Respiratory virus season is only starting, and demand has already outstripped supply for the newly approved and potentially lifesaving monoclonal antibody injection for preventing respiratory syncytial virus (RSV) in children.
David Margraf, PharmD, PhD, pharmaceutical research scientist at the Resilient Drug Supply Project (RDSP), said the nirsevimab-alip (Beyfortus) shortage is reminiscent of the COVID-19 vaccine rollout. RDSP is part of the University of Minnesota's Center for Infectious Disease Research and Policy (CIDRAP), publisher of CIDRAP News.
"Wealthier nations secured most early vaccine supplies, which led to delayed vaccine rollouts in many low- and middle-income countries," he said. "Even in the United States, wealthier communities had better access to vaccines, and rural areas also faced challenges due to distance and scarce resources."
The US Food and Drug Administration (FDA) approved the long-acting drug in July, and in August the Centers for Disease Control and Prevention (CDC) recommended the prescription drug to protect all infants up to 8 months old entering their first RSV season and for high-risk children up to 24 months in their second season. RSV is the No. 1 cause of hospitalization among US infants.
On September 5, the CDC warned that RSV activity was picking up in the southeastern United States, often a bellwether for the rest of the country.
"Despite an aggressive supply plan built to outperform past pediatric immunization launches, demand for this product, especially for the 100 mg doses used primarily for babies born before the RSV season, has been higher than anticipated," Beyfortus co-developer Sanofi said in an October 26 statement.
Margraf said that while the FDA evaluates the manufacturing processes and facilities, the capacity of the manufacturer to meet demand is not a major consideration in the approval process. "However, the FDA does work with pharmaceutical companies post-approval to address issues related to shortages, especially with critical drugs," he said. "It may be time for the FDA to assess manufacturing capacity in the drug approval process."
Sanofi said it was working with the CDC and to ensure equitable distribution of available doses of the drug to Medicaid-eligible, uninsured, or American Indian/Alaska Native children through the Vaccines for Children (VFC) program. The company said it, along with co-developer and manufacturing partner AstraZeneca, would take a similar approach to distribution of the $495-a-dose drug on the private market.
A recent study published in the Canadian Medical Association Journal revealed that virtual urgent care (VUC) had minimal impact on emergency department visits or hospital admissions in Ontario, Canada, during the COVID-19 pandemic. However, a significant number of study participants who initially sought virtual urgent care eventually attended an emergency department in person.
Virtual urgent cares purpose is to assist in redirecting folks with minor health concerns away from in-person emergency department visits to decrease high volumes of patients that dont necessarily need to be there.
The COVID-19 pandemic significantly impacted the Canadian healthcare system, especially early on when social distancing posed challenges for arranging non-urgent, in-person visits. This period witnessed an almost 80% decline in in-person primary care visits and a 50% decrease in emergency department visits, which lead to a surge in the adoption of virtual care tools.
For a better understanding of healthcare use and the outcomes of VUC, researchers of the study observed both variables in comparison to similar patients who opted for an in-person emergency department visit.
Researchers used patient-level encounter data from 14 pilot programs in Ontario where individuals used VUC services. Researchers then collected the data and connected it to administrative databases, which helped them figure out how people used healthcare services and what happened in the 30 days after.
Results revealed that out of the 19,595 patients who used VUC, researchers matched 2,129 patients who were quickly referred to the emergency department by a VUC provider with those who physically went to the emergency department.
The rates of hospital admissions during the first visit (9.4% vs. 8.7%), 30-day emergency department visits (17.0% vs. 17.5%) and hospital admissions (12.9% vs. 11.0%) were similar between these two groups.
Of the 14,179 patients seen by a VUC provider without a documented referral to the emergency department, those who used VUC were more likely to have in-person emergency department visits within 72 hours (13.7% vs. 7.0%), 7 days (16.5% vs. 10.3%), and 30 days (21.9% vs. 17.9%).
However, hospital admissions were similar within 72 hours (1.1% vs. 1.3%) and higher within 30 days for patients discharged home from the emergency department (2.6% vs. 3.4%).
Authors of the study suggest that the increased use of healthcare services following virtual follow-up visits might be due to virtual clinicians facing limitations in physically examining patients.
This limitation could lead clinicians to refer patients back to the emergency department for an in-person evaluation more readily if they have persistent symptoms, they said.
Its recommended that future research efforts should focus on identifying quality-of-care and virtual care practices care to foster a culture of continuous improvement.
Researchers suggest future investigations should highlight and examine the root causes of low healthcare use after a VUC visit as it will help determine necessary changes and improvements that will help improve these trials.
Implementation of an antimicrobial stewardship program (ASP) was associated with a significant reduction in antibiotic consumption and antimicrobial resistance in children with severe bacterial pneumonia at a pediatric intensive care unit (PICU) in China, researchers reported yesterday in the Journal of Global Antimicrobial Resistance.
In the single-center study, researchers from Beijing Children's Hospital set out to examine the impact of ASP 2018, a set of guidelines issued by China's National Health Commission that emphasize strict control of antibiotic use, particularly for vulnerable populations such as children, the elderly, and pregnant women. Under those guidelines, the hospital created a management team of pharmacists, clinicians, infectious disease specialists, microbiologist, and administrators to regularly inspect the use of antibiotics.
To assess the impact of the ASP, the researchers compared resistance rates, antibiotic consumption, and clinical outcomes among children with severe pneumonia in the PICU before and after implementation of the program. The study evaluated data on 287 children, including 165 before the intervention (May 2016 to April 2018) and 122 after the intervention (May 2018 to April 2020).
After the ASP implementation, Staphylococcus aureus replaced Streptococcus pneumoniae as the predominant gram-positive bacterium and Klebsiella pneumoniae replaced Pseudomonas aeruginosa as the most common gram-negative bacterium. The resistance of S pneumoniae to clindamycin, erythromycin, and tetracycline was significantly reduced, while S aureus resistance to tetracycline was reduced from 59.1% to 32.5% after ASP implementation.
Resistance rates of K pneumoniae to amoxicillin/clavulanic acid and trimethoprim/sulfamethoxazole (SXT), and Acinetobacter baumannii to cefotaxime and SXT, also declined significantly. The isolation rate of multidrug-resistant strains decreased significantly as well, from a high of 16.8% before intervention to 6.7% after intervention.
Meanwhile, total consumption (defined daily doses [DDD] per 100 patient-days) of five antimicrobials (cephalosporins, carbapenems, macrolides, antifungal agents, and linezolid) decreased by 21.9% overall. No increase in length of hospital stay or mortality was observed.
The study authors say that while only a small number of PICUs in China have the staff to implement the ASP, the experience at their hospital "may provide some references for its promotion and application nationwide."
WASHINGTON Select Subcommittee on the Coronavirus Pandemic Chairman Brad Wenstrup (R-Ohio) and Representative Nicole Malliotakis (R-N.Y.) are pressing New York Governor Kathy Hochul to hand over information related to her states disastrous COVID-19 nursing home policies after repeated obstruction. Since the start of the pandemic, the Select Subcommittee has sent more than eight letters to Governor Hochul, former Governor Andrew Cuomo, and the Cuomo Administration requesting access to all documents and communications surrounding New Yorks deadly must-admit COVID-19 nursing home mandate. Governor Hochuls office has failed to produce a single responsive document.
In a recent attempt to obfuscate and deflect responsibility, Governor Hochuls office asked the New York State Department of Health (NYSDOH) to respond to the Select Subcommittee on behalf of the Governor. This evasion of accountability raises further questions about Governor Hochuls role in covering-up for the failures of her predecessor Andrew Cuomo. Today, Chairman Wenstrup and Representative Malliotakis are calling on Governor Hochul and New York State Department of Health Commissioner James McDonald to act transparently and provide the Select Subcommittee with all information related to the fatal COVID-19 nursing home directives.
This Select Subcommittee expects your response to this letter, not another deflection of responsibility. These deflections are especially concerning considering your promise to be fully transparent regarding the data surrounding COVID-19 deaths and nursing home readmissions. We are simply requesting that transparency, wrote the lawmakers in their letter to Governor Hochul.
Instead of fulsomely producing documentsespecially those in the custody or control of the Governors Officethe Governor deflected responsibility to the New York State Department of Health (NYSDOH). While the NYSDOH has produced limited responsive documents, to date, it has yet to answer all of the Select Subcommittees questions, wrote the lawmakers in their letter to New York State Department of Health Commissioner McDonald.
