The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index; none of the 2 sources its claims cite is checked for support yet.
Cross-Sectional Studies
Open accessAbstract
Cross-sectional studies are observational studies that analyze data from a population at a single point in time. They are often used to measure the prevalence of health outcomes, understand determinants of health, and describe features of a population. Unlike other types of observational studies, cross-sectional studies do not follow individuals up over time. They are usually inexpensive and easy to conduct. They are useful for establishing preliminary evidence in planning a future advanced study. This article reviews the essential characteristics, describes strengths and weaknesses, discusses methodological issues, and gives our recommendations on design and statistical analysis for cross-sectional studies in pulmonary and critical care medicine. A list of considerations for reviewers is also provided.
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In the paper
“Prevalenceincidence bias (also called the Neyman bias) is also particularly common in cross-sectional studies.13”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Bias
What the sources say
- Not checked — no full text of the sourcecites [13] Tripepi, 2010, Selection bias and information bias in clinical research, Nephron Clin Pract source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“They cannot be used to look at individual change (as in a cohort study).”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Description of Subtypes of Cross-Sectional Studies
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because the outcome and exposure variables are measured at the same time, it is relatively difficult to establish causal relationships from a cross-sectional study.”
- Also stated in: § Description of Subtypes of Cross-Sectional Studies · plain
“The exposures and outcomes are measured simultaneously; therefore, it is difficult to determine whether the exposures preceded or followed the outcomes in an analytical cross-sectional study.”
- Also stated in: § Benefits and Downside of Cross-Sectional Studies · plain
“The weaknesses of cross-sectional studies include the inability to assess incidence, to study rare diseases, and to make a causal inference.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > General Overview of Cross-Sectional Study Design
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Also stated in: § Description of Subtypes of Cross-Sectional Studies · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, repeated cross-sectional studies can be used for analyzing population changes over time (also known as aggregate change over time).”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Description of Subtypes of Cross-Sectional Studies
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“If one wants to compare two prevalence rates in an analytical cross-sectional study, the commonly used sample size formula is the same as is used when designing a cohort study.6”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Sample Size Determination
What the sources say
- Not matchedcites [6] Fleiss, 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Unlike studies starting from a series of patients, cross-sectional studies often need to select a sample of subjects from a large and heterogeneous study population.Thus, they are susceptible to sampling bias.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Benefits and Downside of Cross-Sectional Studies
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The subjects are neither deliberately exposed nor treated; thus, there are seldom ethical difficulties.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Benefits and Downside of Cross-Sectional Studies
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
- Probably not a substantial claim. 4
- It may state two separate claims as one. 3
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Stepwise selection methods and P value-based criteria are discouraged due to overfitting and because they often allow too many parameters to be included, which reduces the generalizability of the model.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Additional information
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Confounding could result in a distortion of the association between exposure and outcome.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Confounding
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Note that the sample size in a descriptive study does not depend on statistical power because this concept only applies to statistical comparisons.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Sample Size Determination
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The weaknesses of cross-sectional studies include the inability to assess incidence, to study rare diseases, and to make a causal inference.”
- Also stated in: § 1. The study population and the research question. · plain
“Unable to measure the incidence”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Benefits and Downside of Cross-Sectional Studies
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Also stated in: § 1. The study population and the research question. · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Only with full and transparent reporting of information on all aspects of a cross-sectional study can potential usefulness of its findings and risk of bias be adequately assessed.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Additional information
Strength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because exposure and outcome are measured simultaneously in a cross-sectional study, prior knowledge of the condition might influence the ascertainment of the exposure or the outcome, which results in recall bias.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Bias
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
The paper relies on this without support.
Cross-sectional studies are usually quick and inexpensive to conduct.
“They are usually inexpensive and easy to conduct.”
“The main strength of cross-sectional studies is that they are relatively quick and inexpensive to conduct.”
The paper relies on this without support.
Cross-sectional studies are the best way to determine prevalence.
“They are the best way to determine the prevalence and can study the associations of multiple exposures and outcomes.”
The paper relies on this without support.
Cross-sectional studies can study the associations of multiple exposures and outcomes.
“They are the best way to determine the prevalence and can study the associations of multiple exposures and outcomes.”
The paper relies on this without support.
Cross-sectional studies are useful for establishing preliminary evidence in planning a future advanced study.
