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.
Overview
Integrity signals
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Claims the paper makes
11 Own interpretation · 1 Sources not found · 1 No full text of the sources
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
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a 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
“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
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a 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 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
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In 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.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a 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
“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
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably 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
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably 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
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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
“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
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably 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
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably 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
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It 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
Cites
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“The cross-sectional design cannot infer causal relationships (32), so future longitudinal studies are needed.”
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Talebi, S., Mehrabani, S., Ghoreishy, S. M., Wong, A., Moghaddam, A., Rahimi-Feyli, P., Amirian, P., Zarpoosh, M., Kermani, M. A. H., & Moradi, S. (2024) · Figshare · doi:10.6084/m9.figshare.26721165
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Talebi, S., Mehrabani, S., Ghoreishy, S. M., Wong, A., Moghaddam, A., Rahimi-Feyli, P., Amirian, P., Zarpoosh, M., Kermani, M. A. H., & Moradi, S. (2024) · Figshare · doi:10.6084/m9.figshare.26721159
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Skjevik, E. P., Schei, E., Boudreau, J. D., Tjølsen, A., Ringberg, U., Fuks, A., Kvernenes, M., & Ofstad, E. H. (2024) · Figshare · doi:10.6084/m9.figshare.26702353
Robbins, M. K., Spence, M., & Steeves, E. A. (2022) · Figshare · doi:10.6084/m9.figshare.19298099
Jebreen, K., RADWAN, E. S., Rebai, W. K., Alattar, E., Radwan, A., Safi, W., Radwan, W., & Alajez, M. (2024) · Figshare · doi:10.6084/m9.figshare.25770366
Ericsson, C. R., Nordquist, H., Lindström, V., & Rudman, A. (2021) · Figshare · doi:10.6084/m9.figshare.16746745
Ericsson, C. R., Nordquist, H., Lindström, V., & Rudman, A. (2021) · Figshare · doi:10.6084/m9.figshare.16746748
Talebi, S., Mehrabani, S., Ghoreishy, S. M., Wong, A., Moghaddam, A., Rahimi-Feyli, P., Amirian, P., Zarpoosh, M., Kermani, M. A. H., & Moradi, S. (2024) · Figshare · doi:10.6084/m9.figshare.26721162
Ericsson, C. R., Nordquist, H., Lindström, V., & Rudman, A. (2021) · Figshare · doi:10.6084/m9.figshare.16746739
Talebi, S., Mehrabani, S., Ghoreishy, S. M., Wong, A., Moghaddam, A., Rahimi-Feyli, P., Amirian, P., Zarpoosh, M., Kermani, M. A. H., & Moradi, S. (2024) · Figshare · doi:10.6084/m9.figshare.26721168
Ericsson, C. R., Nordquist, H., Lindström, V., & Rudman, A. (2021) · Figshare · doi:10.6084/m9.figshare.16746751
Sparrow-Downes, V. M., Trincao-Batra, S., Cloutier, P., Helleman, A., Salamatmanesh, M., Gardner, W. P., Baksh, A., Kapur, R., Sheridan, N., Suntharalingam, S., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19711000
Robbins, M. K., Spence, M., & Steeves, E. A. (2022) · Figshare · doi:10.6084/m9.figshare.19298096
Ericsson, C. R., Nordquist, H., Lindström, V., & Rudman, A. (2021) · Figshare · doi:10.6084/m9.figshare.16746742
Ericsson, C. R., Nordquist, H., Lindström, V., & Rudman, A. (2021) · Figshare · doi:10.6084/m9.figshare.16746757
Robbins, M. K., Spence, M., & Steeves, E. A. (2022) · Figshare · doi:10.6084/m9.figshare.19298108
