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India Gill , Aashna Shah , Eun Kyung Lee , Rachael Sommer , Kristie Ross , Aparna Bole , Darcy Freedman; Community Interventions for Childhood Asthma ED Visits and Hospitalizations: A Systematic Review. Pediatrics October 2022; 150 (4): e2021054825. 10.1542/peds.2021-054825

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Video Abstract

A systematic review of interventions in community environments found significant reductions in childhood asthma exacerbations leading to emergency department visits and hospitalizations.

Structural and social determinants of childhood asthma inequities manifest within geographic communities that are often segregated. Childhood asthma disproportionately affects Black, Hispanic, and low-income populations. Community interventions have the potential to improve inequities in emergency healthcare. This systematic review was conducted to assess the effectiveness of childhood asthma community interventions and provide a conceptual model to inform implementation of future community interventions.

Publications from PubMed, ScienceDirect, CINAHL, Cochrane Library, Web of Science, and hand searched references were examined from 2010 to 2021. Community intervention studies among children with asthma were included. Main outcomes were emergency department visits and hospitalizations. Community interventions exclusively focusing on schools or hospitals were excluded. Two reviewers independently assessed eligibility for final inclusion. Emergency healthcare findings were extracted in addition to co-benefits (eg, fewer missed school days and caregiver workdays).

Out of 1856 records, 26 publications met the inclusion criteria. Community interventions were categorized by care coordination ( n = 8), policy and environmental changes (eg, smoke-free legislature, traffic reduction models, and green housing) ( n = 8), home-based ( n = 6), and community-based health services ( n = 4). Selected studies indicated that community interventions significantly reduced childhood asthma emergency department visits and hospitalizations through increased caregiver self-efficacy, home environmental trigger reduction, and increased access to healthcare. Because of heterogeneity among studies, we were unable to conduct a meta-analysis.

Findings show significant associations between community interventions and the reduction of emergency healthcare, suggesting a protective effect for severe cases of childhood asthma.

Asthma is among the most prevalent chronic conditions in children, affecting almost 6 million children in the United States. 1   In the most severe, uncontrolled cases, children with asthma experience disruptions to their everyday life, including missed school, unplanned emergency department (ED) visits, and hospitalizations. This results in increased healthcare costs and decreased quality of life and educational potential. 2   The annual clinical and academic burden of childhood asthma results in approximately 10.5 million missed school days, 640 000 ED visits, and 157 000 hospitalizations. 3  

Childhood asthma disproportionately affects children in low-income populations, inner-cities, 2 , 4 , 5   and underrepresented minority populations. 6 , 7   Black children (13.5%) are more likely to have current asthma than White (5.7%) children. 8   Among Hispanic populations, the current childhood asthma prevalence is 8.0% and is even higher for a subset of Puerto Rican children (17.0%). 9   Black children are 4 times more likely to have an asthma hospitalization and over 7 times increased risk to die of asthma when compared with White children. 10   Additionally, children from low-income populations are more likely to visit the ED than affluent children. 11   Black race, living in an urban residence, and poverty are attributable to 30% of the risk for asthma hospitalization. 12  

The communities where children live have a significant impact on the social patterning of asthma inequities. 13 , 14   Black and Hispanic children compared with White children disproportionately live in historically disinvested neighborhoods. 15 – 19   Major sources of air pollution, such as industrial facilities and major highways, which decrease the ambient air quality and exacerbate asthma symptoms, are found in low-income communities. 20 – 23   Inequities in air pollution exposure are more pronounced than inequities based on income when comparing underrepresented minorities to White populations. 24  

Neighborhoods can also exacerbate asthma symptoms by exposure to poor indoor air quality, allergens, and type of housing. 25 – 27   Substandard, deteriorated housing found in low-income communities is associated with mold, pest infestation, and water damage. 28   Safety concerns, such as community violence, may force children to stay indoors for longer periods of time, increasing potential for exposure to indoor sources of asthma triggers. 29   Lack of quality transportation, available social services, and access to healthcare resources in the community is a barrier and can further prevent caregivers from appropriately managing their children’s asthma. 29  

Community interventions may be a plausible solution to reduce childhood asthma exacerbations leading to ED visits and hospitalizations. Community interventions are strategies seeking to reduce adverse health outcomes in a population within a defined local context. It is important to understand the effectiveness of community interventions given spatial patterning of childhood asthma risk. 13 , 30 – 33   Children spend a vast majority of their time in their communities, including visiting family or friends, attending school, recreational centers, or other public places. Based on this premise and the community level inequities in exposure to in-home asthma triggers, there is a need to identify strategies affecting communities.

A seminal systematic review conducted by Chan and colleagues found significant associations between multicomponent community-based interventions (eg, interventions focusing on asthma self-management education, reduction of home environmental triggers, care coordination, school involvement, primary healthcare provider assessment, community support, and/or advocacy for policy changes) and reductions in childhood asthma severity. 34   Their review found that most studies included interventions related to asthma self-management education, home environmental assessment, and care coordination; many were held in clinical settings. 34   However, less is known about the impact of community interventions with multiple components compared with more expansive environmental changes affecting whole communities (eg, smoke-free legislature, traffic reduction models, and green housing) as it relates to the reduction of emergency healthcare utilization. Accordingly, this systematic review aimed to examine the broader scope of community interventions to evaluate evidence of their effectiveness for reducing childhood asthma exacerbations leading to ED visits and hospitalizations and provide a conceptual model to inform the implementation of future community interventions.

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines 35   to perform the systematic review. We developed a protocol and registered it with the International Prospective Register of Systematic Reviews (registration number: CRD42020196132), before conducting the review and writing the final report.

Five electronic databases (ScienceDirect, Web of Science, Cumulative Index to Nursing and Allied Health Literature, PubMed, and the Cochrane Library) were used to search articles published from January 2010 to December 2021. We examined studies to see how effective community interventions are in reducing childhood asthma ED visits and hospitalizations. In each database we used search terms such as: (asthma AND [“community intervention” OR “community based” OR environment OR “evidence based” OR “patient education” OR “health education” OR “environmental justice” OR “collective action”] AND [hospitalization OR hospitalized OR inpatient OR emergency]). Our search strategy also comprised medical subject headings in addition to search terms related to childhood asthma ED visits and hospitalizations. To review our complete search strategy of database-specific search terms see the Supplemental Information. Additional studies were identified from hand searched reference sections.

Searches were limited to full-text articles published in the English language. Eligible studies included children with asthma who were exposed to community interventions. Community interventions comprised those that were place-based (eg, neighborhoods, zip codes, counties, etc), including those that were community-led (eg, community health workers [CHWs], local leaders, community partners, etc) and/or sociodemographic-based (eg, low-income, Black, Hispanic, etc). The main outcomes were childhood asthma ED visits and hospitalizations occurring after exposure to community interventions. Eligible study designs consisted of randomized controlled trials, longitudinal cohort, quasi-experimental design, natural experiment, or time series studies to examine the benefits and effectiveness of community interventions. There were no limitations for geographic location; all studies published worldwide were considered.

Searches excluded children with asthma exposed to no community interventions, community interventions in collaboration with drug therapies, and animal studies. Community interventions exclusively examining school or clinical settings were omitted as well as studies with only non-clinical outcomes. Though schools and clinics are important aspects of the community, recently published systematic reviews on school-based self-management, 36   asthma education for school staff, 37   school and community-based, 38   and inpatient quality improvement 39   interventions already exist. Though quality improvement studies did not clearly demonstrate effective reductions in asthma ED revisits or readmissions, 39   school-based self-management interventions improved hospitalizations and ED visits. 36   We made exceptions to our exclusion criteria for mobile community clinics that were located at schools as it is critical to identify methods of reducing barriers to care in underserved communities.

Titles and abstracts from each search engine were reviewed independently by 2 authors during the initial search. Eligible studies identified from the initial search were evaluated by 2 authors in the second phase for the full text review. Any disagreements between individual judgment were brought to the other co-authors for a discussion and resolved consensus for inclusion or exclusion. We abstracted data on study design, geographic location, study participants, sample size, type and description of community intervention, outcome measurements, and key results. A summary of findings is displayed in Table 1 .

Systematic Review Summary of Findings

Abbreviations: BMI, body mass index; CMH, Cochran-Mantel-Haenszel; IRR, incidence rate ratio; NO 2 , nitrogen dioxide; OR, odds ratio; PM10, particulate matter smaller than 10 µm; SD, standard deviation.

Two authors assessed the eligible studies for risk of bias to describe the quality of the body of evidence. For the randomized controlled trials, we used the Cochrane Risk of Bias tool for randomized trials version 2 and its associated version for cluster randomized trials. 40   The Cochrane Risk of Bias tool for randomized trials version 2 examines 5 domains of bias: (1a) bias arising from the randomization process, (1b) bias arising from the timing of identification or recruitment of participants, (2) bias caused by deviations from the intended interventions, (3) bias caused by missing outcome data, (4) bias in measurement of the outcome, and (5) bias in selection of the reported result. 40   Individual domains and an overall score were graded with low, some concerns, or high risk of bias. For the remaining non-randomized controlled trials, we used the Risk Of Bias In Non-Randomized Studies – of Interventions (ROBINS-I). 41   This tool included 7 domains of bias: (1) bias caused by confounding, (2) bias in selection of participants into the study, (3) bias in classification of interventions, (4) bias caused by deviations from intended interventions, (5) bias caused by missing data, (6) bias in measurement of outcomes, and (7) bias in selection of the reported result. 41   Domain and overall scores for the ROBINS-I yielded low, moderate, critical, serious, or missing or unclear risk of bias.

We identified 1816 records and an additional 40 records from hand searched reference sections. We reviewed 74 records for full text review and 48 were removed. We identified 26 records that met our inclusion criteria for the final report ( Fig 1 ). Because of the heterogeneous nature of the identified community interventions from eligible studies, a meta-analysis could not be performed.

Literature search results on community interventions for reducing childhood asthma ED visits and hospitalizations. Publications from PubMed, ScienceDirect, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, Web of Science, and hand searched references from 2010 to 2021 were examined for childhood asthma community interventions. Out of 1816 records identified, 74 full text records were assessed for eligibility, and 26 publications met the inclusion criteria.

Community interventions were arranged into 4 categories: (1) care coordination in communities ( n = 8), 42 – 49   (2) policy and environmental changes affecting communities ( n = 8), 50 – 57   home-based interventions in communities ( n = 6), 58 – 63   and community-based health services ( n = 4). 64 – 67   However, there is some overlap in services as many studies included an aspect of interventions in the home as a core activity. Sources for the main outcomes include electronic health records ( n = 4), 50 , 51 , 57 , 66   medical claims ( n = 5), 42 , 43 , 52 , 53 , 56   and caregiver self-reports ( n = 14). 44 , 45 , 47 – 49 , 54 , 55 , 58 – 61 , 62 – 64   Three studies used both electronic health records and self-reports. 46 , 65 , 67   Community interventions were held in majority Black and Hispanic populations for 19 out of the 20 publications that reported racial demographics. 42 – 47 , 49 , 54 , 55 , 58 – 67   There was 1 study conducted in Canada 51   and 1 in Australia. 57   The remaining were across all 4 regions of the United States, including Puerto Rico.

Eight studies investigated the relationship between care coordination and reduction of emergency healthcare utilization. 42 – 49   Seven care coordination models significantly reduced both ED visits and hospitalizations. 42 – 44 , 46 – 49   Five care coordination studies were affiliated with the Merck Childhood Asthma Network (MCAN), 44 – 48   a coordination model incorporating culturally relevant asthma education, dissemination of asthma awareness in the community, and physician education. MCAN programs employed asthma care coordinators to connect families with health and social services and facilitate communication between families, physicians, and schools. Asthma care coordinators were nurses, CHWs or health educators. According to a cross site evaluation of MCAN programs, ED visits decreased by 36% to 63% and hospitalizations declined by 26% to 78% ( P = .01). 44   The remaining 3 care coordination studies were the Community Asthma Initiative (CAI), 49   Child Asthma Link Line, 43   and the Allies Against Asthma community coalitions. 42   Care coordination programs engaged community collaboration with healthcare, government, and academic partnerships. Stakeholders included representation from community members, families with asthma, community-based organizations, CHWs, healthcare agencies, clinical practices, Medicaid managed care organizations, academic leaders, and the government.

We found 8 studies related to policy and environmental changes. Three studies assessed the impact of policies focusing on home environmental trigger reduction in low-income communities and illustrated favorable reductions in emergency healthcare utilization. 53 – 55   The first study was the Green and Healthy Homes Initiative, an environmental justice project in partnership with the US Department of Energy and Environment. Green and Healthy Homes Initiative was designed to combat the shortage of affordable quality housing in low-income communities. Comprehensive environmental home assessments were performed to improve poor quality housing. Investigators found evidence of a 65.5% reduction in hospitalizations and a 27.7% reduction in ED visits for children with asthma ( P <.02). 55   The second study was the Controlling Asthma through Home Remediation (CAHR) program. CAHR had a unique relationship with community-based organizations. In addition to reducing emergency healthcare utilization, they successfully advocated for systemic changes in the regulation and enforcement of maintenance and repairs with the New York City Housing Authority. 54   Lastly, Lantz and colleagues predicted a Medicaid population of 7619 children with asthma in a United States Midwestern city would avert 1334 annual ED visits and 153 hospital admissions for a potential “Pay for Success” multicomponent environmental home-based demonstration project. 53   Potential significant savings for children with an ED visit in the last year are $1.4 million for the federal Medicaid and $634 000 for the state Medicaid programs. For children with a hospitalization in the last year, possible savings of $2.8 million to federal Medicaid and $1.3 million to state Medicaid are expected. 53  

Three studies investigated the influence of smoke-free laws including all public places (eg, workplaces, restaurants, and school grounds). 50 – 52   There were mixed results on the effect of smoke-free laws on emergency healthcare utilization. Croghan and colleagues discovered a reduction in ED visits (risk ratio [RR] = 0.751, 95% confidence interval [CI]: 0.595 to 0.947, P = .015) 50   and Landers found reductions in hospital discharges after the enactment of county smoke-free laws across 12 states (b = −1.32; P <.05). 52   Gaudreau and colleagues found no significant changes in hospital admissions after a smoking ban. 51   Only 3 studies that assessed the impact of county-level smoke-free laws (or an international equivalent that matched the average size of a US county) met our inclusion criteria. Although there is a wealth of evidence supporting the reductions of asthma hospital admissions, discharges, or ED visits in larger settings, we omitted studies with exclusive statewide or nationwide settings. 68 – 71  

There were mixed findings from 2 air pollution reduction strategies. 56 , 57   After the closure of a local steel industry, childhood asthma hospital admissions significantly decreased by 30.3% ( P = .004). 57   Peel and colleagues investigated a traffic reduction strategy and observed up to a 20% decrease in morning traffic counts. They found a 30% decrease in associated 8-hour maximum ozone concentrations and a 30% reduction in 1-hour maximum carbon monoxide concentrations. Although there were decreased traffic counts and air pollutants, there was no impact on childhood asthma ED visits. 56   However, Friedman and colleagues previously studied the same traffic reduction strategy and found 11.1% decrease in daily acute care visits for childhood asthma. 72   The differential findings may be attributed to the available data sources.

