Background: Chronic non-cancer pain (CNCP) is a prevalent condition, imposing significant burden on healthcare systems. Ketamine is suggested as a potential intervention for CNCP management. We conducted a systematic review and network meta-analysis to assess ketamine's effects in adults with CNCP. Methods: We searched Medline, Embase, CINAHL, and Cochrane CENTRAL up to January-2024 for randomized trials involving adults with CNCP, comparing ketamine with placebo, usual care, or other interventions. Reviewers independently assessed trial eligibility, extracted data, and evaluated risk-of-bias using the Cochrane tool. A random-effects network meta-analysis was performed. We assessed evidence certainty using GRADE. Results: We included 38 trials, with the following comparisons made between ketamine and placebo, using 0-10 VAS: At <30 minutes, ketamine may slightly reduce pain intensity (-1.32, 95% CI: [-1.73 to -0.90], low-certainty). At 1-3 hours follow-up, ketamine may slightly reduce pain intensity (MD: -1.25, (95% CI: [-1.76 to -0.74], low-certainty). At 3-to-7 days follow-up, ketamine may have little to no effect on pain intensity (MD: -1.34, 95% CI: [-2.29 to -0.39], low-certainty). At 3-to-5 weeks follow-up, ketamine likely results in no pain reduction (MD: -0.99, 95% CI: [-2.00 to 0.03], moderate-certainty). At beyond 5 weeks the evidence about ketamine pain reduction is very uncertain (MD: -1.09, 95% CI: [-1.86 to -0.32], very-low-certainty). Ketamine had no effect on physical functioning. Compared to placebo, ketamine may result in a slight increase in the risk of gastrointestinal adverse events (RR: 3.97, 95% CI: [2.18 to 7.22], RD: 12%, 95% CI: [5% to 25%], very-low-certainty), an increase in risk of dizziness (RR: 3.66, 95% CI: [1.25 to 10.74], RD: 11%, 95% CI: [1% to 40%], low-certainty), may increase the risk of fatigue, somnolence, and sedation (RR: 2.89, 95% CI: [1.84 to 4.53], RD: 27%, 95% CI: [12% to 50%], low-certainty), may increase of the incidence of dissociative symptoms (RR: 4.22, 95% CI: [2.20 to 8.10], RD: 17%, 95% CI: [6% to 37%], low- M.Sc. Thesis – Sara Moradi; McMaster University – Health Research Methodology iv certainty), and it may result in a slight increase in the risk of visual impairment (RR: 10.21, 95% CI: [2.86 to 36.42], RD: not evaluable, very-low-certainty). We did not have enough data to pool effect estimates for other outcomes. Conclusion: Ketamine may provide small but important benefit in CNCP patients at immediate-to-short follow-up, but it probably has little to no benefit at beyond 3-weeks. Ketamine is likely to provide similar benefits compared to alternative active interventions; however, these benefits may be associated with important side-effects. / Thesis / Master of Science (MSc)

Children of today are gaining exposure to electronic reading environments at earlier ages and in greater frequencies than prior generations, as evidenced by the ubiquity of modern technologies. Such technologies provide affordances beyond basic text by supporting the screen-based rendering of aural, visual, and gestural elements. This research investigates, by way of a fixed effects meta-analysis, the overall effect of electronic reading environments on the comprehension outcomes of children between the 4th and 8th grades. Findings yielded three published studies between 2016 and 2020. Results from a total population sample of 2,125 students across the United States, showed small but significant effects of reading technology on comprehension. The implications of these findings are discussed in light of their pedagogical applications and future research directions.

