Strengths and Limitations. The limitations to our investigations are the test setting for interpretations; there was only one glass slide for each skin biopsy case (although pathologists were asked to assume it was representative); and pathologists were unable to perform immunohistochemical staining or other diagnostic tests. In addition, pathologists were not provided detailed clinical history for the cases, and they were not able to procure a second opinion if desired. Pathologists were also given only four different options for treatment suggestions, which may have limited the ability to fully communicate their suggestions. Furthermore, we are currently refining the MPATH-Dx schema, in light of new research evidence on Class II and III categories, and we are aware there is disagreement on some of the MPATH-Dx classifications and their respective treatment recommendations2–5. Author Manuscript Strengths of our study include the broad spectrum and high number of cases and the large number of participating pathologists from across the U.S. While other studies have found variation in diagnostic interpretations of melanocytic lesions between pathologists6–9,20–31, our study is unique in that it quantifies variation in treatment suggestions. Our study also identified pathologist characteristics associated with providing treatment suggestions that are discordant with national guidelines. Author Manuscript Xxxxx et al. Page 8
Strengths and Limitations. The overall distribution of patients at the four urgency levels in this study is similar to the one found by a larger prospective trial comparing CTA to ADAPT, indicating a representative sample was collected in our study. (5) Although the sample size of 100 seemed sufficient, it is still relatively small compared to the number of annual visits to the ED and the broad spectrum of patients. The number of raters and their experience range (nurses, nursing students, SOSU assistants) reflect the reality of the triage process according to the working procedures in Danish ED’s. This represents a strength regarding the credibility and application of the results to the clinical situation, but the heterogeneity of the group may have resulted in a decreased level of agreement. The large number of raters also introduces an increased statistical uncertainty as reflected in the wide confidence interval. The ED personnel had limited experience with the use of CTA and received only a brief instruction prior to using the triage system. Because the data was collected alternately in the three sections of the ED and sporadically during the study period, the personnel were not given an opportunity of increasing their experience using the system over time. Their lack of experience with the method may have reduced the level of agreement, and it is possible that the interrater agreement would increase over time, if the CTA was implemented as the standard triage method in the ED.
Strengths and Limitations. As demonstrated with Figure 15 to Figure 20, one of the strengths of the disaggregate approach is that ZIP code areas with increased deaths and DALYs that could be results of underlying socioeconomic and health environment inequity in the neighborhoods can be identified geographically. Such inequities cannot be identified with aggregate approach at the regional level. A geospatially disaggregated ITHIM tool can help visualize the health impacts of different planning scenarios, which can help planners and policy makers reach informed decisions about the region’s future that address the well-beings of every citizen. However, spatial resolution of such analysis is limited by available resources at the neighborhood levels. For example, Xxxxxxxxxx, Xxxxxx, Xx, Igbinedion, and London (2017) noted difficulties in obtaining health and leisure time physical activity data at the ZIP code level. Instead, simplified assumptions were made to approximate values for these ZIP codes based on regional statistics. Thus, the study could not fully address the benefits and challenges inherent in modeling disaggregate health outcomes. The research team recommended performing sensitivity analysis to various model formulations to identify the potential range of uncertainties resulting from the data limitation.
