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In research studies, it is difficult to recruit a sample that is representative of family physician’s entire population. Some groups may be overrepresented while others are underrepresented. Therefore, some marginalized patient populations may be understudied because of socioeconomic status; race; ethnicity; age; sex; sexual orientation; gender identification; and physical, mental, or cognitive abilities. This can result in inadequate or insufficient data to derive either accurate or generalizable conclusions. This checklist will reveal potential limitations of a research study. When reviewing articles, answering yes does not make the study inherently good and answering no does not make the study inherently bad, but rather reveals limitations.
Start
Assess Internal Validity
Does the study have sound methodology surrounding the recruitment and analysis of marginalized populations to limit bias?
1. Are demographic categories (e.g. race; ethnicity; socioeconomic status; age; sex; sexual orientation; gender identified; and physical, mental, or cognitive abilities) of participating patients provided?
No
Yes
This is a limitation. The absence of demographic information limits the ability to determine the generalizability of the results to other settings, hides biases by not providing information to assess if certain groups were underrepresented, and leads to skewed results that may disproportionately affect or exclude certain populations. This reduces the utility of the research in diverse clinical settings. The limitation is: The absence of demographic information decreases transparency hindering the ability to assess for biases, underrepresentation, and generalizability, reducing the applicability of the results.
Reporting demographic categories ensures transparency, allows a more accurate understanding of how study results apply to various populations, and helps identify healthcare disparities.
Next
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Are the demographic categories...
Patient-reported demographics reduce the potential for bias by preventing researchers from imposing their assumptions about participants' identities and perpetuating stereotypes and bias. This is crucial when examining health disparities, as demographic misclassification can skew results and obscure the true nature of inequities.
This is a limitation. Investigator-assigned categories can perpetuate marginalization by enforcing binary or narrow demographic labels that may not fit participants' experiences, exacerbating bias and inequity. Additionally, assigning categories perpetuates bias and is disrespectful to the patients. The limitation is: The demographics of this study were not patient-reported, limiting the validity through misclassification bias impacting accuracy and generalizability.
Yes
No/Unclear
a. Patient-reported?
Described in a way that would be easy for another researcher to reproduce.
Clearly defined demographic categories improve reproducibility, enhance transparency, help avoid misclassification, and ensure the results can be correctly understood and applied appropriately in clinical practice. This is particularly important for marginalized groups, where demographic categories can oversimplify their identity, leading to their experiences being misunderstood.
This is a limitation. The lack of clearly defined demographic categories creates hidden or misrepresented health disparities, perpetuating gaps in healthcare for underserved populations. Additionally, a lack of clear definitions may allow for oversimplification and assumptions regarding identities, leading to experiences of marginalized groups being misunderstood. The limitation is: The lack of clearly defined demographic categories may introduce ambiguity and hide health disparities, leading to potential misinterpretation of results, misunderstanding of the experiences of marginalized groups, and the perpetuation of health disparities.
Yes
No/Unclear
b. Clearly defined?
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Are the demographic categories...
This is a limitation. When patient demographics are not independent of the intervention assignment, bias is introduced, the study's credibility is reduced, and the application of the study results to diverse patient populations is limited. Additionally, this perpetuates disparities by not ensuring everyone has an equal opportunity to receive the intervention. The limitation is: The demographics of the participants were not independent of the intervention assignment, which introduces confounding variables and selection bias, making it difficult to determine whether the intervention or socioeconomic variables are responsible for the outcome of the study
Independent demographic assignment supports the integrity of the research by ensuring each group is comparable in terms of demographic characteristics, strengthening the study's internal validity. It also ensures that all participants have an equal opportunity to receive an intervention, regardless of their background.
c. Independent of the intervention assignment?
Yes
No/Unclear
This is a limitation. If researchers are not blinded to participant demographics while assigning the intervention, they may consciously or unconsciously influence the assignment based on preconceived notions about which groups may benefit from the treatment, skewing the study results. The limitation is: Patient demographics were not blinded when the researchers assigned participants to the intervention, creating a risk for selection bias and potentially skewing the study results.
Blinding researchers to patient demographics ensures the intervention is assigned without conscious or unconscious bias, promoting fairness in how participants are distributed between treatment groups.
d. Blinded when assigning interventions?
Yes
No/Unclear
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Insert education on why ths is important
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Determine the Applicability of the Results
Applicability refers to the extent to which research findings can be generalized to clinical practice and diverse patient populations.
