Strength Of Empirical Evidence Research Articles

P-value and the probability of direction of effect

The p-value has been widely criticized in the scientific literature for its naive use in classifying results as 'significant' and 'non significant'. Much has been written about it; for example, see the American Statistical Association position statement of march 2016. To date, few alternative measures have been suggested and few changes were observed in the scientific practice regarding the use of p-value despite general agreement on the critics raised on it. In this paper, we use an alternative measure to p-value. It consists in the probability of the direction of the effect, that is the strength of empirical evidence in favour of the alternative directional hypothesis. In the context of scientific research, reporting the probability of the direction of the effect is easier to understand. Moreover, it focuses on the effect in the study rather than on the value under the null hypothesis, which sometimes has little meaning or has been used opportunistically. The proposal is not intended as an alternative to using the confidence interval, but as a probabilistic metric to be used instead of the p-value when we refer to particular hypotheses to be tested.

The Empirical Basis for Determinations of Medical Futility

Decisions to limit treatment in critically ill patients often rely on publications that make claims of futility based on outcome data. Our objective was to systematically review the criteria for futility and the strength of empirical evidence across clinical studies that purport to support or refute claims of futility. The MEDLINE database was searched for relevant articles published between 1980 and 2008. Selected studies reported original outcome data in critically ill or cardiac arrest patients and claimed that these data can support or refute decisions to limit treatment in comparable patients. Two authors independently abstracted data on patient characteristics, intervention, outcomes, cost, and design. Forty seven studies supporting a claim of futility and 45 refuting it were reviewed. Median point estimate for adverse outcome in studies supporting claims of futility was 100% (range 75% to 100%); median lower 95% confidence limit was 91% (range 48% to 99%). Explicit thresholds for futility were missing in 88% of articles. The original criteria for quantitative futility were fulfilled by only 28% of data, and almost exclusively in studies of cardiopulmonary resuscitation (CPR) for cardiac arrest. Substantial statistical overlap was observed between data brought in support of futility claims and data brought to refute them. Most studies that purport to guide determinations of futility are based on insufficient data to provide statistical confidence for clinical decision-making. They usually lack explicit a priori thresholds for determination of futility. Many studies draw disparate conclusions based on statistically similar data. In most circumstances these problems preclude confident determinations of futility.

Drug courts: Conceptual foundation, empirical findings, and policy implications

While drug courts have emerged on the criminal justice policy-making agenda with considerable fanfare in recent years, they have now reached the point in their operational advancement and political advocacy where continued growth and development are becoming more dependent on the strength of empirical evidence. Along with insights obtained from descriptions related to the history and function of drug courts, their divergence from traditional judicial practices, and their role in the new paradigm of therapeutic jurisprudence, this article analyzes the results of systematic reviews and meta-analyses of the drug court evaluation literature. From a public policy perspective, these empirical assessments are considered in conjunction with the conceptual foundations and implementation strategies associated with contemporary drug courts, in an effort to address their future potential to maintain a prominent position on the public policy agenda. As with similar public initiatives, it is argued that the long-term survival of drug courts can be strengthened to the extent that they are based on theory that is solidly anchored to policy, policy to practice, and, ultimately, practice to evidence-based outcomes.

Use of Herbal Therapies to Relieve Pain: A Review of Efficacy and Adverse Effects

To find holistic treatment with effective pain relief and few side effects, Americans spend billions of dollars annually on complementary and alternative medicine, including herbal therapies. Despite extensive use, the lack of regulatory scrutiny of these herbal supplements contributes to the paucity of reliable clinical data assessing their efficacy and safety. This review summarizes the existing studies investigating the efficacy of herbal therapies as a treatment for pain. Possible side effects, potential drug–herb interactions, and information about common herbal therapies are also summarized. MEDLINE, AMED, and the Cochrane Library databases were searched for the period from January 1966 to June 2005. Uses, dosages, routes of administration, and side effects were summarized. Strength of empirical evidence also was evaluated. This review found few well-controlled clinical studies. Furthermore, these studies documented limited efficacy of herbal therapies to treat pain. The information presented here may be used to further educate nurses and patients on the use of herbal therapies as well as direct future research efforts.

Model building and judgment: Implications for benefit transfers with travel cost models

Benefit transfer is the process by which researchers take recreational demand models or other models which are estimated for one site or region and apply them to another site or region. Model estimation is frequently viewed as a simple exercise in classical statistics. Here it is argued that, while standard hypothesis testing plays a role in model estimation, it may be less important than the researcher's judgment about how the model ought to work. The power of economics lies principally with the logic of theory, and then with the strength of empirical evidence. These arguments are illustrated using the travel cost approach to estimating the demand for recreation. There are several major research issues (for example, the role of substitute prices) which influence the final estimates of benefits but which must be determined at least in part by the researcher. The implication for benefit transfer is that this is also within the realm of judgment for the researcher, but that it will be more acceptable when judgment is recognized. That is, the original benefit estimates are tailored for a specific application. They cannot be treated as if they came from a strictly random process. Recognizing this tailoring process will put the researcher in a better position for transferring model results.