Kappner, N., Lang, J., Berthold, A., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20423690
Sparrow-Downes, V. M., Trincao-Batra, S., Cloutier, P., Helleman, A., Salamatmanesh, M., Gardner, W. P., Baksh, A., Kapur, R., Sheridan, N., Suntharalingam, S., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19710997
Talebi, S., Mehrabani, S., Ghoreishy, S. M., Wong, A., Moghaddam, A., Rahimi-Feyli, P., Amirian, P., Zarpoosh, M., Kermani, M. A. H., & Moradi, S. (2024) · Figshare · doi:10.6084/m9.figshare.26721174
Talebi, S., Mehrabani, S., Ghoreishy, S. M., Wong, A., Moghaddam, A., Rahimi-Feyli, P., Amirian, P., Zarpoosh, M., Kermani, M. A. H., & Moradi, S. (2024) · Figshare · doi:10.6084/m9.figshare.26721171
Bokemeyer, F., Lebherz, L., Bokemeyer, C., Gali, K., Schulz, H., & Bleich, C. (2024) · Figshare · doi:10.6084/m9.figshare.25989248
Brandt, S. K., Essig, S., & Balthasar, A. (2024) · Figshare · doi:10.6084/m9.figshare.26725841
Talebi, S., Mehrabani, S., Ghoreishy, S. M., Wong, A., Moghaddam, A., Rahimi-Feyli, P., Amirian, P., Zarpoosh, M., Kermani, M. A. H., & Moradi, S. (2024) · Figshare · doi:10.6084/m9.figshare.26721177
Brandt, S. K., Essig, S., & Balthasar, A. (2024) · Figshare · doi:10.6084/m9.figshare.26725844
Nutrient and Discretionary Food Intake in Vegan Adult Australians: A Cross‐Sectional Study
Smillie, L., Minehan, M., & Knight-Agarwal, C. R. (2025) · Nutrition Bulletin · doi:10.1016/j.clnesp.2025.07.777
Hoffmeister, L. V., Gama, A. F., Gonçalves, B., Canas, A. M., Figueiredo, C., Peixoto, V. R., Aguiar, P., & Dias, S. (2025) · Health & Social Care in the Community · doi:10.1155/hsc/5454688 · Cited by 1
Isagova, M., & Ervits, I. (2026) · Journal of Sustainable Business · doi:10.1186/s40991-026-00150-9
“Cross-sectional design provides a snapshot of a trend or phenomenon at a particular point in time; there is no retrospective analysis (Wang & Cheng, 2020).”
Sugiarto, A., & Rusli, R. (2025) · Journal of Smart Pedagogy and Education · doi:10.65101/spedu.v1i1.20
Goyanes, M., Lee, H. M., Scheffauer, R., & de Zúñiga, H. G. (2025) · Social Media + Society · doi:10.1177/20563051251399008
“This study focuses on cross-sectional results, providing valuable insights by “establishing preliminary evidence” to guide future research (Wang & Cheng, 2020), especially longitudinal studies.”
Ha, K. H., Yang, H. J., Park, M.-J., Lee, S.-G., & Kim, S. H. (2025) · Journal of Health Informatics and Statistics · doi:10.21032/jhis.2025.50.4.441
Classification of Brazilian airports using multiple operational criteria: A data mining approach
Prata, B. D. A. (2025) · Latin American Transport Studies · doi:10.1016/j.latran.2025.100049
Munir, A., Tufail, A., Haq, E. U., et al. (2025) · New Zealand Journal of Applied Business Research · doi:10.34074/jabr.19102.21
“This approach captured the current views and experiences of em-Volume ployees at a single point in time, making it possible to identify connections among the variables (Wang & Cheng, 2020).”
Assessing health literacy and digital health literacy: evidence from Brazil’s Distrito Federal
Tabak, B. M., Moraes, K. L., Buta, B. O., Froner, M. B., & Couto, L. C. D. (2025) · Health Promotion International · doi:10.1093/heapro/daaf226 · Cited by 1
Impacts of Screen Time on Motor Ability and Mental Health of Children
Indahwati, N., Maksum, A., Sasminta Christine, Y. H., et al. (2025) · Annals of Applied Sport Science · doi:10.61882/aassjournal.1552
“This study employs a cross-sectional method, an observational research design that analyzes data from a population at a single point in time, including group differences, to confirm the influence of maturation (26, 27).”
Bariham, I., Vida, K., & Kankpog, E. B. (2025) · Education Journal · doi:10.11648/j.edu.20251406.14
Winkelmann, Z. K., Scarneo‐Miller, S. E., Smith, E. C., Argetsinger, R. M., & Eberman, L. E. (2025) · BMC Medical Research Methodology · doi:10.1186/s12874-025-02728-6
Öz-yeterliğin Öğretmen Stresi ve İş Tatmini İlişkisindeki Düzenleyici Rolü: TALIS 2018 Bulguları
Uslukaya, A. (2025) · İnönü Üniversitesi Eğitim Fakültesi Dergisi · doi:10.17679/inuefd.1670791 · Cited by 1
Towards Post-study Employment in Australia: Do International Students Make the Most of Internships?
