Science topic

# Health Outcomes - Science topic

Explore the latest questions and answers in Health Outcomes, and find Health Outcomes experts.
Questions related to Health Outcomes
• asked a question related to Health Outcomes
Question
I'm designing a study to estimate the proportion of girls having challenges accessing menstrual health products and materials. The sampling approach I plan to use is a multi-stage clustered sampling design with probability proportional to size. 12 counties with poor educational and sexual and reproductive health outcomes will be selected to participate. Following this, administrative wards will be randomly selected from the 12 counties of interest (Number of wards per county are available online). The wards will be selected systematically with urban/rural stratification from the 12 counties (Not yet sure of the number of wards to include per county - this is part of the question as well). For each sampled ward, a complete list of public primary and secondary schools will be made from which a random selection of schools to participate in the study will be done. Following schools’ selection, random sampling will be used to select adolescent girls from a sampling frame generated from the class registers. Only girls in grades 4-8 meeting the eligibility criteria and those in secondary schools will be included. A situational analysis commissioned by the Ministry of Health in Kenya showed that 54% (58% in rural and 53% in urban areas) of Kenyan girls faced challenges accessing menstrual health hygiene products. From these estimates, how do I calculate my sample size seeing that this is a complex survey or which is the most appropriate formula to use?
Thanks
Calculating the sample size for a complex multi-stage sampling design involves several steps. I will guide you through the process.
Step 1: Determine the required level of precision
The level of precision refers to how close you want your estimate to be to the true population value. This is usually expressed as a margin of error (MOE) or confidence interval. For example, if you want to estimate the proportion of girls facing challenges accessing menstrual health hygiene products within a specific margin of error (e.g., +/- 3%), you would need to determine the desired level of precision.
Step 2: Determine the desired level of confidence
The level of confidence refers to the probability that the true population parameter falls within the estimated interval. Common levels of confidence are 95% or 99%. Decide on the level of confidence you would like for your study.
Step 3: Adjust the sample size for the design effect
In complex multi-stage sampling designs, there is often a design effect that accounts for the clustering and stratification. The design effect is a measure of how much larger the required sample size is compared to a simple random sample. It accounts for the correlation among participants within the same cluster or stratum. The design effect varies depending on the specific design and analysis plan. For now, let's assume a design effect of 2 for your study.
Step 4: Calculate the initial sample size
To calculate the initial sample size, you will need to use a formula appropriate for estimating proportions. The most commonly used formula is the one for calculating sample size for a simple random sample:
n = [(Z^2 * p * (1-p)) / MOE^2]
where:
n is the required sample size
Z is the z-score corresponding to the desired level of confidence (e.g., 1.96 for 95% confidence)
p is the estimated proportion of the population with the characteristic of interest (use 0.54 as the estimated proportion)
MOE is the margin of error expressed as a decimal (e.g., 0.03 for +/- 3% MOE)
Using this formula will give you the required sample size for a simple random sample.
Step 5: Adjust the sample size for the design effect
To adjust the sample size for the design effect in multi-stage sampling, you will multiply the initial sample size by the design effect:
final_sample_size = initial_sample_size * design_effect
For example, if your initial sample size calculated in Step 4 is 400, and the design effect is 2, the final sample size would be 400 * 2 = 800.
Step 6: Determine the number of clusters or units at each stage
At each stage of the sampling design, you need to determine the number of clusters or units to select. For example, you mentioned selecting 12 counties, wards within each county, and schools within each ward. The number of clusters or units at each stage will depend on the population size and the desired precision. It is important to consult resources specific to your study area or consult with a statistician to determine the appropriate number of clusters or units at each stage.
Considering the complexity of your sampling design, it would be beneficial to consult with a statistician to properly determine the final sample size and the number of clusters or units at each stage based on the specific details of your study.
• asked a question related to Health Outcomes
Question
I am reviewing some papers and am trying to understand why in a study the researchers have chosen to categorise age of injury (into early age 0-9 and later age 9+) when looking at outcomes. Would it not make sense to leave age as continuous variable? If so how would this be analysed? For context this is to see if age of brain injury predicts or results in poor mental health outcomes. The outcomes can be entered as whole number scores or could be categorised into clinical/non-clinical severities.
thanks
Logistic regression refers to the outcome - any regression can include a mixture of continuous or categorical predictors. In this context, the question as to whether or not it is better to use age as a continuous or categorical variable will largely depend on the nature of the relationship between age and the outcome. In theory, categorising the variable loses information and so keeping it as a continuous variable is, on the face of it preferable. However, if, as seems likely, the relationship between age and the outcome is not a linear one (because, for example, of developmental differences) categorizing it may be a simple way of dealing with such non-linearity. There are other approaches but categorisation is an easily implemented one that is potentially valid - provided the cut point makes biological sense. I think the arguments about categorizing the outcome are less compelling if it is measured on a continuous scale although if there are clear diagnostic cut points doing so (and thus changing to a logistic regression model) may aid interpretation.
• asked a question related to Health Outcomes
Question
"Avoiding a hostile emotional climate at home won’t necessarily prevent poor mental health outcomes from occurring, but it will probably help"
Ioannis Katsantonis
Easier said than done. Avoidance strategy does not solve existing problems
• asked a question related to Health Outcomes
Question
I want to conduct a meta-analysis on the association between substance use and mental health outcomes, and I want to do a pooled ORs between these two variables. However, some studies may report their results as a continuous variable (e.g., substance use was associated with a higher PHQ-9 score) instead of a dichotomized variable. What should I do with these studies? I have read papers - some of them did not include those studies, and some said, "Where studies did not report prevalence estimates or ORs, these were calculated from raw data where possible".
Is there a standard approach?
It is mathematically possible to convert between the odds ratio, actually the log of the odds ratio, and the standardized mean difference. See Chapter 7 in "Introduction to Meta-Analysis" by Borenstein et al (2021). As already pointed out, you will have to justify doing that conversion.
• asked a question related to Health Outcomes
Question
This research question seeks to understand how a lack of physical activity affects mental health. Specifically, it seeks to identify the impact of leading a sedentary lifestyle on the mental well-being of individuals. It will explore any potential correlations between lack of physical activity and mental health issues such as depression, anxiety, and stress. Additionally, this research will investigate potential interventions and strategies that can be used to improve mental health outcomes for those living a sedentary lifestyle.
A sedentary lifestyle has been shown to have negative impacts on mental health, which can be mitigated through targeted interventions and strategies. This view presents potential interventions and strategies to improve mental health outcomes for individuals living a sedentary lifestyle.
One potential intervention is physical activity. Regular physical activity has been associated with improved mental health outcomes, such as the reduced risk of depression, anxiety, and cognitive decline. Physical activity interventions can include group exercise classes, one-on-one personal training, or community-based programs, which can promote social interaction and support.
Another potential intervention is mindfulness-based practices. Mindfulness-based practices, such as meditation and yoga, have been shown to improve mental health outcomes by reducing stress, anxiety, and depression. These practices can be incorporated into a sedentary lifestyle through online classes, mobile applications, or guided meditation recordings.
