemic Impact on the National Health Care Surveys.

While underscoring the need for timely, nationally representative data in ambulatory, hospital, and long-term-care settings, the COVID-19 pandemic posed many challenges to traditional methods and mechanisms of data collection. To continue generating data from health care and long-term-care providers and establishments in the midst of the COVID-19 pandemic, the National Center for Health Statistics had to modify survey operations for several of its provider-based National Health Care Surveys, including quickly adding survey questions that captured the experiences of providing care during the pandemic. With the aim of providing information that may be useful to other health care data collection systems, this article presents some key challenges that affected data collection activities for these national provider surveys, as well as the measures taken to minimize the disruption in data collection and to optimize the likelihood of disseminating quality data in a timely manner. (Am J Public Health. 2021;111(12):2141-2148. https://doi.org/10.2105/AJPH.2021.306514).

Evaluating the reliability of mobility metrics from aggregated mobile phone data as proxies for SARS-CoV-2 transmission in the USA: a population-based study.

BACKGROUND: In early 2020, the response to the SARS-CoV-2 pandemic focused on non-pharmaceutical interventions, some of which aimed to reduce transmission by changing mixing patterns between people. Aggregated location data from mobile phones are an important source of real-time information about human mobility on a population level, but the degree to which these mobility metrics capture the relevant contact patterns of individuals at risk of transmitting SARS-CoV-2 is not clear. In this study we describe changes in the relationship between mobile phone data and SARS-CoV-2 transmission in the USA. METHODS: In this population-based study, we collected epidemiological data on COVID-19 cases and deaths, as well as human mobility metrics collated by advertisement technology that was derived from global positioning systems, from 1396 counties across the USA that had at least 100 laboratory-confirmed cases of COVID-19. We grouped these counties into six ordinal categories, defined by the National Center for Health Statistics (NCHS) and graded from urban to rural, and quantified the changes in COVID-19 transmission using estimates of the effective reproduction number (Rt) between Jan 22 and July 9, 2020, to investigate the relationship between aggregated mobility metrics and epidemic trajectory. For each county, we model the time series of Rt values with mobility proxies. FINDINGS: We show that the reproduction number is most strongly associated with mobility proxies for change in the travel into counties (0·757 [95% CI 0·689 to 0·857]), but this relationship primarily holds for counties in the three most urban categories as defined by the NCHS. This relationship weakens considerably after the initial 15 weeks of the epidemic (0·442 [-0·492 to -0·392]), consistent with the emergence of more complex local policies and behaviours, including masking. INTERPRETATION: Our study shows that the integration of mobility metrics into retrospective modelling efforts can be useful in identifying links between these metrics and Rt. Importantly, we highlight potential issues in the data generation process for transmission indicators derived from mobile phone data, representativeness, and equity of access, which must be addressed to improve the interpretability of these data in public health. FUNDING: There was no funding source for this study.