Limitations and Strengths Sample Clauses

Limitations and Strengths. An important limitation of the systematic review and meta-analysis is the limited generalizability and power of the findings as a result of the small number of studies that could be included in our analyses. Furthermore, we could not examine the association between prevalence rates of subthreshold anxiety and age, and the interaction effects between age and other relevant characteristics, because very little to no studies were suited to answer these questions. This underscores that most studies into the prevalence of anxiety in later life have not focused on the more nuanced questions related to this topic and that much work remains to be done in this field of study. The findings of the meta-analysis should be interpreted with caution, and do not allow for firm conclusions due to the high heterogeneity between included studies. While it could be argued that no meta-analysis should be conducted in the presence of large heterogeneity, we think that an integration of available information on a topic should still be preferred over leaving clinicians and scientists to make their own estimation of pooled effect sizes. Our elaborate search procedure resulted in the description and integration of a large number of studies into the prevalence of anxiety in older adults conducted over the last decades. Chapter 2 therefore provides a good overview of this field of study, the shortcomings and gaps in the currently available literature, and topics requiring further scientific attention.

Limitations and Strengths. This project was subject to several limitations. As a qualitative project, the findings are not considered generalizable. Very few survivors attended focus groups, so the discussion in 2/3 of the focus groups was primarily between law enforcement, clinicians, and social workers.

Limitations and Strengths. This study was limited due to the inability to confirm MTBI and by factors related to the study design. The lack of a confirmatory test for MTBI presents a challenge when comparing test results because there is no standard to verify accuracy. However, young, US-born military recruits reporting no history of increased risk for MTBI, are among those with the lowest prevalence of MTBI in the US, and may be presumed almost entirely free of infection [103]. The analysis was limited in power due to the small number of positive test results and discordant results. Larger studies may be able to detect smaller associations and additional interactions to TST and QFT-GIT discordant results. Differences in interpretation criteria between QFT-G and QFT-GIT may allow the same blood sample to be interpreted differently. Similarly, the single cut-point used by QFT- GIT to interpret positive results has been described with some uncertainty, especially regarding subjects with IFN-γ concentrations near the 0.35 IU/ml threshold [134,135]. Adjusting the positivity threshold for QFT-GIT, i.e. using a TB Response of less than 0.35 IU/ml to be interpreted as positive may be more appropriate to identify MTBI in low-TB prevalence populations [136]. However in this study, among recruits with a TB Responses < 0.35 IU, the 99th percentile for TB Response was 0.18 IU/ml, signifying most recruits had a TB Response far from the threshold of positivity. This study used cross-sectional data on subjects to investigate tests for LTBI. Without performing a longitudinal study or reanalysis of positive results, the cross-sectional design may underestimate the agreement between TST and QFT-GIT due to false-positive results or reversions in QFT-GIT [42,111,137]. Variability within subjects may change result interpretations by subsequent tests, and is unrelated to infection. Similarly, false-positive TST results due to BCG vaccination and NTM sensitization cannot be corrected for in cross-sectional analysis. However, the increased adjusted odds of discordant TST positive but QFT-GIT negative, at a 10 mm cutoff, among recruits reactive to avian PPD by QFT compared to those who are not, supports that cross-reaction of tuberculin PPD by NTM sensitization reduces agreement between QFT-GIT and TST. Additional follow-up after 1 year to assess the development of TB may have been helpful, but such results may be biased due to recent transmission and progression to disease occurring after participation in ...