Technology-based interventions, such as telehealth services, can also be effective in improving mental health outcomes for those living a sedentary lifestyle. Telehealth services can provide access to mental health professionals, support groups, and self-help resources, which can be accessed from the comfort of one's home. This can be particularly useful for individuals who have limited access to physical resources or live in remote areas.
In addition to these interventions, the adoption of healthy lifestyle habits, such as a balanced diet and sufficient sleep, can also improve mental health outcomes for those living a sedentary lifestyle. A balanced diet rich in nutrients can provide the body with the necessary fuel to function optimally, while sufficient sleep can help reduce stress and anxiety.
In conclusion, a sedentary lifestyle can have negative effects on mental health outcomes, but interventions and strategies such as physical activity, mindfulness-based practices, technology-based interventions, and healthy lifestyle habits can be effective in improving mental health outcomes for individuals living a sedentary lifestyle. It is important to tailor interventions and strategies to individual needs and preferences to promote engagement and adherence. Further research is needed to determine the most effective interventions and strategies for specific populations.
• asked a question related to Health Outcomes
Question
Nursing is a profession that focuses on patient centered and holistic approach to care and achieving positive health outcomes for patients. However, at times nurses fall short in achieving patient centered and holistic care and positive outcomes.
What are the key ingredients to achieving patient centered care and positive care outcomes for patients in healthcare?
How do make these work in practice?
Patient-centered care is an approach to healthcare that prioritizes the needs, preferences, and values of the patient. It is a holistic approach that focuses on the whole person, rather than just their illness or condition. This approach has been shown to lead to better health outcomes, increased patient satisfaction, and improved healthcare experiences.
The key ingredients to achieving patient-centred care and positive outcomes for patients in healthcare include:
1. Communication: Clear and effective communication between healthcare providers and patients is essential to understanding and addressing the patient's needs and preferences.
2. Empathy: Empathy is the ability to understand and share the feelings of others. It is important for healthcare providers to be empathetic towards their patients, as it helps to build trust and understanding.
3. Patient involvement: Patient involvement in their care is essential for patient-centered care. Patients should be involved in decision-making, goal-setting, and treatment planning.
4. Coordination: Coordination of care is essential for ensuring that patients receive the right care, at the right time, and in the right place.
5. Accessibility: Accessibility is important for ensuring that patients can access the care they need when they need it.
6. Continuity: Continuity of care is important for ensuring that patients receive consistent, high-quality care over time.
To implement these ingredients, healthcare providers and organizations should establish a culture that prioritizes patient-centred care, train their staff to communicate effectively with patients, and involve patients in their care. They should also create systems and processes that facilitate coordination and continuity of care, and ensure that care is accessible to all patients. Additionally, it's important to measure and track the progress of patient outcomes and use these insights to improve patient care.
• asked a question related to Health Outcomes
Question
Hello,
I am looking for a publicly available database that contains data on maternal demographics as well as their children's health outcomes, cancer incidences, etc.
Any suggestions?
Best,
Amr
INTRODUCTION
Childhood cancer has been increasing in
Scotland. A published report estimates that
its incidence has risen from an age standardised rate of 120 cases per million population in the time period 1983–1987 to 161
cases per million in the period 2003–2007.1
The reason for this increasing trend remains
unexplained as the aetiopathogenesis of
childhood cancer is poorly understood. As
most of the children present with cancer in
the first few years of life, epidemiologists
hypothesise that prenatal and perinatal exposures may have a part to play in its pathogenesis. The evidence surrounding this is,
however, conflicting. While some researchers
have found associations of younger maternal
age at delivery2 maternal anaemia,3 4 history
of miscarriage,256 maternal overweight7 and
smoking8 with some childhood cancers,
others have found no such associations.9–11
Fetal growth is perhaps the most investigated
perinatal risk factor for childhood
cancer7 12 13; but the authors report conflicting results. While specific central nervous
system tumours have been found to be associated with intrauterine growth restriction
(IUGR), the overall risk was small.12
Therefore, apart from the associations with
Down’s syndrome and in utero exposure to
radiation, research into the maternal and
perinatal risk factors has remained inconsistent, the results limited by small sample sizes
and recall or reporting bias.
Our objective was, therefore, to investigate
the maternal and perinatal risk factors for
childhood cancer, specifically to examine the
effects of IUGR, preterm birth and birth
asphyxia on the development of childhoodcancer in the offspring, taking advantage of the opportunities offered by record linkage of a cancer registry
with a local birth register.
odel.
Conclusions: Younger maternal age, maternal
smoking, delivery by caesarean section and low Apgar
score at 5 min were independently associated with
increased risk of childhood cancer. These general
findings should be interpreted with caution as this
study did not have the power to detect any association
with individual diagnostic categories of childhood
cancer.
• asked a question related to Health Outcomes
Question
I am interested in understanding which could be the best spectrum of topics for a research study (academic) in the area of Long-Term Conditions and Telehealth applications knowing that the research project would be undertaken by a Clinician knowledgeable about medicine and care, in addition to frontline processes (in primary, secondary and tertiary care settings), but lacking specialised programming and IT knowledge. Sociotechnical systems theory? To understand the optimal generation of health outcomes in generic contexts?
Project can be on "Impact of Telehealth platforms on reducing adverse morbidity from chronic health condition and increasing DALY"
I am a Telemedicine expert and will like to be part of your research study. my email is noblesmathsmagic@gmail.com
• asked a question related to Health Outcomes
Question
I am conducting a Systematic Literature Review about the relationship between active transportation modes and mental health and it has been pointed out to me that there are too many mental health outcomes, and I should narrow it down. Accordingly to the most recent knowledge and trends and your expertise on the topic, I would appreciate your opinion.
Thank you!
Mental health is the ability to self-regulate your moods.
• asked a question related to Health Outcomes
Question
While color psychology is the study of how different colors can influence human behavior and perception, color therapy is different. It is based upon the unproven assumption that certain colors can impact people's "energy" and impact health outcomes.
The underlying principle of Colour Therapy is that every cell and organ in the body vibrates at a particular frequency, as do colours.
• asked a question related to Health Outcomes
Question
Hi all,
To determine the impact of policy implementation on health outcomes (count), I used a difference-in-difference (DID) approach with a negative binomial GEE model.
I would appreciate insight on how to word the DID-interaction for the paper.
Thank you all for your time.
I generally find the easiest way to 'word' a report of an interaction in these circumstances is to plot the relevant coefficients. Assuming a relatively simple situation picture you have two cases (with/without policy) and outcomes at t1 and t2.
A significant interaction term is evidence that any difference in slope from t1 to t2 for the two cases is not likely to arise simply due to chance (assuming all parameter assumptions of your model is correct) - so it is evidence of a 'difference in difference'. Having plotted it (I assume your outcome is some sort of rate) then you can interpret it (and describe it) in terms of whether (and how) the rate has changed more in one case than another. The interaction term itself isn't easily interpretable unless you use it to plot the effects. Hopefully your software can give you the plots but otherwise it is relatively trivial to calculate (and then plot) the marginal effects (assuming all other values in the model are at the mean or reference value) as the product of parameter X main effects X the interaction term.
I hope that helps!