“They are useful for establishing preliminary evidence in planning a future advanced study.”
The paper relies on this without support.
Cross-sectional studies are suitable for generating hypotheses and may provide information about the prevalence of outcomes and exposures that informs other study designs.
“They are suitable for generating hypotheses and may provide information about the prevalence of outcomes and exposures that informs other study designs.”
The paper relies on this without support.
Using questionnaires to reach a large sample of the population of interest is relatively inexpensive but can result in low response rates.
“Using questionnaires to reach a large sample of the population of interest is relatively inexpensive but can result in low response rates.”
The paper relies on this without support.
Interviews are more expensive and time-consuming than using questionnaires, potentially limiting the sample size but leading to a higher response rate.
“Interviews are more expensive and time-consuming than using questionnaires, potentially limiting the sample size but leading to a higher response rate.”
The paper relies on this without support.
Cross-sectional studies cannot study rare diseases.
“The weaknesses of cross-sectional studies include the inability to assess incidence, to study rare diseases, and to make a causal inference.”
The paper relies on this without support.
Probability sampling methods are more accurate and rigorous than nonprobability sampling methods.
“In general, probability sampling methods are preferred over nonprobability ones, as the former are considered to be more accurate and rigorous.”
The paper relies on this without support.
Nonresponse bias is usually encountered in cross-sectional survey studies with mailed questionnaires.
“A common type of selection bias is the nonresponse bias, which is usually encountered in crosssectional survey studies with mailed questionnaires.”
The paper relies on this without support.
Recall bias and detection bias are two common information biases.
“Recall bias and detection bias are two common information biases.”
Citations
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“The reviewed studies were largely cross-sectional (19) which are often considered useful for establishing preliminary evidence when planning for a future advanced study (Wang & Cheng, 2020).”
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“[38] Our sampling strategy of seeking a relatively large, international participant pool for the survey increases the generalizability of our findings regarding how CAIM researchers engage with open science practices.”
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Life Satisfaction in Adolescence: A Bibliometric Analysis
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“However, cross-sectional studies provide weak evidence for causal inferences (Wang & Cheng, 2020 ).”
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“A cross-sectional study design is useful to create preliminary base evidence for the literature in a particular topic area (X. Wang & Cheng, 2020).”
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“Similarly, a prior study found that while Australian psychologists were open to using CAIM with patients, there was also scepticism surrounding certain aspects (30).”
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Predicting Adoption Intention of ChatGPT- A Study on Business Professionals of BangladeshPreprint
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“However, cross-sectional studies remain vital especially among under-assessed populations to assess potential relationships that can inform future longitudinal studies [ 87 ].”
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E-SERVICESCAPE AND CUSTOMER PATRONAGE OF INTERNET BANKING IN DEPOSIT MONEY BANKS
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“Tis qualifed the study to use an analytical crosssectional design as recommended by Wang and Cheng [24].”
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“Due to a larger period, participants might be susceptible to recall bias (Wang and Cheng 2020), which could result in an underestimation of structural and functional network aspects.”
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Determinants of pro-environmental behaviour of urban youth in Ghana
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“Although cross-sectional design leads to results that are snapshots of issues (Wang & Cheng, 2020), it nevertheless provides an opportunity to reach a large population and enhance the representativeness of the study findings.”
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“Like all cross-sectional studies [52], our study faces the limitation of measuring exposure and outcome simultaneously at a single point in time.”
BackgroundNational trends in sexual intercourse and usage of contraception among Korean adolescents
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“A stratified analysis for sexual intercourse and contraception usage by the risk factors was conducted using the weighted multivariable logistic regression models [20].”
Dirupo, G., Totaro, S., Richard, J. C. M., & Corradi‐Dell’Acqua, C. (2021) · eLife · doi:10.7554/elife.63272 · Cited by 10
“As such, our study shares the weaknesses of cross-sectional investigations (Wang and Cheng, 2020), as the role of experience was not tested longitudinally in the same population.”