Read the letter to Governor Kathy Hochul here and the letter to New York State Department of Health Commissioner James McDonald here.
Read More:
###
The types of parks chosen for analysis
The total number of park visits determined from SafeGraph points of interest (POIs) located in NYC parks was 20,913,290 in 2019, but only 10,279,798 in 2020, representing a decrease of 49.2 percent.
There are 18 types of parks listed in the NYC Open Space Parks Data29. However, the top eight types of parks accounted for 91.35% of total park visits in 2019 and 92.17% in 2020, respectively, and are thus the focus of this study (Fig.1). These parks are classified by the NYC Department of Parks and Recreation29 as (1) Community Park, (2) Flagship Park, (3) Jointly Operated Playground, (4) Nature Area, (5) Neighborhood Park, (6) Playground, (7) Recreation Field/Courts, and (8) Triangle/Plaza. The detailed classification standard can be found in Table S-7.
Locations of parks in New York City. Each point represents an individual park. The number of parks and the median park area are shown for each park type.
We calculated four metrics associated with the number of park visits and the number of park visitors, namely (1) all visits: the total number of visits from all visitors; From the SafeGraph documentation, the duration of a visit must last at least 4min, and there could be multiple visits from a single visitor during the time period when the data were collected; (2) all visitors: the total number of unique visitors, regardless of their origin; (3) US visitors: the total number of unique visitors whose home locations are within the US; (4) NYC local visitors: the total number of unique visitors whose home locations are within NYC. Since temperature has been reported as a vital factor influencing park visitation30,31, we corrected the data for the effects of temperature, as described in the Data and methods section. The total numbers of these four types of visit/visitor counts by park type, and after the temperature correction, are summarized in Table S-1.
We examined the park visits and visitors change rate in each NYC borough by computing the total number of park visits or visitors in a month in that borough, then calculating the percentage change in 2020 visits (or visitors) compared to 2019 (i.e., (the visits in 2020the visits in 2019)/the visits in 2019). Manhattan was divided into lower Manhattan and upper Manhattan using 86th street as a divide. Results for total visits, total visitors, US visitors, and NYC visitors are shown in Fig.2.
Park visits and visitors change rate by borough, which is calculated as the percent change of total monthly park visits/visitors in 2020 compared to 2019. The letters on the right of each figure are the Tukey HSD multi-group comparison results, the same letters indicate the boroughs belong to the same group.
Starting from March 2020, the parks in all boroughs experienced decreased total visits (Fig.2a). April 2020 was the month with the greatest percentage decrease in visits compared to 2019, then visits slowly increased as the months progressed. Lower Manhattan had the greatest decrease in park visits from March to December (overall 61.1%, with a maximum of 86.6% in April 2020), while Staten Island experienced the smallest decrease (overall 20.3%, with a maximum of 57.5% in April 2020). All other boroughs experienced similar changes in visits, and shared a similar trend through time. All visitors (Fig.2b), U.S. visitors (Fig.2b), and NYC visitors (Fig.2d) had the same pattern with the greatest decrease in April, followed by a slow rebound with progressing time. Again, lower Manhattan had the largest decrease in unique visitors while Staten Island the smallest (Fig.2bd).
We examined the park visits and visitors change rate across the eight selected park types, by computing the total number of visits or unique visitors in a month to each park type and then calculating the percentage change of visits/visitors in 2020 compared to 2019 (Fig.3). There was a decrease in all types of visits and visitors to all eight park types across the city when comparing 2019 to 2020 for the months of March to June (Fig.3ad). For NYC local visitors, Triangle/Plazas (overall 62.9%, with a maximum of 82.9% in April 2020) and Flagship Parks (overall 57.0%, with a maximum of 78.7% in April 2020) had the largest decrease, followed by Jointly Operated Playground, Playground, Community Park, Neighborhood Park, then Recreation Field/Courts. Nature Areas had the smallest decrease in the number of NYC local visitors (overall 3.6%, with a maximum of 44.5% in April 2020) with some months even showing an increase. Beginning in June, the number of NYC local visitors to Nature Areas returned to about the same level as 2019 and even increased in some months (with a maximum increase of 29.0% in July 2020) (Fig.3d). The other three types of visits/visitors shared similar trends as NYC local visitors (Fig.3ac).
Park visits and visitors change rate by park type, which is calculated as the percent change of total monthly park visits/visitors in 2020 compared to 2019. The letters on the right of each figure are the Tukey HSD multi-group comparison results, any common letter shared by two park types indicates that the two park types were found to belong to the same group.
In order to better understand the needs and park usage of local urban residents, we focused our remaining analyses on data for NYC residents (also subsequently referred to as NYC local visitors) only. We also defined the visitor census block group (visitor CBG) as the home census block group where a visitor lived; and defined the park census block group (park CBG) as the census block group that a park was in, or was the closest to.
The CBGs (neighborhoods) that surround parks were divided into three income groups: lower, middle and upper, based on per capita income. The results for park visits change rate between 2019 and 2020 for each of the analyzed park types are provided in Fig.4.
NYC park visitors change rate by park type and by income level of park CBGs. The letters before the income groups are the Tukey HSD multi-group comparison results, any common letter shared by two income level groups indicates that the two groups were found to belong to the same group.
All eight park types saw decreased NYC local visitors regardless of the park CBG income level (Fig.4). Overall, parks in lower-income neighborhoods experienced statistically greater decreases in NYC local visitors than those in upper-income neighborhoods. No trend in visits change rate with income level was observed for Jointly Operated Playground, Neighborhood Park, Playground, and Triangle/Plaza. Community Parks and Nature Areas showed greater reductions in NYC local visitors in lower-income neighborhoods but showed no difference between middle- and upper-income neighborhoods. Flagship Parks showed greater reductions in NYC local visitors in lower- and middle-income neighborhoods. The outlier to the overall trend is Recreational Field/Courts, which showed greater reductions in NYC local visitors in upper-income neighborhoods than in lower-income neighborhoods.
The travel distance of visitors was used to examine how the travel behavior of NYC residents to parks changed during the early stages of the COVID-19 pandemic. In this section, the mean travel distances were computed for the time period from March to December in 2019 and 2020, as the major outbreak of the pandemic and the associated travel restrictions began in March 2020.
Overall, the mean travel distance of NYC residents to all parks reduced from 5.9km in 2019 to 5.1km in 2020 over March to December, representing a change of 13.2% (95% CI 13.4%, 13.1%). In 2020, there was a significant decrease in travel distance compared to 2019 for all study park types except for the Jointly Operated Playground, Playground, and Nature Area park types (Fig.5).
(a) Mean travel distance by park type. (b) Percentage change of mean travel distance by park type, with 95% CI error bars.
Before the pandemic, the mean travel distances to the Triangle/Plaza and Flagship Park types were the longest, both averaging 7.1kmover March to December in 2019; while the travel distances to the Playground and Jointly Operated Playground were the shortest, averaging 5.0km and 4.5km, respectively. The Nature Area, Jointly Operated Playground and Playground park types experienced a smaller decrease than average or even a slight increase, which were 1.2% (95% CI 2.0%, 0.3%), 1.9% (95% CI 2.5%, 1.3%) and 1.1% (95% CI 0.6%, 1.7%), respectively. All other types of parks experienced a greater reduction in travel distance (Table S-4).
The overall mean travel distances of NYC residents from lower-, middle- and upper-income level CBGs were 5.3km, 6.5km, and 6.0km, respectively, from March to December in 2019; and were 4.7km, 5.6km, and 5.0km, respectively, in the same period in 2020 (Fig.6a,b). In general, people from lower-income CBGs traveled a statistically shorter distance to parks than those from middle-income and upper-income CBGs in both 2019 and 2020. This pattern was common across all types of parks, except for Nature Areas and Triangle/Plazas, to which visitors from upper-income CBGs traveled the shortest distance.
(a,b) Mean travel distance by park type and by income level of visitor CBGs; The letters to the right of the mean travel distances are the Tukey HSD multi-group comparison results between income groups for each park type, any common letter shared by two income groups indicates that the two groups were found to belong to the same group. (c) Percentage change of mean travel distance by park type and by income level of visitor CBGs, with 95% CI error bars.
Overall, visitors from higher income CBGs had the greatest reduction in travel distance (Fig.6c). The percentage change of travel distance for visitors from lower-income, middle-income and upper-income CBGs are 10.7% (95% CI 11.0%, 10.4%), 13.9% (95% CI 14.2%, 13.7%), and 15.8% (95% CI 16.2%, 15.5%), respectively (Table S-5).