Peter
• asked a question related to Health Outcomes
Question
Cost-effectiveness of intervention is estimated by dividing cost of intervention to health outcome. DALY, cases averted, deaths averted etc. are commonly used by studies as health outcome. Can incidence rate be used as health outcome of intervention or how it can be converted to commonly used health outcomes?
Thank you?
Robert Boer, thanks again!
Your suggestion simplify things but although we estimated equal sample size, response rate may introduce minor variations.
• asked a question related to Health Outcomes
Question
1. My understanding is that when conducting an economic evaluation of clinical trial data, no discounting of costs is applied if the follow-up period of the trial was 12 months or less. Is this still the standard practice and can you please provide a recent reference?
2. How can one adjust for uncertainties/biases when you use historic health outcomes data? If the trial was non-randomised, how can you adjust for that within an economic evaluation other than the usual probabilistic sensitivity analysis?
Thank you so much.
Hi,
Maybe some of these references are of help to you:
Economic Evaluation in Clinical Trials By Henry A. Glick, Jalpa A. Doshi, Seema S. Sonnad, Daniel Polsky 2014 | 272 Pages | ISBN: 0199685029
Economic Evaluation of Cancer Drugs: Using Clinical Trial and Real-World Data by Iftekhar Khan, Ralph Crott, et al. English | 2019 | ISBN: 1498761305 | 442 pages
Design & analysis of clinical trials for economic evaluation & reimbursement: an applied approach using SAS & STATA
Iftekhar Khan
Series: Chapman & Hall/CRC biostatistics series
Publisher: CRC Press, Year: 2015
ISBN: 978-1-4665-0548-3,1466505486
Methods for the Economic Evaluation of Health Care Programmes
Michael F. Drummond, Mark J. Sculpher, Karl Claxton, Greg L. Stoddart, George W. Torrance,ISBN: 0199665877 | 2015 | 461 pages |
• asked a question related to Health Outcomes
Question
Dear Researchers,
Preliminary data of various studies showed the proportion of the population from Black (in New York), Asian (UK) and other minority ethnic backgrounds and people from low income are highly deprived with COVID-19. These groups reported higher COVID-19 mortality rates irrespective of population density. Furthermore, most of these minority groups are aged 50-79. Since the epidemic started, several studies have confirmed these findings. It is interesting to discuss the reasons behind these adverse outcomes and also share your experience about COVID-19.
Also see the following RG links for better insights.
• asked a question related to Health Outcomes
Question
I was wondering if anyone knows of a database containing nationally representative information on individuals with depression, anxiety, or any other measurable mental health outcome. The data I am looking for should be related to the United States.
Any help in this matter is appreciated.
Sheikh Shoib have a look please
• asked a question related to Health Outcomes
Question
I am exploring the dose-response relationship between intervention use and improvement in health outcomes. The use of intervention component A, B, C, and D are positively correlated to the improved health outcomes. But in the multi linear regression, the beta value of component C become negative, and multicollinearity test have VIF<5. How to interpret/resolve this? Many thanks.
Correlation is an association between two variables. It ranges from+1 to -1! Strongly correlated variables cannot be placed in the same model, especially for linear regression model! Placing in the same model can lead to mutlicollinearity! Regression model is not related to correlation analysis
• asked a question related to Health Outcomes
Question
I'm investigating the effect of economic freedom on health outcomes in Sub-saharan Africa. I use panel data which N=37 and T= 19. When I tape xtset idc and year, Stata told me it's strongly balanced. I would like to ask you if I can use the lsdvc estimator method? Or is there another estimator than GMM or 2SLS, because I've use it before
The Least Square Dummy Variable (LSDV) estimator for dynamic panel data models is not consistent for N large and finite T.
• asked a question related to Health Outcomes
Question
As a part of my PhD, I conducted a study to assess health inequities in Amaravati capital region of Andhra Pradesh using two composite indices made from health determinants indicators and health outcome indicators.
Health outcome indicators data was available at the sub-district level. The data were interpolated to create a heatmap of the health outcome index. Whereas health determinants data was available at the village level. Thus I created a choropleth map using the health determinants index.
Later interpolated health outcome index map was overlayered on the choropleth map of health outcomes. It highlighted some interesting findings, i.e. areas of concern (Villages). The colour combinations created because of overlaying two layers revealed the areas with poor health outcomes and poor health determinants and areas with poor health outcomes with better determinants.
Kindly check these files and give your valuable opinions. Whether this type of analysis can be used to highlight the areas with health inequities or not? Please comment on the method used and the results obtained in the overlayered map.
The OPGD model and "GD" R software package were recommended to identify spatial determinants from a perspective of spatial heterogeneity. You can refer the guide to use the model https://cran.r-project.org/web/packages/GD/vignettes/GD.html. As a result, you can visualise contributions of determinants, and the interactive impacts of spatial variables.
• asked a question related to Health Outcomes
Question
Hello honorables,
Please I am designing a study that investigates the linkage between certain health outcomes and wildfire-driven air pollution. Is there a simple way we can derive these air pollutants from fire ignition points?
Thank you for your invaluable suggestions.
I suggest you consider greatly expanding the concept of pollution to include the combined effects of the global pandemic and the global devastation from the fires (climate change). One is very local (internal pollution) the other widespread. But together will add to an extended effort to recover...my guess if we're lucky and both subside, beyond 10 years. If the fires, the extreme heat, storms and disease stay the current course (some are expected to worsen) way beyond that.
• asked a question related to Health Outcomes
Question
I am conducting a study on multiple marginalized identities and mental health outcomes.
What would be the best data analysis I should use to assess the interaction between different variables and the way they intersect with each other.
Thank you
I think that a mixed methods study which includes a qualitative analysis could be better to assess that intersectionality. I did It in my masters' research and I found Very positively results.
You can acess it at this link:
• asked a question related to Health Outcomes
Question
I need help with proxies I can use for health outcomes aside mortality and morbidity rate and the source of data.
You will increase the chance of more helpful answers if you describe with greater precision what you actually want.
• asked a question related to Health Outcomes
Question
Climate change disaster is a great amplifier of health inequities. It is already affecting and will continue to affect vulnerable populations’ health and well-being like migrants, both in Canada and internationally. We are conducting a critical scoping review to explore work that has been done to examine and address the needs, challenges, experiences, and health outcomes of immigrant populations. Your critical reflections and suggestion will be helpful.
Some of the immigrants are moving away from their homes because of war (Afghanistan towards Europe) others because of poverty (Africans towards Europe) and still others because of flooding and climate change effects.
In all these cases, they suffer due to lack of proper health conditions on their way until they settle in a new country.
If the newcomers settle in Canada for instance, they will be looked after and have no ill effects.
A good example of sufferers from climate change effects are the people in Honduras and Nicaragua after they were hit twice by damaging hurricanes. The countries are poor and couldn't look after their health needs even before the hurricanes. Now they have a good reason to immigrate.
• asked a question related to Health Outcomes
Question
I am trying to see if there's a connection between globalization and health outcome. Going through the KOFGI data set, there are different categories or forms of globalization which includes : social globalization, financial globalization, trade globalization and more. Also , there's dejure which is the policy that preceded the actual globalization event and defacto which is the actual globalization event. I would appreciate if anyone could suggest a good journal or journals that discussed empirical analysis of the globalization-health outcome nexus.