2. Were potential confounders, such as socioeconomic status, education level, structural racism, and others, identified as factors that could influence intervention response, compliance, or outcome assessment?
No/Unclear
Yes
This is a limitation. Not identifying confounders compromises the applicability of the findings as it does not acknowledge variables other than the intervention or exposure that could influence the study's outcomes. The limitation is: Confounders were not identified in the study, increasing the risk of bias and reducing applicability as it does not acknowledge variables that could influence the results, limiting the ability to draw accurate conclusions.
Recognizing confounders acknowledges that variables other than the intervention or exposure may influence the study's outcomes. Understanding the impact of these variables can guide the statistical analysis and application of the study's findings to diverse populations in clinical settings.
Next
Back
a. If confounders were identified, was an adjusted statistical analysis completed?
No/Unclear
Yes
This is a limitation. Failing to adjust for confounders leaves the study open to confounding bias, where the observed effect may incorrectly be attributed to the intervention rather than the uncontrolled variables. The limitation is: No adjusted statistical analysis was completed, introducing confounding bias and limiting the accuracy and applicability of the findings.
Adjusting for confounders ensures that differences in outcomes are due to the intervention, not external factors, improving the applicability of the results.
Next
Back
3. Was the data stratified by one or more demographic categories?
No/Unclear
Yes
This is a limitation. When one or more demographic categories do not stratify the data of a study, the study results may overlook significant differences in how the intervention impacts different demographic groups, potentially masking health disparities. The limitation is: The data was not stratified by at least one demographic category, masking potentially relevant health disparities and reducing the applicability of the study's findings to diverse patient populations.
Stratifying the data by one or more demographic categories allows for exploring potential health disparities. Understanding how an intervention or exposure may affect subsets of the population is crucial to addressing inequities.
Next
Next
Back
a. If the data was stratified by demographic categories, did the authors provide a rationale for doing so?
This is a limitation. If data has been stratified, and there is no discussion as to why those groups are evaluated, it disregards the impact of social determinants of health, increasing the risk of bias against marginalized populations. The limitation is: The data was stratified by demographic categories without a rationale for doing so, overlooking the impact of social determinants of health in the interpretation and relevance of the results.
Rationale for stratification is essential as it acknowledges the impact of social determinants of health and helps ensure that the findings are relevant and applicable to diverse populations.
No/Unclear
Yes
b. If the data was stratified by demographic categories, did the authors find the outcomes to be statistically significant?
No/Unclear
Yes
Next
Next
Back
c. How did the authors explain the statistically significant differences for data stratified by race?
Sociological
Biological
No explanation
This is a limitation. Most demographic categories are socially constructed, not scientifically accurate markers for genetic differences. Stating results are different based on biological differences reinforces harmful stereotypes and disregards social determinants of health. The limitation is: The study attributes the differences in outcomes for (insert demographic category being assessed) to biological differences, reinforcing harmful stereotypes, perpetuating health disparities, and leading to misguided healthcare interventions.
Sociological reasoning for differences in data stratified by demographic categories allows researchers to take social determinants of health into account, leading to more accurate, equitable, and effective interventions and avoiding biased care.
This is a limitation. Providing no explanation disregards the impact of social determinants of health, increasing the risk of bias against marginalized populations. The limitation is: The authors did not explain why the results are different for (insert the demographic category being assessed), disregarding the complexities and influence of social determinants of health perpetuating health disparities.
Next
Back
Assess External Validity
Are the study's findings generalizable to real-word practice?
4. Do the patient demographics included in the study align with the patient population you see as a primary care physician?
No/Unclear
Yes
This is a limitation. Patient demographics that do not align with your patient population reduce the generalizability of the results to real-world clinical settings, leading to suboptimal care, especially for those underrepresented in the study. The limitation is: (insert overrepresented demographic such as White males) are overrepresented in this study, limiting the generalizability of the results to other patient populations.
It is vital that the study population mirrors your patient population, increasing the generalizability of the results so the findings can be applied with greater confidence.
Next
Back
Thank you for utilizing The FPIN Bias Assessment!