The specific changes varied by park type. For Community Park, Flagship Park, Jointly Operated Playground, Nature Area and Triangle/Plaza park types, the visitors from upper income level CBGs experienced the greatest percentage reduction in travel distance. While for Recreation Field/Courts, the visitors from upper income level CBGs had the smallest percentage reduction in travel distance.
The mean travel distances to parks located in lower-, middle- and upper-income level CBGs were 5.7km, 5.6km, and 6.3km, respectively, from March to December in 2019, and were 4.9km, 4.7km, and 5.6km, respectively, during the pandemic from March to December in 2020 (Fig.7a,b). In general, people tended to travel a statistically longer distance to parks in upper-income CBGs than to parks in middle-income and lower-income CBGs in both 2019 and 2020, with the exception of Community Park and Flagship Park in 2019.
(a,b) Mean travel distance by park type and by income level of park CBGs; The letters to the right of the mean travel distances are the Tukey HSD multi-group comparison results between income groups for each park type, any common letter shared by two income groups indicates that the two groups were found to belong to the same group. (c) Percentage change of mean travel distance by park type and by income level of park CBGs, with 95% CI error bars.
The travel distance to parks located in upper-income level CBGs had the smallest percentage decrease (Fig.7c), which was 10.6% (95% CI 10.9%, 10.3%), while it was 16.0% (95% CI 16.3%, 15.7%) for parks located in middle-income CBGs, and was 14.1% (95% CI 14.4%, 13.8%) for parks located in lower-income CBGs (Table S-6).
Examining by park type, for Community Park, Flagship Park, Recreational Field/Courts and Triangle/Plaza park types, the parks located in upper-income level CBGs experienced the smallest percentage reduction in travel distance. While for Nature Area, Jointly Operated Playground and Playground park types, the parks located in lower income level CBGs had an increase in travel distance.
Baloch S, Baloch MA, Zheng T, Pei X. The Coronavirus Disease 2019 (COVID-19) pandemic. Tohoku J Exp Med. 2020;250(4):2718. https://doi.org/10.1620/tjem.250.271.
Article CAS PubMed Google Scholar
Yamada M, Kimura Y, Ishiyama D, Otobe Y, Suzuki M, Koyama S, et al. Effect of the COVID-19 epidemic on physical activity in Community-Dwelling older adults in Japan: a cross-sectional online survey. J Nutr Health Aging. 2020;24(9):94850. https://doi.org/10.1007/s12603-020-1424-2.
Article CAS PubMed PubMed Central Google Scholar
Bates LC, Zieff G, Stanford K. COVID-19 impact on behaviors across the 24-Hour day in children and adolescents: physical activity, sedentary behavior, and Sleep. 2020, 7(9). https://doi.org/10.3390/children7090138.
Koohsari MJ, Nakaya T. Changes in Workers Sedentary and Physical Activity Behaviors in Response to the COVID-19 Pandemic and Their Relationships With Fatigue: Longitudinal Online Study. 2021, 7(3):e26293. https://doi.org/10.2196/26293.
Moore SA, Faulkner G, Rhodes RE, Brussoni M, Chulak-Bozzer T, Ferguson LJ, BEHAVIORAL NUTRITION AND PHYSICAL ACTIVITY. Impact of the COVID-19 virus outbreak on movement and play behaviours of Canadian children and youth: a national survey. Volume 17. INTERNATIONAL JOURNAL OF; 2020. 1https://doi.org/10.1186/s12966-020-00987-8.
Mitra R, Moore SA, Gillespie M, Faulkner G, Vanderloo LM, Chulak-Bozzer T, et al. Healthy movement behaviours in children and youth during the COVID-19 pandemic: exploring the role of the neighbourhood environment. Health Place. 2020;65. https://doi.org/10.1016/j.healthplace.2020.102418.
Kharel M, Sakamoto JL, Carandang RR, Ulambayar S, Shibanuma A, Yarotskaya E, et al. Impact of COVID-19 pandemic lockdown on movement behaviours of children and adolescents: a systematic review. BMJ GLOBAL HEALTH. 2022;7(1). https://doi.org/10.1136/bmjgh-2021-007190.
Tison GH, Avram R. Worldwide Effect of COVID-19 on physical activity: a descriptive study. 2020, 173(9):76770. https://doi.org/10.7326/m20-2665.
Ammar A, Brach M, Trabelsi K, Chtourou H. Effects of COVID-19 Home Confinement on eating Behaviour and physical activity: results of the ECLB-COVID19 International Online Survey. 2020, 12(6). https://doi.org/10.3390/nu12061583.
Lu N. The Significance of Loneliness in Later Life in the Context of COVID-19 Pandemic. 2022.
Scully JL, Disability, Disablism, COVID-19 Pandemic Triage. J Bioethical Inq. 2020;17(4):6015. https://doi.org/10.1007/s11673-020-10005-y.
Article Google Scholar
Tomata Y, Suzuki Y, Kawado M, Yamada H, Murakami Y, Mieno MN, et al. Long-term impact of the 2011 Great East Japan Earthquake and tsunami on functional disability among older people: a 3-year longitudinal comparison of disability prevalence among Japanese municipalities. Soc Sci Med. 2015;147:2969. https://doi.org/10.1016/j.socscimed.2015.11.016.
Article PubMed Google Scholar
Paterson DC, Ramage K, Moore SA, Riazi N, Tremblay MS, Faulkner G. Exploring the impact of COVID-19 on the movement behaviors of children and youth: a scoping review of evidence after the first year. J Sport Health Sci. 2021;10(6):67589. https://doi.org/10.1016/j.jshs.2021.07.001.
Article PubMed PubMed Central Google Scholar
Caputo EL, Reichert FF. Studies of physical activity and COVID-19 during the pandemic: a scoping review. J Phys Activity Health. 2020;17(12):127584. https://doi.org/10.1123/jpah.2020-0406.
Article Google Scholar
Rossi L, Behme N, Breuer C. Physical Activity of Children and Adolescents during the COVID-19 PandemicA Scoping Review. In: International journal of environmental research and public health. vol. 18; 2021.
Violant-Holz V, Gallego-Jimnez MG, Gonzlez-Gonzlez CS, Muoz-Violant S, Rodrguez MJ, Sansano-Nadal O et al. Psychological health and physical activity levels during the COVID-19 pandemic: a systematic review. In: Int J Environ Res Public Health. vol. 17; 2020.
Musa S, Elyamani R, Dergaa I. COVID-19 and screen-based sedentary behaviour: systematic review of digital screen time and metabolic syndrome in adolescents. PLoS ONE. 2022;17(3). https://doi.org/10.1371/journal.pone.0265560.
Knight RL, McNarry MA, Sheeran L, Runacres AW, Thatcher R, Shelley J et al. Moving Forward: understanding correlates of physical activity and sedentary behaviour during COVID-19An integrative review and Socioecological Approach. In: Int J Environ Res Public Health. vol. 18; 2021.
Christensen A, Bond S, McKenna J. The COVID-19 conundrum: keeping safe while becoming inactive. A rapid review of physical activity, sedentary behaviour, and exercise in adults by gender and age. PLoS ONE. 2022;17(1). https://doi.org/10.1371/journal.pone.0263053.
Camacho-Montano LR, Iranzo A, Martinez-Piedrola RM, Camacho-Montano LM, Huertas-Hoyas E, Serrada-Tejeda S, et al. Effects of COVID-19 home confinement on sleep in children: a review. Sleep Med Rev. 2022;62. https://doi.org/10.1016/j.smrv.2022.101596.
Neculicioiu VS, Colosi IA, Costache C, Sevastre-Berghian A, Clichici S. Time to Sleep?-A review of the impact of the COVID-19 pandemic on Sleep and Mental Health. Int J Environ Res Public Health. 2022;19(6). https://doi.org/10.3390/ijerph19063497.
Sharma M, Aggarwal S, Madaan P, Saini L, Bhutani M. Impact of COVID-19 pandemic on sleep in children and adolescents: a systematic review and meta-analysis. Sleep Med. 2021;84:25967. https://doi.org/10.1016/j.sleep.2021.06.002.
