quality of empirically supported treatments

 quality of empirically supported treatments

The discovery of empirically supported treatments (ESTs) has had considerable influence in psychology and associated mental health disciplines. Based on several methodologies and statistical standards, the American Psychological Association (APA) allocated certain treatment diagnosis permutations ESTs condition and assessed their empirical support as powerful and of quantity. However, this paper is of the view that the quality of empirically supported treatments is of low quality because increased misrepresentation of data because of errors and its inability to differentiate similar treatments,

Empirically supported treatments (EST) must place more confidence in the treatments for which the accompanying results are presented with accuracy. However, research indicates that the misrepresentation of inferential data is a common practice in psychological studies, with almost 50% of papers published using the null hypothesis significance testing (NHST) that includes at least a reporting mistake. Approximately 13% also includes a “gross” reporting miscalculation, which weakens the findings of statistical importance (SakalukWilliams, Kilshaw, & Rhyner, 2019). Thus, the result of human mistakes, misrepresented statistics undermine trust in reliability findings. Inability to identify minor effects, inadequate empirical evidence, limitations of innovations in psychotherapy,

In the case of ESTs literary studies, reviewers must have faith in treatments projected on well-powered research that might consistently identify minor effects. Research shows that statistical power, which refers to the long-run likelihood of identifying an impact when one exists, has been a recurrent worry in the reproducibility of scientific results. Despite recommendations that research must be carried out with 80% power for foreseeable impact size, recent assessments have shown that a typical social science survey holds only a 44% probability of identifying an existing average-sized actual effect (SakalukWilliams, Kilshaw, & Rhyner, 2019). Thus, percentage weakens the trust in ESTs’ ability to detect minor effects.

EST literature must provide readers with certainty in treatments and data that is far more likely beneath the hypothesis of therapeutic effectiveness than below the null of no therapeutic efficacy. Studies show that, unlike the dichotomous conclusion of NHST, Bayes factor provides a way of assessing competing hypotheses on a constant measured value of evidential power. A Bayes factor is the probability proportion of two distinct hypotheses for a particular set of statistics. For instance, in research that compared the effectiveness of an EST to that of a control condition, a Bayes factor of ten indicated that the figures are ten times more likely to occur under the alternative hypothesis that is EST value than they are under a null hypothesis of no effect. Besides these findings, research also indicates that treatment can be regarded as EST with an only minimal criterion of two supporting studies even when 50 other tests were unable to find impacts (SakalukWilliams, Kilshaw, & Rhyner, 2019). Thus, there is a bias against the publication of null results.

Readers should also trust that ESTs are underpinned by research that has non-exaggerated percentages of statistical importance, considering their statistical power. Research suggests that, the Replicability-Index (points to the likelihood of research with an vital result to yield a substantial result again in a duplication research of initial research with the same sample size and importance criterion) could be used to further assess how plausible a series of stated significant impacts is, considering the level of noted power for those impacts. Exaggerated rates of significance beyond the power monitored for a set of impacts, may suggest the implications are implausible, and possibly the outcome of selective reports and controversial research methods. (SakalukWilliams, Kilshaw, & Rhyner, 2019). With sometimes only two empirical results used to determine impact, there is a probability of exaggerated empirical data in ESTs.

If the quality of EST was as strong as APA suggests, it should be able to treat all psychiatric conditions. However, this is not the case. Studies indicate that people do not fit in the established diagnostic groups on which ESTs are founded and tested, and this is a trial amongst psychiatrists who must be innovative when evaluating and handling patients’ challenges. Besides, warning signs clusters across ailments are most of the time not exclusive, and patients sometimes present with co-occurring illnesses that create significant trials when they seek to acquire ideal treatment plans. A patient requesting treatment for depression can also have anxiety, panic attacks, and a record of childhood distress, and may have recourse to self-harm as a way of controlling emotions. If this is the case, identify which diagnostic hypotheses to consider and which aspects could be leading the patient’s dilemmas may be intimidating. To make things more complicated, therapists have had inadequate guidelines in selecting ever-expanding disorder-specific therapeutic protocols in their possession (newharbingerpublications, 2014). Thus, this procedure restricts clinical innovations in psychotherapy practice and study. Such findings create doubt into the assumed quality of EST emphasized by APA.

Another problem with ESTs is the inability to differentiate similar treatments. The result could be that one hypothetically, a considerable number of differences of similar treatments could be included in a patient’s list. For example, the characteristics that may differentiate EMDR (Eye Movement Desensitization and Reprocessing), considered as EST, from imaginal exposure, are unnecessary. Besides, the existing conditions employed do not involve the likelihood to eliminate a treatment from the list even though alternate methods have proved their dominance. Following the principle of primum non nocere (first, do not harm), it is vital to prevent the addition of possibly dangerous treatments (SakalukWilliams, Kilshaw, & Rhyner, 2019). ESTs can thus cause danger to patients, thus, their ineffectiveness.

The program to recognize ESTs as an active program in psychology is one of the most significant in the history of psychotherapy. However, the existing low quality of the procedure highlighted above is alarming. Thus, researchers should take note of such limitations to execute research findings to enhance psychotherapy treatment.