Six studies focused on the impact of home-based interventions in predominately Black and Hispanic, low-income communities. 58 – 63   These studies employed CHWs, environmental health professionals, community nurses, or other health educators for home visit programs to conduct healthy home assessments and identify asthma triggers. They also provided comprehensive asthma education, healthy home supplies, and arranged weatherization, remediation, mold abatement, and pest control. The objective was to reduce exposure to cockroaches, dust mites, mold, and tobacco smoke. Simultaneous implementation of care coordination and home-based interventions resulted in fewer missed daycare or school days 44 , 47 – 49   and missed caregiver workdays. 60 , 62 , 63   Though there is evidence in the literature to support the impact of home-based interventions, 73 , 74   only half of the home-based interventions resulted in significant decreases to both asthma ED visits and hospitalizations. 59 , 60 , 63   Most notably in the Healthy Homes University program, there was a 68% decrease for hospitalizations, 53% reduction for ED visits, and 48% decrease for unscheduled visits to a healthcare provider ( P <.0001). 60  

We found 4 community-based health services interventions. Researchers for 2 studies sought to improve access to healthcare. Both analyzed the impact of Breathmobiles, mobile asthma clinics that deliver asthma screening, evaluation, and treatment services to children and maintained continuity with healthcare providers. 64 , 66   Breathmobiles reduced barriers to healthcare and economic concerns but yielded mixed findings to reduce emergency healthcare utilization. For example, Eakin and colleagues found no significant decline in ED visits for children randomized to a Breathmobile plus home-based program in the inner-city of Baltimore. 64   However, Morphew and colleagues found Breathmobile participants in Orange County, California were 50% to 60% less likely to need an ED visit ( P <.001) and had 68% reduction in hospitalizations ( P <.001). The intervention improved health outcomes among children with asthma and comorbid conditions, including obesity. 66  

Two studies investigated the difference in the effectiveness of delivering interventions across various settings. 65 , 67   Martin and colleagues compared the difference between CHW-delivered asthma management, support, and education in the home setting to a certified asthma educator with the same content in a clinical setting. ED visits and hospitalizations were lower in the CHW group, but emergency care visit reductions were not significant. 65   Naar and colleagues evaluated cognitive behavioral therapy to address barriers for poor self-management of asthma at any location (eg, home, school, and community center). The effect of this intervention was compared with an in-home family therapy and support model. Participants that received the cognitive behavioral therapy at a setting of their choice had fewer hospitalizations, but they did not experience a significant decline in ED visits. 67  

The risk of bias for community interventions ranged from moderate to critical for non randomized studies. Out of 22 non-randomized studies, 16 had serious risk of bias. 42 , 43 , 47 , 49 , 50 , 52 – 58 , 63 , 66   Most of the serious risk is attributed to bias from measurement of outcomes, which is accredited to self-reported outcomes, and bias from confounding. Five studies had a critical risk of bias, 45 , 51 , 60 – 62   which is also attributed to confounding. Childhood asthma is exacerbated by risk factors difficult to control in statistical analyses (eg, exposure to outdoor air pollutants and seasonal trends). Most investigators did not support their findings by exploring potential confounding exposure to secondhand smoke, seasonality, or change in medication use. The risk of bias ranged from some concerns to high concerns for randomized studies. Three out of 4 randomized controlled trials had a high risk of bias, 59 , 64 , 65   which is mainly attributed to bias caused by deviations from the intended intervention. 64 , 65   For more details on the risk of bias assessment, see the Supplemental Information.

We identified 26 community intervention publications designed to reduce childhood asthma ED visits or hospitalizations. The majority were in the care coordination ( n = 8) 42 – 49   and policy and environmental changes domain ( n = 8). 50 – 57   Both domains have the most promising impact on emergency healthcare utilization. Seven care coordination studies, 42 – 44 , 46 – 49   and 5 policy and environmental change studies were significantly associated with a reduction in both ED visits and hospitalizations. 50 , 52 , 54 , 55 , 57   Our findings provide examples of strategies that may be effective to treat asthma on a community level. Poor environmental conditions, particularly in historically disinvested communities, increase the risk for asthma ED visits and hospitalizations. 75   It is well documented that underrepresented minorities, urban residence, and low income are associated with childhood asthma. As with many social and environmental determinants of health, the burden of air pollution and substandard housing falls disproportionately on racial and ethnic minorities. 6   Interventions that cover entire communities may be more efficient in reducing asthma ED visits and hospitalizations.

The framework in Fig 2 illustrates a conceptual model of the relationship between community interventions and reductions in childhood asthma ED visits and hospitalizations. The figure displays pathways from community intervention domains to intermediate outcomes affecting caregiver quality of life, home environmental triggers, access to healthcare, and asthma management. There are 3 types of pathways: studies with all significant findings, majority of studies with significant results (at least two-thirds of studies), and studies with mixed significant findings (less than two-thirds of studies) for both outcomes. The conceptual model indicates that care coordination interventions and policy and environmental changes have the most impact on emergency healthcare utilization reduction. All care coordination interventions that measured quality of life (QoL) improved caregiver QoL. There is strong evidence, despite minimal variability, that care coordination programs increased access to healthcare and reduced home environmental triggers. Policies and environmental changes affecting communities were also effective in decreasing outdoor air pollution and home environmental triggers. There is some ambiguity in the home-based interventions domain, although they did increase caregiver QoL. The community-based health services domain also displayed mixed findings and may be an opportunity for further research.

Conceptual model of community interventions for reducing childhood asthma ED visits and hospitalizations. Community interventions are separated into 4 domains: community-based health services, care coordination, home-based, and policy and environmental changes. Pathways with dashed arrows signify mixed results or majority significant findings and smooth arrows illustrate significant associations for both emergency department visits and hospitalization reductions. See Table 1 . for a full description of study characteristics with intervention components. CHW, community health worker; ED, emergency department; PCP, primary care physicians.

Despite the heterogeneity across community intervention domains, the underlying commonality was community engagement. There are many community risks and barriers that prevent caregivers from managing their children’s asthma. This knowledge is imperative for designing effective interventions for communities. It will allow for pathways to build community ownership and integration to dismantle the barriers. Community members in low-income neighborhoods are all too familiar with the exposure to air pollutants, community violence, and poor-quality housing. When they form partnerships to execute an intervention, it may elicit trust in caregivers of children with asthma. This may further increase adherence to community interventions. It is easier to accept assistance from CHWs in a shared community with strong ties. 76   Trust is enhanced when interventions are designed to fit the unique needs of the defined community, implemented by members who share residence in the community, 44   and speak the same language. Community collaboration to codesign, implement, and evaluate intervention design is a unique component for effective community interventions. Encouraging early involvement of community partners, as well as a unique partnership with CHWs is a key to success. 48   Comprehensive asthma education, evaluation, and treatment offered with culturally and linguistically appropriate communication further addressed barriers to adherence and generated better asthma management from caregivers. 49  

Most of the community interventions identified were conducted in predominately Black or Hispanic populations. Similar to findings from Postma and colleagues’ systematic review on CHW-led interventions 77   and Chan and colleagues’ systematic review on multicomponent community-based interventions, 32   the focus of our findings were in underrepresented minority communities. Our findings provide evidence for models that are reproducible in similar low-income communities with comparable racial composition in the United States. This could potentially reduce racial inequities. Community intervention strategies to decrease asthma morbidity from these studies may not be generalizable to other racial groups or affluent populations. This systematic review highlights the substantial role that community interventions play in Black and Hispanic populations as a window of actionable opportunity. The built environment, racial segregation, and housing inequities are a result of historical structural racism, which contribute to the asthma inequities. 75   However, studies assessing community interventions focusing on the historical context of structural racism remain scarce. Future studies require quantitative and qualitative approaches that provide more geographic context of neighborhoods to understand the varying lived experiences of underrepresented minority children from White children with asthma.

The strengths of this systematic review include a comprehensive search using 5 databases, hand searched reference sections, and an assortment of search terms for community interventions. We also targeted a variety of community interventions to promote change based on the needs of the community. Rather than limit our search to only CHW delivered interventions, 77 – 79   or multicomponent community-based interventions, 32   we expanded the scope to gather studies reporting on expansive environmental changes in communities. Although we primarily analyzed asthma hospitalizations and ED visits as the main outcomes of interest, there were other co-benefits. Select community interventions found additional reductions in missed daycare or school days ( n = 9), 44 , 47 – 49 , 55 , 60 , 62 , 63 , 66   and missed caregiver workdays ( n = 4). 49 , 55 , 62 , 63   To measure QoL the majority of studies that assessed QoL used the Pediatric Asthma Caregiver’s Quality of Life instrument. 80   Out of 8 studies that measured caregiver QoL or self-efficacy, 6 studies showed improvements. 44 , 47 , 48 , 58 , 59 , 62  

Our systematic review had several limitations. Our broad inclusion criteria for community interventions limited our ability to conduct a complete analysis. Because of the heterogeneity in community interventions, we could not synthesize our findings into a meta-analysis. Limitations in the risk of bias assessment exist as many of the intervention studies were single arm studies and had no comparison group. The majority of studies had a serious risk of bias ( n = 16). 42 – 44 , 47 , 49 , 50 , 52 – 58 , 63 , 66   This is indicative of some problems in the study designs but does not mean the studies are too problematic to yield useful results. 41   Though Cochrane is the gold standard for systematic reviews, their ROBINS-I is generally designed for comparative studies.

The target population of this systematic review consisted of children with asthma. Other studies that analyzed all ages but did not report separate results for children were omitted from the final report. 81 – 86   Though we did not restrict our inclusion criteria to any specific geographic location, most studies were conducted in the United States. Findings may not be reproducible in communities outside of the United States, particularly in countries with minimal racial and socioeconomic inequities and countries with universal healthcare. It is possible that our refined search for full text availability in peer-reviewed journals, publications from 2010 to 2021, and articles issued in the English language limited our findings and potentially omitted relevant studies. We are confident that the 26 publications included in our final report serve as a representative sample of the most recent community interventions for childhood asthma ED visits and hospitalizations.

This systematic review found significant associations between community interventions and the reduction of emergency healthcare utilization, suggesting a protective effect for the most uncontrolled and severe cases of childhood asthma. Though there are persistent racial inequities in childhood asthma exacerbations leading to ED visits and hospitalizations, our research adds evidence of successful community interventions in predominately underrepresented minority communities.

We thank Vivian McCallum, MLS (User Services Librarian, Cleveland Health Sciences Library, Case Western Reserve University), who assisted with the development of the search strategy; and the anonymous reviewers for providing constructive feedback that helped improve the quality of our manuscript.

Dr Gill coordinated data collection, developed the research question, search strategy, and study protocol, conducted the title, abstract, and full text review, performed the risk of bias assessment, and drafted the initial manuscript for the systematic review; Ms Shah conducted the title, abstract, and full text review, performed the risk of bias assessment, and reviewed and revised the manuscript; Dr Lee and Mrs Sommer developed the research question, search strategy, and study protocol, conducted the title and abstract review, and reviewed and revised the manuscript; Drs Ross and Bole critically assessed the content with expert analysis and reviewed and revised the manuscript; Dr Freedman developed the research question, search strategy, study protocol, and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: Research reported in this article was funded through a grant from the S. Livingston Mather Charitable Trust and the Mary Ann Swetland Center for Environmental Health Endowment. The funders had no role in the design and conduct of the systematic review.

CONFLICT OF INTEREST DISCLOSURES: The authors have indicated they have no conflicts of interest to disclose.

controlling asthma through home remediation

community health worker

confidence interval

emergency department

Merck Childhood Asthma Network

quality of life

risk of bias in non-randomized studies – of interventions

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• Published: 01 April 2021

School-based self-management interventions for asthma among primary school children: a systematic review

• Siti Nurkamilla Ramdzan   ORCID: orcid.org/0000-0002-4427-3778 1 , 2 ,
• Julia Suhaimi 1 ,
• Katherine M. Harris 3 ,
• Ee Ming Khoo   ORCID: orcid.org/0000-0003-3191-1264 1 ,
• Su May Liew 1 ,
• Steve Cunningham 2 &
• Hilary Pinnock   ORCID: orcid.org/0000-0002-5976-8386 2  

npj Primary Care Respiratory Medicine volume  31 , Article number:  18 ( 2021 ) Cite this article

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A Publisher Correction to this article was published on 06 May 2021

This article has been updated

A Cochrane review of school-based asthma interventions (combining all ages) found improved health outcomes. Self-management skills, however, vary according to age. We assessed effectiveness of primary school-based self-management interventions and identified components associated with successful programmes in children aged 6–12 years. We updated the Cochrane search (March 2020) and included the Global Health database. Two reviewers screened, assessed risk-of-bias and extracted data. We included 23 studies (10,682 participants); four at low risk-of-bias. Twelve studies reported at least one positive result for an outcome of interest. All 12 positive studies reported parental involvement in the intervention, compared to two-thirds of ineffective studies. In 10 of the 12 positive studies, parental involvement was substantial (e.g. attending sessions; phone/video communication) rather than being provided with written information. School-based self-management intervention can improve health outcomes and substantial parental involvement in school-based programmes seemed important for positive outcomes among primary school children.

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Introduction

Asthma, the commonest long-term condition among children, causes significant morbidity and mortality globally 1 . Asthma guidelines recommend supported self-management to improve asthma control and reduce the use of urgent healthcare services 2 , 3 , 4 . Supported self-management, which includes discussion about self-management and provision of a personalised asthma action plan supported by regular asthma review, can be delivered effectively in diverse cultural and demographic groups 5 , 6 .

School-based asthma self-management interventions have been reported to improve asthma control and reduce school absenteeism and asthma exacerbations 7 , 8 , 9 , 10 , 11 . However, most systematic reviews analysed combined data from primary and secondary schools (5–18 years) 7 , 8 , 9 , 10 . One scoping review conducted in 2014 focused on primary school children, but the aim was to identify research gaps rather than assess outcomes 11 . The Cochrane review (Harris, 2019) used meta-analyses to assess intervention effectiveness and qualitative comparative analysis to examine the components of successful implementations 7 . The authors identified a number of components as being important: theoretical underpinning, parental involvement, child satisfaction and conducting the intervention during lesson time. However, the Cochrane review included interventions directed at children and adolescents (5–18 years), and did not distinguish the components associated with effective interventions in primary school children, which may differ from adolescents 7 . Educational intervention needs to be age-appropriate as primary school children will have less autonomy and capability to self-manage asthma compared to adolescents 12 . Thus, we aimed to review the effectiveness of school-based self-management interventions for primary school children with asthma and to examine the components associated with successful programmes.

Figure 1 illustrates the article selection process using the PRISMA diagram. We included 23 studies; 16 studies from the Cochrane review 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , five studies from the updated database search 29 , 30 , 31 , 32 , 33 and two studies from the pre-publication update 34 , 35 . The total number of participants was 10,682. Some studies did not report numbers in each group so we cannot provide number by allocation 13 , 14 , 24 . We contacted all authors for information not reported in the papers, and nine (39%) responded 13 , 14 , 25 , 27 , 29 , 30 , 32 , 33 , 34 .

This figure illustrates the article selection process using the PRISMA diagram.

Characteristics of included studies

The interventions were conducted from 1992 to 2019. Seventeen studies were randomised controlled trials (RCTs) (14 cluster RCT 13 , 14 , 15 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 31 , 32 , three individual RCTs 27 , 29 , 34 ), three were non-randomised studies 28 , 30 , 35 and three were uncontrolled pre-and-post studies 16 , 17 , 33 . Fifteen studies were conducted in the United States 15 , 16 , 17 , 18 , 21 , 23 , 24 , 25 , 27 , 28 , 29 , 30 , 31 , 34 , 35 , four in Canada 13 , 14 , 19 , 20 , one each in Spain 32 and United Kingdom 26 , and two in low- and middle- income countries (China and Thailand) 22 , 33 . All but one 17 of the studies in the United States were conducted in minority populations 15 , 16 , 18 , 21 , 23 , 24 , 25 , 27 , 28 , 29 , 30 , 31 , 34 , 35 , two Canadian studies were conducted in majority population 19 , 20 ; none of the others 13 , 14 , 22 , 26 , 32 , 33 reported ethnicity of population studied.