Limitations and Strengths. Part II has several limitations. A significant limitation of the effectiveness, efficacy and economic evaluation studies was the time horizon. Chapter eight and nine showed efficacy and cost-effectiveness over a three months time horizon. Since patients randomized to the waiting-list also received guided self-help CBT-E during follow-up, comparison of efficacy, cost-effectiveness and cost-utility was not possible after three months. This precluded evaluation of long-term effectiveness as well as the costs of guided self-help CBT- E as compared to no treatment. With regard to efficacy of guided self-help CBT-E only within group comparisons were meaningful during follow-up, though this was taken in consideration with the choice of statistical analyses. A different study design, with a comparison to a treatment-as-usual control condition (e.g., in-person CBT-E), would have enabled comparison of efficacy and an economic evaluation with a longer time horizon, which is recommended for future research. In addition, effectiveness of in-person CBT-E in chapter six could only be examined until 20-weeks of follow-up. Longer term follow-up data were necessary in order to assess if long-term recovery was attained. Another limitation of the designs was that chapter six was based on self-report data and the follow-up data of chapter eight and nine were only measured by self-report. Interview data are generally viewed as more reliable, especially when measuring binge eating behavior (▇▇▇▇ et al., 2012). Low concordance between interview and self-report data was also demonstrated in our data. In chapter eight, the frequency of objective binges at end of treatment showed a moderate relationship between interview and self-report data. This limits the comparison of the self-reported number of binges after conclusion of in-person CBT-E (chapter six) and number of binges as assessed by independent assessors after conclusion of guided self-help CBT-E (chapter eight). In both studies 48% of the BED patients showed abstinence from binges. However, around the globe there is high concordance of eating disorder severity as measured by self-report and interview data (▇▇▇▇ 2011, ▇▇▇▇ 2012, (▇▇▇▇▇▇▇ et al., 2021). Therefore, guided self-help CBT-E could be as effective as in-person CBT-E when outcomes are based on scores on the clinical cut-off of eating disorder measures. The use of self-report data was also a limitation of the economic evaluation. Though patient’s electronic files wer...

Limitations and Strengths. The major limitation in our study is a cross-sectional study design such that we cannot prove a causal relationship between home environment and the quality of children’s healthcare services. However, as we have explained above, it is not likely to have reverse causality given previous evidence and limited time of PCMH implementation, while caregiver’s behavior takes a comparatively long time to change. There are other issues due to the nature of survey data as well, including that the data are subject to self-report bias. One particular example is caregivers’ smoking status being underestimated. Our analysis showed that about 90% of all respondents reported not smoking in the household, much lower than the level in a previous national report [57]. There are also missing values for other variables, the most important being mother’s age, where we lost around 14.3% of the total sample size. This missing information could cause underestimation or overestimation of our results. In spite of these limitations, the NSCH demonstrates that consumers are able to report PCMH characteristics; among publicly insured children that had utilized medical services during the previous 12 months, the response rate of PCMH questions was as high as 98.6%, and the responses showed considerable variability, suggesting its validity as a measure of children’s health care quality. Furthermore, although the smoking component of home environment may be biased, other components showed adequate variability. Therefore, the entire scale of home environment is a valid measurement. Many state and federal programs, such as Medicaid, have begun to provide incentives and rewards to PCMH providers in order to expedite the transformation to a high-quality primary care model. Therefore, it is especially important to understand the true values that PCMH have brought to children, caregivers and health care providers. This study provides a new perspective with which to evaluate PCMH qualities for low-income children, or more accurately the healthcare quality measured by PCMH criteria. Our results show that home environment is a critical demand side predictor for children’s healthcare quality, and therefore, we need to control for home environment in future studies that examine the health benefits of PCMH, especially those used as justification for care-management payments. In the national movement of expanding and promoting PCMH, we recommend preferentially targeting children in poor home environmen...

