Paired-sample T -test were used to determine patient’s pre and post success criterion and whether success criteria differed from desired and expected outcomes following intervention. Chi-squared were used to determine if individuals desired, expected, and success criteria for treatment outcome differed from established MCIDs. Results
Full Answer
How do you measure the effectiveness of treatment?
Develop a specific and narrow definition of treatment effectiveness, one that all treatments are intended to directly impact. Effectiveness may be determined by a single outcome measure, but qualitative differences among treatment approaches must necessarily be restricted.
What is detailed pretreatment assessment and why is it important?
Detailed pretreatment assessment also allows for the search for prognostic indicators of outcome, some of which may be as powerful predictors of outcome as the treatment experience itself.
How do you test for attrition in clinical trials?
Typically, attrition (yes/no) is crossed with treatment assignment via a chi–square test to assess whether attrition was random or systematically related to the kind of treatment offered.
What is the proof of effectiveness of therapy?
The proof of effectiveness is in the measured outcomes, e.g., student test scores, lowered blood pressure, or in the case of therapy, concrete measures of progress, effectiveness, and outcome. 1. Miller, S., Wampold, B. and Varhely, K. (2008).
How do I know which statistical test to use?
For a statistical test to be valid, your sample size needs to be large enough to approximate the true distribution of the population being studied. To determine which statistical test to use, you need to know: whether your data meets certain assumptions. the types of variables that you're dealing with.
What kind of statistical test should I use to compare two groups?
The two most widely used statistical techniques for comparing two groups, where the measurements of the groups are normally distributed, are the Independent Group t-test and the Paired t-test.
What statistical test can you use to determine if any of the two treatments have a significantly different affect compared to the control?
Paired t-test A paired (samples) t-test is used when you have two related observations (i.e., two observations per subject) and you want to see if the means on these two normally distributed interval variables differ from one another.
What are the three types of t tests?
There are three t-tests to compare means: a one-sample t-test, a two-sample t-test and a paired t-test.
When do you use ANOVA or t-test?
The Student's t test is used to compare the means between two groups, whereas ANOVA is used to compare the means among three or more groups.
What is the t-test used for?
A t-test is a statistical test that is used to compare the means of two groups. It is often used in hypothesis testing to determine whether a process or treatment actually has an effect on the population of interest, or whether two groups are different from one another.
What is at test and Z test?
Content: T-test Vs Z-test T-test refers to a type of parametric test that is applied to identify, how the means of two sets of data differ from one another when variance is not given. Z-test implies a hypothesis test which ascertains if the means of two datasets are different from each other when variance is given.
What are treatments in ANOVA?
In the context of an ANOVA, a treatment refers to a level of the independent variable included in the model.
What is the treatment effect in ANOVA?
The ANOVA Model. A treatment effect is the difference between the overall, grand mean, and the mean of a cell (treatment level). Error is the difference between a score and a cell (treatment level) mean.
When do you use chi-square vs t-test?
a t-test is to simply look at the types of variables you are working with. If you have two variables that are both categorical, i.e. they can be placed in categories like male, female and republican, democrat, independent, then you should use a chi-square test.
When do you use z-test example?
Examples on Z Test Example 1: A teacher claims that the mean score of students in his class is greater than 82 with a standard deviation of 20. If a sample of 81 students was selected with a mean score of 90 then check if there is enough evidence to support this claim at a 0.05 significance level.
What is the difference between t-test and paired t-test?
A paired t-test is designed to compare the means of the same group or item under two separate scenarios. An unpaired t-test compares the means of two independent or unrelated groups. In an unpaired t-test, the variance between groups is assumed to be equal.
What is the purpose of individual based outcome evaluation?
These examples illustrate the major purposes of individual–based outcome evaluation, namely (1) therapeutic feedback to the client or therapist and/or (2) feedback to improve delivery of services.
When an outcome is measured, is it important?
Clearly, when an outcome is measured can be as important a decision as what is measured . In the case of severity of medical problems, for example, evaluation of pre–post changes using intake and 6–month data would lead to the erroneous conclusion that the intervention led to an increase in medical severity.
What is the difference between summative and formative evaluation?
This change often refers to a reduction or cessation of alcohol consumption, although “harm reduction” models may place equal importance on changes in alcohol–related problems and high–risk–related behaviors. Summative evaluation addresses the question of programmatic value or the relative effectiveness of treatments; formative evaluation focuses on collection of information to improve existing treatment services. Generally, the unit of analysis in summative evaluation is aggregated, group–based data, whereas formative evaluation may include both individual–based and group–based information. This distinction is not firm, however, as summative evaluation may include case studies to illustrate group–based findings.
What are the advantages of parallel testing?
A unique advantage of a parallel test is that, in pre–post applications , the potential biasing effect of recall is minimized. In prevention research where knowledge gains following a school–based intervention are to be measured, the use of parallel tests with high reliability is worthy of consideration.