Strengths and Limitations. To my knowledge this is the first study examining arguments for and against issuing policy recommendations for cognitive health in aging. The issue is of immediate and of long-ranging public health concern due to public fears about cognition, the exorbitant personal and monetary costs of caring for people with dementia, and the projections that cognitive impairment prevalence will rise with continuing population aging. The arguments by prominent cognitive health experts provocatively question whether the randomized controlled trial standard used by the State-of-the-Science Conference on Preventing Dementia and Cognitive Decline for conclusions is an inappropriate standard for public health-
Strengths and Limitations. A previous study by Xxxxxx & Xxxxxxxx investigated the cost of conducting clinical trials using data from Medidata Solutions, Inc. and found that among biomedical research and development (R&D), grant cost per patient is increasing over time at a rate of 7.5% from 1989 to 2011 (2013). More importantly, they found that the growth rate of clinical trials pertaining to cardiovascular therapeutic areas in the United States increased at an average 14.1% between 2000 and 0000 (Xxxxxx & Xxxxxxxx, 2013). Therefore, our results indicate an increase of 14.56% (described earlier as roughly 15%) per year from 1999-2012 are in agreement with previous literature. Study strengths include strict trial selection criteria, inclusion of impactful variables, and the analysis of transparent, traceable, and publicly available information. Limitations of this partial evaluation study include concerns about sample size, indirect costs, and a few necessary assumptions. The small sample size provides a wide 95% confidence interval, and may have reduced generalizability as a limited, partial evaluation (Xxxxxxxx, 2008; Kumar, Williams, & Xxxxx, 2006). Additionally, there were challenges to collecting data because even among government-only sponsors, individual trial funding data from United States Department of Defense (DOD) and U.S. Department of Veterans Affairs (VA) could not be traced, limiting the trial database to xxxxxxxxxxxxxx.xxx. According to previous literature, trial data from xxxxxxxxxxxxxx.xxx may sometimes show incomplete information, because up to 29% of registered trials remain unpublished (Roumiantseva et al., 2013; Xxxxx et al., 2013). More importantly, this study did not include indirect costs and costs associated with clinical phases that could have provided more information as to the factors impacting cost trends. Additionally, a major limitation is present due to the nature of analyzing study duration and participant enrollment by year first received. More specifically, those studies received more recently by xxxxxxxxxxxxxx.xxx are faced with a temporal bias such that more recent trials are shorter and therefore have smaller durations and potentially less patient enrollment as well as costs. Further studies investigating more complete figures on industry-inclusive funding, private donations, and outcome variables should proceed with acknowledgment of these limitations. Other research, such as a trial focusing on cancer trial costs per patient, looks beyond pub...
Strengths and Limitations. The relationship between geographic location and colorectal cancer survival has been studied in many countries using statewide and countrywide cancer registries including the SEER database (8, 28, 36, 51). However, no population-based research has been performed in the United States, to the knowledge of the author, to determine differences in early stage surgically treated colorectal cancer survival which may exist as a result of proximity to a metropolitan area, and by inference to cancer care. SEER’s 18 cancer registries house data on a significant proportion of the U.S. population and are widely distributed across the country (52). The large sample size of the study population increased statistical power, which lent to the validity of the analyses. In addition, re-categorization of USDA RUCC allowed for our study population to be assessed not only on sociodemographic characteristics, but also by proxy, on proximity from cancer care. The use of the exposure variable in this way provided a more in-depth analysis of the nuances surrounding early stage CRC survival. Furthermore, the use of this data allows for generalizability of study findings and possibly, advances in cancer research and cancer care. SEER data, however, posed several limitations. While SEER data provides information on major clinical and sociodemographic predictors, data on colorectal cancer screening and time to surgery are not available using SEER public-access database. Lead time is the time added to survival as a result of early screening and diagnosis of cancer. With increasing CRC screening trends, the presence of lead-time bias has become more evident in survival analysis and has been known to exaggerate relative survival estimates; however, because this study mainly focuses on the differences in survival across time, the risk of bias may have been reduced (63). With the ability to identify time to surgery, defined as duration of time from diagnosis to surgery, immortal time bias could have potentially been removed from the study by excluding immortal person-time from the survival analysis (59). Based on the sub-analysis performed earlier, it is anticipated that this bias was insignificant in this study; however, this limitation is worthy of note for future survival studies. More importantly for this study, the lack of facility-related data in SEER created a drawback in the direct assessment of access to and utilization of colorectal cancer care. Provision of variables which descri...
Strengths and Limitations. Actual data usage may differ from reported data usage. Also, although we explicitly defined research to mean as ―an activity that involves a research plan and data analysis to answer a research question intended to contribute to generalizable knowledge.‖(67) it is possible that some IPMs considered certain activities to be programmatic, and did not consider such investigations as ―research.‖ Our very high response rate for this survey limits some sources of bias and provides a representative set of results.