Best Regards
A google search will yield a myriad of references, eg WHO, NIH and the like. You can also go for specific discussions on nutrition outcomes and globalization. Or health outcomes and international trade. There were papers on globalization and disease, tackling SARS from around 2004.
• asked a question related to Health Outcomes
Question
It is glaring that Medical Data collection in healthcare allows health systems to create holistic views of patients, personalize treatments, advance treatment methods, improve communication between doctors and patients, and enhance health outcomes.
Inconsistent medical data have grave effects on proper planning of health care system. How can the problems of inconsistency in medical data be tackled, in various health institutions?
The question becomes the degree to which national economies are affected by disease burdens when the nature of that burden is unclear because of different standards of reportage. Similarly, if you mean data on supply--for instance ventilators or certain medications--if unreliable the limits of those records will result in a lack of resources at treatment sites. The effect on the economy in the first will involve the cost of unanticipated disease incidence or the expansion of diseases (for example in epidemic cases) that might have been anticipated, with better records, and thus better prepared for. Similarly, if it's about supply of equipments or pharmaceuticals the shortages that result from inconsistent records will mean either higher costs for emergency purchase or higher mortality/morbidity in the absence of necessary equipment or pharmaceuticals. If the numbers are sufficient--for instance provision of vaccines, or undercounting of those with critical conditions requiring extensive medication, the effect may be broadly economic as well as clnical.
• asked a question related to Health Outcomes
Question
I am writing a new proposal for my Thesis. I want to know what of the research methodology will be appropriate.
The method will depend upon your research hypothesis and/or research questions. Qualitative methods are good for general experiences - like what is it like to be ill from COVID-19? Quantitative methods are best for specific outcomes - fatigue, respiratory distress on the patient level. Or impact on the economics of a city or country. I'm thinking this is a master's thesis. Look at what access to data you have. One of the as yet under-reported stats are the death rates from COVID in different parts of a country, or in the US, a state. There are number of variables that affect death rates including quality of hospital care besides where people work, general access to care. Good luck!
• asked a question related to Health Outcomes
Question
I am currently looking for ways/methods to separate air pollution from mobile (vehicles) and industrial sources, if any. I need this information to be compared to health outcomes later on (YLL, DALY, that kind of analysis).
I do have separate emission information from industrial and vehicle sources for the area, but it's difficult to associate emissions to measured concentrations, and in my viewpoint it would be very questionable to compare emission information to health data later on, which would increase uncertainties even more. As far as I know, most tools for health impact assessment usually require concentration-related data, such as yearly averages (I have limited knowledge of those tools anyway).
I do not have access to any air quality modelling involving the industrial pollution, so my first thought was to use data from the monitoring stations located near industrial sites here (we have a handful of those monitoring points), which are representative of that type of exposure. Another option would be to investigate the PM composition, but I would like to avoid this option since it involves lab procedures which are time-consuming and costly, etc.
Any help or insights will be welcomed, thank you!
Hi
I guess that now is the time to have a deeper look into the data and use the effects of the Covid-19 pandemic. Traffic is down but industrial sources might have been reduced to a lesser amount in some countries. Use it and try to differentiate the sources. Make sure to compare data that is comparable, i.e. you also Need to take into account weather that might have a big influence e.g. if you compare the Levels of NOx before and after start of Lockdown, the weather might have changed as well.
Good luck
Thomas
• asked a question related to Health Outcomes
Question
Currently I am doing research about ASeAn countries in environment and health outcomes
There is always missing data for variable health expenditures and energy consumption for certain countries in ASeaN during period of 1990-2017
thanks a lot for your kind help Mr. Ambrosini
• asked a question related to Health Outcomes
Question
Hello dear colleagues!
Can someone kindly explain to me what is endogeneity is, how to determine it and eliminate it using simple words? I am using a regression model in my research, where I examine the impact of migration on health outcomes of children left behind. What in this case could be endogeneity? Thank you in advance.
Asylgul Kanatbekova these papers extensively explain the endogeneity issue and discuss different methods to overcome this problem. Your regression estimates suffer from endogeneity if at least one of the regressors is correlated with the residual. To take care of the potential endogeneity issue, you assume one of your dependent variables to be endogenous and you find an appropriate instrument (1: cov(x, w) not equal to zero and 2: cov(w, u) equal to zero) that is correlated with the endogeneous variable, but uncorrelated with unobserved factors (error term) that affect your dependent variable. Then you can use, for instance, 2SLS estimator to estimate your model (ivregress 2sls y x(b=b2 b3)cd, endog(b) robust) here y is the dependent variable and x,b,c, and d are the independent variables. Assuming that b is endogenous, we include two instruments b2 and b3. You then look at the results of underidentification, weak-identification, overidentification, and endogeneity tests. To meet the instrumental variables requirements, you should have p<0.05 for underidentification test and p>0.1 for overidentification test. Your endogeneity test results (p<0.05 or p>0.1) could be both significant or insignificant. p<0.05 implies that you may have an endogeneity issue, whereas p>0.1 indicates your model doesn't suffer endogeneity problem. If you need further assistance you are welcome to contact me.
• asked a question related to Health Outcomes
Question
.
Only see your question now - I don't think that SPEAR will offer solutions for human health. However, you may be interested in this one - much more related to human health: Liess M, Henz S, Knillmann S. 2019. Predicting low-concentration effects of pesticides. Scientific Reports, 9:15248. https://doi.org/10.1038/s41598-019-51645-4
• asked a question related to Health Outcomes
Question
For my master's thesis, I am using meta-analytic techniques to explore the relationship between LGBTQ community connectedness and indicators of physical health. I am conducting multilevel meta-analyses in order to include multiple effect sizes from the same articles while accounting for the nested structure of the data. I am using the metafor package in R to run my analyses and I would like to run a separate meta-analysis for each of the four health outcomes that I am investigating. I am new to R and I am wondering if there is a specific command that I can use to calculate four separate overall effect sizes (one for each of the four health outcome variables) and test moderators for each of the four effect sizes separately. So far, I have only been able to calculate one overall effect size for the whole data set.
Agree with the above. I'd suggest to draw the subsets in producing the actual meta-analytical models, so you still work with the same data set. To make it more specific:
ma.ONE<-rma.mv(yi,vi, ... , subset=(HealthOutcome==ONE)
• asked a question related to Health Outcomes
Question
Metabolomics, the study of small molecules in biological systems, is the comprehensive analysis of all metabolites of an organism. It has the potential to improve exposure measures and delineate mechanistic links between exposures and potential health outcome. Moreover, metabolomics has the potential to measure patterns of exposure-specific biologic perturbations. I would be happy to have your opinion on the role of metabolomics in exposure assessment science.
Naw I am studying metabolic applications in pharmacognosy for identification of new phytocemicals used in as a drug. Thanks for this important topic.
• asked a question related to Health Outcomes
Question
Assessment of study quality usually aims to develop a tool which is universal for all disciplines using a specific study methodology. However, the implementation of new methods may require further criteria to ascertain the validity of results - Which domains should be additionally addressed by observational studies investigating the associations between metabolomics and health outcomes?