Limitations and Strengths. There are several limitations to this study. First, the dataset does not fully capture the total number of ED encounters related to deliberate self-harm, as patients admitted to an inpatient setting are excluded from the analysis. Therefore, self-harm with high acuity may not be adequately represented in this analytic sample. This was confirmed by the E-code distributions in the overall sample, which yielded a deficient proportion of firearm injuries. Additionally, there may be a differential bias in the sample of insured patients that are not admitted to an inpatient setting. As a result, the subset of ED encounters being analyzed may not represent the actual length of stay for insured and uninsured patients. Second, the extrapolation of findings is limited due to the arbitrary selection of four states based on what variables were available. However, certain hospital-level and regional characteristics like hospital size or rural residence are incorporated into the model, which allows for relative comparability among states. Third, several unmeasured variables, including injury severity score and presence of psychiatric emergency services, create bias in the overall analysis. However, specific covariates are included in the model that are highly correlated with injury severity level, including male gender and method of suicide. This will serve to partially mediate the missingness of certain variables. Fourth, there are limitations associated with what comprises of an intentional self-injury. However, according to the published HCUP Methods report, three of four states in this analysis report a diagnosis correlation of higher than 97%, while New Jersey reported 85% correlation.82 This alludes to the robust nature of the dataset that was used. Additionally, each unit of analysis is the ED encounter, so patients are not tracked over time. Therefore, patients may have been considered more than once in a single analysis if they a) had a transfer to another hospital's ED or b) had another ED admission in 2014. However, since this is an analysis on LOS, the effect of this on the overall results is minimal. Despite these limitations, there are several strengths to this study. First, this is the first study observing the relationship between insurance status and ED length of stay among deliberate self-harm admissions. Prior research has explored this relationship in broader patient settings, including in psychiatric and trauma care.16,61-64,67,74 Second, the datase...

Limitations and Strengths. While this study reveals many aspects surrounding infant feeding practices among indigenous Mayan women of Guatemala, it is not without its limitations. To begin with, the study sample is small. During data collection, 13 interviews took place, only 10 of which were included in the analysis. The intention to compare among groups of women with roughly a three month age difference in their infants was not possible due to this fact. Another limitation was the quality of data gathered which is very thin. This could be due to several factors. First, an interpreter was used in all of the interviews. Some richness of the data could have been lost between the Spanish/Chuj translation. Also, cultural differences may be the cause of a lack of sharing on the part of the participant although measures were taken by the researcher and the interpreter to build rapport. However, analysis of the data was conducted in Spanish (not English) in an attempt to retain what richness there is in the data which can be considered a strength of the study. Another limitation to the data gathered has not to do with the quality of the data gathering but rather with the quality of the data provided. All of the women were asked to provide information about their first and other early feeding practices. Half of the women have infants aged six months or older. Recall bias must be considered when analyzing and interpreting the data. Finally, as this is a qualitative study conducted in a rural village in the highlands of Guatemala, the information gathered here may not be generalizable to other populations. However, this author feels that this reveals a strength of the study and of qualitative methodology in general. Through the use of this form of research, important, rich, and revealing data was gathered which not only illuminates more the difficulties facing Guatemala today but may also inform future undertakings in order to try to work toward a better resolution.