BackgroundQedan, R. I., Daibes, M. A., Al‐Jabi, S. W., et al. (2022) · BMC Nursing · doi:10.1186/s12912-022-00895-1 · Cited by 9
Drumond, V. Z., Andrade, A. A., de Arruda, J. A. A., Mesquita, R. A., & Abreu, L. G. (2022) · European Archives of Paediatric Dentistry · doi:10.1007/s40368-022-00732-8 · Cited by 9
Shi, J., Lu, D., Pan, R., et al. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.955418 · Cited by 9
The burden and predictors of late antenatal booking in a rural setting in Ghana
Oduro, C. A., Opoku, D. A., Osarfo, J., Adam, F., Attua, A. A., Owusu‐Ansah, E., Issah, S., Barfi, A., Kwadzodeh, E. F., & Mohammed, A. (2022) · Nursing Open · doi:10.1002/nop2.1467 · Cited by 9
“The chosen study design is justified as it allows reporting of a prevalence measure as well as inferential statistics including odds ratios that describe the strength of association between exposure and dependent variables (Wang & Cheng, 2020).”
BackgroundZaccarin, M., Zanni, S., Gallé, F., et al. (2022) · Toxics · doi:10.3390/toxics10120759 · Cited by 8
Vieira, W. D. A., Paranhos, L. R., Santos, D. M., et al. (2023) · Dentomaxillofacial Radiology · doi:10.1259/dmfr.20230004 · Cited by 8
Differentiating Childhood Traumas in Inflammatory Bowel Disease
Gnat, L., Mihajlovic, V., Jones, K. L., & Tripp, D. A. (2023) · Journal of the Canadian Association of Gastroenterology · doi:10.1093/jcag/gwad026 · Cited by 8
“25,26 Finally, online recruitment may introduce self-selection sampling bias, as individuals seeking health information online may differ from the general population of chronic disease patients.”
Yun, H., Kim, S., & Han, E. (2023) · PLoS ONE · doi:10.1371/journal.pone.0292843 · Cited by 9
“The current study used a cross-sectional survey which is the suitable way to study the associations of the effectiveness profiles of tutor performance with learning outcomes [29].”
MethodAkinwande, T., & Hui, E. C. M. (2024) · Cities · doi:10.1016/j.cities.2024.104964 · Cited by 8
Yu, B., Wan, G., Cheng, S., Wen, P., Yang, X., Li, J., Tian, H., Gao, Y., Zhong, Q., Liu, J. H., et al. (2023) · Current Alzheimer Research · doi:10.2174/0115672050303878240319054149 · Cited by 8
Petrovic, J., Mills, D. J., & Heath, N. L. (2024) · Journal of Clinical Psychology · doi:10.1002/jclp.23708 · Cited by 8
Zhang, W., Pan, Z., Zhu, Y., et al. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1405594 · Cited by 8
“A cross-sectional (26) exploratory survey method was used in this study, because this research method has been widely used to investigate the current status of psychological indicators such as illness uncertainty (27), perceived social support (28) and resilience (29) of patients.”
MethodIddris, F., Salifu, I., & Kparl, E. M. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2024.2383831 · Cited by 9
“This study used the quantitative approach and relied on a cross-sectional research design (X. Wang & Cheng, 2020).”
de Saboya, R. T., d’Orsi, E., & Keivani, R. (2024) · Cities · doi:10.1016/j.cities.2024.105318 · Cited by 9
Climate change distress and impairment in Germany
König, L., Breves, P. L., Linnemann, G. A., Hamer, T., & Suhr, R. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1432881 · Cited by 9
“Because a cross-sectional study design was chosen, no causal inferences can be drawn (44).”
BackgroundOwusu, R., Kwarteng, E. B., Bawua, S. A., Otoo, D. D., & Nonvignon, J. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1383743 · Cited by 9
Jural, L. A., Fagundes, F. A. U., RISSO, P. D. A., et al. (2024) · Trauma Violence & Abuse · doi:10.1177/15248380241297423 · Cited by 8
“Despite the generally limited certainty of evidence provided by cross-sectional designs, these studies are less costly and less time-consuming, making them advantageous for covering broad population samples and identifying associations with important outcomes (Wang & Cheng, 2020).”
Taccini, F., & Mannarini, S. (2025) · Journal of Interpersonal Violence · doi:10.1177/08862605241307224 · Cited by 8
“Cross-sectional studies come with certain limitations that require careful consideration (Wang & Cheng, 2020).”
