Kevin Sykes

90 timestamped statements across 2 topics — auto-found in recorded discussions, each timestamp jumps to the exact moment.

Featured statements

▶ Ep 4 · 12:43
Oftentimes when you read research around health disparities, the racial categories are aggregated into groups because of numbers. This is particularly true in head and neck cancer where we're talking about a relatively rare cancer in the grand scheme of things, and we start to aggregate racial groups into another category or we'll say there's white, there's African American and black, and then there's everybody else.
quote · Academic Leadership and Health Equity in Otolaryngology
▶ Ep 4 · 0:08
If I'm interviewing you and there's a point at which you say something and you get emotional and you take a pause because you need to collect yourself, I'm going to make a note of that in my transcript. I'm going to take what are called field notes, and field notes are going to say the question about this particular thing had an emotional break.
quote · Academic Leadership and Health Equity in Otolaryngology
▶ Ep 2 · 25:07
If you don't have a reason that race in and of itself is playing a role in your particular outcome, then you should just not collect that data because it's not helpful. Ultimately, it's going to, in the best case scenario, bias you towards something. In the worst case scenario, just really confuse you and make a muddy mess of the analysis.
quote · Head and Neck Cancer
▶ Ep 2 · 30:31
I will always ask the question of in what context it was validated, but was it validated in a population that's similar to my population? If that's not true, then frankly, the conversations about your validity are moot. It doesn't matter. You've asked a question and you think you're getting one answer, but you're actually getting another.
quote · Head and Neck Cancer

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Kevin's statements about Academic Leadership and Health Equity in Otolaryngology 45 statements

Open the Academic Leadership and Health Equity in Otolaryngology collection →

Understanding Health Equity Research w/ Kevin Sykes, PhD, MPH | BackTable ENT Podcast Ep. 152