Article PubMed PubMed Central Google Scholar
Chaput JP, Carson V, Gray CE, Tremblay MS. Importance of all movement behaviors in a 24 hour period for overall health. Int J Environ Res Public Health. 2014;11(12):1257581. https://doi.org/10.3390/ijerph111212575.
Article PubMed PubMed Central Google Scholar
Tremblay MS, Carson V, Chaput JP, Connor Gorber S, Dinh T, Duggan M et al. Canadian 24-Hour Movement Guidelines for Children and Youth: An Integration of Physical Activity, Sedentary Behaviour, and Sleep. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme 2016, 41(6 Suppl 3):S311-327. https://doi.org/10.1139/apnm-2016-0151.
Ross R, Chaput JP, Giangregorio LM, Janssen I, Saunders TJ, Kho ME et al. Canadian 24-Hour Movement Guidelines for Adults aged 1864 years and Adults aged 65 years or older: an integration of physical activity, sedentary behaviour, and sleep. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme 2020, 45(10 (Suppl. 2)):S57-s102. https://doi.org/10.1139/apnm-2020-0467.
Tremblay MS, Chaput JP, Adamo KB, Aubert S, Barnes JD, Choquette L, et al. Canadian 24-Hour Movement guidelines for the early years (04 years): an integration of physical activity, sedentary Behaviour, and Sleep. BMC Public Health. 2017;17(Suppl 5):874. https://doi.org/10.1186/s12889-017-4859-6.
Article PubMed PubMed Central Google Scholar
Dogra S, Good J, Buman MP, Gardiner PA, Copeland JL, Stickland MK. Physical activity and sedentary time are related to clinically relevant health outcomes among adults with obstructive lung Disease. BMC Pulm Med. 2018;18(1):98. https://doi.org/10.1186/s12890-018-0659-8.
Article PubMed PubMed Central Google Scholar
Dogra S, Good J, Buman MP, Gardiner PA, Stickland MK, Copeland JL. Movement behaviours are associated with lung function in middle-aged and older adults: a cross-sectional analysis of the Canadian longitudinal study on aging. BMC Public Health. 2018;18(1):818. https://doi.org/10.1186/s12889-018-5739-4.
Article PubMed PubMed Central Google Scholar
Chastin SF, Palarea-Albaladejo J, Dontje ML, Skelton DA. Combined effects of Time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: a Novel Compositional Data Analysis Approach. PLoS ONE. 2015;10(10):e0139984. https://doi.org/10.1371/journal.pone.0139984.
Article CAS PubMed PubMed Central Google Scholar
Rhodes RE, Spence JC, Berry T, Faulkner G, Latimer-Cheung AE, OReilly N, et al. Parental support of the Canadian 24-hour movement guidelines for children and youth: prevalence and correlates. BMC Public Health. 2019;19(1):1385. https://doi.org/10.1186/s12889-019-7744-7.
Article PubMed PubMed Central Google Scholar
Friel CP, Duran AT, Shechter A, Diaz KM. Meeting 24-Hour Movement guidelines among US children and adolescents: Prevalence and Age trends, 20162017. CIRCULATION 2019, 140.
da Costa BGG, Chaput J-P, Lopes MVV, Malheiros LEA, Tremblay MS, Silva KS. Prevalence and sociodemographic factors associated with meeting the 24-hour movement guidelines in a sample of Brazilian adolescents. PLoS ONE. 2020;15(9). https://doi.org/10.1371/journal.pone.0239833.
Ferrari G, Alberico C, Drenowatz C, Kovalskys I, Gomez G, Rigotti A, et al. Prevalence and sociodemographic correlates of meeting the Canadian 24-hour movement guidelines among latin American adults: a multi-national cross-sectional study. BMC Public Health. 2022;22(1). https://doi.org/10.1186/s12889-022-12613-2.
Tapia-Serrano MA, Sevil-Serrano J, Sanchez-Miguel PA, Lopez-Gil JF, Tremblay MS, Garcia-Hermoso A. Prevalence of meeting 24-Hour Movement guidelines from pre-school to adolescence: a systematic review and meta-analysis including 387,437 participants and 23 countries. J Sport Health Sci. 2022;11(4):42737. https://doi.org/10.1016/j.jshs.2022.01.005.
Article PubMed PubMed Central Google Scholar
Chen ST, Liu Y, Tremblay MS, Hong JT, Tang Y, Cao ZB, et al. Meeting 24-h movement guidelines: prevalence, correlates, and the relationships with overweight and obesity among Chinese children and adolescents. J Sport Health Sci. 2021;10(3):34959. https://doi.org/10.1016/j.jshs.2020.07.002.
Article PubMed Google Scholar
Liangruenrom N, Dumuid D, Craike M, Biddle SJH, Pedisic Z. Trends and correlates of meeting 24-hour movement guidelines: a 15-year study among 167,577 Thai adults. INTERNATIONAL JOURNAL OF BEHAVIORAL NUTRITION AND PHYSICAL ACTIVITY 2020, 17(1). https://doi.org/10.1186/s12966-020-01011-9.
Scully M, Gascoyne C, Wakefield M, Morley B. Prevalence and trends in Australian adolescents adherence to 24-hour movement guidelines: findings from a repeated national cross-sectional survey. BMC Public Health. 2022;22(1). https://doi.org/10.1186/s12889-021-12387-z.
Carson V, Zhang Z, Predy M, Pritchard L, Hesketh KD. Adherence to Canadian 24-Hour Movement guidelines among infants and associations with development: a longitudinal study. INTERNATIONAL JOURNAL OF BEHAVIORAL NUTRITION AND PHYSICAL ACTIVITY 2022, 19(1). https://doi.org/10.1186/s12966-022-01397-8.
Leppanen MH, Haapala EA, Vaisto J, Ekelund U, Brage S, Kilpelaeinen TO et al. Longitudinal and cross-sectional associations of adherence to 24-hour movement guidelines with cardiometabolic risk. Scandinavian J Med Sci Sports 2022, 32(1):25566. https://doi.org/10.1111/sms.14081.
Ferrari G, Guzman-Habinger J, Herreros-Irarrazabal D, Marques A, Marconcin P, Kovalskys I, et al. Correlates of meeting the Canadian 24-hour Movement guidelines among adults: a multi-national cross-sectional study. Volume 54. MEDICINE & SCIENCE IN SPORTS; & EXERCISE 2022. pp. 4622. 9.
Carson V, Chaput J-P, Janssen I, Tremblay MS. Health associations with meeting new 24-hour movement guidelines for Canadian children and youth. Prev Med. 2017;95(1):713. https://doi.org/10.1016/j.ypmed.2016.12.005.
Article PubMed Google Scholar
Porter C, McPhee P, Kwan M, Timmons B, Brown D. 24-Hour Movement Guideline Adherence and Mental Health: a cross-sectional study of emerging adults with Chronic Health conditions and disabilities. Volume 44. JOURNAL OF SPORT & EXERCISE PSYCHOLOGY; 2022. pp. 106S106.
Sampasa-Kanyinga H, Lien A, Hamilton HA, Chaput J-P, CANADIAN JOURNAL OF PUBLIC HEALTH-REVUE CANADIENNE DE SANTE PUBLIQUE. The Canadian 24-hour movement guidelines and self-rated physical and mental health among adolescents. 2022, 113(2):31221. https://doi.org/10.17269/s41997-021-00568-7.
Janssen I, Roberts KC, Thompson W. Is adherence to the Canadian 24-Hour Movement Behaviour Guidelines for Children and Youth associated with improved indicators of physical, mental, and social health? APPLIED PHYSIOLOGY NUTRITION AND METABOLISM 2017, 42(7):72531. https://doi.org/10.1139/apnm-2016-0681.
Pedisic Z, Dumuid D, Olds T. Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods, theoretical framework, and future directions. Kinesiology 2017, 49.
Hyunshik K, Ma J, Sunkyoung L, Gu Y. Change in Japanese childrens 24-hour movement guidelines and mental health during the COVID-19 pandemic. Sci Rep. 2021;11(1). https://doi.org/10.1038/s41598-021-01803-4.
Moore SA, Faulkner G, Rhodes RE, Vanderloo LM, Ferguson LJ, Guerrero MD, et al. Few Canadian children and youth were meeting the 24-hour movement behaviour guidelines 6-months into the COVID-19 pandemic: follow-up from a national study. Appl Physiol Nutr METABOLISM. 2021;46(10):122540. https://doi.org/10.1139/apnm-2021-0354.
