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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Claims the paper makes
0 of 2 cited sources checked · 0 supported · 0 flagged
- Premisecitation
Prevalence-incidence bias (Neyman bias) is particularly common in cross-sectional studies.
“Prevalenceincidence bias (also called the Neyman bias) is also particularly common in cross-sectional studies.13”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [13] Tripepi, 2010, Selection bias and information bias in clinical research, Nephron Clin Pract source
- Interpretationreasoning
Repeated cross-sectional studies cannot be used to look at individual change.
“They cannot be used to look at individual change (as in a cohort study).”
Quote in the paperNot a substantial claim - Interpretationreasoning
Because outcome and exposure variables are measured at the same time in a cross-sectional study, it is relatively difficult to establish causal relationships from such a study.
“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.”
Quote in the paperSubstantial claim - Also stated in: § Description of Subtypes of Cross-Sectional Studies · plain
- Interpretationreasoning
Repeated cross-sectional studies can be used for analyzing population changes over time (aggregate change over time).
“Thus, repeated cross-sectional studies can be used for analyzing population changes over time (also known as aggregate change over time).”
Quote in the paperNot a substantial claim - Premisecitation
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.
“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”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [6] Fleiss, 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
Cross-sectional studies are susceptible to sampling bias because they often need to select a sample from a large and heterogeneous study population.
“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.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Because subjects in cross-sectional studies are neither deliberately exposed nor treated, there are seldom ethical difficulties.
“The subjects are neither deliberately exposed nor treated; thus, there are seldom ethical difficulties.”
Quote in the paperNot a substantial claim
- Classified as probably not a substantial claim. 4
- May combine two claims. 3
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationreasoningStepwise selection methods and P value-based criteria often allow too many parameters to be included, which reduces the generalizability of the model.
“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.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenConfounding could result in a distortion of the association between exposure and outcome.
“Confounding could result in a distortion of the association between exposure and outcome.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningIn a descriptive cross-sectional study, the sample size does not depend on statistical power because statistical power only applies to statistical comparisons.
“Note that the sample size in a descriptive study does not depend on statistical power because this concept only applies to statistical comparisons.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Interpretationnone givenCross-sectional studies cannot assess incidence.
“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”
Quote in the paperSubstantial claim- Also stated in: § 1. The study population and the research question. · plain
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenOnly with full and transparent reporting of information on all aspects of a cross-sectional study can the potential usefulness of its findings and risk of bias be adequately assessed.
“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.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningBecause 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, resulting in recall bias.
“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.”
Quote in the paperNot a substantial claim
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.”
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“Finally, the majority of eligible studies employed a prospective, cross-sectional survey design, which apart from being fallible to subject biases (i.e. social desirability) offers limited predictive power in establishing cause and effect temporal relationships (Wang and Cheng 2020).”
BackgroundBrewster, G. S., Wang, D., McPhillips, M., Epps, F., & Yang, I. (2022) · Clinical Gerontologist · doi:10.1080/07317115.2022.2139655 · Cited by 36 · see citing works
“Most of the studies were cross-sectional, which prevented the assessment of temporal relationships, as well as identification of causality or directionality (Wang & Cheng, 2020).”
BackgroundGlobal prevalence of self-harm during the COVID-19 pandemic: a systematic review and meta-analysis
Cheng, H., Wang, D., Wang, L., Zou, H., & Qu, Y. (2023) · BMC Psychology · doi:10.1186/s40359-023-01181-8 · Cited by 40 · see citing works
Burnout, well-being and self-reported medical errors among physicians
Owoc, J., Mańczak, M., Tombarkiewicz, M., & Olszewski, R. (2021) · Polskie Archiwum Medycyny Wewnętrznej · doi:10.20452/pamw.16033 · Cited by 38 · see citing works
“The underlying cause of this may be that the overall burnout rate was very high and in fact referred to the large majority of the studied group which may have blurred some associations [32].”