Creativity research in medicine and nursing: A scoping review
Thabane, A., Saleh, S., Pallapothu, S., McKechnie, T., Staibano, P., Busse, J. W., Calic, G., Sonnadara, R., Parpia, S., & Bhandari, M. (2025) · PLoS ONE · doi:10.1371/journal.pone.0317209 · Cited by 8
Kebe, I. A., Liu, Y., & Kahl, C. (2025) · Behavioral Sciences · doi:10.3390/bs15030349 · Cited by 8
“2025 , 15 , 349 6 of 19 design is suitable for examining relationships because it allows data to be collected at a single point in time (Wang & Cheng, 2020).”
Risk Assessment and Health Impact Studies: Strategic Tools for Managing Environmental Health
Izah, S. C., & Ogwu, M. C. (2025) · Environmental science and engineering · doi:10.1007/978-3-031-81966-7_12 · Cited by 10
Ou, J., Wang, K., Zuo, M., Chen, D., & Luo, H. (2025) · Behavioral Sciences · doi:10.3390/bs15050618 · Cited by 13
“The core feature of this method is its cross-sectional nature, which involves conducting a one-time survey and the observation of individuals within a group or social phenomenon to gather information about that group (X. Wang & Cheng, 2020).”
Language Mindsets: A Systematic Review
Oruç, E. (2025) · European Journal of Education · doi:10.1111/ejed.70124 · Cited by 13
Coelho, D. R. A., Nicoloro‐SantaBarbara, J. M., Majd, M., Vieira, W. F., Laney, M. D., Lydston, M., Martins‐Filho, O. A., Bahia‐Oliveira, L. M. G., Salvi, J. D., Cassano, P., et al. (2025) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13824 · Cited by 8
When meta-analysis misleads: the need for methodological integrity in e-cigarette research
Polosa, R., Geraci, G., & Adebisi, Y. A. (2025) · Internal and Emergency Medicine · doi:10.1007/s11739-025-04019-w · Cited by 8
Organic food research: Key contributors, research hotspots, and emerging trends
Azizan, A., Awal, A., Zain, W. Z. W. M., Hairoman, N., Endrini, S., & Hassan, F. (2025) · Applied Food Research · doi:10.1016/j.afres.2025.101109 · Cited by 10
Community engagement in promoting malaria vaccine uptake for children Under-Five
Adoma, P. O., Acquah, F. N., Yakubu, A., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-01616-9 · Cited by 8
Akoğlu, A. S., Adın, R. M., Ada, A. M., et al. (2025) · Medicina · doi:10.3390/medicina61091547 · Cited by 8
“We employed a cross-sectional comparative study design, which involves observational data at a single time point [13].”
Tak, E., Kim, J., Lee, H., & Kang, M. (2025) · Nutrition Journal · doi:10.1186/s12937-025-01235-0 · Cited by 9
“Nevertheless, due to the cross-sectional design of KNHANES, temporal causality cannot be drawn from identified dietary patterns and cardiometabolic outcomes [26].”
Aliuş, C., Breazu, A., Panţu, C., Toader, C., Șerban, M., Covache-Busuioc, R.-A., Munteanu, O., & Dumitru, A. V. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms262210959 · Cited by 12
Differential associations between smoking, e-cigarette use, and diabetes prevalence
Adebisi, Y. A., Ngoma, C., Campagna, D., et al. (2025) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2025.103331 · Cited by 8
Health impacts of micro- and nanoplastics in humans: systematic review of in vivo evidence
Anna, H. A. T., Ng, J. J., Tang, D. H., Yong, C. T., & Ho, A. F. W. (2026) · Environmental Health · doi:10.1186/s12940-026-01282-y · Cited by 12
Cofini, V., Muselli, M., Lolli, C., Fabiani, L., & Necozione, S. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20010625 · Cited by 8
Silalahi, S. A. F., Junaidi, A., Nasution, L. Z., Sutoto, A., Hutomo, A. S., Sutrisno, J., Lukas, A., Ginting, J., Suripto, S., & Lestari, R. (2023) · Cogent Business & Management · doi:10.1080/23311975.2023.2284442 · Cited by 10
“The design was chosen as it can generate multiple outcomes and is convenient for testing the proposed hypotheses (Wang & Cheng, 2020).”