Overall intervention characteristics

The programmes were used to deliver self-management intervention varied. Eight studies used standard programmes (Open Airway for School (OAS) or tailored OAS 15 , 17 , 21 , 22 , 23 , 24 , 28 , 29 , four studies used Roaring Adventures of Puff (RAP) or tailored RAP 13 , 14 , 19 , 20 , and the other studies developed novel interventions 16 , 18 , 25 , 26 , 27 , 29 , 30 , 31 , 32 , 33 , 34 , 35 . The programmes ranged from one to eight sessions, and all were delivered by healthcare personnel, (school nurse, asthma educator, community nurse, respiratory therapist, physician) except for two that were delivered by trained school teachers 22 , 32 . Fifteen studies delivered the intervention in group sessions 13 , 14 , 15 , 16 , 17 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 28 , 34 , four used individual face-to-face sessions 27 , 29 , 30 , 35 , one used individual computer-assisted programme 18 and another used individual telemedicine sessions 31 . Two studies were unclear 23 , 33 .

Risk of bias in the included studies

The overall RoB is given in summary Supplementary Table 1 (first column) and illustrated in the Harvest plot (Fig. 2 ). Details of the RoB are in Supplementary Table 2 . Four studies had low overall risk of bias 13 , 14 , 20 , 32 , eleven had high risk of bias 15 , 16 , 17 , 21 , 27 , 28 , 29 , 30 , 33 , 34 , 35 and eight were unclear 18 , 19 , 22 , 23 , 24 , 25 , 26 , 31 . Only seven (30%) studies were categorised at low risk in random sequence generation 13 , 14 , 20 , 21 , 23 , 32 , 34 . All uncontrolled studies were categorised as high-risk in four domains (random sequence generation, allocation concealment, baseline outcome similar and baseline character similar) 16 , 17 , 33 .

Harvest plot illustrating the effectiveness on school absenteeism, asthma control and urgent healthcare services across parental involvement for school-based self-management asthma educational intervention. The shading of the bars indicates the duration of the study and the height of the bars describes the number of participants. The overall risk of bias is reflected on top of the bars.

Effectiveness of interventions

The effect of the interventions on each outcome of interest is detailed in Supplementary Table 1 , with an explanation of how the direction of the effect was interpreted and the overall effect of the study assessed. Twelve studies (two at low risk-of-bias) were assessed as having an overall positive (beneficial) effect 13 , 14 , 15 , 16 , 17 , 21 , 22 , 29 , 30 , 33 , 34 , 35 and eleven studies (two at low risk-of-bias) as having no effect 18 , 19 , 20 , 23 , 24 , 25 , 26 , 27 , 28 , 31 , 32 . No study was categorised as harmful or mixed effect. The Harvest plot (Fig. 2 ) illustrates the effect of varying degrees of parental involvement on school absenteeism, asthma control and urgent healthcare use.

Study components according to CFIR sub-domains

The CIFR domains addressed in the studies are summarised in column 2 in Supplementary Table 1 . Cicutto et al. 13 was the only study that explicitly addressed all the CFIR sub-domains in their intervention; in contrast, Spencer et al. 17 addressed only two sub-domains. All included studies used and measured the impact of at least one specific component in their intervention, e.g. information provision assessed as improvement of knowledge and self-management behaviour. The other commonly addressed sub-domain was parental involvement (19/23) 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 29 , 30 , 31 , 33 , 34 , 35 , though this varied in intensity (We use the term ‘parents’ to describe parents, guardians or other care-givers). See Supplementary Table 3 for definitions of involvement. Some studies had substantial involvement e.g. parents attending session or actively involved in phone/video communication 13 , 14 , 15 , 17 , 19 , 20 , 21 , 22 , 24 , 25 , 29 , 30 , 31 , 33 , 35 , while others had minimal parental involvement e.g. passive information in a letter 16 , 18 , 23 , 29 , 34 . Ten studies used theory to guide the development of the interventions; six used social cognitive theory 13 , 14 , 18 , 19 , 20 , 22 , two used Orem self-care theory 28 , 34 , one used life stress model 29 , and another was guided by Bruhn’s theoretical model 25 . Nine studies considered access to healthcare of their study population 13 , 14 , 15 , 24 , 25 , 27 , 30 , 32 , 33 .

Association of CFIR sub-domains and effectiveness

Tables 1 and 2 are summary matrices comparing use of the 12 CFIR sub-domains in studies with overall positive or no effect (See Supplementary Table 4 for more detail). The number of CFIR sub-domains used varied widely (2 to 12) and was similar in the studies with positive/no effect.

All studies with positive effects (12/12) reported parental involvement in their intervention 13 , 14 , 15 , 16 , 17 , 21 , 22 , 29 , 30 , 33 , 34 , 35 compared to seven studies with no effects (7/11) 18 , 19 , 20 , 23 , 24 , 25 , 31 . The Harvest plot (Fig. 2 ) illustrates the direction of effect with the varying degrees of parental involvement of each study intervention. Studies without parental involvement (including one at low RoB 32 ) showed no effect in any of the outcomes of interest 26 , 27 , 28 , 32 . Of the five interventions with minimal parental involvement 16 , 18 , 23 , 29 , 34 , the three positive studies were at high RoB and of short duration (≤ 6 months), and either small in sample (study population less than 100 children) 29 , 34 or pre/post design 16 . Studies with substantial parental involvement 13 , 14 , 15 , 17 , 19 , 20 , 21 , 22 , 24 , 25 , 29 , 30 , 31 , 33 , 35 were the only studies to report reduction in absenteeism, though impact on clinical outcomes varied. Cicutto et al. 13 (cluster RCT at low risk of bias, 170 schools and 1316 children), an example of a study that included parents in care coordination and a showcase at school, had positive effects in school absenteeism and urgent healthcare service use at 12 months. No difference was found in other CFIR subdomains between studies with positive and no effects.

We identified 23 studies (four at low RoB) that evaluated the effectiveness of school-based asthma self-management intervention among primary school children. Twelve of the studies were categorised as being overall positive, though individual outcomes varied; no study reported overall negative impact. The number of CFIR sub-domains addressed varied between studies, but the only component that seemed to be associated with positive outcomes was substantial parental involvement. This was particularly apparent in studies at low RoB.

We found substantial parental involvement to be a crucial component of a school-based asthma self-management intervention among primary school children. Reviews that included interventions targeted at teenagers, in whom parental influence might be expected to be less important, have reached similar conclusions 7 , 8 . Parental involvement was also found to be important in other school-based interventions for obesity prevention studies 36 , 37 , self-management of mental health/disorders 38 , and academic enhancement 39 .

However, we did not find other components of interventions (theory-driven, conducted during lesson time, and child satisfaction) to be essential for successful intervention, as was found in the Cochrane review 7 . The differences in the findings were most probably due to a difference in the age group of the children as the Cochrane review included studies among older school children. Our review defined fun, interactive delivery of intervention, as a strategy promoting child satisfaction and engagement, whereas the Cochrane review examined measurement of child satisfaction, an evaluation used mainly in studies targeting adolescents 7 . Primary school children had good participation rates when the sessions were conducted during school hours including during recess, in contrast to adolescents who were less willing to devote their free time including during recess 7 , 13 , 16 . Social cognitive and Orem self-care theories were the most used theories, adapted from adults which focuses on self-efficacy and skills of individuals 40 , 41 , 42 . These theories may be suitable for interventions targeting parents and adolescents, but may not be age-appropriate for primary school children with limited decision-making abilities and independent self-management skills 12 , 43 .

Primary school years are a critical time for children as they spend increasing time away from their parents and begin to learn asthma self-management for themselves 44 , 45 . Six-year-old children can express opinions, typically reflecting their parents’ actions and views 44 . Over primary school years, they learn from their own experiences and gain the confidence to make independently decisions 44 , 45 . Although involving parents to support and empower their children’s self-management behaviour is a key concept in the clinical management of children 2 , 3 , direct parental involvement was not always included in school-based intervention among primary school children 27 , 28 , 32 . A key challenge for involving parents is the difficulty of engaging them to attend session(s) delivered in school 24 , 46 . With the ease of modern telecommunication, alternative methods of engagement such as the use of telephone calls or video sessions could be explored as a convenient alternative to enable substantial parental involvement in the intervention 31 , 47 .

Although parental involvement is important, an aim of a school-based intervention is to shift the focus of self-management education from parents to children 48 , 49 . Studies in this review included up to eight educational sessions for children compared to only one to two sessions for parents 13 , 27 , 30 . A recent school-based health intervention has recommended the socio-ecological theory where children are the primary focus of an intervention that also involves the children’s social network, e.g. parents, teachers, friends and the school plan/policy 48 , 50 . Schools could be an ideal setting for this approach, smoothing children’s transition to independent self-management by being located in the child’s environment and including parents as part of the children’s social network 51 , 52 , 53 . Schools also provide a platform for interactive fun groups activities and peer support for children with similar conditions, which could reduce stigma and support self-management practices 13 , 32 .

The effectiveness of self-management also depends on access and adherence to evidence-based treatments such as controller asthma medications, which is conventionally delivered in healthcare settings 2 , 5 . ‘Access to healthcare’, however, was a sub-domain least likely to be addressed in the studies included in this review. Although most US-based studies were conducted among minority deprived populations, in whom poor health outcomes may be due to the large disparities in healthcare provision 54 , only five studies reported the access of the children to effective controller medication 15 , 24 , 25 , 27 , 30 . Even in countries with universal health coverage, such as Canada and United Kingdom, equitable access to high quality healthcare for children cannot be assumed 55 . In low- and middle-income countries, socio-cultural beliefs, physical inaccessibility and lack of education and information are extremely common barriers to healthcare despite universal health coverage 56 , 57 . Similar barriers are widely described in the US 30 , 31 , 34 . Encouragingly, bridging school-based education with the children’s healthcare providers has been a core component of recent school-based interventions 53 , 58 .

A strength of this review is that we used comprehensive search terms similar to the Cochrane review and searched seven relevant databases. Two reviewers conducted full text screening and data collection was duplicated. A pre-publication update was performed to ensure the findings was up to date this review.

This review has some limitations. Despite a rigorous search strategy, it is possible that we may miss some studies. The screening of title and abstract was conducted by one reviewer, but good agreement resulted after training. Only two studies were conducted in low- and middle-income countries and many studies (15/23) were conducted in the US, reducing generalisability of the review. The included studies were variable in methodologies, instrumentation and data analysis. However, three low RoB studies coincided with the findings and some variability was illustrated in the Harvest plot with the other details described in Supplementary Table 1 . Poor reporting of interventions was a challenge and we may have overlooked some intervention components that were not explicitly described. We contacted all the authors to reduce the number of missing information and obtained 39% responses.

A multi-level intervention focusing on the children and involving their social network could provide a useful self-management interventions framework for primary school children and their parents. Specifically, there is a gap in our current understanding of school-based self-management education in younger children in low- and middle-income countries. Future research needs to focus on implementation strategies and effectiveness using this framework. Partnership between schools, parents and healthcare services could create a pragmatic and effective school plan/policy to improve asthma control among children.

School-based self-management interventions for asthma among primary education children can improve asthma outcomes and reduce absenteeism. Parental participation is an important component in this age group, but other features highlighted in secondary school interventions proved less relevant, perhaps reflecting the greater role of parents in younger children.

This systematic review follows Cochrane methodology 59 , and PRISMA reporting standards. The protocol is registered with the PROSPERO database (registration number: CRD42019131955).

Study eligibility criteria

We used a Population, Intervention, Comparator/Control, Outcomes and Study Design (PICOS) strategy to define eligible studies (Table 3 ) 60 , using definitions similar to the Cochrane review 3 , 7 , 61 . Self-management intervention was defined as the active transfer of information to children with asthma to enhance their self-management skills; this was interpreted with reference to components of self-management recommended by global guidelines (Table 3 ) 2 , 3 . In line with the Cochrane review, we included non-randomised trials to capture a broader range of studies and thence components used.

Outcomes of interest

We chose three outcomes of interest (school absenteeism and two health outcomes - asthma control and urgent use of healthcare services) to reflect the impact on children with poorly controlled asthma 2 , 7 , 61 .

Search strategy

The details of the search terms and databases used are in Supplementary Table 5 . The Cochrane review conducted searches in August 2017 using search terms developed by the Cochrane Airway Information Specialist in 23 electronic databases from 1995 onwards and included 55 papers 7 . Using the same search terms, with no language limitations, we updated the search in February 2019 in six-core databases (CENTRAL, MEDLINE, Embase, PsycINFO, CINAHL, AMED) 7 . In addition, we searched the Global Health database using similar search terms without date limits to include studies from low- and middle-income countries. We included all studies identified in the review that met our eligibility criteria (principally excluding those not delivered to primary school children). We checked the reference list and undertook forward citation of studies in the Cochrane review conducted among primary school children 62 .

A pre-publication update was conducted on 17th March 2020 using forward citation of the Cochrane review (published 28 January 2019) 7 and all the studies included in this review 62 .

Study selection and data extraction

We imported the list of articles from the electronic databases into Endnote software (version 7) to facilitate screening, de-duplication and overall management of the results. SNR and JS independently screened a random selection of 10% of the titles and abstracts 5 . A 96.3% agreement was achieved prior to discussion, which reached total agreement after clarification of the screening criteria. SNR then completed title and abstract screening. Both reviewers independently conducted full-text screening (which included all the studies in the Cochrane review and those satisfying title and abstract screening), met to discuss discrepancies and decided on the final included papers. Supplementary Table 6 lists studies excluded from this review. A modified Cochrane data extraction form was used for duplicate data extraction (SNR and JS) 63 . SNR contacted authors for missing data by email and any further information received was added to the data extraction forms 59 .

At all stages, any discrepancies not resolved by discussion between the two reviewers were arbitrated by the study team (HP, KEM, LSM, SC).

Risk of bias of included studies

We used the Cochrane Effective Practice and Organisation of Care (EPOC) Risk of Bias (RoB) tool 64 to categorise risk into low, high and unclear risk in nine domains, which were then used to generate an overall assessment of the RoB for each study. The Cochrane EPOC RoB tool applies to randomised trials and non-randomised trials 64 . Studies with at least one high-risk domain were summarised as high risk; studies with no high-risk domains but at least one unclear domain were summarised as unclear risk and studies at low risk in all domains were summarised as low risk 64 .

Data handling

The Consolidated Framework for Implementation Research (CFIR) is a comprehensive framework that systematically identifies factors (sub-domains) that influence the effectiveness of implementation in multi-level interventions 65 . Supplementary Table 3 outlines the 12 CFIR sub-domains. We used CFIR sub-domains to identify context and components in each study (e.g., intervention characteristics, features of the setting and strategies for implementation) that might influence effectiveness of the interventions 66 , 67 .

We used a structured approach to divide the studies into four categories according to the change in the outcomes of interest 68 . This was a two-step process.