BackgroundA cross-sectional, multicenter survey of the prevalence and risk factors for Long COVID
Imoto, W., Yamada, K., Kawai, R., Imai, T., Kawamoto, K., Uji, M., Kanda, H., Takada, M., Ohno, Y., Ohtani, H., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-25398-6 · Cited by 35 · see citing works
Determinants of household food expenditure in Tanzania: implications on food security
Rashid, F. N., Sesabo, J. K., Lihawa, R. M., et al. (2024) · Agriculture & Food Security · doi:10.1186/s40066-023-00462-0 · Cited by 37 · see citing works
“It involved cross-sectional research design, where data from households were collected at a single point in time, since the design is time and cost-effective [56].”
BackgroundCheng, C. K. T., Chua, J. H., Cheng, L. J., Ang, W. H. D., & Lau, Y. (2022) · Journal of Nursing Management · doi:10.1111/jonm.13558 · Cited by 41 · see citing works
Vahedi, A., Eriksdotter, M., Ihle‐Hansen, H., Wyller, T. B., Øksengård, A. R., & Fure, B. (2022) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.5822 · Cited by 35 · see citing works
Steinmetz, F., Fiedler, I., von Meduna, M., & Ante, L. (2021) · Journal of Gambling Studies · doi:10.1007/s10899-021-10042-1 · Cited by 38 · see citing works
“As with any other cross-sectional study design, our study is at risk for selection bias and information bias (Wang & Cheng, 2020).”
The interrelations of cryptocurrency and gambling: Results from a representative survey
Steinmetz, F. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107437 · Cited by 34 · see citing works
Li, S., Cui, G., Zhou, F., Liu, S., Guo, Y., Yin, Y., & Xu, H. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.868279 · Cited by 35 · see citing works
Hossian, M., Mielke, G. I., Nisar, M., Tremblay, M. S., & Khan, A. (2025) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-025-01809-5 · Cited by 39 · see citing works
Suprapti, B., Izzah, Z., Anjani, A., Andarsari, M. R., Nilamsari, W., & Nugroho, C. W. (2023) · Global Epidemiology · doi:10.1016/j.gloepi.2023.100113 · Cited by 36 · see citing works
Alsheweir, A., Goyder, E., Alnooh, G., & Caton, S. J. (2023) · Nutrients · doi:10.3390/nu15214643 · Cited by 33 · see citing works
“Despite how each study presented valuable findings in relation to DEB among school students and adolescents in Saudi Arabia, the cross-sectional nature of the studies increases the possibility of bias and may limit the generalisability of the findings [123].”
BackgroundThe mental health of migrants living in limbo: A mixed-methods systematic review with meta-analysis
Côté‐Olijnyk, M., Perry, J. C., Paré, M.-È., & Kronick, R. (2024) · Psychiatry Research · doi:10.1016/j.psychres.2024.115931 · Cited by 35 · see citing works
“Further, the cross-sectional design of most studies prevents us from drawing conclusions about causality and may introduce bias by preferentially identifying long-standing cases (Sedgwick, 2014; Wang and Cheng, 2020).”
BackgroundRicart, S., Gandolfi, C., & Castelletti, A. F. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e41328 · Cited by 32 · see citing works
Electrifying the future: analysing the determinants of electric vehicle adoption
Pandita, D., Bhatt, V., Kumar, V. V. R., Fatma, A., & Vapiwala, F. (2024) · International Journal of Energy Sector Management · doi:10.1108/ijesm-06-2023-0004 · Cited by 34 · see citing works
Hermansson, S. K., Norström, F., Hilli, Y., et al. (2024) · BMC Health Services Research · doi:10.1186/s12913-024-11177-8 · Cited by 31 · see citing works
Kato, A. I., Chiloane-Tsoka, G. E., & Mugambe, P. (2024) · Cogent Business & Management · doi:10.1080/23311975.2024.2391122 · Cited by 32 · see citing works
“…as those of Jain et al. (2019), who conducted a cross-sectional study on sustainable finance in sub-saharan africa. it is however important to note that the design may be faced with imitations including challenges of conferring causation and the impact of confounding variables (Wang & cheng, 2020).”