▶ Ep 4 · 0:08
quote If I'm interviewing you and there's a point at which you say something and you get emotional and you take a pause because you need to collect yourself, I'm going to make a note of that in my transcript. I'm going to take what are called field notes, and field notes are going to say the question about this particular thing had an emotional break. ↗
▶ Ep 4 · 1:57
opinion Dr. Sykes is a cisgender white man whose lived experience does not always reflect the experiences of the communities he works in, which may introduce bias into his thoughts, writing, or work. ↗
▶ Ep 4 · 1:57
quote I think it's really important to disclose first and foremost that I'm a cisgender white man and my lived experience doesn't always reflect the experiences of some of the communities that I work in. And so I think it's really important to kind of ground everything in that frame of reference. ↗
▶ Ep 4 · 8:06
epidemiological Life expectancy varies dramatically by zip code; in Dr. Sykes' current work area, two zip codes have a mean life expectancy of 68 years, one zip code north it increases to 76 years, and two zip codes north it jumps to 90 years. ↗
▶ Ep 4 · 8:23
quote In my current role, the two zip codes that we work in the most have a life expectancy of 68 years. Our mean life expectancy of 68 years. But then when you move one zip code to the north, it increases to 76. If we go to zip codes to the north, it jumps to 90. ↗
▶ Ep 4 · 8:45
epidemiological Life expectancy differences across zip codes are linked to socioeconomics, race, ethnicity, education levels, healthcare access, historical redlining, and segregation of communities. ↗
▶ Ep 4 · 12:43
quote Oftentimes when you read research around health disparities, the racial categories are aggregated into groups because of numbers. This is particularly true in head and neck cancer where we're talking about a relatively rare cancer in the grand scheme of things, and we start to aggregate racial groups into another category or we'll say there's white, there's African American and black, and then there's everybody else. ↗
▶ Ep 4 · 12:59
clinical When racial categories are aggregated into groups (e.g., 'white, African American/Black, and everybody else') for statistical reasons, this hinders the ability to see health inequities within Asian communities and American Indian populations. ↗
▶ Ep 4 · 14:09
quote If our diversity is absent from clinical trials, then we can't be confident that those interventions are effective for all populations and that the data that we've generated are generalizable. ↗
▶ Ep 4 · 14:17
clinical If diversity is absent from clinical trials, we cannot be confident that interventions are effective for all populations or that the data generated are generalizable. ↗
▶ Ep 4 · 15:17
epidemiological Large databases like the National Cancer Database or SEER are not fully representative of safety net community hospitals or areas where historically minoritized communities seek care. ↗
▶ Ep 4 · 16:09
quote We use community health workers because their awareness of what's going on in their population that they work in or that they relate to most when they understand that better than we do, then they understand how to craft the messaging to encourage people to be participants in research. ↗
▶ Ep 4 · 16:09
clinical Using community health workers as part of recruiting teams helps reduce cultural barriers to research participation because they understand their population better than academic researchers do. ↗
▶ Ep 4 · 16:45
clinical Health equity research takes more time and requires budgets that include appropriate compensation for participation and recognize transportation barriers to arriving at healthcare centers. ↗
▶ Ep 4 · 20:44
opinion Community health workers should be included as full-time equivalent key personnel on research grants, not paid $40 per hour only when they show up, because they contribute to study design, recruitment, analysis, and dissemination. ↗
▶ Ep 4 · 20:55
quote They are part of our research design. They are part of our conversations about recruitment. They are part of our conversations about analysis and importantly part of our conversation about dissemination. ↗
▶ Ep 4 · 25:07
clinical If a researcher does not intend to disaggregate data by race to examine outcomes, they should not collect race data because it will either bias the analysis or create confusion. ↗
▶ Ep 4 · 25:07
quote If you don't have a reason that race in and of itself is playing a role in your particular outcome, then you should just not collect that data because it's not helpful. Ultimately, it's going to, in the best case scenario, bias you towards something. In the worst case scenario, just really confuse you and make a muddy mess of the analysis. ↗
▶ Ep 4 · 25:28
quote Are we using race as a proxy for socioeconomics? Are we using race as a proxy for racism? Are we using race as a proxy for some other form of oppression? If that's the case, then we should ask questions about oppression and we should not ask questions about race. ↗
▶ Ep 4 · 25:28
clinical Researchers should not use race as a proxy for socioeconomics, racism, or other forms of oppression; instead, they should directly measure those constructs. ↗
▶ Ep 4 · 27:36
clinical Health equity research requires accepting lower statistical power to achieve reasonable recruitment goals within budget and time constraints, rather than sacrificing population diversity to meet recruitment targets. ↗
▶ Ep 4 · 27:36
quote We may have to accept lower power in order to achieve reasonable recruitment goals within the constructs of whatever the budget may be that's given to us or the sort of time parameters around our research design. ↗
▶ Ep 4 · 28:20
clinical Survey materials must be available in multiple languages, make sense in low-literacy settings, and be administered in private settings when asking about socially undesirable behaviors (drug use, etc.) to avoid making participants uncomfortable. ↗