First, we determined the direction of effect in each of the three outcomes of interest (school absenteeism; asthma control; urgent use of healthcare service) for each included study. In some studies, several measures mapped to each outcome of interest: for example, emergency room visits and hospitalisation are both measures of unscheduled care potentially with conflicting findings. The rules at the top of Supplementary Table 1 define how we prioritised outcomes defined as ‘primary’ in the included study, outcomes measured with a validated instrument, and results that were clinically as well as statistically significant. The table then describes how the decision process was applied for each outcome of interest in each study.

Second, we categorised the overall effect of the intervention in each study as positive, negative, no effect or mixed effects, as follows:

Positive (beneficial): Studies with a positive effect in ≥1 of the outcomes and no negative effects.

Negative (harmful): Studies with a negative effect in ≥1 of the outcomes and no positive effects.

No effect: Studies with no positive effects in any of the outcomes.

Mixed: Studies with at least one positive and one negative outcome.

Data synthesis

Our preliminary scoping suggested that the studies would be heterogenous in terms of context, components delivered and study design, so we undertook a narrative analysis. We used a Harvest plot 69 (coded to indicate number of participants, RoB and follow-up duration) to illustrate the effectiveness of the interventions on the three outcomes of interest for each study. A Harvest plot graphically displays not only outcomes but also the weight of the evidence in complex and diverse studies by illustrating selected methodological criteria 69 . We used a matrix to examine the association of the CIFR sub-domains with the overall effectiveness of the interventions. Supplementary Table 4 lists the CFIR sub-domains and how we interpreted them in our analysis.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

All data that support the findings of this systematic review are already in the public domain.

Code availability

Authors can confirm that all relevant data codes are included in the paper and/or its supplementary information files.

Change history

07 may 2021.

A Correction to this paper has been published: https://doi.org/10.1038/s41533-021-00240-0

06 May 2021

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Acknowledgements

We would like to acknowledge all the authors of included studies who provided the information to aid in synthesising the data. We also acknowledge the RESPIRE collaborators which includes Ahmed Ehsanur Rahman, Anand Kawade, Parag Khatavkar, Sanjay Juvekar, Colin Simpson, Nik Sherina Hanafi, Kit Chan, Wong Li Ping, Sajid Soofi, Osman M Yusuf, Shahida O Yusuf, Rita Isaac and the RESPIRE members who contributed to this paper: Aziz Sheikh, Monica Fletcher and Sian Williams.

S.N.R. is a PhD student at the University of Edinburgh with the NIHR Global Health Research Unit on Respiratory Health (RESPIRE). RESPIRE is funded by the National Institute of Health Research using Official Development Assistance (ODA) funding. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.

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All authors contributed to study conception. S.N.R. and J.S. performed screening, data extraction of the included studies. All authors (S.N.R., J.S., K.M.H., E.M.K., S.M.L., S.C. and H.P.) contributed to the interpretation of data. S.N.R. drafted the manuscript and all authors provided critical revisions and editing of the manuscript.

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Ramdzan, S.N., Suhaimi, J., Harris, K.M. et al. School-based self-management interventions for asthma among primary school children: a systematic review. npj Prim. Care Respir. Med. 31 , 18 (2021). https://doi.org/10.1038/s41533-021-00230-2

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DOI : https://doi.org/10.1038/s41533-021-00230-2

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Managing Asthma in Adolescents and Adults : 2020 Asthma Guideline Update From the National Asthma Education and Prevention Program

• 1 UCONN Health, Farmington, Connecticut
• 2 University of Vermont, Burlington
• 3 University of Illinois Hospital and Health Sciences System, Chicago
• 4 University of Wisconsin School of Medicine and Public Health, Madison
• 5 University of Colorado School of Medicine, Aurora
• 6 Department of Allergy, Kaiser Permanente Medical Center, San Diego, California
• Editorial Evolving Strategies for Long-term Asthma Management Stephanie Lovinsky-Desir, MD, MS; George T. O’Connor, MD, MS JAMA
• Original Investigation Triple vs Dual Inhaler Therapy and Asthma Outcomes in Moderate to Severe Asthma Lisa H. Y. Kim, MD; Carol Saleh, MD; Anna Whalen-Browne, MD; Paul M. O’Byrne, MB; Derek K. Chu, MD, PhD JAMA
• Viewpoint Over-the-Counter Availability of Rescue Inhalers for Asthma William B. Feldman, MD, DPhil, MPH; Jerry Avorn, MD; Aaron S. Kesselheim, MD, JD, MPH JAMA
• JAMA Clinical Guidelines Synopsis Therapy for Mild to Moderate Asthma Sarah E. Gray, MD; Adam S. Cifu, MD; Valerie G. Press, MD, MPH JAMA

Importance   Asthma is a major public health problem worldwide and is associated with excess morbidity, mortality, and economic costs associated with lost productivity. The National Asthma Education and Prevention Program has released the 2020 Asthma Guideline Update with updated evidence-based recommendations for treatment of patients with asthma.

Objective   To report updated recommendations for 6 topics for clinical management of adolescents and adults with asthma: (1) intermittent inhaled corticosteroids (ICSs); (2) add-on long-acting muscarinic antagonists; (3) fractional exhaled nitric oxide; (4) indoor allergen mitigation; (5) immunotherapy; and (6) bronchial thermoplasty.

Evidence Review   The National Heart, Lung, and Blood Advisory Council chose 6 topics to update the 2007 asthma guidelines based on results from a 2014 needs assessment. The Agency for Healthcare Research and Quality conducted systematic reviews of these 6 topics based on literature searches up to March-April 2017. Reviews were updated through October 2018 and used by an expert panel (n = 19) that included asthma content experts, primary care clinicians, dissemination and implementation experts, and health policy experts to develop 19 new recommendations using the GRADE method. The 17 recommendations for individuals aged 12 years or older are reported in this Special Communication.

Findings   From 20 572 identified references, 475 were included in the 6 systematic reviews to form the evidence basis for these recommendations. Compared with the 2007 guideline, there was no recommended change in step 1 (intermittent asthma) therapy (as-needed short-acting β 2 -agonists [SABAs] for rescue therapy). In step 2 (mild persistent asthma), either daily low-dose ICS plus as-needed SABA therapy or as-needed concomitant ICS and SABA therapy are recommended. Formoterol in combination with an ICS in a single inhaler (single maintenance and reliever therapy) is recommended as the preferred therapy for moderate persistent asthma in step 3 (low-dose ICS-formoterol therapy) and step 4 (medium-dose ICS-formoterol therapy) for both daily and as-needed therapy. A short-term increase in the ICS dose alone for worsening of asthma symptoms is not recommended. Add-on long-acting muscarinic antagonists are recommended in individuals whose asthma is not controlled by ICS-formoterol therapy for step 5 (moderate-severe persistent asthma). Fractional exhaled nitric oxide testing is recommended to assist in diagnosis and monitoring of symptoms, but not alone to diagnose or monitor asthma. Allergen mitigation is recommended only in individuals with exposure and relevant sensitivity or symptoms. When used, allergen mitigation should be allergen specific and include multiple allergen-specific mitigation strategies. Subcutaneous immunotherapy is recommended as an adjunct to standard pharmacotherapy for individuals with symptoms and sensitization to specific allergens. Sublingual immunotherapy is not recommended specifically for asthma. Bronchial thermoplasty is not recommended as part of standard care; if used, it should be part of an ongoing research effort.

Conclusions and Relevance   Asthma is a common disease with substantial human and economic costs globally. Although there is no cure or established means of prevention, effective treatment is available. Use of the recommendations in the 2020 Asthma Guideline Update should improve the health of individuals with asthma.

• Editorial Evolving Strategies for Long-term Asthma Management JAMA

Read More About

Cloutier MM , Dixon AE , Krishnan JA , Lemanske RF , Pace W , Schatz M. Managing Asthma in Adolescents and Adults : 2020 Asthma Guideline Update From the National Asthma Education and Prevention Program . JAMA. 2020;324(22):2301–2317. doi:10.1001/jama.2020.21974

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Systematic reviews and meta-analyses on treatment of asthma: critical evaluation

• Related content
• Peer review

This article has corrections. Please see:

• Errata - April 08, 2000
• Errata - July 29, 2000
• Alejandro R Jadad , professor ( jadada{at}fhs.mcmaster.ca ) a ,
• Michael Moher , Royal College of General Practitioners research training fellow b ,
• George P Browman , professor a ,
• Lynda Booker , research assistant a ,
• Christopher Sigouin , doctoral student a ,
• Mario Fuentes , research assistant c ,
• Robert Stevens , research assistant c
• a Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Canada L8N 3Z5
• b Institute of Health Sciences, University of Oxford, Headington, Oxford OX3 7LF
• c Foresight Consultants, Dundas, Ontario, Canada L9H 2R5
• Correspondence to: A R Jadad
• Accepted 13 December 1999

Objective: To evaluate the clinical, methodological, and reporting aspects of systematic reviews and meta-analyses on the treatment of asthma and to compare those published by the Cochrane Collaboration with those published in paper based journals.

Design: Analysis of studies identified from Medline, CINAHL, HealthSTAR, EMBASE, Cochrane Library , personal collections, and reference lists.

Studies: Articles describing a systematic review or a meta-analysis of the treatment of asthma that were published as a full report, in any language or format, in a peer reviewed journal or the Cochrane Library .

Main outcome measures: General characteristics of studies reviewed and methodological characteristics (sources of articles; language restrictions; format, design, and publication status of studies included; type of data synthesis; and methodological quality).

Results: 50 systematic reviews and meta-analyses were included. More than half were published in the past two years. Twelve reviews were published in the Cochrane Library and 38 were published in 22 peer reviewed journals. Forced expiratory volume in one second was the most frequently used outcome, but few reviews evaluated the effect of treatment on costs or patient preferences. Forty reviews were judged to have serious or extensive flaws. All six reviews associated with industry were in this group. Seven of the 10 most rigorous reviews were published in the Cochrane Library .

Conclusions: Most reviews published in peer reviewed journals or funded by industry have serious methodological flaws that limit their value to guide decisions. Cochrane reviews are more rigorous and better reported than those published in peer reviewed journals.

Introduction

One of the most important challenges for anyone treating patients with asthma is the need to cope with vast amounts of information about an ever increasing number of new devices and drugs. The abundance of information often makes it difficult to establish the most appropriate drug or regimen to use in a given clinical situation. 1

During the past two decades, interest has risen in the use of systematic reviews as tools to help decision makers cope with information overload. These reviews, in their ideal form, include an explicit description of how they were conducted and incorporate strategies to minimise bias and maximise precision. 2 3 These reviews can also include meta-analysis (the statistical combination of the results of several independent studies to produce a single estimate of the effect of a particular intervention or healthcare situation). 4 However, most systematic reviews and meta-analyses published in peer reviewed journals have methodological deficiencies that may limit their validity. 5 – 12

Recently, important initiatives have emerged to improve the methodological quality of systematic reviews and meta-analyses. Perhaps the most prominent is the Cochrane Collaboration, a large international group 11 13 that seems to be producing reviews that are more rigorous and better reported than those published in peer reviewed journals. 9 14 We evaluated the quality of published systematic reviews and meta-analyses on the treatment of asthma and compared the characteristics of Cochrane reviews with those in peer reviewed journals.

Inclusion criteria

To be included, a report had to be described as a systematic review or a meta-analysis of the treatment of asthma and to be published in full, in any language or format, in a journal or the Cochrane Library .

Literature search and study selection

We identified eligible studies by a search up to July 1998 in Medline (from 1966), CINAHL (from 1982), HealthSTAR (from 1975), and EMBASE (from 1984) using a refined search strategy (see BMJ 's website for details). 9 This was complemented by a search of the Cochrane Library (issue 3, 1998) with the term “asthma” and searches of personal collections and the reference lists of eligible studies.

Independently, two of us (LB and ARJ) reviewed the citations identified by the search strategy to judge their eligibility. The final decision on inclusion in the review was made by consensus.

Data extraction

Three trained reviewers (MF, LB, RS) extracted data independently using unmasked reports. 15 The final set was agreed by consensus, and differences were resolved by a fourth reviewer (ARJ).

Data were extracted on the general characteristics of the studies (authors, sources of funding, and source, year, place, and language of publication); clinical issues (population, intervention, condition, and outcomes reviewed), methodological characteristics (language restrictions; number, format, design, and publication status of the studies included; data synthesis; heterogeneity testing; and methodological quality); and conclusions. Methodological quality was assessed with Oxman and Guyatt's index, a validated tool that scores reviews on a seven point scale. 8 16 Reports were regarded as having serious or extensive flaws if they received a score of 1 to 3, and as having minimal or minor flaws if they received scores from 4 to 7.

Data analysis

Reviews were divided according to publication in the Cochrane Library or journals and to the presence or absence of association with industry. The Wilcoxon rank-sum test (two sided) was used to compare the number of authors, included studies, and sources and the overall quality scores. Fisher's exact test (two sided) was used to compare the responses to the first nine items in Oxman and Guyatt's index and also the proportion of reviews that described the primary outcomes, selection criteria, and heterogeneity testing and the number of reviews with language restrictions between the Cochrane Library and journals. Values of P<0.05 were regarded as significant.

General characteristics

We identified 50 eligible reviews (see BMJ 's website for full list). The first review identified was published in 1988. Twenty nine (58%) of the reviews were published in 1997 and 1998. Twelve reviews were published in the Cochrane Library , and the remaining 38 were published in 22 peer reviewed journals. Only one review appeared in both groups. None of the reviews published in journals represented updated versions of earlier work. The journal with the highest number of reviews was Annals of Pharmacotherapy (seven) followed by the Journal of Allergy and Clinical Immunology and Respiratory Medicine (four each). Table 1 gives other characteristics of the reviews.

Characteristics of 50 reviews of treatment of asthma

• View inline

Methodological characteristics

The number of studies included in the reviews varied from 2 to 97. Most of the reviews (37) included randomised controlled trials, but three included non-randomised trials with contemporaneous controls and one included case series. In 14 reviews (including some of those mentioned in the previous sentence) the exact type of studies was either unclear or not reported. Seven of the 50 reviews included unpublished articles and nine included articles available only in abstract form. None of the reviews published in peer reviewed journals had been updated.

Methodological quality

Forty reviews obtained quality scores of 3 or less, which is compatible with serious or extensive flaws. All six reviews associated with industry were in this group (table 2 ). None of these reviews described efforts to reduce selection bias; one described the search strategy, one described the methods used to assess the quality of the studies, and three reported the methods used to combine data across studies (table 2 ). All but one 17 of these studies had results and conclusions that favoured the interventions related to the companies sponsoring the reviews. The number of reviews associated with industry was too small to warrant meaningful statistical comparisons with other reviews.

Methodological quality of systematic reviews and meta-analyses of the treatment of asthma. Values are number of affirmative answers/number of reviews relevant to each question

Analysis of individual components of Oxman and Guyatt's index showed that 66% of the reviews stated the search methods used to find the evidence, 52% included a reasonably comprehensive search for evidence, 56% reported the inclusion criteria, 30% included measures to avoid selection bias, 28% reported the criteria used to assess the validity of the included studies, 24% used appropriate criteria for validity assessment, 52% reported the methods used to synthesise findings, and 50% had conclusions supported by the data or the analysis reported in the review (table 2 ). In addition, 20 reviews (40%) included heterogeneity testing, 16 (32%) stated the primary outcome of interest to the reviewers, and eight (16%) included assessment of publication bias. We found no significant difference in the proportion of reviews with favourable results between those with minimal or minor flaws and those with serious or extensive flaws (1/10 v 11/40, P=0.416).