Chen, L., Zhang, J., Zhou, N., Weng, J., Bao, Z., & Wu, L. (2023) · Scientific Reports · doi:10.1038/s41598-023-37302-x · Cited by 31 · see citing works
Xiao, Y., & Xiao, Z. (2023) · American Journal of Nephrology · doi:10.1159/000531045 · Cited by 30 · see citing works
Jala, S., Fry, M., & Elliott, R. M. (2023) · Journal of Clinical Nursing · doi:10.1111/jocn.16845 · Cited by 34 · see citing works
Expanded-multidimensional turnover intentions: scale development and validation
Ike, O. O., Ugwu, L. E., Enwereuzor, I. K., Eze, I. C., Omeje, O., & Okonkwo, E. (2023) · BMC Psychology · doi:10.1186/s40359-023-01303-2 · Cited by 56 · see citing works
Oshagbemi, O. A., López‐Romero, P., Winnips, C., et al. (2023) · Malaria Journal · doi:10.1186/s12936-023-04811-z · Cited by 29 · see citing works
“Most studies reporting the incidence of malaria among children are cross-sectional by design, making them less robust in evaluating the incidence of the disease condition; also, surveys are generally more prone to non-response and recall biases [14].”
BackgroundKnipschild, R., Hein, I. M., Pieters, S., Lindauer, R., Bicanic, I., Staal, W., de Jongh, A., & Klip, H. (2024) · European Journal of Psychotraumatology · doi:10.1080/20008066.2024.2330880 · Cited by 30 · see citing works
“Cross-sectional studies allow for the examination of these relationships at a single point in time (Wang & Cheng, 2020).”
BackgroundTalebi, S., Mehrabani, S., Ghoreishy, S. M., Wong, A., Moghaddam, A., Rahimi-Feyli, P., Amirian, P., Zarpoosh, M., Kermani, M. A. H., & Moradi, S. (2024) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-024-06489-w · Cited by 32 · see citing works
“The inherent recall bias in cross-sectional studies that rely on self-reporting, is a notable limitation affecting the reliability of outcomes [109].”
BackgroundA Personalised Approach to Identifying Important Determinants of Well-being
Ciarrochi, J., Sahdra, B. K., Hayes, S. C., Hofmann, S. G., Sanford, B., Stanton, C. E., Yap, K., Fraser, M. I., Gates, K. M., & Gloster, A. T. (2024) · Cognitive Therapy and Research · doi:10.1007/s10608-024-10486-w · Cited by 41 · see citing works
“Cross-sectional studies, for instance, analyze data from one point in time and are used to understand the prevalence of health outcomes and determinants of health, and describe features of a population (Wang & Cheng, 2020).”
Gillen, P. A., Neill, R. D., Manthorpe, J., Mallett, J., Schroder, H. S., Nicholl, P., Currie, D., Moriarty, J., Ravalier, J. M., McGrory, S., et al. (2022) · Epidemiologia · doi:10.3390/epidemiologia3010003 · Cited by 30 · see citing works
Akingbade, O., Adeleye, K. K., Fadodun, O. A., Fawole, I. O., Li, J., Choi, E. P. H., Ho, M. M., Lok, K. Y. W., Wong, J. Y. H., Fong, D., et al. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1194908 · Cited by 29 · see citing works
Sosso, F. A. E., Silva, F., Rodrigues, R., Carvalho, M., Zoukal, S., & Zárate, G. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12247508 · Cited by 31 · see citing works
“18 of 21 support public health strategies, randomized controlled trials and longitudinal studies are required with a broader objective related to the SES– sleep health gradient, including the role of unhealthy behaviors, chronic diseases, and psychological factors [68].”
BackgroundBeyond the hype: Deciphering brand trust amid sustainability skepticism
Riva, F., Μαγρίζος, Σ., Rizomyliotis, I., & Uddin, M. R. (2024) · Business Strategy and the Environment · doi:10.1002/bse.3829 · Cited by 50 · see citing works
Asio, J. M. R., & Gadia, E. D. (2024) · International Journal of Didactical Studies · doi:10.33902/ijods.202427763 · Cited by 43 · see citing works
“According to Wang and Cheng (2020), cross-sectional studies are observational researches that assess data from a specific population at a single point in time.”