Interesting question, Jakub Morze, do you intend to develop such a tool or improve an existing one? If so, could you reference an example or more detailed description of what is considered reasonable in other disciplines/which questions are usually adressed/how evaluation is done.
In my opinion, you have to consider 3 major sources of bias: experimental, technical and data analysis related points. Following a brief description of what I mean:
[experimental] everything up to sample storage in N2; including: appropriate selection of matched control subjects, balanced study design, sufficient size of the study population, consistent/reproducible sampling protocol, excellent documentation of meta data, clear communication of study limits (if only young, male white subjects are investigated you obviously can not make claims for the world population...), and many more
[technical] everything from sample preprocessing until MS measurement; smart sample randomization during extraction and measurement, reproducible protocol, additional QC samples; documentation and communication of meta data (extraction group, sample batch, runorder etc.) to investigate biases posteriori, documentation of machine quality (e.g. sample blanks, mass precision after tuning)
[data processing] everything following MS analysis; documentation and communication of workflow - ideally in reproducible way
All 3 groups are demanding in their own. To define formal criteria is hardest for the last step as one can set so many thresholds and parameters at multiple points in a pipeline that may change results drastically. You may want to ensure that reported results are rigorously tested for statistical significance and pipeline is documented and reproducible at least.
Let me know what you think. Bests, Jan
• asked a question related to Health Outcomes
Question
In terms of food interaction and confounding, are associations with health outcomes likely to be direct, or could it be explained by other factors such as decreased consumption of other foods? How would design a study to address this question?
In my opinion, I think it should be mixed effect, and food patterns analysis can apply to exam this mixed effects. Yes, you do factor analysis first to determine the patterns and use the factor score as dependent variables in regression model/
• asked a question related to Health Outcomes
Question
I am a doctoral student in Public Health and about to begin my dissertation process and was excited to learn a little about this theory. My topic is related to improving health outcomes for African American women in Texas and this theory would fit well. I would like to have more information about this theory to justify its use in my research. Thank you!
Here is an excellent special issue on the topic — Special Issue "Health Disparities Due to Minorities’ Diminished Returns (MDRs)"
• asked a question related to Health Outcomes
Question
I am looking at results of two types of “predictor” analyses on a longitudinal cohort of 150 children.
the question is “does socioeconomic status (SES) at the time of birth predict health outcomes during the first 5 yesars of life?“
the first approach was a simple multiple regression analysis where SES at birth was the predictor variable and health outcomes at age 5 years (e.g. weight, height inflammation etc) the response variables
eg: does SES at birth predict weight at age 5 years
confounders were identified and controlled for
the second approach was taken where GLMMs were developed to examine SES at birth as a predictor of health outcomes at each year of life (at age 1, age 2, age 3 and so forth to age 5 years)
repeated measures and attrition - all accounted for
SES is further catagorised into indexes that examine slightly different aspects of SES advantage or disadvantage: so you can examine index of education and occupation at birth, or index of economic resource etc and we looked at each of these SES indexes as predictors
The results are different: the index of education and occupation score at birth predicted certain age related outcomes in the GLMM model, but didn’t predict outcomes in multiple regression analysis of health outcomes at 5. Different SES indexes emerged as significant predictors of different health outcomes between the two anlayses in a nutshell
I am happy to accept the differences are related to the way the data was analysed, the temporal component etc and both sets of results have important messages.
Can someone kindly explain in simple language why the results would differ? I think it maybe to do with the first regression analysis producing averaged odds ratios for the study population and the GLMM er - well - not doing that and ? considering the inter-individual characteristics - oh god I don’t understand!! I give up;.
thanks for any help here folks. I need to help to interpret these results and why we see differences here between the two analyses (how to interpret the results). Google has not been forthcoming!
I have sort of bad news. Statistically you are working in a very complicated area called longitudinal models. The best source that I know of is:
by Prof. Marie Davidian, an expert in the field.
If this doesn't help I suggest contacting Prof. Davidian directly for advice. her contact information is here:
Best wishes, David Booth
Sorry I can't be of more help. Best wishes, David Booth
• asked a question related to Health Outcomes
Question
I am looking for recent research on "functional addicts or alcoholics" who are still employed and went through out-patient treatment. I does not have to be published work, it could be internal outcome studies. In particular, I am interested in job retention or mental health outcome measures.
Any pointers or papers are much appreciated.
kind regards
Oliver
Thank you Bryan
• asked a question related to Health Outcomes
Question
Health care services are becoming costly and for many difficult to access. In effect the number of people suffering from preventable illnesses and accidents is alarming. There are studies that indicate that ignorance about health is a crosscutting issue that exacerbates ill health irrespective of socio economic differences. Existing theories and models of health communication/education mostly assume that scocio economic status determine health outcomes. The type of illness may vary, but one way or the other the number of people suffering from preventable illness whether chronic and/or communicable diseases, including accidents is increasing irrespective of socio economic status.
Patient-perceived “capacity to change"
• asked a question related to Health Outcomes
Question
I am looking at remote health. And focussed upon finding innovative ways of solving the challenge of improving the health outcomes among remote populations. Remoteness is a condition, an actor, in the network construction of the human body - is one way of constructing the human body.
I have worked in rural remote areas where the health services to the community need to be percolated. Some issues like literacy (among people of poor socioeconomic status) inequality, cultural factors, beliefs, myths, taboos, depends on old remedies for treatment and access to health care services still to addressed on priority in the areas like remote rural, bricklin , riverine and industrial areas. The concept of primary health care ( inter sectoral coordination, equitable distribution, community participation and appreciate technology) required to have universal health coverage. The female literacy, lack of awareness about causation and treatment of ailments, unreachable to unreached , lack of proper planning, execute it , monitoring and supervision at the level of health system, inadequate skilled staff perhaps may explain the situation. There's need of political will, deployment of dedicated volunteers, public awareness for community participation, investment of ample resources and creating adequate referral transport system are the real challenges which should be sufficiently addressed.
• asked a question related to Health Outcomes
Question
I'm attempting to summarize the literature on prevention or intervention mental health clinical trials in athletes.
Here are some studies you may find relevant:
• asked a question related to Health Outcomes
Question
I'm looking at the opportunities and barriers for a national pharmacare program.
If you're interested in health outcomes, I would suggest looking at the CLEAN Meds project by Nav Persaud.
So I hope that Siva got his question answered. If he needs more help, I will be happy to share some resources.
• asked a question related to Health Outcomes
Question
The percentage of human health outcome attributed to the urban environment varies in the literature. Of course everyone is measuring a different concept. Such as built environment, or determinants of health, or preventable disease.
I am interested in different sources and ways that the environments that we ourselves manage, design, built and govern is being assessed as impacting on our health? What percentages are being supported in the literature?
Interesting answer setting the percentage at 100%. But I have not seen that in any 'evidence' based papers. I guess it is about the details and parameters of the question. Robert Wood Johnson Foundation in the USA have published quite a bit and get the percentage at about 20%. I have seen studies with 25% quoted too. Anuradha Potlapalli
• asked a question related to Health Outcomes
Question
I am interested to look for the relationship between XXX and different health outcomes among people living with type 2 diabetes. However, I found a similar systematic review looking into the same issues (although some outcome may vary) covering both type 1 and type 2 diabetes. On the ground of that systematic review being published in 2011 (new literatures to be added) and the conclusion being drawn covering both type 1 and type 2 diabetes, do you think it will be a new contribution if I focus only on type 2 diabetes?