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This resource is designed as a tool to help identify areas of bias, but there is potential for unrealized bias.
assessing bias
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Transcript
MOBILE
Using a phone? Switch to
The FPIN Bias Assessment
Info
In research studies, it is difficult to recruit a sample that is representative of family physician’s entire population. Some groups may be overrepresented while others are underrepresented. Therefore, some marginalized patient populations may be understudied because of socioeconomic status; race; ethnicity; age; sex; sexual orientation; gender identification; and physical, mental, or cognitive abilities. This can result in inadequate or insufficient data to derive either accurate or generalizable conclusions. This checklist will reveal potential limitations of a research study. When reviewing articles, answering yes does not make the study inherently good and answering no does not make the study inherently bad, but rather reveals limitations.
Start
Assess Internal Validity
Does the study have sound methodology surrounding the recruitment and analysis of marginalized populations to limit bias?
1. Are demographic categories (e.g. race; ethnicity; socioeconomic status; age; sex; sexual orientation; gender identified; and physical, mental, or cognitive abilities) of participating patients provided?
No
Yes
This is a limitation. The absence of demographic information limits the ability to determine the generalizability of the results to other settings, hides biases by not providing information to assess if certain groups were underrepresented, and leads to skewed results that may disproportionately affect or exclude certain populations. This reduces the utility of the research in diverse clinical settings. The limitation is: The absence of demographic information decreases transparency hindering the ability to assess for biases, underrepresentation, and generalizability, reducing the applicability of the results.
Reporting demographic categories ensures transparency, allows a more accurate understanding of how study results apply to various populations, and helps identify healthcare disparities.
Next
Next
Back
Insert education on why ths is important
Next
Back
Are the demographic categories...
Patient-reported demographics reduce the potential for bias by preventing researchers from imposing their assumptions about participants' identities and perpetuating stereotypes and bias. This is crucial when examining health disparities, as demographic misclassification can skew results and obscure the true nature of inequities.
This is a limitation. Investigator-assigned categories can perpetuate marginalization by enforcing binary or narrow demographic labels that may not fit participants' experiences, exacerbating bias and inequity. Additionally, assigning categories perpetuates bias and is disrespectful to the patients. The limitation is: The demographics of this study were not patient-reported, limiting the validity through misclassification bias impacting accuracy and generalizability.
Yes
No/Unclear
a. Patient-reported?
Described in a way that would be easy for another researcher to reproduce.
Clearly defined demographic categories improve reproducibility, enhance transparency, help avoid misclassification, and ensure the results can be correctly understood and applied appropriately in clinical practice. This is particularly important for marginalized groups, where demographic categories can oversimplify their identity, leading to their experiences being misunderstood.
This is a limitation. The lack of clearly defined demographic categories creates hidden or misrepresented health disparities, perpetuating gaps in healthcare for underserved populations. Additionally, a lack of clear definitions may allow for oversimplification and assumptions regarding identities, leading to experiences of marginalized groups being misunderstood. The limitation is: The lack of clearly defined demographic categories may introduce ambiguity and hide health disparities, leading to potential misinterpretation of results, misunderstanding of the experiences of marginalized groups, and the perpetuation of health disparities.
Yes
No/Unclear
b. Clearly defined?
Next
Back
Insert education on why ths is important
Next
Back
Are the demographic categories...
This is a limitation. When patient demographics are not independent of the intervention assignment, bias is introduced, the study's credibility is reduced, and the application of the study results to diverse patient populations is limited. Additionally, this perpetuates disparities by not ensuring everyone has an equal opportunity to receive the intervention. The limitation is: The demographics of the participants were not independent of the intervention assignment, which introduces confounding variables and selection bias, making it difficult to determine whether the intervention or socioeconomic variables are responsible for the outcome of the study
Independent demographic assignment supports the integrity of the research by ensuring each group is comparable in terms of demographic characteristics, strengthening the study's internal validity. It also ensures that all participants have an equal opportunity to receive an intervention, regardless of their background.
c. Independent of the intervention assignment?
Yes
No/Unclear
This is a limitation. If researchers are not blinded to participant demographics while assigning the intervention, they may consciously or unconsciously influence the assignment based on preconceived notions about which groups may benefit from the treatment, skewing the study results. The limitation is: Patient demographics were not blinded when the researchers assigned participants to the intervention, creating a risk for selection bias and potentially skewing the study results.
Blinding researchers to patient demographics ensures the intervention is assigned without conscious or unconscious bias, promoting fairness in how participants are distributed between treatment groups.
d. Blinded when assigning interventions?