Strengths and Limitations. The systematic use of grounded theory in analyzing these FGDs provided a theory that the research team hopes can then be disseminated to stakeholders and presented for policy improvements. The use of Grounded Theory also allowed for the inclusive of context and gave a greater understanding of the full dietary and social changes taking place. Additionally, this study was led with local organizations that have existing relationships with the pastoralist communities of Morogoro and Tanga regions, and the FGDs were carried out by Tanzanian host country nationals in Kinyarwanda, all of which aided in the development of rapport. One weakness is that pastoral communities are very diverse. This means that the weight of each driver of diet change and the role of social connectedness will differ between communities. This means that caution must be taken when generalizing the results of this study to populations that are of different ethnic groups than those included here. It should be noted that factors biasing participants responses, such as seasonality, most recent foods eaten, and hunger at the time of the discussion could be present. Additionally, the lack of research among young adult pastoralists and social connectedness was limiting to the involvement of literature in deductive analysis.
Strengths and Limitations. This study was able to capture a large sample of AI/AN women using a validated questionnaire to obtain exposure data along with data on many clinical variables. The variety of information the PRAMS questionnaires collect allows data to be captured on many other pregnancy-related behaviors and attitudes that cannot be extracted solely from birth certificates. For example, in this study reported nausea during pregnancy was found to be an important confounder for GWG. In addition, the study was able to include AI/AN women who reside in many geographic regions across the United States. Many states have predominant Native American tribes, which is why state specific estimates for macrosomia were included. The PRAMS’s sampling methodology allows estimates to represent the entire state and also allows inter-state comparisons. Although this study had important and clinically relevant findings for AI/AN women, it did not come without some limitations. Not all the states that have large AI/AN populations, like Arizona and the Dakotas, participate in PRAMS, and PRAMS is only generalizable to the states included in the analysis. In addition, PRAMS only samples women who have had a live birth, so the findings cannot be applied to pregnancies that result in miscarriages or stillbirths. There are some limitations surrounding quality of information on variables such as misclassification of prepregnancy BMI and GWG due to post hoc assessment of prepregnancy weight reported by mothers at the time of the questionnaire. Women may underestimate reported prepregnancy weight, whereas weight at birth is objectively measured. Therefore, pregnancy BMI may be underestimated, and GWG may be slightly overestimated. The largest limitation to this study is the inability to control for history of previous macrosomia, a well-known risk factor for macrosomia reflecting both environmental and genetic factors, since no question on PRAMS captures this information.3
Strengths and Limitations. One strength of this study is the use of multiple measures to determine whether a latrine was in use. While 76.2% of household members who were surveyed indicated their latrine was in use, only 65.9% of households had latrines with two or more signs of use (smell, pan being wet, slippers present, etc.). Other measures, such as whether any household member had used the latrine the last time they defecated (73.0% of households) and whether and the enumerator’s opinion on whether the latrine appeared to be in use (69.6% of latrines), likewise indicated fewer latrines were in use. Measuring whether a latrine is in use in this manner resulted in a more conservative and hopefully more accurate measure of latrine use. One major limitation of this study is that it relies on cross sectional data and may be prone to reverse causality. The same aspects of a latrine that encourage individuals to use the latrine may also be the improvements or changes regular latrine users are most likely to make. For example, a household that uses, or would use a latrine if one were built, are more likely to build a place for handwashing than households that do not use their latrines are. This could be assessed through a study that repairs or builds specific aspects of latrines, examining latrine use before and after improvements are made to the latrine. An additional limitation of this study is that while it examines whether a latrine is in use, it does not measure associations with other important measures of latrine use. Complete elimination of open defecation in a household or occasional versus frequent latrine use are two measures that are not captured by the outcome variable used here. Some variables, such as the availability of water or the number of pits, were not found to impact whether a latrine is in use but may encourage a high proportion of a household to use a latrine or may encourage more frequent use of the latrine.