Limitations and Strengths. The cross-sectional design of this national survey facilitated the determination of associations but not causation between medication non-use and social determinants of health. The analysis for model selection was done using an unweighted logistic regression stepwise analysis with entry of 0.2 and exit of 0.25. For survey methods however, it has been reported that a more optimal method of model selection would be to use multilevel analysis and comparing both the weighted and unweighted results prior to sharing the model through a second order penalized quasi-likelihood linearization method (▇▇▇▇▇▇▇ & San Sebastian, 2014) which was outside the scope of this program. Another option explored was to use proc glimmix which would allow for multilevel models for complex sample survey data (West et al., 2015) however the methodology for data preparation were also outside the scope of this program. n = 1888 (88.5%) n = 244 (11.4%) n = 258 (13.7%) n = 1156 (61.2%) n = 474 (25.1%) n = 31 (12.7%) n = 194 (79.5%) n = 19 (7.8%) Both Diabetes and Hypertension Hypertension only Diabetes only Both Diabetes and Hypertension Hypertension Only Diabetes only No Medication Use Medication Use n = 2135 Age 25 years and older n = 2174 n =13109 JSLC Data Subset for Age 18 and over Economic Stability Education Health Care Environment Social Context Income Poverty Employm Food Economic Highest Quintile ent Security Support level a d ttaine Health Insurance Coverage Health Perception Disability Smoking Status Status Housing Technology Access Access Social Protection Age Group Enrollment Sample Size (n, %) 2132 1888 (88.6%) 244 (11.4%) Age (mean ± SD) 60.9±14.7 61.9 ± 14.2 53.8 ± 16.0 Diabetes 782 (36.2%) 732 (94.0%) 50 (6.0%) <0.0001 Hypertension 1843 (87.1%) 1630 (89.5%) 213 (10.5%) 0.50 25-34 Years 94 (4.1%) 55 (63.9%) 39 (36.1%) <0.0001 35-44 Years 182 (8.0%) 149 (84.3%) 33 (15.7%) 45-54 Years 440 (20.1%) 389 (88.5%) 51 (11.5%) 55 – 64 Years 551 (25.8%) 493 (90.4%) 58 (9.6%) 65-74 Years 467 (21.4%) 431 (92.4%) 36 (7.6%) 75-84 Years 284 (14.1%) 263 (92.9%) 21 (7.1%) 85 and over 114 (6.5%) 108 (96.6%) 6 (3.4%) Male 660 (30.9%) 566 (87.8%) 94 (12.2%) 0.11 Female 1472 (69.1%) 1322 (90.4%) 150 (9.6%) Married 767 (35.7%) 689 (90.1%) 78 (9.9%) 0.0004 Never Married 967 (44.8%) 824 (86.7%) 143 (13.3%) Divorced 63 (3.3%) 59 (95.6%) 4 (4.4%) Separated 41 (1.6%) 37 (92.9%) 4 (7.9%) Widowed 294 (14.4%) 279 (95.8%) 15 (4.2%) Ever Received PATHE Benefit 657 (63.2%) 587 (89.2%) 70 (10.8%) 0.78 Rec...

Limitations and Strengths. The findings of this study must be interpreted in light of some conceptual and methodological limitations. In a context where a permanent method such as sterilization is the most prevalent form of contraception uptake, the role of woman’s autonomy remains unclear. With a prevailing pattern in rural India whereby women turn to sterilization upon reaching certain parity often including the birth of at least one son, autonomy’s importance amidst such practices maybe disputed. It can be argued that the role of autonomy may have greater implications when a woman is aware of, and has access to, non-permanent methods (oral pills, IUDs, etc.) for the benefits of birth spacing and preventing conception. When supplies of temporary contraceptive methods along with an enabling environment for informed choice exists, the impacts of autonomy in influencing contraceptive uptake may potentially be greater than in an environment with limited contraceptive choice where the primary method is a permanent one. Thus, in the context that this study is set in, other gender-related indicators namely measuring preference for sons, attitudes towards girls’ education, ideal number of boys vs. girls; maybe more likely to influence the use of sterilization and further research should investigate these proposed linkages. The other conceptual limitation is the absence of community-level measures in this study, including health infrastructure and other supply- side characteristics, which have been found to be important predictors of service use in India (▇▇▇▇▇▇, et al., 2000) (▇▇▇▇▇▇, et al., 2009). In an analysis by ▇▇▇▇▇▇▇▇▇▇ and ▇▇▇▇ (2002) examining the determinants of contraceptive service use in rural India; the authors found that community-level factors such as the presence of a secondary health facility and the number of family planning methods available have significant influence on contraceptive choice. A future analysis including these community-level infrastructural measures might shed light on the linkages between a woman’s autonomy and her resources at hand to consequently achieve her health outcomes; building on the process of empowerment theorized by ▇▇▇▇▇▇ (1999). Some methodological drawbacks of this study also need to be highlighted. Firstly, although this study made considerable efforts to control for a range of sociodemographic factors associated with contraception use, there may have been some important variables that were not included. Past studies have shown that i...