Nguyen, H., Nghia, T. L. H., Nhi, L. T. P., & Pham, H. H. (2026) · Springer briefs in education · doi:10.1007/978-981-95-4412-7_5
Rivera, J. S., Morris, C., & la fuente, V. Á. D. (2026) · Physical & Occupational Therapy In Pediatrics · doi:10.1080/01942638.2025.2607054
“An exploratory mixed-methods study was conducted, with a cross-sectional survey serving as a quantitative instrument that provided information to understand the breadth of OT services (Wang & Cheng, 2020).”
Mental health literacy and stigma towards eating disorders in Saudi Arabia: a cross-sectional study
Alqhtani, S. S., Bakheet, J. L., Alnajjar, H. A., Alselami, S., & Elgalad, S. K. K. (2026) · Journal of Eating Disorders · doi:10.1186/s40337-025-01513-6
“This could lead to better support, quicker help for those affected, and healthier outcomes. and internalized shame, discouraging people from seeking help and hindering recovery [30].”
Mappa, N., Rumallang, A., Akbar, A. M. A., et al. (2025) · Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi · doi:10.29133/yyutbd.1604541
Tandane, H. J., Waized, B. M., & Turuka, F. M. (2026) · Plant-Environment Interactions · doi:10.1002/pei3.70108
“This approach neglects potential changes in farmers' adoption behavior over time, including changes in risk aversion (Wang and Cheng 2020).”
Ni, Y., Balakumar, P., Islam, T., Haque, S. E., Shahriar, H., Sarwar, G., Ahmed, A., Liu, C., Pierce, B. L., Sargis, R. M., et al. (2026) · Environmental Health · doi:10.1186/s12940-025-01261-9
Giannakou, I., Mallabone, J., Joseph, M., Jenkinson, N., & Punt, T. D. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2025.106186
Thini, K. D., Malebatja, M. F., & Mokwena, K. E. (2026) · International Journal of Research in Business and Social Science (2147-4478) · doi:10.20525/ijrbs.v14i9.4318
“This approach allowed the researcher to collect data at one point in time, making it efficient, cost-effective, and less time-consuming (Wang & Cheng, 2020).”
The role of empathy in teaching and implications for pedagogy
Bui, H. T. T., Ha, T. T., Hoang, P. A., et al. (2025) · Multidisciplinary Science Journal · doi:10.31893/multiscience.2026388
What factors influence the knowledge and attitudes of UK university students towards breastfeeding?
Malekian, M., Irving, M., & Hundley, V. A. (2026) · Midwifery · doi:10.1016/j.midw.2026.104706
Boxtha, C., El-Kolalli, S., Denis, J., et al. (2026) · American Journal of Men s Health · doi:10.1177/15579883251410526
“For individuals who completed both components of the study, researchers would be able to gauge an individual’s genetic risk with a one-time approach (Wang & Cheng, 2020).”
Alharbi, E., Hewat, S., Walters, J., et al. (2026) · Journal of Fluency Disorders · doi:10.1016/j.jfludis.2026.106193
Wainwright, H., Skouteris, H., & Morris, H. (2026) · Journal of Social Service Research · doi:10.1080/01488376.2025.2606056
Type 2 diabetes after gestational diabetes, a cross‐sectional study— DIVINE ‐ NSW
Lee, V. Y., Donges, K., Beech, A., Makris, A., Arnott, C. G., Patel, A. A., & Henry, A. (2026) · Diabetic Medicine · doi:10.1111/dme.70155
Sobrecarga del cuidador y funcionamiento ejecutivo en cuidadores primarios
Asitimbay, A. E. G. (2025) · Revista Científica y Arbitrada de Psicología NUNA YACHAY · doi:10.56124/nuna-yachay.v7i14.029
Lv, Z., Li, X., & Zhang, X. (2026) · Addiction · doi:10.1111/add.70312
Calle, F. D. L., Bagienska, J., & Beasley, J. M. (2026) · Nutrients · doi:10.3390/nu18020220
“However, reliance on cross-sectional designs and self-reported data increases the likelihood of information and sampling bias, including socially desirable answers [34,35].”
Wang, H., Xiao, J., Zhang, T., et al. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1655437
“It is descriptive research that involves analyzing the information about a population at a specific point in time and also can be used to determine relationships between variables (Wang and Cheng, 2020).”
Valle, K. M. D., Lagamayo, J., Ramos, C. D., et al. (2025) · Research in Clinical Pharmacy · doi:10.59931/rcp.25.0016
Developmental Language Risk and Social and Behavioral Functioning in Bilingual Latinx Adolescents
Palma, J., Peña, E. D., Esperanza, C., Albudoor, N., & Rodríguez, E. M. (2026) · Journal of Speech Language and Hearing Research · doi:10.1044/2025_jslhr-25-00416
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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