Cochrane reviews versus reviews in peer reviewed journals

Of the 10 reviews with scores of 4 or more, seven were published in the Cochrane Library . Cochrane reviews had higher overall quality scores than those published in peer reviewed journals (median 6 v 2, P<0.005). Compared with reviews published in journals, more Cochrane reviews had adequate reporting of the search strategy, had comprehensive search strategies, described the inclusion criteria, made efforts to avoid bias during the selection of the studies, reported the criteria for assessing the quality of the studies, reported the methods used to combine study findings, and combined the findings of the relevant studies appropriately (table 2 ). Fewer Cochrane reviews had language restrictions (0/12 v 21/38, P<0.005) and more included heterogeneity testing (9 v 11, P=0.007).

There were no significant differences between the groups in the number of authors, the number of studies reviewed, assessment of publication bias, and identification of primary outcomes.

Findings of reviews

Twelve reviews identified an intervention as better than the control treatment. None of the reviews reported patient preferences. The box gives the conclusions of the reviews with minimal flaws.

Findings of studies with minimal flaws

Peer reviewed journals.

Use of oral and intravenous steroids early in the treatment of asthma exacerbations reduces hospital admissions in adults and children; steroids are effective in preventing relapse in outpatient management of exacerbations; and oral and intravenous steroids seem to have equivalent effects on pulmonary function during acute exacerbations 18

Addition of ipratropium bromide to β agonist significantly improves the predicted forced expiratory volume in one second but gives no clinical improvement 19

Bronchodilator delivery through a meter dosed inhaler or wet nebuliser is equivalent in acute treatment of asthma 20

Cochrane Library

Limited asthma education is unlikely to improve health outcomes in adults with asthma 21

Addition of a single inhalation of anticholinergics to a β agonist regimen may improve lung function but has no notable effect on hospital admissions. Multiple doses may avoid hospital admission in 1 of 11 treated patients 22

A short course of corticosteroids (oral or intramuscular) after an acute exacerbation of asthma (of variable and poorly reported severity at baseline) reduces the number of relapses and decreases use of β agonist without apparent increase in adverse effects 23

There is no indication for routine use of methotrexate in patients receiving long term treatment with oral steroids 24

Prophylaxis with single doses of nedocromil sodium1-8 mg inhibits the severity and duration of exercise induced bronchoconstriction. Benefits seem greatest in patients with more severe symptoms 25

Allergen specific immunotherapy reduces the symptoms and drug requirements but has no consistent effect on lung function. The effects are greater in patients with allergen specific bronchial hyperreactivity than in those with non-specific hyperreactivity 26

Chemical and physical measures to reduce exposure to mites or their products at home seem to be ineffective 27

The number of systematic reviews and meta-analyses evaluating the treatment of asthma is increasing. Most of the reviews have clinical relevance but have methodological limitations that could have been avoided easily. Future reviews should include comprehensive and well reported search strategies, attempts to reduce bias during the selection of the studies, assessment of the validity of the studies, and clear description of the methods used to synthesise the data available. Few reviews address safety issues or the effect of treatment on quality of life, costs, or patient preferences.

This study also confirms that Cochrane reviews are more rigorous than reviews published in peer reviewed journals. 9 14 Several factors may explain the differences. Cochrane reviews follow standardised instructions, are peer reviewed at several levels, and receive input from different groups at different stages. 13 One limitation of our analyses is that the tool used for quality assessments was developed by Andrew Oxman, who led the development of the methodology of Cochrane reviews.

Perhaps peer reviewed journals could improve the quality of the systematic reviews they publish by providing authors and peer reviewers with clear reporting criteria, including those followed by Cochrane reviewers, 28 29 by influencing the review process at a much earlier stage, and by promoting more frequent updates or correction of published material on the internet. Authors should be particularly careful when doing reviews in association with industry, as such reviews have been shown to have an increased risk of producing results in favour of the interventions promoted by the sponsors. 12 This was the case for all but one of the reviews associated with industry in our study. The only review that did not favour an intervention was designed to evaluate the effects of vitamin C on asthma, not a new proprietary compound. 17

Bridging the gap between methodological research and methodological practice will require unprecedented efforts by researchers, consumers, funders, journal editors, and peer reviewers. Efforts made by members of the Cochrane Collaboration are already contributing to filling the gap and should be emulated by peer reviewed journals.

What is already known on this topic

Systematic reviews and meta-analyses could help decision makers cope with information overload

The number of systematic reviews and meta-analyses evaluating asthma treatments is increasing

What this study adds

Most reviews of asthma treatment published in peer reviewed journals or funded by industry have serious methodological flaws that limit their usefulness

Cochrane reviews are more rigorous and better reported than those published in peer reviewed journals

The clinically relevant messages from the 10 most rigorous reviews are summarised

Acknowledgments

We thank Ann Murray for editorial assistance. The review was coordinated by Foresight Consultants, a division of Foresight Links Corporation.

Contributors: ARJ (guarantor) initiated and designed the study, participated in data collection and analysis, wrote the first draft of the paper, collated comments from the other authors, and incorporated the comments of the peer reviewers into the final version. MM and GB provided input to the design of the study, contributed to the design of the data extraction forms, and commented on all the drafts of the paper. LB, MF, and RS provided input to the data extraction forms and extracted the data from the reviews. CS was responsible for data checking and the statistical analysis.

Funding Foresight Consultants was commissioned by AstraZeneca Research and Development Lund, Sweden, and AstraZeneca US to perform an independent review of this topic through an unrestricted contract. Representatives from AstraZeneca did not participate in the study selection or appraisal or in the analysis of the data. ARJ was supported in part by a National Health Research Scholar Award from Health Canada, Ottawa, Ontario.

Competing interests ARJ is codirector of the Canadian Cochrane Network and Centre.

website e xtra: Details of the search strategy and all included studies are available on the BMJ's website www.bmj.com

• Chalmers I ,
• Ioannidis JPA ,
• Bailar III JC ,
• Mosteller F
• Berrier J ,
• Reitman D ,
• Kupelnick B
• Assendelft WJJ ,
• Knipschild PG ,
• Klassen TP ,
• Tugwell P ,
• Barnes EC ,
• Davey Smith G ,
• Schneider M ,
• Berlin JA ,
• for the University of Pennsylvania Meta-analysis Blinding Study Group
• Bielory L ,
• Keller JL ,
• Osmond MH ,
• Turner MO ,
• Ginsburg S ,
• FitzGerald JM
• Cochrane Collaboration
• Gibson PG ,
• Coughlan J ,
• Wilson AJ ,
• Hensley MJ ,
• Abramson M ,
• Plotnick LH ,
• Ducharme FM
• Spooner CH ,
• Ducharme FM ,
• Bretzlaff JA ,
• Saunders LD ,
• Abramson MJ ,
• Hammerquist C ,
• Gotzsche PC
• Eastwood S ,
• Stroup DF ,
• for the QUOROM Group

Asthma education

Affiliation.

• 1 Department of Respiratory and Sleep Medicine, Hunter Medical Research Institute, John Hunter Hospital, University of Newcastle, Locked Bag 1, Hunter Region Mail Centre, NSW 2310, Australia. [email protected]
• PMID: 14509558
• DOI: 10.1016/s0954-6111(03)00134-3

Education about asthma and self-management of asthma are now key recommendations of asthma management guidelines. A Cochrane systematic review of 12 RCTs found that limited education programmes that offer information about asthma but not self-management skills did not reduce hospitalisation rates or visits to the doctor for asthma. The positive outcomes from limited asthma education were a reduction in symptoms. Asthma self-management education which consists of information, self-monitoring, regular medical review, and a written action plan is effective and leads to a reduction in hospitalisation and ER visits for asthma, unscheduled doctors visits, days lost from work, episodes of nocturnal asthma, indirect costs and an improvement in quality of life. The effects were large enough to be of both clinical and statistical significance. While a structured asthma self-management programme is effective in a hospital setting, attempts to deliver these programmes in primary care have met with varying success.

Publication types

• Research Support, Non-U.S. Gov't
• Asthma / therapy*
• Clinical Trials as Topic
• Patient Compliance
• Patient Education as Topic / methods*
• Primary Health Care
• Teaching Materials

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Open Access

Study Protocol

Pathophysiology of non-cystic fibrosis bronchiectasis in children and adolescents with asthma: A protocol for systematic review and meta-analysis

Contributed equally to this work with: Natali Caroline da Silva, Beatriz Cocato Malagutti, Joelia Maria Costa Dias Ladeira, Milena Baptistella Grotta, Adyleia Aparecida Dalbo Contrera Toro

Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Postgraduate Program in Child and Adolescent Health of the School of Medical Sciences (FCM), State University of Campinas (UNICAMP), Campinas, São Paulo, Brazil

Affiliation Medical School, Pontifical Catholic University of Campinas, Campinas, São Paulo, Brazil

Affiliation Center of Integration in Pediatrics (CIPED) of the School of Medical Sciences (FCM), State University of Campinas (UNICAMP), Campinas, São Paulo, Brazil

• Natali Caroline da Silva, 
• Beatriz Cocato Malagutti, 
• Joelia Maria Costa Dias Ladeira, 
• Milena Baptistella Grotta, 
• Adyleia Aparecida Dalbo Contrera Toro

• Published: April 18, 2024
• https://doi.org/10.1371/journal.pone.0294921
• Reader Comments

The pathophysiological mechanisms by which asthma and bronchiectasis are associated are still unclear. The association of these two diseases can result in more severe symptoms and a greater number of exacerbations.

The aim of this systematic review is to collect evidence of the pathophysiology of non-cystic fibrosis bronchiectasis with associated asthma in children and adolescents, aged 6–18 years old.

A systematic and comprehensive search will be performed using eight main databases, PubMed, PubMed PMC, BVS/BIREME, Scopus, EMBASE, Cochrane Library, Scielo and Web of Science. Articles will be searched from the earliest available time to July 2023. The studied population will be composed of children and adolescents with asthma and non-cystic fibrosis bronchiectasis. From the data obtained, all articles found will be transferred to the Rayyan platform. Study selection will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols Checklist (PRISMA P-2015). In addition, if sufficient data are available, a meta-analysis will be conducted. Two independent reviewers will conduct the studies selection, data extraction, and risk of bias assessment. The outcome measures will be to analyze if non-cystic fibrosis bronchiectasis is related to a specific inflammatory profile.

A systematic review will provide better knowledge about the etiopathogenesis and causes of the association between asthma and bronchiectasis and its role in the severity and control of asthma. Identifying, selecting and critically evaluating studies on asthma and bronchiectasis, would be possible to illuminate the characteristics of children and adolescents with associated diagnoses and provide information to help individualized treatments in order to control and prevent complications. The findings of this study will be published in a peer-reviewed journal.

Systematic review registration

The systematic review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) in July 2023 (registration number CRD42023440355).

Citation: da Silva NC, Malagutti BC, Ladeira JMCD, Grotta MB, Toro AADC (2024) Pathophysiology of non-cystic fibrosis bronchiectasis in children and adolescents with asthma: A protocol for systematic review and meta-analysis. PLoS ONE 19(4): e0294921. https://doi.org/10.1371/journal.pone.0294921

Editor: Pisirai Ndarukwa, Bindura University of Science Education, SOUTH AFRICA

Received: August 23, 2023; Accepted: November 12, 2023; Published: April 18, 2024

Copyright: © 2024 da Silva et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: No datasets were generated or analysed during the current study. All relevant data from this study will be made available upon study completion.

Funding: This study was financed in part by the Coordination for the Improvement of Higher Education Personnel – Brazil (CAPES) - Finance Code 001.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

1.1. rationale.

The Global Initiative for Asthma (GINA) define asthma as “a heterogeneous disease characterized by chronic airway inflammation,” affecting 1–29% of the population worldwide [ 1 ]. In recent years, there has been evidence of an association between asthma and other diseases, including bronchiectasis [ 2 , 3 ].

Bronchiectasis is a chronic lung disease defined by an irreversible widening of the bronchial tree, usually characterized by a vicious cycle of infection and inflammation, leading to structural damage of the small airways and, eventually, of its surrounding parenchyma [ 4 , 5 ]. In the literature, bronchiectasis is divided into those caused by cystic fibrosis and those not associated with cystic fibrosis (non-cystic fibrosis bronchiectasis) [ 6 ].

The major goal for asthma control, especially in cases of severe asthma, would be identify and manage its comorbidities and that the lack of this identification would be the responsible of therapy failures and for the worsening of symptoms [ 2 , 7 , 8 ].

Asthma would be identified as one of the causes of bronchiectasis, due to its prevalence in the disease, both atopic and non-atopic, in the pediatric population [ 2 , 3 ]. However, the pathophysiological mechanisms by which the two diseases are associated are still unclear [ 9 ].

It is believed that non-cystic fibrosis bronchiectasis in children is caused by repeatedly episodes of external agents associated with genetic vulnerability, however, the other possible etiologies are poorly defined, with heterogeneous risk factors [ 4 , 10 ]. Diagnosis consists of evaluating the patient’s clinical condition and the results of computed tomography, but it is possible to observe that children with bronchiectasis also develop similar symptoms to asthma, which can be easily confused [ 4 , 11 – 14 ].

The association of these two diseases can result in more severe symptoms and a greater number of exacerbations [ 13 , 14 ], therefore, this systematic review is justified because we believe that by identifying, selecting and critically evaluating studies on asthma and bronchiectasis, would be possible to enlighten the characteristics of children and adolescents with associated diagnoses and provide information to help individualized treatments in order to control and prevent complications.

1.2. Objectives

The aim of this systematic review is to collect evidence that supports that non-cystic fibrosis bronchiectasis diagnosed in children and adolescents is associated with control and severity of asthma and worsening lung function. To this end, the proposed systematic review will look to answer the following questions:

• Do children and adolescents with associated asthma and non-cystic fibrosis bronchiectasis show a worse lung function profile evidenced by pulmonary function tests?
• Does the presence of both non-cystic fibrosis bronchiectasis and asthma, in children and adolescents, results in worse asthma control and severity?
• Is non-cystic fibrosis bronchiectasis, in asthmatic children and adolescents, related to a specific inflammatory profile?

2.1. Eligibility criteria

Study selection will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols Checklist (PRISMA P-2015) ( S1 Checklist ).

2.1.1. Study designs.

We will include observational studies (including cohort, case-control and cross-sectional studies). Will be excluded letters to editor, case reports, editorials and narrative reviews. Table 1 shows the inclusion and exclusion criteria that will be used in the study screening, first by title and abstract and then by full text. The study population must be composed of children and/or adolescents with asthma with associated non-cystic fibrosis bronchiectasis.

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https://doi.org/10.1371/journal.pone.0294921.t001

2.1.2. Participants.

We will include children and adolescents aged 6 to 18 years old, diagnosed with asthma with associated non-cystic fibrosis bronchiectasis, irrespective of gender and ethnicity. All participants must be diagnosed with asthma using clearly defined or internationally recognized criteria and have non-cystic fibrosis bronchiectasis confirmed by computed tomography. Participants with cystic fibrosis and ciliary dyskinesia as the cause of bronchiectasis will not be included.

2.1.3. Interventions.

Studies to be examined will include any article with children and adolescents with asthma and associated non-cystic fibrosis bronchiectasis. Those articles reporting asthma control, asthma severity, inflammation pattern and pulmonary function will be considered.

2.1.4. Comparators.

Given the broad perspective for interventions of interest, comparisons will include the data from groups with no bronchiectasis. It is more likely to appear in experimental studies if they match the inclusion criteria for the review. Comparisons between asthma and non-cystic fibrosis group and asthma without bronchiectasis group may include:

• Asthma severity
• Asthma control
• Pulmonary function
• Inflammation pattern

2.1.5. Outcomes.

Outcomes will be collected individually as reported in the studies, including for those data reported as a composite measure. The outcomes must be reported through a validated tool, in accordance with its particularities.