What is the split half method of equivalency testing?
Theoretically, the split–half method of determining the internal item consistency of a test (discussed below) is a specialized aspect of equivalency testing. Statistics used to determine the equivalency of two parallel tests include the Pearson product moment and ICC coefficients. A unique advantage of a parallel test is that, in pre–post applications, the potential biasing effect of recall is minimized. In prevention research where knowledge gains following a school–based intervention are to be measured, the use of parallel tests with high reliability is worthy of consideration.
What is the laundry list of considerations?
In essence, a laundry list of considerations is presented, ranging from the importance of collecting representative baseline data to problems associated with using different versions of the same assessment over the course of a study.
Can you administer a test twice?
Sometimes it is not possible to administer a test twice in a pre–post format to obtain reliability estimates, and for other reasons it may not be feasible or desirable to create parallel tests as is done in equivalency studies. It is still possible, nevertheless, to loosely assess the reliability of an assessment (using a single administration). Coefficients of internal item consistency, for example, identify the extent of item homogeneity in an assessment, which can inform one about the extent to which item content forms single or multiple predicted domains. As an example, the Drinker Inventory of Consequences (DrInC) (Miller et al. 1995 b) was designed to measure adverse consequences associated with alcohol use. Miller and colleagues reasoned that such consequences could be grouped into discrete categories, including legal, health–related, interpersonal consequences, and the like. To this end, they developed an item pool representing each domain, had experts in the field review the items, and then administered the total pool of items to a sample of treatment–seeking clients (with items within each domain scattered in order). Logically, item responses within a domain ought to form a more homogeneous set than items combined across domains (or all items combined). Cronbach alpha is the most commonly reported statistic to reflect item homogeneity, which technically reflects the averaged extent to which each item correlates with its total set of items.
What is test of treatment?
Though ideally we should have a clear diagnosis before starting treatment, such certainty is not always possible. Sometimes this uncertainty can be resolved by using the treatment as the test that confirms the diagnosis.
When is it used?
As illustrated in figure 1 ⇓, a “test of treatment” is one strategy for the final stage of arriving at a diagnosis. It is appropriate when a single diagnosis is highly probable but not certain, when an available treatment works for most patients if the diagnosis is correct, and when there is a measurable short term outcome or surrogate.
How does a test of treatment go wrong?
As with every diagnostic test, the test of treatment can have both false negative and false positive results. If a test of treatment has been assessed against a diagnostic “gold standard” it is possible to quantify the accuracy of the test (table ⇑ ).
How can we improve?
Since tests of treatment can easily lead to an inappropriate diagnosis, assessment of response to treatment should be more rigorous than in treatments where diagnosis is “certain.” A test of treatment has several potentially remediable problems. False positives can arise because of spontaneous remission of the condition or from placebo effects.
Footnotes
This series aims to set out a diagnostic strategy and illustrate its application with a case.
NAATP Foundation (FoRSE) Addiction Treatment Outcomes Program
The NAATP Foundation for Recovery Science and Education (FoRSE) has launched a national Addiction Treatment Outcomes Program to aggregate data collected from clients by a diverse set of providers. While some treatment centers have been measuring their own outcomes for decades, many providers do not have the time or resources to do this work.
Outcomes Pilot Program (OPP) and Measurement Toolkit
From 2016 to 2019, NAATP's Outcomes Pilot Program (OPP) was a major undertaking wherein eight NAATP addiction treatment provider pilot sites participated in a rigorous and uniform outcomes measurement process.
Why measure outcomes in therapy?
Why measure therapy outcomes? There are a variety of answers to this question, but if you are a person seeking therapy or counseling the answer is "so you and your therapist know if the therapy is helping". Tracking progress or outcomes in therapy helps you determine whether to continue spending your time, effort, ...
What is the purpose of measuring progress in therapy?
Measuring progress or effectiveness during the course of therapy allows a client and therapist to discuss what seems to be working, what doesn't seem to be working, and any need for adjustments to the treatment ( e.g., different approach, different focus, different therapist, or even an intervention other than therapy) if it is not helping.
Why is tracking progress important in therapy?
Tracking progress or outcomes in therapy helps you determine whether to continue spending your time, effort, and money on the process or to try something or someone different. For decades the measurement of therapy outcomes has primarily been the focus of researchers, not therapists. These researchers have typically focused on identifying which ...
What is proof of effectiveness?
The proof of effectiveness is in the measured outcomes, e.g., student test scores, lowered blood pressure, or in the case of therapy, concrete measures of progress, effectiveness, and outcome. 1.
Is research evidence that therapy in general is effective?
Consequently, the research evidence that therapy in general is effective is good to know if you are considering therapy. - If there was no evidence that the activity helps, why bother? However, having outcome research that demonstrates the general effectiveness of therapy is only a start.
Do you have to understand the process of blood pressure medication?