Conclusions. The sensitivity and positive predictive value are generally more concerned than the specificity and negative predictive value in assessing and adjusting publication bias in meta-analyses. In this sense, Egger's regression can be recommended for its high sensitivity, while any positive result from Tang's method would suggest a probability of bias that should be taken seriously. Given the different patterns of the accuracy with the OR and the P1-P2 combination, a combination of Egger's regression and Tang's regression would be advisable. Further studies are needed to study the accuracy of methods used in combination. / Due to sampling error and true heterogeneity, a single study cannot provide a comprehensive picture and a precise estimate of, say the effectiveness of a treatment. Systematic reviews that identify and integrate relevant studies have become the most important scientific, quantitative method to summarize scientific research. Meta-analysis is the statistical method used in systematic reviews to combine results from individual studies. / However, due to selective submission and publication, not all relevant studies conducted, especially those unpublished studies with an insignificant negative result, are easily accessible to those who conduct reviews. As a result, the truth, say, the effect of a treatment, would be overestimated. This phenomenon is known as publication bias. A few methods for detecting the bias have been developed and used in meta-analyses. Although their accuracy has been studied, some important issues remain to be answered, such as when would a method be good enough for practical use and is it similarly good for different definitions of the odds ratio? / Methods. We conducted a simulation study to examine the accuracy of four commonly used bias-detection methods with various ORs and P1-P2 combinations. In a simulation study, the true bias status can be predetermined and thus be compared with the results of the bias-detection methods. The four methods are Egger's regression, funnel plot regression, rank correlation regression, and Tang's regression. Realistic sample size was used for simulating individual studies and the numbers of studies in a meta-analysis was also varied. Both the sensitivity and specificity are examined against the magnitude of the OR and the P1-P 2 combination to identify the ORs and P1-P 2 combinations for which a method is sufficiently accurate. Predictive values are also examined for the same reason and in the same manner. / Results. The sensitivity and positive predictive value are generally low and in particular when the OR is close to one for which publication bias is of a particular concern. Egger's regression has the highest sensitivity among the four, in particular when the OR is neither close to one nor exceptionally large or small. Due to the relatively lower specificity, the positive predictive value of Egger's regression is not as high as that for Tang's regression and funnel plot regression. Tang's regression and funnel plot regression are very similar in sensitivity, specificity and predictive values, with the former being slightly better. Rank correlation seems the least accurate method overall. Tang's regression has in general the highest positive predictive value among the four methods in particular when the OR is below one. / Chung Chi-keung. / "June 2006." / Adviser: Tang Jin Ling. / Source: Dissertation Abstracts International, Volume: 68-03, Section: B, page: 1588. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 116-124). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