Article CAS Google Scholar
Nascimento-Ferreira MV, Carvalho JA, Nascimento EP, Maciel EDS, De Moraes ACF. The 24-hour Movement Guidelines Adherence During The Covid-19 Pandemic In Undergraduate Students From Low-income Region. CIRCULATION 2022, 145. https://doi.org/10.1161/circ.145.suppl_1.P066.
Juregui A, Salvo D, Aguilar-Farias N, Okely A. Movement behaviors during COVID-19 among latin American/Latino toddlers and pre-schoolers in Chile, Mexico and the US. Int J Environ Res Public Health. 2022;12(1):19156. https://doi.org/10.3390/ijerph17228491https://doi.org/10.1038/s41598-022-23850-1.
Article Google Scholar
Angel Tapia-Serrano M, Sanchez-Oliva D, Sevil-Serrano J, Marques A, Antonio Sanchez-Miguel P. 24-h movement behaviours in Spanish youth before and after 1-year into the covid-19 pandemic and its relationship to academic performance. Sci Rep. 2022;12(1). https://doi.org/10.1038/s41598-022-21096-5.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical Research ed). 2021;372:n71. https://doi.org/10.1136/bmj.n71.
Article PubMed Google Scholar
Alanazi YA, Parrish A-M, Okely AD. 24-Hour movement behaviours and COVID-19 among children in the Kingdom of Saudi Arabia: a repeat cross-sectional study. Sports Med Health Sci 2022a, 4(3):17782. https://doi.org/10.1016/j.smhs.2022.05.001.
Alanazi YA, Parrish A-M, Okely AD. Impact of the COVID-19 virus outbreak on 24-h movement behaviours among children in Saudi Arabia: a cross-sectional survey. CHILD CARE HEALTH AND DEVELOPMENT. 2022b;48(6):10319. https://doi.org/10.1111/cch.12999.
Article Google Scholar
Arbour-Nicitopoulos KP, James ME, Moore SA, Sharma R, Martin Ginis KA. Movement behaviours and health of children and youth with disabilities: impact of the 2020 COVID-19 pandemic. Paediatr Child Health. 2022;27(Suppl 1):66S71. https://doi.org/10.1093/pch/pxac007.
Article Google Scholar
Caldwell HAT, Faulkner G, Tremblay MS, Rhodes RE, de Lannoy L, Kirk SFL, PUBLIC HEALTH-REVUE CANADIENNE DE SANTE PUBLIQUE. Regional differences in movement behaviours of children and youth during the second wave of the COVID-19 pandemic in Canada: follow-up from a national study. Volume 113. CANADIAN JOURNAL OF; 2022. pp. 53546. 4https://doi.org/10.17269/s41997-022-00644-6.
Delisle Nystrm C, Alexandrou C, Henstrm M, Nilsson E, Okely AD, Wehbe El Masri S, et al. International Study of Movement Behaviors in the Early Years (SUNRISE): Results from SUNRISE Swedens Pilot and COVID-19 Study. Int J Environ Res Public Health. 2020;17(22). https://doi.org/10.3390/ijerph17228491.
Hossain MS, Deeba IM, Hasan M, Kariippanon KE, Chong KH, Cross PL, et al. International study of 24-h movement behaviors of early years (SUNRISE): a pilot study from Bangladesh. Pilot and Feasibility Studies. 2021;7(1):176. https://doi.org/10.1186/s40814-021-00912-1.
Article PubMed PubMed Central Google Scholar
Liang K. Sleep as a Priority: 24-Hour Movement Guidelines and Mental Health of Chinese College Students during the COVID-19 pandemic. Life (Basel Switzerland). 2021;9(9). https://doi.org/10.3390/life12010028https://doi.org/10.3390/healthcare9091166.
Lpez-Gil JF, Tremblay MS, Brazo-Sayavera J. Changes in healthy behaviors and meeting 24-h Movement guidelines in Spanish and Brazilian preschoolers, children and adolescents during the COVID-19 Lockdown. Child (Basel Switzerland). 2021;8(2). https://doi.org/10.3390/children8020083.
Okely AD, Kariippanon KE, Guan H, Taylor EK, Suesse T, Cross PL, et al. Global effect of COVID-19 pandemic on physical activity, sedentary behaviour and sleep among 3-to 5-year-old children: a longitudinal study of 14 countries. BMC Public Health. 2021;21(1). https://doi.org/10.1186/s12889-021-10852-3.
Feng J, Huang WY, Lau PWC, Wong SH-S, Sit CH-P. Movement behaviors and mental health of caregivers of preschoolers in China during the COVID-19 pandemic. Prev Med. 2022;155. https://doi.org/10.1016/j.ypmed.2021.106913.
Wilde LJ, Ward G, Sewell L, Muller AM, Wark PA. Apps and wearables for monitoring physical activity and sedentary behaviour: a qualitative systematic review protocol on barriers and facilitators. 2018, 4:2055207618776454. https://doi.org/10.1177/2055207618776454.
Zeng N, Pope Z, GAO Z. Foundations of technology and health effects of physical activity. Technology in physical activity and Health Promotion. edn.: Routledge; 2017. pp. 1739.
Feng J, Zheng C. Associations between meeting 24-hour movement guidelines and health in the early years: a systematic review and meta-analysis. 2021, 39(22):254557. https://doi.org/10.1080/02640414.2021.1945183.
Memon AR, Vandelanotte C, Olds T, Duncan MJ, Vincent GE. Research Combining Physical Activity and Sleep: a bibliometric analysis. Percept Mot Skills. 2020;127(1):15481. https://doi.org/10.1177/0031512519889780.
Article PubMed Google Scholar
Messing S, Rtten A, Abu-Omar K, Ungerer-Rhrich U, Goodwin L, Burlacu I et al. How can physical activity be promoted among children and adolescents? A systematic review of Reviews Across settings. Frontiers in public health 2019, 7:55. https://doi.org/10.3389/fpubh.2019.00055.
Larouche R, Saunders TJ, Faulkner G, Colley R, Tremblay M. Associations between active school transport and physical activity, body composition, and cardiovascular fitness: a systematic review of 68 studies. J Phys Act Health. 2014;11(1):20627. https://doi.org/10.1123/jpah.2011-0345.
Article PubMed Google Scholar
Julian V, Haschke F, Fearnbach N, Gomahr J, Pixner T, Furthner D, et al. Effects of Movement Behaviors on Overall Health and Appetite Control: current evidence and perspectives in children and adolescents. Curr Obes Rep. 2022;11(1):1022. https://doi.org/10.1007/s13679-021-00467-5.
Article PubMed PubMed Central Google Scholar
Stavridou A, Kapsali E, Panagouli E, Thirios A, Polychronis K, Bacopoulou F. Obesity in children and adolescents during COVID-19 pandemic. 2021, 8(2). https://doi.org/10.3390/children8020135.
Mei X, Zhou Q, Li X, Jing P, Wang X, Hu Z. Sleep problems in excessive technology use among adolescent: a systemic review and meta-analysis. Sleep Sci Pract. 2018;2(1):9. https://doi.org/10.1186/s41606-018-0028-9.
Article Google Scholar
Wilke J, Mohr L, Tenforde AS, Edouard P, Fossati C, Gonzlez-Gross M, et al. A pandemic within the pandemic? Physical activity levels substantially decreased in Countries affected by COVID-19. Int J Environ Res Public Health. 2021;18(5). https://doi.org/10.3390/ijerph18052235.
Grao-Cruces A, Segura-Jimnez V. The role of School in Helping Children and adolescents Reach the physical activity recommendations: the UP&DOWN Study. 2019, 89(8):6128. https://doi.org/10.1111/josh.12785.
Dunton GF, Do B, Wang SD. Early effects of the COVID-19 pandemic on physical activity and sedentary behavior in children living in the U.S. BMC public health 2020, 20(1):1351. https://doi.org/10.1186/s12889-020-09429-3.
Kuzik N, Poitras VJ, Tremblay MS, Lee E-Y, Hunter S, Carson V. Systematic review of the relationships between combinations of movement behaviours and health indicators in the early years (04 years). BMC Public Health. 2017;17(5):849. https://doi.org/10.1186/s12889-017-4851-1.
The emergence of infectious diseases has historically caused serious problems for both global stability and public health. In 2002, the world grappled with the severe acute respiratory syndrome (SARS) outbreak, which, by 2003, had spread to 29 countries, resulting in 774 deaths, and affecting over 8,000 individuals [1]. In a striking parallel, the novel coronavirus (COVID-19) surfaced in December 2019 in Wuhan, China, and has since evolved into a global concern of unprecedented proportions.