▶ Ep 4 · 30:31
clinical A validated survey instrument may not be valid in a population different from the one in which it was originally validated; researchers must validate instruments in their target population. ↗
▶ Ep 4 · 30:31
quote I will always ask the question of in what context it was validated, but was it validated in a population that's similar to my population? If that's not true, then frankly, the conversations about your validity are moot. It doesn't matter. You've asked a question and you think you're getting one answer, but you're actually getting another. ↗
▶ Ep 4 · 31:30
opinion Qualitative research provides depth that quantitative research lacks; when researchers sacrifice depth for breadth, they often miss the point of why disparities exist. ↗
▶ Ep 4 · 31:30
quote When we sacrifice depth for breadth, which would be quantitative versus qualitative, then we often miss the point. ↗
▶ Ep 4 · 32:23
clinical Semi-structured interviews allow questions to flow conversationally rather than in a fixed order, which is important for understanding the depth of someone's experiences. ↗
▶ Ep 4 · 32:58
epidemiological There is data to support that Black and African American individuals choose surgery less often than other populations in the context of head and neck cancer, a nuanced question requiring in-depth qualitative interviews to understand. ↗
▶ Ep 4 · 32:58
quote There's some data out there to support the fact that our black African American individuals and populations choose surgery less often than other populations in the context of head and neck cancer, and that's a very nuanced question, and a very nuanced research question requires a very nuanced research method. ↗
▶ Ep 4 · 33:48
quote Your goal of a qualitative study is never generalizability. Your goal is exploration of a concept or a phenomenon. ↗
▶ Ep 4 · 33:48
clinical The goal of qualitative research is exploration of a concept or phenomenon, not generalizability; it informs how to design quantitative studies and ask questions in ways that capture the experiences of diverse populations. ↗
▶ Ep 4 · 36:00
clinical Qualitative analysis involves verbatim transcription, field notes documenting emotional moments, independent coding by two reviewers, identification of themes, thematic saturation when no new themes emerge, and member checking with participants to validate findings. ↗
▶ Ep 4 · 41:41
opinion Research is about building relationships with participants; without proper relationships, researchers cannot be confident that the information participants provide reflects their true experience. ↗
▶ Ep 4 · 41:41
quote Research is about a relationship and if we don't build relationships with our participants, then we have no opportunity to allow them to contribute to the work or partner with them to contribute to work in the future, nor do we have any confidence that the information they've given us today is really reflective of their true experience. ↗
▶ Ep 4 · 43:27
opinion Physicians are particularly well-positioned to advocate for marginalized populations with policymakers because policymakers will listen to them. ↗
▶ Ep 4 · 43:27
quote We have advocacy that we need to do, whether we are in a position of power like I am oftentimes because I'm a researcher that's highly educated in all these kinds of things and we have to ask questions about what's my role in advocating for populations who are marginalized and physicians are particularly well positioned to have these conversations with their policymakers at the state, at the local, state and federal level because they will listen to you. ↗
▶ Ep 4 · 44:22
clinical In Indiana, researchers used county-level life expectancy data to secure bipartisan support for sustained public health funding by arguing that investment in public health can improve outcomes, similar to how investment in education improved educational outcomes. ↗
▶ Ep 4 · 45:00
quote They went to their policymakers and they said, we've made a lot of progress on education because we invested in education. Look at all the progress we've made. Look at how much better we're doing. The policymakers said, Yeah, we've made a lot of progress in education because we did invest. ↗
▶ Ep 4 · 46:32
quote We have to figure out how do we use data that's going to mean something to this particular policymaker and how do we tell that story with a lens or through a megaphone, if you will, that's going to speak to them and that they're going to hear, and we have to be sensitive to what their motivations are and then cater our data accordingly. ↗
▶ Ep 4 · 48:45
opinion Medical students today are more sensitive to health equity issues because media and globalized society expose them to differences in quality of life and the plight of others in different parts of the world. ↗
▶ Ep 4 · 49:49
opinion Medical education needs to include health equity researchers speaking to students, inviting them to grand rounds, and changing morbidity and mortality conferences to include questions about health equity. ↗
▶ Ep 4 · 53:28
clinical The inaugural GSK Health Equity grant aims to establish an expert consensus on a uniform data set for health disparities measurement in head and neck cancer, identifying the most meaningful, relevant, and practical data points everyone should collect. ↗
▶ Ep 4 · 54:49
clinical The GSK grant's second aim is to apply the uniform data set in a prospective multi-center observational study at 6 centers to determine if it can predict higher stage of presentation with head and neck cancer, with secondary analyses examining discontinuity of care and timely radiotherapy after surgery. ↗
▶ Ep 4 · 55:46
clinical The GSK grant project uses a pragmatic design to assess not only model performance but also implementation barriers, aiming to identify variables that are meaningful but impractical to collect before launching a widespread national project. ↗
Kevin's statements about Head and Neck Cancer 45 statements