You do not have to fully understand the process of therapy to determine if it is helping, any more than you have to understand the process of how a blood pressure medication works to determine if it is working for you. You simply find an appropriate way to measure the effectiveness of the treatment.
Is tracking progress a standard practice?
In recent years tracking progress for individuals in therapy has started to become more commonplace, but it is by no means a standard practice. Therapy has often been considered a mysterious, emotional, intuitive, and powerful process that is difficult to quantify. These conceptions of therapy can all be true, but they do not ...
Why use Wilcoxon rank sum test?
Try using Wilcoxon Rank Sum Test since you are dealing with same population with same treatment/intervention. It will help you know the group that benefitted well from the intervention before and after.
Can you use t test for parametric test?
For parametric test, you may use t test for two dependent samples while for non parametric test, use its equivalent called paired sample Wil coxon signed rank test. you may consult www.originlab.com where you can also see some statistical test alternatives. I hope this will somehow helps.
Is Wilcoxon paired t test valid for independent variables?
Wilcoxon or paired t tests are valid for one independent variable and one dependent variable. If you have many independent variables (you seem to say so not explicitly) and one dependent, you might need to form a regression model. I could not talk more specific because I do not know the details about your variables.
Can you compare pre and post test results?
Therefore you are to typically compare results of your pre and post test from the same respondents. the statistical tool u may use is depending on the nature of your data. That is, if it is parametric or non parametric test. Parametric test assume compliance with normality and etc.
Patient Characteristics
Program–Level Characteristics
- Program–level characteristics (panel II in figure 1) are general factors related to the program’s organization and structure, policies, services, treatment orientation, social environment, and readiness for organizational change. Relevant organizational or structural variables include ownership, physical design features (e.g., number of buildings), size (number of patients), aggre…
Provider Characteristics
- The quality of alcohol treatment is determined, not only by the therapeutic techniques applied, but also by the characteristics of individual treatment providers (panel III in figure 1). In particular, this domain of variables refers to within–program variation in provider characteristics (aggregate, program–level staff characteristics are considered in panel II). Gerstein (1991) argued that “the …
Therapeutic Alliance
- One of the key factors affecting the impact of alcohol treatment, especially psychosocial treatments, is the quality of the alliance or relationship that is developed between the therapist and client (panel IV in figure 1). A positive therapeutic alliance can be viewed as a necessary but insufficient condition for patients’ becoming involved in treatment, making treatment–specified i…
Treatment Provided/Treatment Involvement
- Alcohol treatment programs typically provide psychosocial and/or pharmacologic interventions to patients. To the extent that it is constant across all patients, treatment provided is a program–level characteristic (panel II in figure 1). In most programs, however, the treatment provided varies across patients (panel V). For example, it may be thought that some patients req…
Proximal Outcomes
- Proximal outcome variables (Rosen and Proctor 1981; panel VII in figure 1) refer to cognitions, attitudes, personality variables, or behaviors that, according to the treatment theory under investigation, should be affected by the treatment provided, and should, in turn, lead to positive ultimate outcomes (e.g., abstinence or reduced alcohol consumption). An Institute of Medicine (…
Ultimate Outcomes
- Ultimate outcomes (panel VIII in figure 1) refer to the end points that the treatment is supposed to effect. All treatment programs for alcohol use disorders attempt to impact drinking behavior, with many seeking to eliminate it entirely and others seeking to limit it to levels that do not cause adverse consequences. Some programs also seek to have a broader impact on patient functioni…
Table 1.—Measures of General Program–Level Characteristics
- Measure: National Drug and Alcoholism Treatment Unit Survey (NDATUS) Citation: Office of Applied Studies 1991 Description: The NDATUS is a brief questionnaire (five pages) that covers (a) the overall organization and structure of programs (ownership, funding sources and levels, organizational setting, capacity in different treatment settings using different treatment modaliti…
Table 2.—Measures of Treatment Orientation
- Measure: Drug and Alcohol Program Treatment Inventory (DAPTI) Citation: Peterson et al. 1994a, Swindle et al. 1995 Description:The DAPTI assesses the distinctive goals and activities of Alcoholics Anonymous/12–step treatment, the therapeutic community approach, cognitive–behavioral treatment, insight/psychodynamic treatment, rehabilitation, dual diagnosis …
The Value of Reliable Measures
Goals of Outcome Evaluation
- The basic question in outcome evaluation is whether, and as the result of alcohol treatment exposure, a behavioral change has occurred. This change often refers to a reduction or cessation of alcohol consumption, although “harm reduction” models may place equal importance on changes in alcohol–related problems and high–risk–related behaviors. Summa...
Relevant Measures of Change
- There is a historical appreciation of the importance of alcohol consumption as a criterion for judging treatment outcome, and most would regard assessment of outcome without such a measure as inadequate. There is less agreement, however, about the need to assess nondrinking domains to define outcome, and even less consensus about which domains may be particularly …