Given that the previous review was published 7 years ago, and that diabetes research is extensive, your systematic review is likely to be of interest as it will provide updated evidence.
Its important to think about the focus of your systematic review, particularly the research question, the search strategy and the inclusion criteria.
• asked a question related to Health Outcomes
Question
there is global interest to introduce and promote nutrition sensitive agriculture to improve the nutrition and health outcomes of the peoples. but the concept of NSA in policy and program developer is not well understood. so can you elaborate me the nutrition sensitive agriculture and its advantage overcoming the chronic nutrition and health problems in developing countries
That is correct. We are now moving from the concept of Food Security to Nutritional Security, and having a wholesome diet. The foodgrain intake is being replaced by fruits & vegetables.
• asked a question related to Health Outcomes
Question
Hello everyone.
I am working on a project relating renewable energy consumption to health outcomes in Nigeria.
My model contains 4 variables, 3 of which are I(1) variables, and the last one an I(2) variable. The I(2) variable is Life expectancy at birth (for Nigeria), and it is my dependent variable. Others are renewable energy consumption per capita, GNI per capita, and CO2 emissions (in metric tons per capita), all for Nigeria.
Is cointegration possible? If yes, which technique exactly? Do I have to find a proxy for life expectancy?
Thanks for anticipated responses.
You have to take difference in the I(2) variables and to consider that you are utilizing the variables in levels (I(1)) and the variables in rate (I(2))
• asked a question related to Health Outcomes
Question
I'm a very new PhD student, may I ask all researcher to share your experience regarding to the international comparative study between developed and developing countries in the theme of long working hours and its negative health outcome in particular coronary heart disease and work stress, is it possible? what's a major problem that I will be faced and how can I overcome it? all suggestions are highly appreciated.
While I agree with the importance of developing a strong foundation in the theoretical and empirical literatrue, I would urge you to focus first on developing a more focused research question that can be sharpened through a lit review. Reading a wide range of literature without taking the time to attempt to develop a sharper research question can easily lead you down many unproductive paths. You can then use the lit review to refine your question. BTW as you start reading you may abandon the original question if you find it will add little to the field.
• asked a question related to Health Outcomes
Question
A growing body of evidence in the literature suggests that there is a clear link between household air pollution (HAP) and poor health outcomes, especially in the developing world. However, it is evident from searching the literature that little is known and empirical evidence is mixed about whether improved cookstoves and cleaner fuels deliver their purported health benefits.
GIZ has been working on this issue through a programme on clean energy. Throughout the years GIZ has amassed plenty of evidence on the linkages between clean cooking stoves and impact of health. One factsheet you can find here: https://www.giz.de/de/downloads/giz2016-en-improved-cooking-stoves.pdf
• asked a question related to Health Outcomes
Question
Dear colleagues,
The VAS is a commonly used tool in health outcome studies, when using it to assess importance of certain action or intervention, how we can interpret the results, for example on 1 to 10 line (where 1; the least and the 10; the highest), the average of importance was 4 out of 10, what does that mean? and if we want to identify the level of importance (very important, important, somewhat important, not important), where are the cut off point for each level? to say for example, one third of student view this intervention is very important.
Can we interpret the result as 1-5 is not important and 6 to 10 is important.
Thank you.
Thank you Paul kind,
• asked a question related to Health Outcomes
Question
can we combine different health outcomes in such a way so as to get overall health index which later on can be treated as output variable in DEA/SFA......
the visual analog scale ranges from 0-10.. 0 means death and 10 means the best health conditions
• asked a question related to Health Outcomes
Question
The data is one time only assessment not before and after and there is a higher response rate among mothers
good information thank you
• asked a question related to Health Outcomes
Question
Hi,
I have 600 baskets. Each contains upto 15 types of fruit. Each fruit maybe ripe, ripening, unripe or rotten.
Each basket has demografic like data eg season picked, density of orchard, hrs of sunlight, water availability.
I wish to build a parsimonius model having identified by pca which variates are the most informative predictors of achieving 7 or more ripe fruits/ basket.
My question centers on whether it would be correct to undertake a PCA comprising the demographic variates AND whether a basket had >=7 ripe fruits, otherwise how the demo variates linked to predicting fruit ripeness?
I apologize in advance for being hazy on the archetypal jargon of guassian this and vector that, although I think i know how to undertake a PCA. But I would value answers which avoided jargon where possible
Thank you.
Thanks very much for these information
• asked a question related to Health Outcomes
Question
As a non-profit CHDA with health outcome funds, we encounter cases of children with EBLLs during our home rehabilitation and lead remediation. We are wanting to build a coalition to support the children and their families during the home rehabilitation process and provide needed medical services. What communities are successful and how did they achieve successes? Resources welcome!
There is a community based group called United Parents Against Lead but not sure how active they still are. http://www.upal.org/ In NC, we have a Lead and Healthy Homes Taskforce which is a group of state, local, and non-profit professionals working on the problems of lead poisoning prevention and providing healthy housing. It has been very effective at providing a platform for sharing best practices.
• asked a question related to Health Outcomes
Question
I am looking for software or preferably an excel template to compare mean values of a health outcome measure across studies e.g. comparing average steps/day or BMI. I do not have access to raw/individual data and am NOT looking for a t-test for individual data. I have a series of studies that have reported mean outcomes and SD or 95%CI, I want to combine in a forest plot and assess whether they differ and heterogeneity and overall effect size. I'd appreciate any help!
Hey Stephanie,
Have you used Comprehensive Meta-Analysis? I'm pretty familiar with it. It'll examine mean outcomes (outputted as SMDs or MDs in effect sizes) provided you have the sample size and 95% CI's (or variations of this). It'll also work out heterogeneity and run meta-regressions too.
• asked a question related to Health Outcomes
Question
If anyone can help with this I'd greatly appreciate it! I'm trying to consolidate my ideas for a thesis proposal and feeling a bit lost! I would like to investigate how the relationships between self-esteem, alcohol use and mental health outcomes differ between males and females. My hypothesis is that the relationship between self-esteem and alcohol use will be stronger in males than females and the relationship between self-esteem and mental health outcomes will be stronger in females than in males. I will be using the Rosenberg self-esteem scale, the DASS to measure mental health outcomes and the Alcohol Dependence Scale.
Can anyone help with the kind of design I would need to use and the best statistical analysis to use?
Thanks!
Dear Jen,
from a statistical point of view, this sound like a classical moderation hypothesis: you want to check if the magnitude and/or direction of arelationship between variables x and y depends on a variable z. In your idea x=self esteem, y=alcohol use or mental health outcomes, z=gender. For the moderation it is not necessary that z is categorical, it could also be continous.