Yes
No/Unclear
Next
Back
Insert education on why ths is important
Next
Back
Determine the Applicability of the Results
Applicability refers to the extent to which research findings can be generalized to clinical practice and diverse patient populations.
2. Were potential confounders, such as socioeconomic status, education level, structural racism, and others, identified as factors that could influence intervention response, compliance, or outcome assessment?
No/Unclear
Yes
This is a limitation. Not identifying confounders compromises the applicability of the findings as it does not acknowledge variables other than the intervention or exposure that could influence the study's outcomes. The limitation is: Confounders were not identified in the study, increasing the risk of bias and reducing applicability as it does not acknowledge variables that could influence the results, limiting the ability to draw accurate conclusions.
Recognizing confounders acknowledges that variables other than the intervention or exposure may influence the study's outcomes. Understanding the impact of these variables can guide the statistical analysis and application of the study's findings to diverse populations in clinical settings.
Next
Back
a. If confounders were identified, was an adjusted statistical analysis completed?
No/Unclear
Yes
This is a limitation. Failing to adjust for confounders leaves the study open to confounding bias, where the observed effect may incorrectly be attributed to the intervention rather than the uncontrolled variables. The limitation is: No adjusted statistical analysis was completed, introducing confounding bias and limiting the accuracy and applicability of the findings.
Adjusting for confounders ensures that differences in outcomes are due to the intervention, not external factors, improving the applicability of the results.
Next
Back
3. Was the data stratified by one or more demographic categories?
No/Unclear
Yes
This is a limitation. When one or more demographic categories do not stratify the data of a study, the study results may overlook significant differences in how the intervention impacts different demographic groups, potentially masking health disparities. The limitation is: The data was not stratified by at least one demographic category, masking potentially relevant health disparities and reducing the applicability of the study's findings to diverse patient populations.
Stratifying the data by one or more demographic categories allows for exploring potential health disparities. Understanding how an intervention or exposure may affect subsets of the population is crucial to addressing inequities.
Next
Next
Back
a. If the data was stratified by demographic categories, did the authors provide a rationale for doing so?
This is a limitation. If data has been stratified, and there is no discussion as to why those groups are evaluated, it disregards the impact of social determinants of health, increasing the risk of bias against marginalized populations. The limitation is: The data was stratified by demographic categories without a rationale for doing so, overlooking the impact of social determinants of health in the interpretation and relevance of the results.
Rationale for stratification is essential as it acknowledges the impact of social determinants of health and helps ensure that the findings are relevant and applicable to diverse populations.
No/Unclear
Yes
b. If the data was stratified by demographic categories, did the authors find the outcomes to be statistically significant?
No/Unclear
Yes
Next
Next
Back
c. How did the authors explain the statistically significant differences for data stratified by race?
Sociological
Biological
No explanation
This is a limitation. Most demographic categories are socially constructed, not scientifically accurate markers for genetic differences. Stating results are different based on biological differences reinforces harmful stereotypes and disregards social determinants of health. The limitation is: The study attributes the differences in outcomes for (insert demographic category being assessed) to biological differences, reinforcing harmful stereotypes, perpetuating health disparities, and leading to misguided healthcare interventions.
Sociological reasoning for differences in data stratified by demographic categories allows researchers to take social determinants of health into account, leading to more accurate, equitable, and effective interventions and avoiding biased care.
This is a limitation. Providing no explanation disregards the impact of social determinants of health, increasing the risk of bias against marginalized populations. The limitation is: The authors did not explain why the results are different for (insert the demographic category being assessed), disregarding the complexities and influence of social determinants of health perpetuating health disparities.
Next
Back
Assess External Validity
Are the study's findings generalizable to real-word practice?
4. Do the patient demographics included in the study align with the patient population you see as a primary care physician?
No/Unclear
Yes
This is a limitation. Patient demographics that do not align with your patient population reduce the generalizability of the results to real-world clinical settings, leading to suboptimal care, especially for those underrepresented in the study. The limitation is: (insert overrepresented demographic such as White males) are overrepresented in this study, limiting the generalizability of the results to other patient populations.
It is vital that the study population mirrors your patient population, increasing the generalizability of the results so the findings can be applied with greater confidence.
Next
Back
Thank you for utilizing The FPIN Bias Assessment!
FPIN Website
Restart Tool
This resource is designed as a tool to help identify areas of bias, but there is potential for unrealized bias.