The World Health Organization observed over 659million confirmed COVID-19 cases as of January 10, 2023, with more than 6.7million fatalities and more than 13million vaccination doses given globally [2]. The World Health Organization classified the pandemic as a global health disaster of substantial concern because of its enormous scope, which caused severe suffering and fatalities across the globe [3].
Beyond the direct impacts of the illness, the COVID-19 pandemic has still sparked widespread fear and hysteria, with far-reaching implications that are frequently unrelated to the viruss actual medical effects [4, 5]. Addressing the psychological effects of COVID-19 has become a pressing concern in the twenty-first century[6].
Numerous research have examined the COVID-19 pandemics psychological effects and found a variety of negative effects on mental health and wellbeing. Sleep issues, increased alertness, feelings of helplessness, alterations in mood, health-related concerns, depression, and irritation are among these effects[7,8,9,10,11,12]. In addition, the epidemic has sparked an alarming rise in conspiracy views and false information, despite intense efforts by governments and groups to stop the viruss spread [13].
Conspiracy thinking, a well-documented phenomenon during societal crises and health pandemics, has been shown to fuel reluctance to engage in health-related behaviors and foster misunderstandings about the underlying issues [14, 15]. Throughout the COVID-19 pandemic, subjects such as the viruss origin, severity, and containment have become focal points for conspiracy theories [16] The study of conspiracy thinking has emerged as a burgeoning field, seeking to uncover the factors that influence individuals acceptance of such beliefs [17, 18].
Different studies highlighted that conspiracy beliefs led to anxiety and threat [7, 17, 19]. Douglas, Uscinski [20] found that people who believe in conspiracies tend to be more anxious. Additionally, those who experience high levels of anxiety are more susceptible to such beliefs. Misinformation beliefs during covid-19 brought about feelings of anxiety [21]. Within the perspective of continued influence theories, misinformation not only cause poor judgements and decision-making, but it also has a long-lasting effect on peoples reasoning after correction [22]. In their model of false beliefs drivers, Ecker, Lewandowsky [22] posited that misinformation beliefs might come from cognitive drivers (intuitive thinking, cognitive failure, and illusory truth), and socio-affective drivers (source cues, emotion, world view). Verma et al., (2022) found that anxiety level doubled or tripled among twitter users who shared COVID-19 misinformation compared to other users who refused to share misinformation. As such, conspiracy thinking decreases trust in traditional media and increase reliance on social media which transmit misinformation [23, 24]. In other studies, anxiety was not strongly associated with conspiracy theories and misinformation beliefs [24]. We hypothesize that COVID-19 anxiety and sources of information drive individuals to believe in conspiracy theories and misinformation beliefs.
The COVID-19 pandemic has significantly impacted Oman, with 399,154 confirmed cases and 4,628 deaths as of January 10, 2023. While the country has made progress in vaccination efforts, with 63.79% of the population having received at least one dose, misinformation remains a significant issue that has not been adequately addressed. In Western cultures, research has shown the importance of conspiratorial and misinformation beliefs in the proliferation of COVID-19 anxiety and Coronaphobia, [25,26,27,28,29,30,31,32] leading to negative effects such as vaccine hesitancy [33]. However, little to no research has been conducted in the Arab Gulf region, specifically in Oman, on the relationship between misinformation beliefs, conspiracy theories, and COVID-19 anxiety.
To address this gap, this study investigates the relationship between misinformation beliefs, conspiracy theories, and COVID-19 anxiety among the Omani population. Research has shown that people believe conspiracy theories when important psychological needs are unmet, such as the desire to satisfy curiosity, avoid uncertainty, and reduce COVID-19 anxiety. By understanding the factors contributing to the spread of misinformation and conspiratorial beliefs in the Omani context, policymakers and health-care professionals can develop targeted interventions to combat this issue.
In simple terms, any activity is conspiratorial if it is undertaken in secret by a group of agents who intend some end [34., p. 24]. Conspiracy theories explain that some kind of conspiracy thinking interprets the incidence of an event. The concept of conspiracy should satisfy three main conditions to be classified as a conspiracy: (a) the conspirators condition (plotters), (b) the secrecy condition, and (c) the goal condition [34]. Considering these three conditions, we can assume that they are inherent in most conspiracy thoughts that accompanied the outbreak of COVID-19 pandemic.
Conspiracy theories significantly increased following the outbreak of COVID-19. The main purpose of these theories is to explain important events and situations as the malicious acts of third parties [35]. For example, during the pandemic, many people believed that COVID-19 was manufactured in a Chinese laboratory, while others believed that governments exaggerated the severity of the virus as part of a plot to control citizens [28]. People who believe in conspiracy theories tend to engage in irrational behaviors, leading to severe or negative impacts on their health [20]. Additionally, conspiracy theories can harm trust in health institutions and hinder efforts to combat the virus [36].
Scholars have begun to explore the impact of conspiracy theories on individual and public health during the pandemic [25, 37, 38]. For example, Romer and Jamieson [39] examined the impact of conspiracy theories on protective measures in the United States. The results showed that these theories lead to resistance to precautionary actions and vaccination. People avoided wearing masks and getting vaccinated because they believed the virus did not exist and that the vaccine was a means of control. Previous studies have also confirmed the link between conspiracy theories and individuals hesitancy to make informed decisions [40, 41].
Uscinski, Enders [32] found that, while many people recognized the seriousness of COVID-19, a significant number of study participants agreed that the danger posed by the virus had been exaggerated and that the virus was purposely produced and spread by other parties. The study highlighted that individuals beliefs in conspiracy theories may be driven by denialism, conspiracy thinking, and biased or ideological motivations.
It is difficult to identify a single mechanism that controls the association between education and conspiracy thinking as different psychological mechanisms underlie this relationship e.g., [17]. Not surprisingly, low-educated individuals and those dissatisfied with government actions in response to the pandemic are particularly susceptible to conspiracy theories [42]. Conversely, past research has shown that high levels of education predict low belief in conspiracy theories due to educations cognitive, emotional, and social outcomes e.g., [17, 43, 44].
It is widely acknowledged in the literature that false beliefs led to an underestimation of the threat and hindered individuals efforts to get vaccinated [45]. Different conspiracy theories spread during the pandemic, for example, the belief that 5G technology was the direct cause of the outbreak of COVID-19 [46] and that the virus was manufactured in a Chinese laboratory [35]. As a result, conspiracy theories describing COVID-19 as a hoax were positively associated with less preparedness in containment procedures [30] and predicted vaccine hesitancy [47].
The spread of the virus worldwide was accompanied by thousands of people, backed by pseudoscientific treatment ideas and conspiracies [31, 48]. Misinformation has increased on social media due to people believing in this type of information and conspiracy theories, which made social media outlets fertile to germinate a massive amount of misinformation [49, 50].
In the last phases of the pandemic, most false claims were about the vaccine, specifically its side-effect, which cause fear and panic [51, 52]. Some examples of these claims are:
Vaccines are not safe and cause health risks,
A way to reduce the population will alter human DNA and causes infertility or death.
In Oman, many refused to get the vaccine because of such rumors [53, 54]. Smith, Ng [55] argued that false information about a cure for the Coronavirus had caused widespread fear and distrust among the public. Vaccine hesitancy was added to the World Health Organizations top ten global health issues for 2019, according to the WHOs website. This highlights the concern over the growing trend of individuals refusing vaccines for themselves or their children. The inclusion of vaccine hesitancy on this list predates the COVID-19 pandemic [56]. The authors revealed that misinformation and unfavorable attitudes are very contagious and can lower vaccination rates. For example, during the 2009 swine flu outbreak, the spread of skepticism and unproven hypotheses about vaccine safety affected peoples willingness to be vaccinated. Several studies have found that exposure to anti-vaccination beliefs and misinformation on Twitter has increased vaccine reluctance and refusal and a drop in vaccination uptake [57,58,59]. Omani citizens and Omani government made positive efforts to deal with misinformation [21].