There are two typical approaches: if you have only one variable/measure for each of your constructs, i.e. you only use Rosenberg's scale for the self esteem measure, than a (moderated) multiple regression is preferrable, because it is very simple to do, analyze and interpret. On the other hand, if you have several measures for one construct (e.g. different self esteem measures to catch different aspects of self esteem; or mental health as a general construct measured with different tools and approaches) then you could/should use structural equation modeling (SEM). Herein you are able to construct and estimate latent variables ("true" selfesteem/mental health) and you can explicitly model which variable interacts with which other ones. But moderation analyses are not implemented in all SEM programs, as far as I know.
I am not so much into SEM, but I have two very good references for multiple regression and moderation analyses:
Darlington, R. B., & Hayes, A. F. (2016). Regression analysis and linear models: Concepts, applications, and implementation. Guilford Publications.
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.
• asked a question related to Health Outcomes
Question
Dear Researchers,
I would like to know what were technical, practical challenges with integratation of various country-, regional- and provider-level health data and how you overcome them (i.e. from problem to solution).
As the prescription drugs, getting more severe side effects, the low acupuncturist reimbursement makes the alternative treatments more useless.
When there are more symptoms and more severe diseases, the patients need more needles and/or longer treating time. Due to there is no acupuncturist's seat on any insurance company's board, the insurance low payments to the acupuncture clinics makes an acupuncturist need to treat multiple patients in an hour. That destroyed acupuncture treatment effectiveness.
• asked a question related to Health Outcomes
Question
Hi everyone with experience,
I am working on a systematic review project on Type 2 Diabetes Mellitus. I was organizing the main outcomes that are retrieved from the literature. However, I have some difficulties where to classify Quality of life, vitality, general health and role functioning outcomes. I was wondering which category fits best for these outcomes? 1. Cognitive and psychosocial measures, 2. Long-term impact measures.
I feel they fit in both psychosocial as well as long term outcomes. You will find psychosocial measures for quality of life and vitality. Quality of life and wellness/ overall health are long term outcomes for diabetics. For instance, you can't focus on self management without having an end in sight for long term prevention of complications. Quality of life is linked with complications, overall health, etc.
• asked a question related to Health Outcomes
Question
I am Interested in working on bioaerosol and its role in nosocomial infections in hospital. Especially how pathogens identified in hospital air is explicitly related to nosocomial infection or health outcome. But I need concrete dose-response relationships to establish epidemiological outcome which has been difficult so far. Because of potential confounders which may be difficult to adjust.  Note that this is an epidemiological study borrowing microbiological risk assessment techniques. Any advice on the way forward?
If you could study some classes of inpatient wards with otherwise well patients (eg elective orthopaedic), You would reduce many confounder problems. Look at time trends of infection rates  in relation to air pathogen levels over a year or two.
• asked a question related to Health Outcomes
Question
I am working on a research which aims to develop a risk  score to predict critical /bad outcomes of preterm babies. As there are several  outcomes  but can collectively be called as critical outcomes is it possible for me to develop a single risk score? The risk factors for different outcomes may differ.
Dear Dimuth Peiris, I am not quite sure I understand your question correctly, but if you aim at developing a model to predict critical oucomes on the basis of several independent risk factors I suggest you take a look at the "Decision Tree" models (e.g. http://www.stat.wisc.edu/~loh/treeprogs/guide/wires11.pdf). Yours, AG
• asked a question related to Health Outcomes
Question
Dear all,
I am interested in air pollution and health studies and I am looking for  an accurate wearable GPS logger. I have read about HeraLogger GPS. Is it a good and appropriate one? Where can I order a GPS logger?
Thanks
It depends what you want to measure. A GPS monitor does not need to be "worn" since it usually does not contain a pedometer. What I have found to be important is the number of readings per unit of time (one per second is good), the capacity to store all that information, and the ability to hold out for 18 hours or so (i.e. plugging it in overnight should be enough to ensure sufficient charge for all the following day).
As a consequence, I am working with a product called GT-730:
I don't know about the HERALogger, but the fact that scientific articles mention it is usually good, I think. It might be worthwhile asking them the same 3 questions: how many readings per unit of time, how much can be stored, and if it can take 18 hours or so without recharging.
• asked a question related to Health Outcomes
Question
I've recently been wondering about overdiagnosis and problem with treating people to target surrogate markers and not health outcomes.
Prehypertension, prediabetes and overweight are construed as intermediate health states, between ideal health and clinically-diagnosed conditions which indicate elevated risks to health. They are increasingly recognized as major risk factors for some of the leading causes of mortality among high-income and middle-income economies and are advocated as clinical entities deserving targeted identification and clinical intervention. Early intervention in cardiovascular disease mortality has been proposed predicated on the diagnosis of prehypertension, prediabetes and overweight as well as borderline hypertriglyceridemia.
The recognition of prehypertension, prediabetes and overweight as clinical entities is valuable to the extent that the diagnosis alerts the individual to act in order to prevent the onset of disease or worsening of risks . While health information alone is no guarantee for the promotion of health, health-related behavioral changes are contingent on health information and the understanding of such. Far from turning healthy individuals into or labeling them “patients”, prehypertension, prediabetes and overweight ought to be seen in the context of disease prevention.
• asked a question related to Health Outcomes
Question
There is evidence that stress is mediating the effect of diet on body weight (Peters, A et al).
Is there  also evidence on whether (reduction of) stress may be involved in the beneficial health effects of leisure physical exercise?
• asked a question related to Health Outcomes
Question
I am working on my master's thesis and will be testing models that have facets of health as the outcome. Specifically, I am looking at:
• physical health (i.e., health problems, such as hypertension, pain, vision problems),
• functional health (i.e., how health problems impair or limit daily functioning, such as working, sleeping, seeing),
I'm thinking that these facets of health are formed by their indicators, rather than the indicators being reflective of the facet of health. But can an argument be made in favor of reflective?
Related, if I do treat these are formative, what are the implications for treating these latent variables as endogenous outcomes? I've read Diamantopoulos et al (2008) and I am not sure how, or if any recommendations for formative latent variables change if the latent variable is the outcome.
If it helps in any way, most of my indicators are categorical, but I also have a few continuous. I was planning on using robust weighted least squares as my estimator and conducting my analyses in Mplus.
Thank you in advance, and let me know if you need more details.
Gretchen, I think we get into trouble when we try to turn "physical [or mental] health" into an outcome measure. There's no agreed-on measure for that, if we even agreed on what "that" is.
I'd try for more precise constructs like physical function, perceived health status, medical history and distinct biometric values like BP and BMI.
• asked a question related to Health Outcomes
Question
The SRS scores reported in scoliosis series are highly variable. Some authors use SRS22, others SRS30. Some papers report SRS as mean for each domain, and others report a total score. How can I convert these scores into a single one in order to do a meta-analysis? Do you have any reference?
Thanks,
Alisson R. Teles
I found it at:
Spine (Phila Pa 1976). 2011 Nov 1;36(23):E1525-33. doi: 10.1097/BRS.0b013e3182118adf.
Converting SRS-24, SRS-23, and SRS-22 to SRS-22r: establishing conversion equations using regressionmodeling.
Lai SM1, Burton DC, Asher MA, Carlson BB.

Abstract
STUDY DESIGN:
Cross-sectional mail questionnaire.