Open the Head and Neck Cancer collection →

Understanding Health Equity Research w/ Kevin Sykes, PhD, MPH | BackTable ENT Podcast Ep. 152

▶ Ep 2 · 0:08
quote If I'm interviewing you and there's a point at which you say something and you get emotional and you take a pause because you need to collect yourself, I'm going to make a note of that in my transcript. I'm going to take what are called field notes, and field notes are going to say the question about this particular thing had an emotional break. ↗
▶ Ep 2 · 1:57
quote I think it's really important to disclose first and foremost that I'm a cisgender white man and my lived experience doesn't always reflect the experiences of some of the communities that I work in. And so I think it's really important to kind of ground everything in that frame of reference. ↗
▶ Ep 2 · 1:57
opinion Dr. Sykes is a cisgender white man whose lived experience does not always reflect the experiences of the communities he works in, which may introduce bias into his thoughts, writing, or work. ↗
▶ Ep 2 · 8:06
epidemiological Life expectancy varies dramatically by zip code; in Dr. Sykes' current work area, two zip codes have a mean life expectancy of 68 years, one zip code north it increases to 76 years, and two zip codes north it jumps to 90 years. ↗
▶ Ep 2 · 8:23
quote In my current role, the two zip codes that we work in the most have a life expectancy of 68 years. Our mean life expectancy of 68 years. But then when you move one zip code to the north, it increases to 76. If we go to zip codes to the north, it jumps to 90. ↗
▶ Ep 2 · 8:45
epidemiological Life expectancy differences across zip codes are linked to socioeconomics, race, ethnicity, education levels, healthcare access, historical redlining, and segregation of communities. ↗
▶ Ep 2 · 12:43
quote Oftentimes when you read research around health disparities, the racial categories are aggregated into groups because of numbers. This is particularly true in head and neck cancer where we're talking about a relatively rare cancer in the grand scheme of things, and we start to aggregate racial groups into another category or we'll say there's white, there's African American and black, and then there's everybody else. ↗
▶ Ep 2 · 12:59
clinical When racial categories are aggregated into groups (e.g., 'white, African American/Black, and everybody else') for statistical reasons, this hinders the ability to see health inequities within Asian communities and American Indian populations. ↗
▶ Ep 2 · 14:09
quote If our diversity is absent from clinical trials, then we can't be confident that those interventions are effective for all populations and that the data that we've generated are generalizable. ↗
▶ Ep 2 · 14:17
clinical If diversity is absent from clinical trials, we cannot be confident that interventions are effective for all populations or that the data generated are generalizable. ↗
▶ Ep 2 · 15:17
epidemiological Large databases like the National Cancer Database or SEER are not fully representative of safety net community hospitals or areas where historically minoritized communities seek care. ↗
▶ Ep 2 · 16:09
clinical Using community health workers as part of recruiting teams helps reduce cultural barriers to research participation because they understand their population better than academic researchers do. ↗
▶ Ep 2 · 16:09
quote We use community health workers because their awareness of what's going on in their population that they work in or that they relate to most when they understand that better than we do, then they understand how to craft the messaging to encourage people to be participants in research. ↗
▶ Ep 2 · 16:45
clinical Health equity research takes more time and requires budgets that include appropriate compensation for participation and recognize transportation barriers to arriving at healthcare centers. ↗
▶ Ep 2 · 20:44
opinion Community health workers should be included as full-time equivalent key personnel on research grants, not paid $40 per hour only when they show up, because they contribute to study design, recruitment, analysis, and dissemination. ↗
▶ Ep 2 · 20:55
quote They are part of our research design. They are part of our conversations about recruitment. They are part of our conversations about analysis and importantly part of our conversation about dissemination. ↗
▶ Ep 2 · 25:07
quote If you don't have a reason that race in and of itself is playing a role in your particular outcome, then you should just not collect that data because it's not helpful. Ultimately, it's going to, in the best case scenario, bias you towards something. In the worst case scenario, just really confuse you and make a muddy mess of the analysis. ↗
▶ Ep 2 · 25:07
clinical If a researcher does not intend to disaggregate data by race to examine outcomes, they should not collect race data because it will either bias the analysis or create confusion. ↗
▶ Ep 2 · 25:28
clinical Researchers should not use race as a proxy for socioeconomics, racism, or other forms of oppression; instead, they should directly measure those constructs. ↗
▶ Ep 2 · 25:28
quote Are we using race as a proxy for socioeconomics? Are we using race as a proxy for racism? Are we using race as a proxy for some other form of oppression? If that's the case, then we should ask questions about oppression and we should not ask questions about race. ↗
▶ Ep 2 · 27:36
quote We may have to accept lower power in order to achieve reasonable recruitment goals within the constructs of whatever the budget may be that's given to us or the sort of time parameters around our research design. ↗
▶ Ep 2 · 27:36
clinical Health equity research requires accepting lower statistical power to achieve reasonable recruitment goals within budget and time constraints, rather than sacrificing population diversity to meet recruitment targets. ↗
▶ Ep 2 · 28:20
clinical Survey materials must be available in multiple languages, make sense in low-literacy settings, and be administered in private settings when asking about socially undesirable behaviors (drug use, etc.) to avoid making participants uncomfortable. ↗