A clinical trial may have no subject (0%) or every subject (100%) developing the outcome of concern in either of the two comparison groups. This will cause a zero-cell in the four-cell (2x2) table of a trial using a binary outcome and make it impossible to estimate the odds ratio, a commonly used effect measure. A usual way to deal with this problem is to add 0.5 to each of the four cells in the 2x2 table. This is known as Haldane's approximation. In meta-analysis, Haldane's approximation can also be applied. Two approaches are possible: add 0.5 to only the trials with a zero cell or to all the trials in the meta-analysis. Little is known which approach is better when used in combination with different definitions of the odds ratio: the ordinary odds ratio, Peto's odds ratio and Mantel-Haenszel odds ratio. / A new formula is derived for converting Peto's odds ratio to the risk difference. The derived risk difference through the new method was then compared with the true risk difference and the risk difference derived by taking the Peto's odds ratio as the ordinary odds ratio. All simulations and analyses were conducted on the Statistical Analysis Software (SAS). / Conclusions. The estimated confidence interval of a meta-analysis would mostly exclude the truth if an inappropriate correction method is used to deal with zero cells. Counter-intuitively, the combined result of a meta-analysis will be worse as the number of studies included becomes larger. Mantel-Haenszel odds ratio without applying Haldane's approximation is recommended in general for dealing with sparse data in meta-analysis. The ordinary odds ratio with adding 0.5 to only the trials with a zero cell can be used when the trials are heterogeneous and the odds ratio is close to 1. Applying Haldane's approximation to all trials in a meta-analysis should always be avoided. Peto's odds ratio without Haldane's approximation can always be considered but the new formula should be used for converting Peto's odds ratio to the risk difference. / In addition, the odds ratio needs to be converted to a risk difference to aid decision making. Peto's odds ratio is preferable in some situations and the risk difference is derived by taking Peto's odds ratio as an ordinary odds ratio. It is unclear whether this is appropriate. / Methods. For studying the validity of Haldane's approximation, we defined 361 types of meta-analysis. Each type of meta-analysis is determined by a unique combination of the risk in the two compared groups and thus provides a unique true odds ratio. The number of trials in a meta-analysis is set at 5, 10 and 50 and the sample size of each trial in a meta-analysis varies at random but is made sufficiently small so that at least one trial in a meta-analysis will have a zero-cell. The number of outcome events in a comparison group of a trial is generated at random according to the pre-determined risk for that group. One thousand homogeneous meta-analyses and one thousand heterogeneous meta-analyses are simulated for each type of meta-analysis. Two Haldane's approximation approaches in addition to no approximation are evaluated for three definitions of the odds ratio. Thus, nine combined odds ratios are estimated for each type of meta-analysis and are all compared with the true odds ratio. The percentage of meta-analyses with the 95% confidence interval including the true odds ratio is estimated as the main index for validity of the correction methods. / Objectives. (1) We conducted a simulation study to examine the validity of Haldane's approximation as applied to meta-analysis, and (2) we derived and evaluated a new method to covert Peto's odds ratio to the risk difference, and compared it with the conventional conversion method. / Results. By using the true ordinary odds ratio, the percentage of meta-analyses with the confidence interval containing the truth was lowest (from 23.2% to 53.6%) when Haldane's approximation was applied to all the trials regardless the definition of the odds ratios used. The percentage was highest with Mantel-Haenszel odds ratio (95.0%) with no approximation applied. The validity of the corrections methods increases as the true odds ratio gets close to one, as the number of trials in a meta-analysis decreases, as the heterogeneity decreases and the trial size increases. / The proposed new formula performed better than the conventional method. The mean relative difference between the true risk difference and the risk difference obtained from the new formula is -0.006% while the mean relative difference between the true risk difference and the risk difference obtained from the conventional method is -10.9%. / The validity is relatively close (varying from 86.8% to 95.8%) when the true odds ratio is between 1/3 and 3 for all combinations of the correction methods and definitions of the odds ratio. However, Peto's odds ratio performed consistently best if the true Peto's odds ratio is used as the truth for comparison among the three definitions of the odds ratio regardless the correction method (varying from 88% to 98.7%). / Tam Wai-san Wilson. / "Jan 2006." / Adviser: J. L. Tang. / Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6488. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 151-157). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Vitamin K has a negligible effect on bone mineral density (BMD) and a large but uncertain effect on fractures. The three studies in the thesis explored uncertainty about the effect of vitamin K on fractures using the methods of economic evaluation and Bayesian meta-analysis. In study 1, a Markov probabilistic microsimulation model was developed for a hypothetical cohort of 50-year-old postmenopausal women without osteoporosis. This was a fracture incidence-based model, populated with data from the literature. It was used to examine the cost-effectiveness of two supplementation strategies over a lifetime horizon. We compared vitamin K2 (or vitamin K1) concurrent with vitamin D3 and calcium versus vitamin D3 and calcium alone. Study 2 included a systematic review, and classical and Bayesian univariate meta-analyses to determine the efficacies of the K vitamins on BMD or fractures in current and future trials. Study 3 used Bayesian bivariate random-effects meta-analysis to jointly model the treatment effects on two correlated bone outcomes. We compared the estimates from the univariate and bivariate meta-analyses and explored how these results would change the conclusions of the cost-effectiveness analysis. The strategies including vitamin K were highly cost-effective at willingness-to-pay of $50,000/QALY (quality-adjusted life year); however, the results were most sensitive to changes in the efficacy of vitamin K. The univariate meta-analyses showed large uncertainties in the anti-fracture effects of vitamin K2 in current and future trials. The bivariate 95% credible intervals were considerably narrower than those from the univariate meta-analyses. Using future odds ratios from the bivariate meta-analyses, vitamin K2 cost more than $100,000/QALY while vitamin K1 was cost-saving. Our analyses found substantial uncertainty around the estimates of the vitamin K effect on fractures. We recommend against routine use of vitamin K for fracture prevention. Bayesian bivariate meta-analysis accounts for all available information and should be considered when the treatment effects are measured on two correlated outcomes.