MethodOumer, A., Ale, A., Hamza, A., & Dagne, I. (2023) · BioMed Research International · doi:10.1155/2023/4726010 · Cited by 10
Vaysi, A., Nazarpour, P., کیانی, ژ., Maleki, M., Hamzehei, M., Amianto, F., Sellbom, M., & Komasi, S. (2023) · Personality and Mental Health · doi:10.1002/pmh.1600 · Cited by 8
Kakooza, S., Tayebwa, D. S., Rashid, N. K., Kayaga, E. B., Asiimwe, I., Komugisha, M., Wanyana, M., Kisekka, R., Kyabarongo, A., Kiryabwire, D., et al. (2023) · Veterinary Medicine Research and Reports · doi:10.2147/vmrr.s418624 · Cited by 7
Chamberlain, S. A. E., McLeod, L. J., & Hine, D. W. (2024) · PLoS ONE · doi:10.1371/journal.pone.0296805 · Cited by 8
Gitiha, R. W., Rugano, P., Wakhu, S., & Ciriaka, M. G. (2024) · Cogent Education · doi:10.1080/2331186x.2024.2310968 · Cited by 8
“The design allows data to be collected simultaneously with all understudied phenomena, without manipulating or influencing the study variables (Wang & Cheng, 2020).”
Prevalence and associated factors of occupational injuries in an industrial city in Ghana
Asiedu, M. T., Opoku, D. A., Ayisi‐Boateng, N. K., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0301339 · Cited by 8
“The adoption of this study design is justified by its ability to estimate both prevalence and inferential statistics like odds ratio which shows the strength of association between dependent (occupational injuries) and independent (such as age, sex, type of engagement etc.) variables [31].”
Identifying Depression Through Machine Learning Analysis of Omics Data: Scoping Review
Taylor, B., Hobensack, M., de Rivera, S. N., Zhao, Y., Creber, R. M., & Cato, K. (2024) · JMIR Nursing · doi:10.2196/54810 · Cited by 11
“This checklist was chosen because the genomic data in the studies included in this review were analyzed at a single point in time [34].”
MethodKc, D., Smith, J., Currie, K., & Ness, V. (2024) · Journal of Infection Prevention · doi:10.1177/17571774241251645 · Cited by 10
“Furthermore, although this review included studies from broad geographical locations, most were cross-sectional, which can establish connections but not causation (Wang and Cheng, 2020).”
Peral‐Suárez, Á., Bermejo, L. M., Salas‐González, M. D., Cuadrado‐Soto, E., Lozano-Estevan, M. D. C., Loria‐Kohen, V., González‐Rodríguez, L. G., Aparicio, A., Olalla, J. M. D., & López-Sobaler, A. M. (2024) · Nutrients · doi:10.3390/nu16132096 · Cited by 8
“However, this design allows us to describe the prevalence of the excess weight and associated factors in Madrid City, suggesting hypotheses for future more in-depth studies [54].”
BackgroundEffects of Metformin on CIMT and FMD in PCOS patients: a systematic review and meta-analysis
Wang, F., Yan, Y., Wang, D., Fan, Q., Yi, F., Yang, X., & Lu, J. (2024) · BMC Women s Health · doi:10.1186/s12905-024-03275-w · Cited by 12
Zhang, Z., Lv, L., Guan, S., et al. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1434299 · Cited by 8
Vinkóczi, T., Végvári, I. M., Németh, M., & Koltai, J. P. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100522 · Cited by 12
Naaman, D., Yeşilada, F., & Aghaei, İ. (2025) · Sustainability · doi:10.3390/su17041714 · Cited by 11
Metadata
- Authors
- Wang, X., & Cheng, Z.
- Affiliations
- Cleveland Clinic (US)
- Zhongnan Hospital of Wuhan University (CN)
- Corresponding author
- Wang, Xiaofeng
- Venue
- CHEST
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 158
- Issue
- 1
- Pages
- S65-S71
- ISSN
- 0012-3692 (ISSN-L)
- OpenAlex
- W3039445169
- Cited by
- 2,214
- References
- 29
- Citations by year
- 2026: 636 · 2025: 638 · 2024: 423 · 2023: 282 · 2022: 162 · 2021: 61 · 2020: 8
- FWCI
- 90.42
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- CHEST Journal (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Nursing › Research and Theory › Methodologies in Health Research and Practice
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- cross-sectional study, observational study design, prevalence, health determinants, methodological issues, statistical analysis, respiratory medicine, intensive care, research design recommendations, peer review
- MeSH terms
- Cross-Sectional Studies, Humans, Guidelines as Topic
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