▶ Ep 2 · 30:31
clinical A validated survey instrument may not be valid in a population different from the one in which it was originally validated; researchers must validate instruments in their target population. ↗
▶ Ep 2 · 30:31
quote I will always ask the question of in what context it was validated, but was it validated in a population that's similar to my population? If that's not true, then frankly, the conversations about your validity are moot. It doesn't matter. You've asked a question and you think you're getting one answer, but you're actually getting another. ↗
▶ Ep 2 · 31:30
quote When we sacrifice depth for breadth, which would be quantitative versus qualitative, then we often miss the point. ↗
▶ Ep 2 · 31:30
opinion Qualitative research provides depth that quantitative research lacks; when researchers sacrifice depth for breadth, they often miss the point of why disparities exist. ↗
▶ Ep 2 · 32:23
clinical Semi-structured interviews allow questions to flow conversationally rather than in a fixed order, which is important for understanding the depth of someone's experiences. ↗
▶ Ep 2 · 32:58
epidemiological There is data to support that Black and African American individuals choose surgery less often than other populations in the context of head and neck cancer, a nuanced question requiring in-depth qualitative interviews to understand. ↗
▶ Ep 2 · 32:58
quote There's some data out there to support the fact that our black African American individuals and populations choose surgery less often than other populations in the context of head and neck cancer, and that's a very nuanced question, and a very nuanced research question requires a very nuanced research method. ↗
▶ Ep 2 · 33:48
quote Your goal of a qualitative study is never generalizability. Your goal is exploration of a concept or a phenomenon. ↗
▶ Ep 2 · 33:48
clinical The goal of qualitative research is exploration of a concept or phenomenon, not generalizability; it informs how to design quantitative studies and ask questions in ways that capture the experiences of diverse populations. ↗
▶ Ep 2 · 36:00
clinical Qualitative analysis involves verbatim transcription, field notes documenting emotional moments, independent coding by two reviewers, identification of themes, thematic saturation when no new themes emerge, and member checking with participants to validate findings. ↗
▶ Ep 2 · 41:41
opinion Research is about building relationships with participants; without proper relationships, researchers cannot be confident that the information participants provide reflects their true experience. ↗
▶ Ep 2 · 41:41
quote Research is about a relationship and if we don't build relationships with our participants, then we have no opportunity to allow them to contribute to the work or partner with them to contribute to work in the future, nor do we have any confidence that the information they've given us today is really reflective of their true experience. ↗
▶ Ep 2 · 43:27
quote We have advocacy that we need to do, whether we are in a position of power like I am oftentimes because I'm a researcher that's highly educated in all these kinds of things and we have to ask questions about what's my role in advocating for populations who are marginalized and physicians are particularly well positioned to have these conversations with their policymakers at the state, at the local, state and federal level because they will listen to you. ↗
▶ Ep 2 · 43:27
opinion Physicians are particularly well-positioned to advocate for marginalized populations with policymakers because policymakers will listen to them. ↗
▶ Ep 2 · 44:22
clinical In Indiana, researchers used county-level life expectancy data to secure bipartisan support for sustained public health funding by arguing that investment in public health can improve outcomes, similar to how investment in education improved educational outcomes. ↗
▶ Ep 2 · 45:00
quote They went to their policymakers and they said, we've made a lot of progress on education because we invested in education. Look at all the progress we've made. Look at how much better we're doing. The policymakers said, Yeah, we've made a lot of progress in education because we did invest. ↗
▶ Ep 2 · 46:32
quote We have to figure out how do we use data that's going to mean something to this particular policymaker and how do we tell that story with a lens or through a megaphone, if you will, that's going to speak to them and that they're going to hear, and we have to be sensitive to what their motivations are and then cater our data accordingly. ↗
▶ Ep 2 · 48:45
opinion Medical students today are more sensitive to health equity issues because media and globalized society expose them to differences in quality of life and the plight of others in different parts of the world. ↗
▶ Ep 2 · 49:49
opinion Medical education needs to include health equity researchers speaking to students, inviting them to grand rounds, and changing morbidity and mortality conferences to include questions about health equity. ↗
▶ Ep 2 · 53:28
clinical The inaugural GSK Health Equity grant aims to establish an expert consensus on a uniform data set for health disparities measurement in head and neck cancer, identifying the most meaningful, relevant, and practical data points everyone should collect. ↗
▶ Ep 2 · 54:49
clinical The GSK grant's second aim is to apply the uniform data set in a prospective multi-center observational study at 6 centers to determine if it can predict higher stage of presentation with head and neck cancer, with secondary analyses examining discontinuity of care and timely radiotherapy after surgery. ↗
▶ Ep 2 · 55:46
clinical The GSK grant project uses a pragmatic design to assess not only model performance but also implementation barriers, aiming to identify variables that are meaningful but impractical to collect before launching a widespread national project. ↗