Health institutions and information systems were not well-prepared to respond to the outflow of infected cases. Although trust in health systems helped shape the public response to the COVID-19 pandemic [60], Peoples belief in misleading thoughts decreased their confidence in medical procedures [36]. In his warning in 2020, the Director General of WHO declared the fighting against infodemic which spreads faster and more easily than the virus [30]. Misleading information about COVID-19 negatively affected governmental efforts in the struggle with the epidemic leading to unintended deaths [61], and vice versa, the awareness of preventive measures might weaken misinformation beliefs also studies found that there was a strong association between trust in science and belief in misinformation e.g., trusting science more are less likely to believe misinformation [62] Those authors later found that the same trust in science scale was associated with COVID-19 vaccination intention [63]. No doubt that misleading information has a negative impact on taking preventative measures [28]. Conversely, Alper, Bayrak [64] found no association between misinformation beliefs and preventative measures. According to Jovanevi and Milievi [65], optimistic people have more preventative measures and less fear than pessimistic people. Kim and Kim [66] claimed that people who perceive danger accept fake news. In this context, McCaffery, Dodd [67] concluded that health knowledge and ways of thinking might have reduced efforts against the pandemic spread in Australia.
The amount of misinformation spread through social networks affected the response to the pandemic, as it had health, psychological and social effects on individuals [25]. The inability to distinguish between facts and misinformation might lead to psychological, health and social distress and may even extend to the economic and political aspects [22, 68]. Many researchers claimed that misinformation increased the level of COVID-19 anxiety among individuals leading to unpredicted actions to avoid infection with covid-19. In addition, it was found that exposure to misinformation increased the level of depression [69]. In order to alleviate these feelings, individuals looked for more information that might comfort them [70].
The COVID-19 outbreak has proved that responding to misinformation is challenging for many reasons. Social, emotional and cultural factors affect the absorption of misinformation, hindering efforts to stop the negative impact of this type of information [71]. In terms of health, Joseph et al. (2022) indicated that spreading false information about the virus through social networks leads to negative results, including reluctance to follow recommendations related to the virus to preserve public health and increasing levels of COVID-19 anxiety and fear. The accumulation of this unfounded information leads to abstaining from vaccinations, which seriously affects public health [72]. Misinformation regarding prevention and treatment measures is particularly harmful because it may directly cause deaths [73]. Misinformation also causes uninformed and rushed health decisions [74].
Psychologically, increased exposure to social media information can negatively affect the community mental health (Hammad and Alqarni [69]. Similarly, in the Arab region, it was believed that the outbreak of the virus has led to continued doubt and uncertainty about the nature of the virus [75]. It has also been proven that the spread of misinformation raises concern and suspicion among the public from the advice given by public health officials [76]. Shehata and Eldakar [75] found that misinformation affects individuals health decisions and mental health, leading to increased fear and anxiety. On the other hand, peoples disagreement about the reality of the virus and their exchange of information led to personal and family conflicts [77]. It can also adversely affect health-care infrastructure and society [76].
People should obtain adequate and accurate information about COVID-19 and vaccine from a trusted source. Public trust building should be a priority through collaboration between citizens and civic institutions in supporting health-care providers [78]. Although Exposure to traditional media regularly undertake efforts to debunk conspiracy theories and misinformation"[24], spread of misinformation about COVID-19 progressed at unprecedented speed worldwide via social media networking sites [79]. Likewise, social media are considered as the main reason behind conspiracy theories as well Georgiou, Delfabbro [42]. Narratives of conspiracy theories and misinformation beliefs were strongly associated with exposure to digital media causing higher feelings of depression [24]. Since COVID-19 preventive precautions were negatively associated with conspiratorial and misinformation beliefs, researchers ought to investigate the psychological, political, and health factors underlying those fake thoughts [80].
A significant number of studies have explored the sources of information adopted by individuals to obtain information about COVID-19 [81,82,83]. These studies have found a variance in the sources utilized by individuals to seek information related to the virus. Interestingly, it was found that social media outlets represented a significant source of information as many used them for health information. However, using social media outlets produced many problems, as much of the information shared through them is false or misleading [84,85,86].
Li, Pastukhova [87] and Andika, Kao [88] explored the use of YouTube as a source of information during the COVID-19 pandemic. Both studies revealed that many videos watched by a huge number of viewers contained misleading information that could negatively affect individuals exposed to this information. The studies recommended that health authorities need to collaborate with Youtubers in producing videos that contain reliable health information as the reach of these videos is higher than traditional communication channels.
A study by Mansour, Shehata [89] explored the sources of information utilized by Egyptian physicians working in isolation hospitals. Results indicated that participants prefer to use traditional information sources when dealing with COVID-19 cases, such as research papers and trusted medical databases, with a little emphasis on non-traditional sources, such as social media. Similarly, Tran, Dang [90] focused on Vietnams health and community workers. The results outlined that the Internet, online newspapers, and social networks were the most popular channels used by health workers in Vietnam, revealing a lack of proper information literacy practices and a need for tailored programs for information literacy skills. In Taiwan, Wang, Lu [82] found that while many participants, including health-care workers, are using the Internet and social media to obtain health information related to COVID-19, the use of such channels was associated with the participants confidence in their ability to obtain reliable information.
Studies also found that individuals utilize other sources of information for health information, including COVID-19 information. A study by Shehata [91] revealed that in addition to social media as a source of health information, personal contacts (family and friends) were among the top sources of information. Other sources, such as authorities webpages, newspapers, and magazines, were confirmed to be used by the participants. Notably, many studies confirmed that social outlets such as WhatsApp, Telegram, Instagram, and Facebook were among the highly used sources of health information on the Internet rather than being a source of rumors and misinformation [92,93,94].
Social networks have facilitated the dissemination of information worldwide; however, with the infodemic that accompanied the COVID-19 pandemic, individuals could not trust the information they find through social outlets [95]. During the pandemic, COVID-19 misinformation evolved continuously, contributing to the digital destruction of the mental model [96]. Therefore, many studies aimed to explore the factors that affect individuals trust in the information they read on the Internet. On an individual level, Shehata and Alnadabi [97] investigated the factors that lead undergraduates to trust and share information online using the theory of reasoned action. The results revealed that age, gender, self-efficacy, personal beliefs, and subjective norms play a key role in determining trust in information. Moreover, using digital platforms was associated with lack of basic ethical competencies [98].
Pan, Liu [99] confirmed the previous results, as the study showed that pre-existing beliefs lead to acceptance of misinformation and trust in online information sources. On the other hand, the study claimed that education level and age are not associated with the acceptance of misinformation or trust in online information. Similarly, Shehata [91] explored the health information behavior of undergraduates and revealed that personal beliefs affect individuals trust of information, confirming Pan, Liu [99] results. Individuals tend to trust information that is consistent with their beliefs to avoid dissonance in behavior.
Notably, Latkin, Dayton [100] reported a decline in trust in formal information sources in the USA. The study revealed that the state health department and the White House were among the samples top untrusted sources of information due to their doubt that politics are playing a part in the spread of COVID-19. Figueiras, Ghorayeb [101] rated health information sources in terms of trust in these sources in UAE. The study argued that trust is influenced by sociodemographic (culture, age, gender) factors. The most trusted sources were physicians, health-care workers, and formal government channels. The results revealed that the use of sources and levels of trust varied based on age, gender, and education. The study also noted that adopting protective behavior affected the level of trust among the sample.
De Coninck, Frissen [24] investigated the relationship between exposure to information sources and conspiracy, and misinformation beliefs; and tested the moderating role of trust in information sources as well as the mediating role of depression and anxiety in eight European, Asian, and American countries during the pandemic. Results indicated that greater exposure to politicians and digital media and personal contacts was associated with higher rate of belief in conspiracy and misinformation, while exposure to traditional media was associated with lower conspiracy and misinformation beliefs. The difference between our study and that of De Coninck et al. is that their study was cross-national comparative research, yet ours is a within-nation comparative study. They used cross-cultural and overseas samples to collect data from USA, UK, New Zealand, Canada, Philippines, Hong Kong, Switzerland, but we recruited only participants from Omani citizens. It is worth noting that we adopted the same instruments.
Overall, studies have shown that the use of information resources varies. The type of information resources used in one region is not necessarily the same in the other as many variables shape the individuals behavior and acceptance of information resources. However, it can be said that personal beliefs, self-efficacy, culture, age, gender, and education were the most visible factors in all studies [95, 102, 103].
Gender has been found to impact the belief in conspiracy theories. Despite the limited research on gender differences in conspiracy thinking, it has been generally observed that men tend to be more inclined to endorse COVID-19 conspiracy theories than females [16] and are more affected by false beliefs [79]. Conversely, Pan, Liu [99] research indicates that females tend to be more accepting of online misinformation than males.