OBJECTIVE:
Assess the feasibility of translating total and domain scores from Scoliosis Research Society (SRS)-24, SRS-23, and SRS-22 to SRS-22r.
SUMMARY OF BACKGROUND DATA:
Three successive editions of the original SRS-24 health-related quality-of-life questionnaire have resulted from efforts to improve its psychometric properties and validate its use in patients down to 10 years of age. This resulted in the need to establish, if possible, conversion equations to the last and most thoroughly validated version, SRS-22r.
METHODS:
A consolidated questionnaire of 49 questions that incorporated the various questions in the four questionnaires was mailed to a consecutive series of 235 patients who had received primary posterior or anterior instrumentation and arthrodesis to treat adolescent idiopathic scoliosis. Regression modeling was used to establish conversion equations from the SRS-24, SRS-23, and SRS-22 to the SRS-22r.
RESULTS:
One hundred twenty-one of the 235 patients (51%), aged 23.3 ± 4.52 years (range 14.2-34.6 years), returned the questionnaire at 8.6 ± 4.00 years (range 2.3-15.9 years) following surgery. Estimation of SRS-22r questionnaire and nonmanagement domains total scores and mean scores from SRS-22 and SRS-23 scores is excellent (R2 scores of 0.97-0.99) and good for SRS-24 scores (R2 scores of 0.80-0.82, improving to 0.86 and 0.87 after minimal domain reconfiguration). Estimation of SRS-22r individual domain total scores and mean scores from SRS-22 and SRS-23 is good to excellent (R2 scores of 0.81-0.99). Minimal domain reconfiguration improves conversion from SRS-24 pain from R2 = 0.71 to 0.76, which are both fair; SRS-24 function from R2 = 0.69 and 0.74 to 0.83, from poor and fair to good; and SRS-24 satisfaction/dissatisfaction with management from R2 = 0.64 to 0.80, from poor to good. Conversion of SRS-24 self-image is poor (R2 = 0.60) despite the correlation being statistically significant.
CONCLUSION:
With one exception, SRS-24, SRS-23, and SRS-22 questionnaire, nonmanagement domains, and individual domain total scores and mean scores can be translated to SRS-22r scores with fair to excellent accuracy, which is further improved in some instances by minimal domain reconfigurations. The sole exception is SRS-24 self-image, which translates poorly.
PMID:
21289546
[PubMed - indexed for MEDLINE]
• asked a question related to Health Outcomes
Question
So far, I am aware of the use of generic QoL instruments like the SF-36 (or similar tools) for this purpose. These might not sufficiently address areas of health impacted by smoking.
I think quality of life in smokers is effected by many problems and in many organs of their body.
It is better you select a QOL scale for diseases such as asthma as Dr. Perriot told.
Regards,
• asked a question related to Health Outcomes
Question
Cortisol measurements as part of large epidemiological studies are valuable for a number of health outcomes - however, the cost of an assay in a hair sample is prohibitive in many settings.  Would appreciate any direction to reliable, validated and cheaper options.
Paul, I'm the first author on the aforementioned JoVE paper and the head of the lab that developed the method described therein. You are correct that hair CORT analysis is not inexpensive (our current fee is \$30 per sample assayed in duplicate), but this is because the way we do it is quite labor intensive. Our early pilot data suggested that the most valid results are obtained when samples are washed, dried, and then ground to a powder prior to CORT extraction in methanol, but not all labs follow this methodology. For large scale screening in epidemiology studies, it might be satisfactory to quickly mince the sample into small pieces and then go right to the extraction step. Of course you still have the cost of the assay, which might be ELISA (our standard method),  RIA, or LC-MS, as well as methanol, extraction tubes, and any other miscellaneous lab items. If you have any questions, I'd be happy to try to answer them.
Best regards,
Jerry Meyer
• asked a question related to Health Outcomes
Question
I'm specifically looking at the intergenerational aspect of historical trauma in Native Americans and its relationship to adverse health outcomes (cortisol effects maybe?).
There's some great info re: relationship of HT to mental health issues (Maria Yellow Horse Brave Heart, Eduardo/Bonnie Duran and Joseph Gone) and some re: Holocaust survivors (Baronowsky), but looking for more info and anything you might know of specifically related to physiologic changes?  Many thanks!
Hi Mary Elizabeth
Not sure if you're interested in material beyond the Native American experience, but here's a link to a paper by Pat Dudgeon (and colleagues), who has done a lot of work on trauma experienced by members of Australia's stolen generations.
The institute's Stewart Sutherland is also about to complete a PhD in this area, so let me know if you are interested and I'll send him you enquiry.
Regards
Pauline
• asked a question related to Health Outcomes
Question
Health Policy globally needs redesign to include “social determinants of health” There is a need to reorganize care around achieving value for patients. In order to improve health outcomes for patients, we first need to define all the activities that are likely to enhance health for specific segments of the population. Health care redesign should essentially include into clinical settings the activities that will influence the social factors (address social needs, such as a lack of housing or access to adequate food) that are intertwined with health. How important it is for clinicians to associate personnel with expertise in social determinants of health to support patients?
Population health is founded on social determinants of health, the problem relates to the transfer of knowledge to enable the health care workforce to understand the economic, political environment and social parameters contributing to the overall health of a community.  This require integrating courses across all medical, nursing and allied-health professions related to social determinants.  Public health graduates and the clinician have a clear understanding of the epidemiological factors contributing to disease prevalence, however the X-ray technician may not understand the link between social determinants and population health.   My research focused on the prevalence of breast cancer in young AA women it has been clearly concluded that regardless of age mortality rates are higher in ethnic women; therefore addressing the factors contributing to the lack of access to health, lack of health insurance, belief systems must be transferred from the clinician to ancillary personnel.
• asked a question related to Health Outcomes
Question
I am currently considering a Lean Sigma Project for the implementation of new geriatric care principles including an Assessment Tool.  I am interested in information related to other facilities who have implemented such a program.  I am curious if anyone has been able to analyze health outcomes related to implementation of a Geriatric Assessment Tool?  or if anyone has been able to document an economic impact ....I would like to determine which allied health professionals are conducting these assessments and if mid-level practitioners are able to bill for this "Provider Service"
We have been doing this for quite some years now as a matter of routine. One of my colleagues Nimit Singhal published the data on the 1st 200 patients triaged with his tool in J Geriatric Oncology in 2010 I the public sector the screening tool is nurse administered, in the prviate it varies: I do it myself (it doesnt take long once you know the tools). An overview was published a couple of years ago by M Puts et al in JNCI in 2012 and more recntly in Annals of Oncology this year showing several tools to be predictive of outcomes of interest (mortality,toxicity). I dont know about the economics aspect although a priori if you avoid adverse effects by better patient selection with a pretty inexpensive tool it sounds unlikely to fail the cost:benefit ratio.
• asked a question related to Health Outcomes
Question
There are several sources for this data, but I am not sure if there are validations of these ratios. They also are for specific years. Do people use them across years or do they adjust for inflation, changes over time, etc?
Mike, call me. We can discuss. The answer in short is: It depends on whether you want them for your institution or another and for what types of charges. And yes, use the medical consumer price index to adjust for inflation.
• asked a question related to Health Outcomes
Question