2.1.6. Timing.

There will be no restrictions related to timing.

2.1.7. Setting.

There will be no restrictions by type of setting.

2.1.8. Language.

There will be no restrictions related to language.

2.2. Information sources

Literature search strategies will be developed using medical subject headings (MeSH) and text words related to asthma and non-cystic fibrosis bronchiectasis. We will search the following electronic bibliographic databases: PubMed, PubMed PMC, BVS-BIREME, EMBASE, COCHRANE, SCOOPUS, Web of Science and Scielo database with use of boolean operators AND and OR. The search did not utilize a year limit or filters.

2.3. Search strategy

This systematic review will use the following search strategy in all databases cited in 2.2: (Child OR Children) OR (Adolescent OR Adolescents OR Adolescence OR Teens OR Teen OR Teenagers OR Teenager OR Youth OR Youths OR "Adolescents, Female" OR "Adolescent, Female" OR "Female Adolescent" OR "Female Adolescents" OR "Adolescents, Male" OR "Adolescent, Male" OR "Male Adolescent" OR "Male Adolescents "") AND (Asthma OR Asthmas OR "Bronchial Asthma" OR "Asthma, Bronchial") AND (Bronchiectasis OR Bronchiectases OR "Saccular Bronchiectasis" OR "Bronchiectasis, Saccular" OR "Saccular Bronchiectases" OR "Cylindrical Bronchiectasis" OR "Bronchiectasis, Cylindrical" OR "Cylindrical Bronchiectases" OR "Varicose Bronchiectasis" OR "Bronchiectasis, Varicose" OR "Varicose Bronchiectases"). ( S1 Appendix )

2.4. Study records

2.4.1. data management..

The selected literature will be managed using Rayyan, a free web and mobile app for systematic review developed by Qatar Computing Research Institute (QCPI) [ 15 ]. Once in Rayyan, duplicate articles will be excluded when identified. Full-text reports will be screen after qualified studies been selected by title and abstract. If necessary, we will provide training to new members of the review team not familiar with the Rayyan platform and the content area prior to the start of the review.

2.4.2. Selection process.

The screening will be performed at Rayyan platform, by two reviewers, who will extract the articles independently, first by title and abstract and then by full text. If any disagreement or inconsistency remains, a third investigator will be involved. After reading the full- text reports, it will be decided whether they meet or not the inclusion criteria.

2.4.3. Data collection process.

We will extract data independently and in pairs from each eligible study. A calibration exercises before starting the review will be conducted to ensure consistency across reviewers. Data abstracted will include demographic information, methodology, intervention details, and all reported patient-important outcomes. Reviewers will resolve disagreements by discussion. In case of incomplete data, the original author will be contacted and if data cannot be obtained, the study will be excluded.

2.5 Data items

The following data will be extracted: study characteristics, type and source of financial support, author names, year of publication, patient characteristics (such as age, gender, symptoms, comorbidities, weight, and height), blood inflammatory biomarkers, pulmonary function tests scores, asthma questionnaires scores, computerized tomography results and other data judge by team as needed for quality assessment and outcomes.

2.6. Outcomes and prioritization

The primary outcome:

Non-cystic fibrosis bronchiectasis is related to asthma control. Since severity and control are assessed in asthma by multiple tools, all of them will be considered and evaluated.

The secondary outcomes:

• Non-cystic fibrosis bronchiectasis, in children and adolescents with associated asthma, is related to asthma severity.
• Non-cystic fibrosis bronchiectasis is related to worse pulmonary function in children and adolescents with associated asthma (assessed by spirometry values).
• Children and adolescents with asthma and non-cystic fibrosis bronchiectasis show a specific inflammatory profile. (assessed by IgE, prick test, serum and sputum inflammatory profile or bronchoalveolar lavage).

2.7. Risk of bias in individual studies

The risk of bias for analytical cross-sectional studies and prevalence in cross-sectional studies will be assessed using the appropriate tool of the Joanna Briggs Institute (JBI) [ 16 ]. For the first one, the tool consists of eight questions that include the possibility of selection bias, measurement bias, and confounding bias.

For prevalence studies, The Critical Assessment Tool for Studies with Prevalence Data is composed of nine questions, which assess from the sample structure of the included study, how it was selected and calculated, to whether the study described in detail how the outcome was evaluated, whether it was evaluated standardized way and with a good response rate, among the study participants included in the prevalence systematic review.

The Newcastle-Ottawa Scale (NOS) [ 17 ] will be used for asses risk of bias in case-control and cohort studies, which assesses three study quality parameters: selection, comparability, and exposure assessment. It assigns a maximum score of four for selection, two for comparability, and three for exposure, for a maximum total score of nine. Studies with a total NOS score of five or more are considered to be of moderate to high quality, while those with a total NOS score of less than five are considered low-quality studies.

The quality of evidence for the clinical outcomes will be assessed according to the recommendations of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group [ 18 ].

2.8. Data synthesis

2.8.1. quantitative synthesis..

If studies are sufficiently homogeneous in terms of design and comparator, we will conduct meta-analyses using RevMan 5.4 software. according to the statistical guidelines referenced in the current version of the Cochrane Handbook for Systematic Reviews of Interventions. The Mantel-Haenszel method will be used for the fixed effect model if tests of heterogeneity are not significant. If statistical heterogeneity is observed (I2 > = 50% or P < 0.1) the random effects model will be chosen. If heterogeneity is substantial, we will not perform a meta-analysis; a narrative, qualitative summary will be done.

2.8.2. Measures of treatment effect.

• For dichotomous outcomes:

Dichotomous data (asthma control and asthma severity) will be reported as risk ratios (RRs) with 95% confidence intervals (CIs). Statistical significance will be set at P<0.05.

• For continuous outcomes:

Continuous outcomes will be analyzed using weighted mean differences (with 95% CI) or standardized mean differences (95% CI) if different measurement scales are used. Skewed data and non-quantitative data will be presented descriptively.

• Dealing with missing data

When there are missing data, we will attempt to contact the original authors of the study to obtain the relevant missing data. Important numerical data will be carefully evaluated. If missing data cannot be obtained, an imputation method will be used. We will use sensitivity analysis to assess the impact on the overall treatment effects of inclusion of trials which do not report an intention to treat analysis, have high rates of participant attrition, or with other missing data.

• Assessment of heterogeneity

Heterogeneity will be evaluated by the I 2 test. The value of I 2 ranges from 0% to 100%. with 0–% to 40% indicating no major heterogeneity, 40–% to 60% indicating moderate heterogeneity, 60–% to 90% indicating substantial heterogeneity, and >90% indicating considerable heterogeneity.

2.8.3 Additional analyses.

Subgroup analyses or sensitivity analyses will be used to explore sources of heterogeneity. If the results can be analyzed quantitatively a meta-regression prediction will be performed. Sensitivity analyses will considerer quality components and risk of bias previously appraised by specific tools.

Subgroup analyses will be based on the following:

• Patient characteristic (age, sex, body mass index)
• Step of treatment for asthma according to GINA

2.8.4. Narrative synthesis.

If quantitative synthesis is not appropriate, a systematic narrative synthesis will be provided with information presented in the text and tables to summarize and explain the characteristics and findings of the included studies. The narrative synthesis will explore the relationship and findings both within and between the included studies, in line with the guidance from the Centre for Reviews and Dissemination.

2.9. Meta-bias(es)

A funnel plot will be used to evaluate publication bias if more than 10 studies are included. RR from each study is plotted against their variance. Asymmetrical appearance of the plot indicates the presence of publication bias. Egger test will be used to test the asymmetry of the funnel plot.

2.10. Confidence in cumulative evidence

The quality of evidence will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. The evidence will be adjusted to 4 levels: high, moderate, low, or very low.

3. Discussion

Both asthma and non-cystic fibrosis bronchiectasis are chronical diseases affecting pediatric population, with great impact in their quality of life, in addition to economic and financial impact to their family and health system [ 12 – 14 , 19 ]. Its association, despite being described in literature, requires better comprehension about the pathophysiology involved. We hope that this systematic review will provide better knowledge about the pathophysiology and causes of the association between asthma and bronchiectasis and its role in the severity and control of asthma. It will be possible to open a new range in the understanding of the diseases, which may result in new research and better management of these diseases.

To achieve this goal, it is necessary to carefully evaluate and summarize the evidence published to date.

Supporting information

S1 checklist. prisma checklist / prisma-p 2015 checklist..

https://doi.org/10.1371/journal.pone.0294921.s001

S1 Appendix. Search strategy/Search strategy for PubMed, PubMed PMC, BVS-BIREME, EMBASE, COCHRANE, SCOOPUS, Web of Science and Scielo databases.

https://doi.org/10.1371/journal.pone.0294921.s002

Acknowledgments

Mrs. Ana Paula Oliveira. Universidade Estadual de Campinas, Campinas SP, Brazil.

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• 16. Joanna Briggs Institute (JBI) critical appraisal tools. Available from: https://jbi.global/critical-appraisal-tools .
• 18. The GRADE working group. Available from: https://www.gradeworkinggroup.org/ .

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A Systematic Review of Asthma Phenotypes Derived by Data-Driven Methods

Francisco cunha.

1 Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal; moc.liamg@79ahnucocsicnarf

Rita Amaral

2 Center for Health Technology and Services Research (CINTESIS), Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal; moc.liamg@otnicajat (T.J.); tp.pu.dem@odranreb (B.S.-P.); [email protected] (J.A.F.)

3 Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal

4 Department of Cardiovascular and Respiratory Sciences, Porto Health School, Polytechnic Institute of Porto, 4200-072 Porto, Portugal

5 Department of Women’s and Children’s Health, Paediatric Research, Uppsala University, 751-05 Uppsala, Sweden

Tiago Jacinto

Bernardo sousa-pinto.

6 Basic and Clinical Immunology Unit, Department of Pathology, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal

João A. Fonseca

7 Allergy Unit, CUF Porto Hospital and Institute, 4100-180 Porto, Portugal

Associated Data

Not applicable.

Classification of asthma phenotypes has a potentially relevant impact on the clinical management of the disease. Methods for statistical classification without a priori assumptions (data-driven approaches) may contribute to developing a better comprehension of trait heterogeneity in disease phenotyping. This study aimed to summarize and characterize asthma phenotypes derived by data-driven methods. We performed a systematic review using three scientific databases, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. We included studies reporting adult asthma phenotypes derived by data-driven methods using easily accessible variables in clinical practice. Two independent reviewers assessed studies. The methodological quality of included primary studies was assessed using the ROBINS-I tool. We retrieved 7446 results and included 68 studies of which 65% ( n = 44) used data from specialized centers and 53% ( n = 36) evaluated the consistency of phenotypes. The most frequent data-driven method was hierarchical cluster analysis ( n = 19). Three major asthma-related domains of easily measurable clinical variables used for phenotyping were identified: personal ( n = 49), functional ( n = 48) and clinical ( n = 47). The identified asthma phenotypes varied according to the sample’s characteristics, variables included in the model, and data availability. Overall, the most frequent phenotypes were related to atopy, gender, and severe disease. This review shows a large variability of asthma phenotypes derived from data-driven methods. Further research should include more population-based samples and assess longitudinal consistency of data-driven phenotypes.

1. Introduction

Asthma is one of the most common chronic diseases in the world and its prevalence is increasing due to the continuous expansion of western lifestyle and urbanization [ 1 ]. Asthma is a chronic inflammatory disease of the airways, characterized by at least partially reversible airway obstruction and bronchial hyper-responsiveness [ 1 , 2 ]. Global Initiative for Asthma (GINA) currently defines asthma as a heterogeneous disease, with a history of respiratory symptoms that vary over time and in intensity, together with variable expiratory airflow [ 2 ]. Taking into account that asthma is such a heterogeneous condition with complex pathophysiology, phenotypic classification is essential for the investigation of etiology and treatment tailoring [ 3 ].

Patients with asthma have been categorized into subgroups using theory- or data-driven approaches. In the classical theory-driven approach, patients with asthma are classified in categories defined a priori according to current knowledge (e.g., based on etiology, severity, and/or triggers) [ 4 ]. However, this approach generates asthma phenotypes that are not mutually exclusive, and the correlation with therapeutic response and prognosis might not be the most adequate [ 5 ].

On the other hand, the data-driven (or unsupervised) approach, which is unbiased by previous classification systems, often starts with a broad hypothesis and uses relevant data to generate a more specific and automatic hypothesis, providing an opportunity to better comprehend the complexity of chronic diseases [ 4 ]. Several classes of data-driven algorithms have been involved in tackling the issue of trait heterogeneity in disease phenotyping. The techniques most used to address phenotypic heterogeneity in health care data include distance-based (item-centered, e.g., clustering analysis) and model-based (patient-centered, e.g., latent class analysis) approaches, both of which are not mutually exclusive [ 6 ].

Distance-based approaches use the information on the distance between observations in a data set to generate natural groupings of cases [ 3 ]. The most commonly used clustering analysis methods are hierarchical, partitioning (k-means or k-medoids), and two-step clustering, which can be roughly described as a combination of the first two. Hierarchical clustering analysis functions by creating a hierarchy of groups that can be represented in a dendrogram, while the partitional methods divide the data into non-overlapping subsets that allow for the classification of each subject to exactly one group [ 3 ].

On the other hand, the most used model-based approaches, which use parametric probability distributions to define clusters instead of the distance/similarities between the observations [ 7 ], are latent class analysis (LCA), latent profile, and latent transition analysis.

Despite the existence of studies that identified clusters mainly coincident with other larger-scale cluster analyses [ 8 , 9 , 10 ], there is a lack of consistency of phenotypes and applied methods. Therefore, this systematic review aimed to summarize and characterize asthma phenotypes derived with data-driven methods in adults, using variables easily measurable in a clinical setting.

2. Materials and Methods

In this systematic review, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [ 11 ] and the Patient, Intervention, Comparison and Outcome (PICO) strategy [ 12 ] to improve the reporting of this systematic review.

2.1. Search Strategy

Primary studies were identified through electronic database search in PubMed, Scopus, and Web of Science (first search in August 2020; updated in March 2021). Broad medical subject headings (MeSH) and subheadings, or the equivalent, were used and search queries are presented in Table 1 .

List of queries used for searching online databases.

2.2. Study Selection

Studies were considered eligible when reporting asthma phenotypes determined by data-driven methods in adult patients (≥18 years old), exclusively using variables easily available in a clinical setting. We did not apply exclusion criteria based on language or publication date criteria. Studies using genotyping variables were excluded.

Two authors (F.C. and R.A.) independently screened all the identified studies by title and abstract, after excluding duplicates. Subsequently, potentially eligible studies were retrieved in full-text and assessed independently by two authors, who selected those that met the predefined inclusion and exclusion criteria. Disagreements in the selection process were solved by consensus. Non-English publications were translated if considered eligible.

Cohen’s kappa coefficient was calculated to evaluate the agreement between the two reviewers in the selection process.

2.3. Data Extraction

Two authors (F.C. and R.A.) were involved in data extraction. Study design, setting, inclusion criteria, patients’ characteristics, variables, and data-driven methods used for phenotyping, and the obtained phenotypes, were assessed for each study.

Variables were divided into eight domains for simplicity and practicality of analysis ( Table 2 ).

List of variables covered by each domain.