Jasem, Z. A., AlMeraj, Z., & Alhuwail, D. (2022) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-022-01868-9 · Cited by 29 · see citing works
Dhivya, D. S., Hariharasudan, A., & Nawaz, N. (2023) · Cogent Social Sciences · doi:10.1080/23311886.2023.2248751 · Cited by 29 · see citing works
“The study employed a robust quantitative method, specifically the cross-sectional survey design, which is a valuable tool for investigating the prevalence and correlation of a phenomenon within a specific population (Wang & Cheng, 2020).”
MethodDrumond, V. Z., de Arruda, J. A. A., Bernabé, E., Mesquita, R. A., & Abreu, L. G. (2023) · Nutrition Reviews · doi:10.1093/nutrit/nuad031 · Cited by 27 · see citing works
Norms and consumer behaviors in tourism: a systematic literature review
Wasaya, A., Prentice, C., & Hsiao, A. (2023) · Tourism Review · doi:10.1108/tr-03-2023-0151 · Cited by 27 · see citing works
Association of depression and sleep quality with frailty: a cross-sectional study in China
Zhang, Y., Yu, G., Bai, W., Wu, S., Geng, X., Zhang, W., Liu, Y., Meng, Y., Gao, J., Li, W., et al. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1361745 · Cited by 31 · see citing works
Digital marketing and purchase intention of bank services: the role of trust and engagement
Otopah, A. A., Dogbe, C. S. K., Amofah, O., & Ahlijah, B. (2024) · International Journal of Bank Marketing · doi:10.1108/ijbm-02-2023-0097 · Cited by 28 · see citing works
Drivers and inhibitors of consumers’ adoption of AI-driven drone food delivery services
Nunkoo, R., Pillai, R., Sivathanu, B., & Rana, N. P. (2024) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2024.103913 · Cited by 29 · see citing works
Social Support and Parenting Stress in Hispanic Parents of Children with Autism Spectrum Disorder
Martinez, V. C., & Turnage, D. M. (2022) · Issues in Mental Health Nursing · doi:10.1080/01612840.2022.2100949 · Cited by 26 · see citing works
“In addition, most of the studies in this review had small sample sizes and were cross-sectional study designs, which limit their generalizability (Wang & Cheng, 2020).”
ResultPérez-Herrera, L. C., Peñaranda, D., Moreno, S., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0244797 · Cited by 26 · see citing works
Fadhli, S. A. M., Yan, J. L. S., Halim, A. S. A., Razak, A. A., & Rahman, A. A. (2022) · Healthcare · doi:10.3390/healthcare10050856 · Cited by 28 · see citing works
Almaraz, D., Galdós, J. S., Martín, F. M., Sánchez‐Iglesias, I., Fernández, A. J. M., & Goldsby, T. L. (2022) · Healthcare · doi:10.3390/healthcare10081447 · Cited by 28 · see citing works
Suhandiah, S., Suhariadi, F., Yulianti, P., & Abbas, A. (2023) · Cogent Business & Management · doi:10.1080/23311975.2023.2178364 · Cited by 30 · see citing works
“Cross-sectional studies allow researchers to collect data at a specific time and are cheaper and faster than other types (Wang & Cheng, 2020).”
BackgroundBlockchain as a driver for transformations in the public sector
Sousa, M. J. (2023) · Policy Design and Practice · doi:10.1080/25741292.2023.2267864 · Cited by 25 · see citing works
“For gathering primary data, a survey created on an internet platform was employed (Wang and Cheng, 2020).”
BackgroundMethodKelly, S., Brooks, S. P. J., Benkhedda, K., MacFarlane, A. J., Greene-Finestone, L. S., Skidmore, B., Clifford, T., & Wells, G. A. (2024) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2024.111408 · Cited by 28 · see citing works
Wamba, S. F., Guthrie, C. H., de Queiroz, M. M., & Oyedijo, A. (2024) · International Journal of Production Research · doi:10.1080/00207543.2024.2428427 · Cited by 28 · see citing works
“While such surveys are less onerous and make it easier for researchers to access and extract data (Wang and Cheng 2020), they are not without weaknesses, including potential endogeneity issues (Guide and Ketokivi 2015) and non-response and recall biases.”