Vitamin K has a negligible effect on bone mineral density (BMD) and a large but uncertain effect on fractures. The three studies in the thesis explored uncertainty about the effect of vitamin K on fractures using the methods of economic evaluation and Bayesian meta-analysis. In study 1, a Markov probabilistic microsimulation model was developed for a hypothetical cohort of 50-year-old postmenopausal women without osteoporosis. This was a fracture incidence-based model, populated with data from the literature. It was used to examine the cost-effectiveness of two supplementation strategies over a lifetime horizon. We compared vitamin K2 (or vitamin K1) concurrent with vitamin D3 and calcium versus vitamin D3 and calcium alone. Study 2 included a systematic review, and classical and Bayesian univariate meta-analyses to determine the efficacies of the K vitamins on BMD or fractures in current and future trials. Study 3 used Bayesian bivariate random-effects meta-analysis to jointly model the treatment effects on two correlated bone outcomes. We compared the estimates from the univariate and bivariate meta-analyses and explored how these results would change the conclusions of the cost-effectiveness analysis. The strategies including vitamin K were highly cost-effective at willingness-to-pay of $50,000/QALY (quality-adjusted life year); however, the results were most sensitive to changes in the efficacy of vitamin K. The univariate meta-analyses showed large uncertainties in the anti-fracture effects of vitamin K2 in current and future trials. The bivariate 95% credible intervals were considerably narrower than those from the univariate meta-analyses. Using future odds ratios from the bivariate meta-analyses, vitamin K2 cost more than $100,000/QALY while vitamin K1 was cost-saving. Our analyses found substantial uncertainty around the estimates of the vitamin K effect on fractures. We recommend against routine use of vitamin K for fracture prevention. Bayesian bivariate meta-analysis accounts for all available information and should be considered when the treatment effects are measured on two correlated outcomes.

Thesis (D.P.H.)--University of Michigan.

Dissertation (D.P.H.)--University of Michigan.

Reliability generalization (RG) is a method for meta-analysis of reliability coefficients to estimate average score reliability across studies, determine variation in reliability, and identify study-level moderator variables influencing score reliability. A total of 107 peer-reviewed RG studies published from 1998 to 2013 were systematically reviewed to characterize the meta-analytic methods employed and to evaluate quality of reporting practice against standards for transparency in meta-analysis reporting. Most commonly, RG studies meta-analyzed alpha coefficients, which were synthesized using an unweighted, fixed-effects model applied to untransformed coefficients. Moderator analyses most frequently included multiple regression and bivariate correlations employing a fixed-effects model on untransformed, unweighted coefficients. Based on a unit-weighted scoring system, mean reporting quality for RG studies was statistically less than that for a comparison study of 198 meta-analyses in the organizational sciences across 42 indicators; however, means were not statistically significantly different between the two studies when evaluating reporting quality on 18 indicators deemed essential to ethical reporting practice in meta-analyses. Since its inception a wide variety of statistical methods have been applied to RG, and meta-analysis of reliability coefficients has extended to fields outside of psychological measurement, such as medicine and business. A set of guidelines for conducting and reporting RG studies is provided.

The burden of depression requires modalities other than individual psychotherapy if we are to reduce it. Over the past two decades preventative programs for depression have been developed and refined for different populations. The six years since the last meta-analysis of preventative interventions—inclusive of all program types—have seen a number of new studies. The current study used the greater statistical power provided by these new studies to analyze moderators of, and sub-group differences in, the effect of these interventions on depression. Moreover, this meta-analysis synthesized effect sizes for outcomes other than, but often related to, depression (e.g., anxiety) and for within-group change scores with the goal of better informing program implementation and evaluation. Twenty-nine studies met inclusion criteria and indicated that small, robust effects exist for reductions in depression diagnoses and symptomatology. Significant effects were also observed for anxiety, general health, and social functioning.