Body mass index (BMI), forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), carbon monoxide transfer coefficient (KCO), immunoglobulin E (IgE), fractional exhaled nitric oxide (FeNO), high-sensitivity C-reactive protein (hsCRP), intensive care unit (ICU), general practitioner (GP).

2.4. Quality Assessment

Two independent researchers (F.C. and R.A.) independently performed the assessment of the quality of the evidence using the ROBINS-I approach [ 13 ]. Based on the information reported in each study, the authors judged each domain as low, moderate, serious, or critical risk of bias. Any disagreement was solved by consensus. Quality assessment was summarized in a risk of bias table.

3.1. Study Selection

A total of 7446 studies were identified in the literature search, of which 2799 were duplicates. After screening all titles and abstracts, which resulted in the exclusion of 4472 records, 175 citations were determined to be potentially eligible for inclusion in our review. Subsequently, full-text assessment resulted in the exclusion of 107 studies in total, including 28 studies incorporating variables or phenotypes with limited applicability in a clinical setting or using phenotypes obtained in previous studies, and 17 studies without available full text. Unavailable references included meeting abstracts, conference papers, posters, and older studies from local publications with no traceable full text. In the end, 68 studies of data-driven asthma phenotypes studies were included. A flowchart for study selection is depicted in Figure 1 .

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram illustrating the studies’ selection process.

For the selection process, the Cohen’s kappa coefficient and the percentage of the agreement were calculated were determined to be 0.76 and 98%, respectively. These results indicate substantial agreement [ 14 ].

3.2. Study Characteristics

All the 68 studies [ 8 , 9 , 10 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 ] were published between 2008 and 2020 and recruited patients mostly from specialized centers ( n = 44, 65%). We identified seven population-based studies. The median sample size of all studies was 249 individuals (range 40–7930).

The included primary studies used a wide variety of methods for cluster analysis, with the most common method being hierarchical cluster analysis ( n = 19), followed by k-means cluster analysis ( n = 16) and two-step cluster analysis ( n = 14). Latent class analysis was the most used model-based approach ( n = 9) ( Figure 2 ).

Data-driven method chosen for asthma phenotyping ordered by absolute frequency of use.

It was not possible to retrieve the variables used in two studies [ 15 , 16 ]. The remaining 66 studies of our review were applied a wide range of variables in their respective analysis. Personal variables (e.g., age, gender, BMI, or smoking) were included in the analysis of 74% of the previously mentioned 66 studies. Variables belonging to the lung function, clinical, and atopy domains were all used in more than half of these studies. Figure 3 shows the percentage of studies that used each one of the represented domains of variables.

Proportion of each domain of variables in the 66 studies with retrievable chosen variables.

The characteristics of the 68 studies included in our review are summarized in Table 3 .

Characteristics of the included studies.

Not applicable (N.A.), inhaled corticosteroids (ICS), oral corticosteroids (OCS), long-acting β2 agonists (LABA), Global Initiative for Asthma (GINA), bronchial hyperreactivity (BHR), American Thoracic Society (ATS), forced expiratory volume in 1 s (FEV1), Asthma Quality of Life Questionnaire (AQLQ), forced vital capacity (FVC), World Health Organization (WHO), Spanish Guideline on the Management of Asthma (GEMA), chronic obstructive pulmonary disease (COPD).

3.3. Asthma Phenotypes

The number of phenotypes per study ranged from two to eight with a median of four, obtained in 23 studies (34%). A majority of studies (82%) identified between three and five phenotypes. The most frequent phenotypes in our analysis were atopic asthma, severe asthma, and female asthma with multiple variants.

We observed that 36 studies (53%) evaluated the consistency of phenotypes based on at least one of the following criteria: longitudinal stability, cluster repeatability, reproducibility, and/or validity.

A visual representation of the variables used for phenotyping by each study is portrayed in Table A1 ( Appendix A ). Studies with an assessment of consistency are highlighted.

Table 4 represents the defining variables of phenotypes obtained by each study. The full phenotypes are compiled in Table A2 ( Appendix A ). The results are stratified by a data-driven method, and the frequency of phenotypes in the sample is presented for each study.

Characterization of the phenotypes obtained in each study according to the defining variables (column), with each row within each study corresponding to one phenotype.

Studies are stratified by a data-driven method. Phenotypes are compiled in their full extent in Appendix A . Chronic obstructive pulmonary disease (COPD), body mass index (BMI), eosinophils (eos), forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), immunoglobulin E (IgE), corticosteroids (CS), inhaled corticosteroids (ICS), oral corticosteroids (OCS), long-acting β2 agonists (LABA), Asthma Quality of Life Questionnaire (AQLQ), exhaled nitric oxide (eNO), uric acid (UA), cholesterol (Chol.), bilirubin (Bili.), high-sensitivity C-reactive protein (hsCRP), bronchial hyperreactivity (BHR).

In hierarchical cluster analysis, the most frequent phenotypes were atopic/allergic asthma, mentioned 24 times in 13 studies, and late-onset asthma, mentioned 19 times in 12 studies. A common association with atopic asthma was the early age of onset, while late-onset asthma was recurrently linked with severe disease. Atopic asthma was also the most frequent phenotype in two-step cluster analysis. In both k-means and k-medoids cluster analysis, severe asthma occurred the most often.

In model-based methods, latent class analysis studies identified mostly phenotypes related to symptoms. Factor analysis used severity of disease to classify asthma, while latent transition analysis used allergic status and symptoms. One study derived longitudinal trajectories in terms of pulmonary function using latent mixture modeling.

3.4. Risk of Bias Assessment

We used the ROBINS-I tool to assess the risk of bias. The methodological quality of the studies was predominantly moderate ( n = 29). Of the 68 included studies, 18 were considered to be at overall low risk of bias, while other 18 studies were considered to be at serious risk of bias. Only three studies were judged to be at critical risk of bias. The results are portrayed in Table 5 .

Risk of bias assessment using ROBINS-I.

Caption: + = Low | 0 = Moderate | - = Serious | -- = Critical.

The studies included in our review were in accordance with most of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist items [ 80 ].

4. Discussion

4.1. main findings.

This systematic review revealed a high degree of variability regarding the data-driven methods and variables applied in the models among the studies that identified data-driven asthma phenotypes in adults. There was a lack of consistency in the studies concerning the study setting, target population, choice of statistical method and variables, and ultimately, the label of the phenotype. Overall, the most frequent phenotypes were related to atopy, gender (female), and severe disease.

Different statistical methodologies were applied among the included studies, with hierarchical and k-means clustering being the most common ones. The earliest study in this review (2008) applied a two-step clustering approach to two different sets of patients [ 33 ]. In the group of patients of the primary care setting, three phenotypes were determined, namely, “early-onset atopic asthma”, “obese, non-eosinophilic asthma”, and “benign asthma.” In the group of patients with refractory asthma managed in secondary care, four phenotypes were obtained “early onset atopic asthma”, “obese, non-eosinophilic asthma”, “early onset symptomatic asthma with minimal eosinophilic disease”, and “late-onset, eosinophilic asthma with few symptoms” [ 33 ]. These phenotypes persisted in later studies, with different variants [ 8 , 15 , 42 , 55 ].

Most of the studies recruited patients from specialized centers. However, we identified two population-based studies with a low risk of bias, both using model-based statistical techniques [ 20 , 25 ]. Amaral et al. identified different classes of allergic respiratory diseases using latent class analysis in a population of 728 adults. The study obtained seven phenotypes, which were distinguished according to allergic status and degree of probability of nasal, ocular, and bronchial symptoms [ 20 ]. Boudier et al. applied latent transition analysis with nine variables covering personal and phenotypic characteristics on longitudinal data of 3320 adult asthmatics, determining seven phenotypes characterized by the level of asthma symptoms, the allergic status, and pulmonary function. These results revealed strong longitudinal stability [ 25 ].

There were four population-based studies with some identifiable validation process. Amaral et al. derived phenotypes independently for two age groups and found similar proportions in both age groups for the two obtained data-driven subtypes (“highly symptomatic with poor lung function”, and “less symptomatic with better lung function”), and for previously defined hypothesis-driven subtypes. However, the set of variables was suboptimal to differentiate asthma subgroups [ 19 ]. Makikyro et al. applied latent class analysis to identify four asthma subtypes in women and three subtypes in men. Phenotypes were classified according to the control and severity of the disease. The subsequent addition of a set of covariates verified the accuracy of results [ 50 ].

An improvement of the characterization of asthma heterogeneity is an essential step in the development of more personalized approaches to asthma management and therapy. There is a need for further research to produce population-based studies with analysis of the longitudinal consistency of data-driven phenotypes. Ilmarinen et al. performed clustering on longitudinal data of Finnish patients with adult-onset asthma. Their approach with 15 variables resulted in the determination of five phenotypes with longitudinal stability, namely “nonrhinitic asthma”, “smoking asthma”, “female asthma”, “obesity-related asthma”, and “early onset atopic adult asthma” [ 35 ]. Furthermore, Khusial et al. identified a set of five phenotypes with longitudinal stability in a primary care cohort of adult asthmatics: “smokers”, “late-onset female asthma”, “early atopic asthma”, “reversible asthma” and “exacerbators” [ 39 ]. Certain similarities with the results of the study by Ilmarinen et al. are identifiable.

Hsiao et al. found a higher risk of asthma exacerbations in current smoker and ex-smoker clusters in males, as well as in atopy and obesity clusters in females [ 34 ]. Park et al. observed an association between smoking males and reduced lung function [ 57 ].

The most used dimensions were variables regarding personal, clinical, and functional data. However, other dimensions were used in several studies. For example, Lefaudeux et al. demonstrated that clustering based on clinicophysiologic parameters can produce stable and reproducible clusters [ 48 ]. Deccache et al. aimed to characterize treatment adherence with a multidimensional approach encompassing asthma control, attitude towards the disease, and compliance with treatment [ 29 ]. Finally, Labor et al. aimed to assess the association of specific asthma phenotypes with mood disorders—five phenotypes were identified by cluster analysis of cross-sectional data in a sample of adult patients of a tertiary center: “allergic asthma”, “aspirin-exacerbated respiratory disease”, “late-onset asthma”, “obesity-associated asthma”, and “infection-associated asthma” [ 46 ].

An ongoing investigation is being conducted to identify novel targets and biomarkers for a better understanding of the pathophysiology of asthma. Eventually, the broader availability of emerging molecular and genetic tools may complement the traditional clinical variables in the determination of asthma phenotypes [ 81 ].

4.2. Strengths and Limitations

We should note that this study has limitations. In an attempt to assemble a complete overview of data-driven asthma phenotyping, some of the included studies focused on specific contexts, which hampered their external validity. Another limitation concerns the possibility of selection bias, as the definition of asthma varied across the studies (questionnaire-based and/or functional-based). This may possibly have implications on selection bias for participant selection and information bias if there are wrong classification and assessment of participants. Other important limitations concern the low quality of most included studies since, of the 68 included studies, 32 did not attempt to assess the consistency of results, and only 18 were considered to be at low risk of bias. Moreover, the association between the obtained phenotypes and the clinical outcomes was out of the study’s scope and should be further explored.

To our knowledge, this is the first systematic review that summarized data-driven asthma phenotypes, based on easily accessible variables, in adults. Unsupervised methods have emerged as a novel tool in adult asthma phenotyping, with the advantage of being free from a priori biases; this study provides an overview of the current state in the field, which may be useful to clinical practitioners and researchers, particularly in the understanding of the heterogeneity of asthma. The main strength of this review is the exhaustive compilation of asthma phenotypes with a detailed description of the data-driven methods used ( Appendix A ). Additionally, our study included an extensive literature search by applying no language or date restrictions and performing risk of bias assessment by ROBINS-I tool. The high number of included publications proves the existence of a need to classify asthma patients using data-driven methods due to the limitations of classical theory-driven approaches.

In conclusion, data-driven methods are increasingly used to derive asthma phenotypes; however, the high heterogeneity and multidimensionality found in this study suggest that both clinic and statistical expertise are required. Further research should focus on population-based samples and evaluation of longitudinal consistency of phenotypes.

Table A1 displays the variable domains used for phenotyping by each study. Studies with an assessment of phenotype consistency are highlighted.

Representation of variables used by each study, stratified by a data-driven method. Studies with an evaluation of phenotype consistency are marked. Variables are presented in the form of domains: personal (P), functional (F), clinical (C), atopy (A), inflammatory (I), medication (M), health care use (H), and behavioral (B).

Table A2 summarizes the phenotypes obtained by each study with the respective frequency in the sample. The results are stratified by a data-driven method.

Asthma phenotypes in adult patients were derived by data-driven methods in the included studies and stratified by the data-driven method applied. The percentage of subjects that belong to each phenotype is presented when available.

General practitioner (GP), inhaled corticosteroids (ICS), long-acting beta-agonists (LABA), chronic obstructive pulmonary disease (COPD), forced expiratory volume in 1 s (FEV1), body mass index (BMI), immunoglobulin E (IgE), exhaled nitric oxide (eNO), bronchial hyperreactivity (BHR), oral corticosteroids (OCS), uric acid (UA), aspartate aminotransferase (AST), alanine aminotransferase (ALT), high-sensitivity C-reactive protein (hsCRP), blood eosinophil (eos), Asthma Quality of Life Questionnaire (AQLQ), nasal polyps and comorbid asthma (NPcA), forced vital capacity (FVC).

Author Contributions

Conceptualization, R.A., T.J. and J.A.F.; methodology, F.C., T.J., B.S.-P. and R.A.; software, F.C. and R.A.; validation, F.C. and R.A.; formal analysis, F.C. and R.A.; investigation, F.C. and R.A.; resources, R.A., J.A.F., B.S.-P.; data curation, F.C.; writing—original draft preparation, F.C. and R.A.; writing—review and editing, F.C. and R.A.; visualization, F.C. and R.A.; supervision, R.A.; project administration, R.A. and J.A.F.; funding acquisition, not applicable. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

• Open access
• Published: 15 April 2024

Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis

• Hamidreza Amiri 1   na1 ,
• Samira Peiravi 2   na1 ,
• Seyedeh sara rezazadeh shojaee 3   na1 ,
• Motahareh Rouhparvarzamin 4 ,
• Mohammad Naser Nateghi 5 ,
• Mohammad Hossein Etemadi 6 ,
• Mahdie ShojaeiBaghini 7 ,
• Farhan Musaie 8 ,
• Mohammad Hossein Anvari 9 &
• Mahsa Asadi Anar 10  

BMC Medical Education volume  24 , Article number:  412 ( 2024 ) Cite this article

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Nowadays, Artificial intelligence (AI) is one of the most popular topics that can be integrated into healthcare activities. Currently, AI is used in specialized fields such as radiology, pathology, and ophthalmology. Despite the advantages of AI, the fear of human labor being replaced by this technology makes some students reluctant to choose specific fields. This meta-analysis aims to investigate the knowledge and attitude of medical, dental, and nursing students and experts in this field about AI and its application.

This study was designed based on PRISMA guidelines. PubMed, Scopus, and Google Scholar databases were searched with relevant keywords. After study selection according to inclusion criteria, data of knowledge and attitude were extracted for meta-analysis.

Twenty-two studies included 8491 participants were included in this meta-analysis. The pooled analysis revealed a proportion of 0.44 (95%CI = [0.34, 0.54], P  < 0.01, I2 = 98.95%) for knowledge. Moreover, the proportion of attitude was 0.65 (95%CI = [0.55, 0.75], P  < 0.01, I2 = 99.47%). The studies did not show any publication bias with a symmetrical funnel plot.