Nutakor, J. A., Zhou, L., Larnyo, E., Addai‐Dansoh, S., & Cui, Y. (2024) · Scientific Reports · doi:10.1038/s41598-024-82187-z · Cited by 29 · see citing works
Al‐Mugheed, K., Bani‐Issa, W., Rababa, M., Hayajneh, A. A., Syouf, A. A., Al‐Bsheish, M., & Jarrar, M. (2022) · Healthcare · doi:10.3390/healthcare10101852 · Cited by 25 · see citing works
Ogbeibu, S., & Gaskin, J. E. (2022) · FIIB Business Review · doi:10.1177/23197145221121084 · Cited by 35 · see citing works
“Consequently, deploying EDM (which is grounded in segmentation mediation) under such conditions may provoke unrealistic and questionable findings due to high uncertainty limiting causal confidence (Wang & Cheng, 2020).”
BackgroundEstimating the prevalence of social and emotional loneliness across the adult lifespan
Manoli, A., McCarthy, J., & Ramsey, R. (2022) · Scientific Reports · doi:10.1038/s41598-022-24084-x · Cited by 27 · see citing works
A scoping review: the psychosocial barriers that exist for people with vulvodynia
Niedenfuehr, J. M., Edwards, M., & King, L. (2023) · The Journal of Sexual Medicine · doi:10.1093/jsxmed/qdad035 · Cited by 25 · see citing works
Dorukbaşi, E., & Cansoy, R. (2024) · European Journal of Education · doi:10.1111/ejed.12672 · Cited by 26 · see citing works
Perry, E. W., Culbreth, R. E., Swahn, M. H., Kasirye, R., & Self-Brown, S. (2020) · Children and Youth Services Review · doi:10.1016/j.childyouth.2020.105587 · Cited by 29 · see citing works
Pre-Service Teachers’ Perceptions of the Effectiveness of Microsoft Teams for Remote Learning
Almodaires, A. A., Almutairi, F. M., & Almsaud, T. E. A. (2021) · International Education Studies · doi:10.5539/ies.v14n9p108 · Cited by 25 · see citing works
“This research design is used to understand the prevalence of a phenomenon by typically describing the distribution of variables in a population without manipulating variables (Wang & Cheng, 2020; Allen, 2017).”
MethodSallam, M., Anwar, S., Yufika, A., Fahriani, M., Husnah, M., Kusuma, H. I., Raad, R., Khiri, N. M., Abdalla, R. Y., Adam, R. Y., et al. (2022) · Narra J · doi:10.52225/narra.v2i1.74 · Cited by 24 · see citing works
Wang, C., Shi, M., Lin, C., Wang, J., Xie, L., & Li, Y. (2024) · Lipids in Health and Disease · doi:10.1186/s12944-024-02125-w · Cited by 25 · see citing works
“Conversely, a smaller sample size may introduce larger sampling errors, thus causing sample statistics to deviate significantly from population parameters and reducing the credibility of the study results [40].”
BackgroundEricsson, C. R., Nordquist, H., Lindström, V., & Rudman, A. (2021) · BMC Public Health · doi:10.1186/s12889-021-11851-0 · Cited by 23 · see citing works
Moshel, M. L., Warburton, W., Batchelor, J., Bennett, J. M., & Ko, K. Y. (2023) · Neuropsychology Review · doi:10.1007/s11065-023-09612-4 · Cited by 28 · see citing works
“In accordance with Carbia et al. (2018), we adapted Item 5 to better capture the quality of the sample size ( n ≥ 25), known to be important when sample size calculations were not computed (Grjibovski et al., 2015; Wang & Cheng, 2020).”
MethodOrrù, L., Taccini, F., & Mannarini, S. (2024) · Behavioral Sciences · doi:10.3390/bs14030255 · Cited by 23 · see citing works
“…of emotional regulation, is not comparable to it), this contribution aimed to focus the a tt ention on the emotional part that in fl uences the management of eco-anxiety and worry about the future, as well as on the literature [30,32] that has highlighted the relationship between anxiety and worry.”
BackgroundMethod
- 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 · 2019: 3 · 2018: 1
- 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 › Health Professions › Health Information Management › 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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