Different studies indicated that people with high level of education are less inclined than those with low level of education to believe in conspiracy theories [17, 43, 44]. To interpret this, Gerosa, Gui [104] argued that people with higher levels of education display higher levels of knowledge. On the other hand, level of education did not have a significant role in believing misinformation. With regard to age, studies in this area are still nascent but some studies, e.g., Douglas, Sutton [105] concluded that young people in middle adolescence are keen on accepting conspiracy theories. Jolley, Douglas [106] believed that conspiracy theories beliefs change across lifespan, and it is not easy to examine conspiracy theories across the lifespan. Concerning employment, countries with high levels of unemployment offer fertile ground for the conspiracy theories [107].
In this study, our primary aims were to elucidate the intricate interplay between conspiracy theories, misinformation beliefs, and COVID-19 anxiety. Specifically, we sought to examine the moderating effect of trust and the mediating effect of COVID-19 anxiety in shaping the relationship between exposure to information sources and individuals tendencies towards conspiracy theories and misinformation beliefs. Additionally, we endeavored to explore how these relationships may vary across demographic factors, including age group, educational level, gender, and place of residence (governorate).
In line with this literature, we formulated the following hypotheses
H1. Exposure to digital media will be associated with greater conspiracy and misinformation beliefs.
H2. Exposure to traditional media is expected to be associated with lower conspiracy and misinformation beliefs.
H3. The impact of COVID-19 anxiety and exposure to information sources on conspiracy theories and misinformation beliefs is moderated by trust in these sources.
H4. COVID-19 anxiety is positively associated with conspiracy and misinformation beliefs.
H5. The rate of conspiracy and misinformation beliefs is similar across all governorates.
H6. Conspiracy theories, misinformation beliefs, and COVID-19 would differ significantly according to gender, education level, employment, place of residence, and age.
By Stacy M. Brown, NNPA Newswire
As COVID-19 continues to evolve, a new variant has emerged, garnering attention from health officials across the United States. Known as HV.1, the latest variant has shown a significant surge in cases, raising questions about its potential impact on public health.
According to data from the Centers for Disease Control and Prevention (CDC), HV.1 was first identified in mid-summer, but it wasnt until September that cases began to spike, making it the cause of nearly 20 percent of all COVID-19 cases in the country.
Infectious disease experts, including Dr. Amesh A. Adalja and Dr. Thomas Russo, told the health and wellness website Prevention.com that they have classified HV.1 as an Omicron XBB variant, descending from the EG.5 variant. They said the lineage highlights its genetic connection to the original Omicron strain.
According to Prevention.com, one of the concerning features of HV.1 is its spike protein, which has undergone notable changes from the EG.5 variant. While the full implications of these alterations are not yet fully understood, the rapid increase in casesfrom 0.5 percent in mid-July to nearly 20 percent in mid-Octobersuggests a high level of transmissibility.
Despite the rise in cases, experts remain cautiously optimistic. Dr. Adalja emphasized that new variants of SARS-CoV-2 are expected, and most may not pose a significant threat. Dr. William Schaffner told Prevention.com that, so far, HV.1 doesnt appear to cause more severe illness than other circulating variants.
Symptoms associated with HV.1 largely mirror those of previous strains, including fever, cough, fatigue, and loss of taste or smell. However, it tends to manifest as a more common cold-like illness, with symptoms like congestion and a runny nose being prominent.
Regarding prevention, the updated COVID-19 vaccine based on the XBB.1.5 variant is expected to protect individuals from HV.1. The new variant is considered a grandchild of XBB.1.5, and experts anticipate the vaccine will effectively mitigate severe cases.
While HV.1 is rising, health officials urge the public to maintain standard precautions. This includes vaccination, proper hand hygiene, and avoiding close contact with visibly unwell individuals. For added protection, N95 or Kn95 face masks are recommended.
COVID is still with us. If you develop symptoms, test yourself ASAP and contact your doctor if youre positive. You may be a candidate for an antiviral medication, Dr. Russo underscored.
This article was originally published by NNPA Newswire.
Tuesday, November 7, 2023
At the beginning of the pandemic, we heard a lot about shortages of hospital beds, ventilators, testing supplies, as well as doctors and nurses. GAO has reported heavily on the impacts of not being prepared for a pandemic. But in a new report, we look at the actions being taken to make sure we're more prepared next time. We'll learn more from GAO's Mary Denigan-Macauley.
As the world enters its fourth full year of living with the COVID-19 virus, general attitudes toward the illness are noticeably less concerned than in previous years, as Professor of Preventive Medicine at Northwesterns Feinberg School Mercedes Carnethon said.
Carnethon said that it appears as if the general public feels safer when it comes to the pandemic: Many adults who are vaccinated or in good health do not deem themselves at particular risk for severe illness. However, the COVID-19 virus still looms, and amid another wave of the sickness this season, it remains important to know and follow best practices for preventing its spread.
People can avoid spreading the virus by getting tested. Experts at the Center for Disease Control and Prevention recommend people get tested for the virus whenever they experience common symptoms including coughing, congestion or a new loss of taste or smell. People who are exposed to COVID regardless of symptoms should also test, though the CDC recommends waiting until five days after initial exposure.
Most COVID tests fall under two categories: PCR lab tests and rapid antigen tests.
PCR lab tests are available through healthcare providers and can take up to three days to return results.
At-home antigen tests can be found over-the-counter at many common pharmaceutical stores like Walgreens and CVS, as well as in general stores like Target. Northwestern students can also go to the Universitys Student Health Service for over-the-counter testing. Most antigen tests produce results within 15 to 30 minutes.
Antigen tests are less likely to detect the virus than PCR tests, so the FDA recommends taking two to three antigen tests over the span of 48 hours to confirm test results.
As a general rule of thumb, Carnethon said its important to err on the side of caution to protect yourself and those around you, especially during the upcoming colder months, when respiratory viruses like the flu and common cold are more prevalent.
It doesnt hurt to rule out COVID-19 since there are many respiratory illnesses circulating, Carnethon said. If [a person isnt] feeling well and even if it isnt COVID, they should try not to pass it along to others. If symptoms dont get better with rest, fluids and over the counter symptom relievers, then they may wish to see a doctor.
In the event of a positive COVID test result, one may feel a lot of uncertainty. However, there are courses of action that people can take to safely and responsibly manage such a situation.
Robert Murphy, professor of Medicine at Feinberg and Biomedical Engineering at McCormick, noted that physical quarantine is key. Even though Northwestern no longer provides isolated housing for those infected with COVID, students can take action independently, he said.
If I was living in the same room with somebody who had COVID, I would leave, Murphy said. Just for a couple of days. As they get better and test negative, then you can go back.
Murphy also said that people should consider themselves infectious for a period of five days after first experiencing symptoms or getting a positive test result, and should at least wear a mask and self-isolate during that time.
There are also ways people can treat infection, should it occur.
The antiviral medication Paxlovid kills the virus and can be an effective treatment for those infected, Murphy said.
If you have an underlying medical problem, you can take Paxlovid even if you're young, he said.
Murphy said vaccines are a very effective method of COVID-19 prevention and treatment.
Although it is true that when people are infected with COVID their body generates an immune response, vaccines provide a more reliable standard of immunity. This is because the degree of immune response that a COVID infection generates depends on how sick the person gets, said Murphy. Vaccines trigger a stronger immunologic response that, according to Murphy, leads to greater protection against future infections than a previous infection alone.
Both Carnethon and Murphy said that the virus is constantly mutating and evading systems of immunity. This means people should keep up to date with available COVID vaccines.
The current vaccine is a new vaccine. It's not the same old one. It's not a booster, Murphy said. It's completely engineered differently.
There are three types of COVID vaccines available: Pfizer, Moderna and NovaVax. All provide immunity against the variant of COVID-19 that is currently circulating, Omicron.
Murphy said COVID is endemic, something that the world has and will continue to have to live with. Ultimately, Carnethon said that operating in a world with COVID entails consideration for others, exercising caution and responsible action.
People should be considerate of others who may be susceptible to severe illness if they catch it and be considerate of others who may not want to risk becoming sick, Carnethon said. It is best to behave in the way one would behave with any other illness they dont want to give to others.
Thumbnail Image: "Hands in protective gloves pushing shopping cart with groceries and protective face mask corona virus or Covid-19 protection" by focusonmore.com is licensed under CC BY 2.0.