Average levels of knowledge indicate the necessity of including relevant educational programs in the student’s academic curriculum. The positive attitude of students promises the acceptance of AI technology. However, dealing with ethics education in AI and the aspects of human-AI cooperation are discussed. Future longitudinal studies could follow students to provide more data to guide how AI can be incorporated into education.

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Introduction

The term "artificial intelligence (AI)" was coined nearly 70 years ago to refer to using of computers to imitate human reasoning [ 1 ]. The first application of AI was in mathematics in 1956 when it was utilized for proving theorems [ 2 ]. Integrating of AI in medicine was a gradual process [ 3 ] that began with the development of a software program that guided doctors on appropriate antimicrobial therapy [ 4 ].

AI is a trending topic that is currently at the forefront of technological advancements [ 5 ] and has the potential to influence the healthcare industry significantly [ 6 ]. The term AI refers to a scientific and engineering discipline that deals with developing computer-based systems capable of exhibiting intelligent behavior, as well as understanding and replicating human-like cognitive processes [ 7 ]. Recent advancements in computer and informatics technologies have paved the way for integrating of AI technologies, such as machine learning and deep learning, into healthcare information systems [ 8 , 9 ]. AI has been extensively integrated into decision support systems (DSSs) in data-intensive medical specialties like radiology, pathology, and ophthalmology [ 10 ].

Several experts have expressed their opinions on the future of radiology in light of AI's emergence [ 11 , 12 ]. Radiological societies have also published white papers promoting their views [ 13 , 14 ]. Studies have indicated that medical students do not express significant concern or fear about being replaced by AI in their profession [ 15 ]. However, some students may experience anxiety related to the possibility of being displaced by AI, which may discourage them from considering certain medical specialties [ 16 ]. Indeed, there are positive and negative perspectives on the impact of AI on daily human life. Pessimistic views suggest that AI may replace humans in various sectors. On the other hand, optimistic views highlight that individuals with AI support will have increased opportunities to leverage future advancements [ 17 ]. To the best of our knowledge, this study aimed to evaluate the attitudes, knowledge, and skills of medical, dental, and nursing students toward AI and to gather information about their opinions on the use of AI.

This systematic review and meta-analysis study was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. The protocol of this study was registered on PROSPERO with the ID of CRD42024521006.

Literature search

A structured literature search was applied up to 12th September 2023 to collect appropriate articles from PubMed /MEDLINE, Scopus, and Google Scholar databases. Search tactics included two main subgroups of keywords. One subgroup was the concepts related to artificial intelligence, and the other group was the perspective of health care and dentists; then, Subgroups were mixed by using ‘AND.’ More specifically, we searched the above databases for (artificial intelligence or machine learning) and (Medical or dentistry or nursing) (Table  1 ). The search process was done according to the query options of each database. In addition, we searched the reference lists of appropriate systematic reviews to prevent missing data. Two reviewers accomplished all strategies in a solitary state, and any controversy between the reviewers was resolved by negotiation.

Criteria for selecting studies

The main goal was to evaluate the attitudes of students and graduates working in dentistry, nursing, or medical (health care providers) fields toward AI and machine learning. We didn't use any restrictions on date and language, but to make the search more specific, we restricted the keyword search to the title. Articles with irrelevant subject matter and studies utilizing animal models were excluded during the initial phase of document selection. Additionally, duplicate documents were eliminated.

Data extraction and study quality assessment

Two reviewers independently assessed the title and abstract of each study to ascertain its suitability for inclusion in this meta-analysis. We excluded studies that didn’t fulfill our criteria. The complete text of the remaining studies was reviewed, and studies that met the criteria were included in the data extraction step. After that, the subsequent items were acquired for extraction and divided into four sets:

1. Study characteristics include authors, type of study, year, location, and follow-up duration.

2. Participant variables (average age, gender).

3. Research Methodology (e.g., participant sample size).

4. Results and outcomes (the attitude, knowledge, and skill toward artificial intelligence).

Two previously mentioned reviewers utilized the critical appraisal checklists for cohort, case–control, and analytical cross-sectional studies created by the Joanna Briggs Institute (JBI). The checklists can be found at the following website: https://jbi.global/critical-appraisal-tools . If there were any inconsistencies, a third author was involved in the process.

Statistical analysis

Our data analysis was conducted using the STATA 13.1 software developed by StataCorp LP in College Station, TX, USA. The findings were presented as combined odds ratios (ORs) and a 95% confidence interval displayed in a forest plot. Heterogeneity among the eligible studies was assessed using the I2 statistic. The random effects model was employed when significant heterogeneity was observed (I2 > 50%). In addition, we performed a sensitivity analysis by systematically excluding one study at a time and repeating the meta-analysis. This allowed us to guarantee the consistency of our conclusions. To assess the possibility of publication bias, we visually examined the symmetry of the funnel plot and conducted Egger’s regression analysis.

Search strategy

We obtained 2426 from PubMed/MEDLINE, Scopus, and Google Scholar in the initial search. Seventeen studies were found by manual search. After the automatic removal of duplicated reports, 2292 studies remained. Two thousand sixty-five studies were excluded in the title and abstract evaluation. Two hundred twenty-seven remaining studies underwent additional assessment through full-text, causing 205 papers to be excluded due to ineligibility to inclusion criteria. Finally, 22 studies were included in this systematic review and meta-analysis (Fig.  1 ).

Prisma diagram for study selection process in this study

Baseline characteristic

This systematic review and meta-analysis evaluated the attitude, knowledge, and skills of medical, dental, and nursing students toward artificial intelligence. We included 22 original articles published from 2020–2023. These studies were performed in several countries, including the U.S.A [ 18 ], Germany [ 19 , 20 ], Lebanon [ 21 ], Pakistan [ 22 ], Canada [ 23 ], The U.K. [ 24 ], United Arab Emirates [ 25 ], Nigeria [ 26 ], Turkey [ 27 , 28 ], Spain [ 29 ] Saudi Arabia [ 30 ], India [ 31 , 32 , 33 ], Egypt [ 34 ], Peru [ 35 ], Nepal [ 36 ], Kuwait [ 37 ], Syria [ 38 ], and multiple countries [ 39 ]. The study design of 19 studies was cross-sectional [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 ], and the rest followed a mixed methodology [ 18 , 19 , 39 ]. This study included 8491 participants, with a mean age of 19–30 years (Table  2 ).

We performed a meta-analysis on 22 studies for attitude of students toward AI. The proportion for attitude was 0.65 (95%CI = [0.55, 0.75], P  < 0.01) according to 22 studies. This means that 65% of all students were agree with the use of AI in medicine and had a favorable view. Similarly, the heterogeneity was severe with I2 of 99.47%, and H2 = 189.47 (Fig.  2 ).

Forest plot of proportion of attitude showed a significant effect of 0.44 (0.34, 0.54)

In comparison between various countries, students in the U.S.A. Kuwait, Saudi Arabia, Turkey, and England showed a higher rate of attitude toward AI than those in Germany, Lebanon, Nigeria, Pakistan, and India. Additionally, the Attitudes of Spanish and United Arab Emirates students varied in different studies. Finally, students in Canada and Egypt displayed a medium rate of positive attitude (Fig.  3 ).

Forest plot for comparing countries in terms of their students' attitudes toward AI

A total of 17 studies had provided the knowledge data. The pooled analysis showed a proportion for knowledge of 0.44 (95%CI = [0.34, 0.54], P  < 0.01). This shows that 44% of the total population of included students had a relatively good knowledge about AI, either in the field of theory or practical. The studies showed a high heterogeneity with an I2 of 98.95% and H2 of 93.35 (Fig.  4 ).

Forest plot of proportion of knowledge showed a significant effect of 0.65 (0.55, 0.75)

Students from Germany, Lebanon, Kuwait, and Pakistan had higher levels of knowledge in the field of AI. In contrast, students from the U.S.A., Nigeria, the United Arab Emirates, and England showed a relatively lower knowledge level. Additionally, the level of knowledge in Indian students varied across different studies. Finally, students from Egypt, Saudi Arabia, and Turkey showed moderate knowledge (Fig.  5 ).

Forest plot for comparing countries in terms of their students' knowledge of AI

Publication bias

The publication bias was evaluated through the funnel plot and Egger’s test. The funnel plot (Fig.  6 ) showed a symmetrical pattern, indicating no publication bias. This was supported by Egger’s test result ( P  = 0.75).

Funnel plot of included studies showed a symmetrical pattern including no publication bias (Egger’s test P -value = 0.75)

This systematic review and meta-analysis aimed to provide evidence on medical, dental, and nursing students’ attitudes, knowledge, and skills regarding AI. Across 24 studies with 5789 participants, students demonstrated moderate knowledge but generally positive attitudes towards AI.

Overall, 44% of students exhibited medium to high knowledge of AI principles and applications. Knowledge encompassed theoretical understanding of AI algorithms, practical abilities to implement AI systems, and programming proficiency. However, the majority of students had limited AI knowledge. This knowledge gap signals an urgent need to incorporate comprehensive AI education into healthcare curricula. Studies show that students support this idea [ 40 , 41 ]. Curricula should cover foundational concepts like machine learning and neural networks as well as applied skills in utilizing AI tools for tasks like diagnostic imaging interpretation. Hands-on experiential learning with real-world case examples could prove highly effective. Other reason is that lack of knowledge is an important barrier to the use of AI [ 42 ]. Notably, students from developed countries demonstrated greater AI knowledge than peers in developing nations. This has been shown in previous studies as well [ 43 ]. This discrepancy highlights concerning global digital divides in accessing AI skills training. Targeted investments and capacity building programs are critical to ensuring students worldwide can gain applied AI competencies.

In contrast to their variable knowledge, 65% of students expressed positive attitudes regarding AI utilization in education and clinical practice. This was also showed in previous studies that most of healthcare students have a positive attitude towards AI [ 19 , 44 , 45 , 46 , 47 ]. Students recognized potential benefits of AI for enhancing diagnostic accuracy, improving healthcare access, and relieving clinical workloads. In contrast there are negative perceptions too [ 44 , 48 , 49 ].

Attitudinal measures had substantial heterogeneity, reflecting divergent perceptions across student subgroups. In particular, developing world students held more skeptical views, fearing AI could dehumanize care or render healthcare jobs obsolete. Curricula must address these valid ethical and social concerns through discussions of AI bias, transparency, and impacts on healthcare roles. It should be noted that patient privacy and autonomy, informed consent, transparency, equality and biases are some of major concerns [ 50 ]. Refining attitudinal measures with more granular subsets and exploring predictors of AI acceptance would further inform targeted educational initiatives based on students’ specific concerns.

Enthusiasm and optimism vs. expertise gaps

Overall students showed enthusiasm and optimism about AI's role in medicine, yet the majority lacked substantial expertise and practical abilities in utilizing AI technology. A similar pattern exists in other majors too. A study by Busch et al. involving 387 pharmacy students from 12 countries found that 58% of students held positive attitudes towards AI in medicine, while 63% reported limited general knowledge of AI [ 51 ]. Bridging these attitude-knowledge gaps represents a key challenge for AI readiness. Curricula must not only transfer technical knowledge but also address values, ethics, and societal impacts. Education should emphasize AI as a collaborative tool to augment human capabilities rather than replace them. Again, having students directly experience AI’s benefits for care quality could show its potential for enhancing work rather than displacing workers. Additionally, equitable access to AI upskilling is imperative, particularly for students from disadvantaged regions who may have heightened concerns about AI’s risks.

Strength and limitations

The strength of our study is the review of articles from three large databases, including PubMed, Scopus, and Google Scholar. Also, we used the random effect model to ensure the robustness of the results. Also, our study had some limitations. We included only studies in English. In addition, most of the included studies used their own questionnaires to evaluate the knowledge and approach of the participants toward artificial intelligence. Finally, it is necessary to mention that there were not enough studies to extract the skill results and perform a meta-analysis.

Future research directions

Future research should investigate the long-term knowledge and attitudinal trajectories of students after graduation. As AI becomes further embedded into real-world practice, how do provider perspectives evolve? Do knowledge gaps persist or does on-the-job exposure improve understanding? How do early attitudinal concerns translate to technology adoption patterns? Longitudinal data tracking cohorts of students into practice could provide pivotal insights to guide continuing education and change management interventions.

Follow-up studies should also assess the durability of AI skills training. Can one-time education produce lasting competencies or is ongoing reinforcement needed? Comparisons of different pedagogical approaches for AI instruction could illuminate best practices as well. And crucially, future work must evaluate links from AI education to concrete improvements in clinical processes and patient outcomes. Demonstrating benefits to care quality represents the strongest incentive for curriculum reform.

AI is rapidly transforming healthcare and medical education. However, the extent to which healthcare students are prepared for this transformation remains unclear. The moderate knowledge levels indicate substantial room for improvement through curricular enhancement. Hands-on experiential learning focused on applied AI skills shows promise for durably improving competencies. Positive baseline attitudes bode well for acceptance, but targeted education around AI ethics, impacts, and human-AI collaboration will be key to realizing this potential.

Important gaps remain in understanding long-term knowledge retention, optimal pedagogies, impacts of improved education on clinical processes and outcomes, and equitable global access. Follow-up longitudinal studies tracking cohorts of students into practice could offer pivotal data to guide continuing education. Comparisons of instructional approaches may illuminate best practices.

Availability of data and materials

The datasets generated and analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Abbreviations

• Artificial intelligence

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Acknowledgements

We appreciate all the authors of included studies.

Author information

Hamidreza Amiri, Samira Peiravi and Seyedeh sara rezazadeh shojaee contributed equally to this work.

Authors and Affiliations

Student Research Committee, Arak University of Medical Sciences, Arak, Iran

Hamidreza Amiri

Department of Emergency Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

Samira Peiravi

Department of Nursing, Faculty of Nursing and Midwifery, Mashhad Medical Sciences, Islamic Azad University, Mashhad, Iran

Seyedeh sara rezazadeh shojaee

Student Research Committee, School of Nursing and Midwifery, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Motahareh Rouhparvarzamin

Student Research Committee, Faculty of Nursing and Midwifery, Mashhad University of Medical Sciences, Mashhad, Iran

Mohammad Naser Nateghi

Students Research Committee, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

Mohammad Hossein Etemadi

Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

Mahdie ShojaeiBaghini

Dentistry Student, Dental Branch, Islamic Azad University, Tehran, Iran

Farhan Musaie

Master of Health Science, Faculty of Health Sciences, Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur, Malaysia

Mohammad Hossein Anvari

Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, SBUMS, Arabi Ave, Daneshjoo Blvd, Velenjak, Tehran, 19839-63113, Iran

Mahsa Asadi Anar

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Study design and conception: M.AA; Search & study selection: H.A, S.P; Data extraction: SS.RS, M.P; Quality assessment: MN.N, MH.E; Statistical analysis and interpretation: M.S, F.M; Drafting the manuscript: H.A, S.P, SS.RS, M.P, MN.N, MH.E, M.S, F.M, MH.A; Critical revision: M.AA. All authors were approved the submitted version.

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Correspondence to Mahsa Asadi Anar .

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Amiri, H., Peiravi, S., rezazadeh shojaee, S. et al. Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis. BMC Med Educ 24 , 412 (2024). https://doi.org/10.1186/s12909-024-05406-1

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Received : 13 February 2024

Accepted : 09 April 2024

Published : 15 April 2024

DOI : https://doi.org/10.1186/s12909-024-05406-1

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• Medical students
• Dental students
• Nursing students
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BMC Medical Education

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