Expert Answer :500 words applied project 496 psychology discussio

  

Solved by verified expert:Mental Health DisciplinesReview at least three websites of professional organizations for mental health and related fields provided in this week’s list of Recommended Websites. Compare and contrast the key features of three mental health-related disciplines.Address the following questions in your initial post:What are common themes found among each of the professional organizations represented in the websites?What are the distinctive themes for each organization?How might a professional from each of the disciplines represented in the websites you selected answer the following question “How would a professional in your organization contribute to the treatment of depression?” chose 3 websites from here:(http://www.arttherapy.org)(http://www.counseling.org)(http://www.adta.org)(http://www.musictherapy.org)(http://www.psych.org)(http://www.psychologicalscience.org)(http://www.iact.org)
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4
Associated Press
Quasi-Experimental Designs
Chapter Learning Outcomes
After reading and studying this chapter, students should be able to:
• understand the important role that quasi-experimental designs play in answering research
questions of interest when participants in a research study cannot be randomly assigned to
conditions.
• articulate the appropriate research scenarios for a number of quasi-experimental design
approaches, including nonequivalent control groups, time series, cohort/panel, and regression discontinuity designs, as well as the applications of program evaluation.
• appreciate the practical applications and limitations of observational designs such as case
studies and naturalistic observation.
• understand the contexts in which archival research approaches, such as content analysis and
meta-analysis, can answer interesting questions based on the availability of pre-existing data.
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CHAPTER 4
Introduction
Introduction
I
n the ideal world, psychology researchers would like to be able to understand causeand-effect relationships as they pertain to attitudes and behaviors. Cause-and-effect
conclusions are powerful, because they provide insight as to how positive behaviors
can be promoted and how negative behaviors can be lessened. Not all research situations
lend themselves to laboratory controls and randomization of participants to conditions.
So outside of the laboratory (and even sometimes in the laboratory), we apply research
methods as best we can, but without random assignment. Much of the research conducted
in the social sciences is conducted using quasi-experimental designs. In fact, there are
times where random assignment is inappropriate, such as withholding health care services from children for the sake of an experimental study (Bawden & Sonenstein, n.d.).
Say that I wanted to study how effective the use of clickers (student response systems)
might be in the classroom. I’m teaching two sections of introductory psychology, and I
decide that I will use clickers in one of the sections, and I won’t use clickers in the other
section. At the end of the semester, I want to see if students earned more points in the section with clickers than in the section without clickers. This would be a quasi-experimental
design, because I am unable to randomly assign students to sections (students usually
like selecting their own classes). In fact, using X and O, here’s what the design would look
like (remember, X represents the independent variable manipulation and O represents the
dependent variable measure):
X clickers   O points
O points
If I had been able to randomly assign participants to conditions, there would have been an
R (for randomization) at the beginning of each line. This design is called a nonequivalent
control groups posttest only design. Although it is a good idea to have a control group,
because of the lack of randomization, we are less confident that the groups were equivalent
even before the start of the study—thus, we label the design as nonequivalent. This is one
example of the types of designs that are collectively known as quasi-experimental designs.
In this chapter, we’ll investigate the advantages and disadvantages of quasi-experimental
designs, observational designs, and archival research.
Voices from the Workplace
Your name: James K.
Your age: 47
Your gender: Male
Your primary job title: Co-Director of Community Living
Your current employer: Village Northwest Unlimited
How long have you been employed in your present position?
27 years (continued)
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CHAPTER 4
Introduction
Voices from the Workplace (continued)
What year did you graduate with your bachelor’s degree in psychology?
1982
Describe your major job duties and responsibilities.
I am responsible for coordinating services for nearly 60 clients. Our clients are all adults with physical or mental disabilities or both. I also help oversee the 60 staff that provides care and services for
these individuals, including meeting with them on a quarterly basis to review the care programs being
provided, conducting performance reviews. I help develop new training goals, and provide guidance
to staff and clients on how to effectively complete their work and grow. I conduct Quality Assurance
on documentation samples that are written by our staff, and perform follow-up reports to the various
staff teams that we supervise. One of our goals is to encourage and support our staff, and we make
this a priority in our work.
What elements of your undergraduate training in psychology do you use in your work?
I would say the training we received in counseling and helping techniques is probably the most beneficial and frequently used education from my undergraduate training.
What do you like most about your job?
The flexibility of schedule.
What do you like least about your job?
Bureaucracy and poor communication with and from the various funding streams that we work with
and those hired to oversee this. Poor wages for staff.
What is the compensation package for an entry-level position in your occupation?
It would be a range of $19,000–$25,000 for a middle management person, $15,000–$18,000 for a fulltime direct care staff.
What benefits (e.g., health insurance, pension, etc.) are typically available for someone in your
profession?
Major Medical Health Insurance, Life Insurance, various perks offered by our agency such as reduced
costs for various items like newspaper subscriptions, wellness or fitness memberships.
What are the key skills necessary for you to succeed in your career?
Patience, good listening abilities, creativity understanding, integrity, honesty, and willingness to go the
extra mile.
Thinking back to your undergraduate career, what courses would you recommend that you believe are
key to success in your type of career?
Abnormal Psychology, Theories of Counseling, Developmental Psychology.
As an undergraduate, do you wish you had done anything differently? If so, what?
I don’t think so, I was adequately prepared in my education for my job.
What advice would you give to someone who was thinking about entering the field you are in?
Be focused and dedicated to the people you are serving or trying to help. They are someone else’s
son or daughter and have tremendous value. Try to instill ways of making your job FUN and enjoyable.
Encourage and support those that work with you. Create a climate of participative decision-making so
that everyone feels invested in what is being decided. Show honor and respect to those above you and
to those you come into contact with each day, make them feel valued and important. (continued)
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CHAPTER 4
Section 4.1 Quasi-Experimental Design Types
Voices from the Workplace (continued)
If you were choosing a career and occupation all over again, what (if anything) would you do differently?
I can’t think of anything that I would choose to do differently.
Copyright . 2009 by the American Psychological Association. Reproduced with permission. The official
citation that should be used in referencing this material is R. Eric Landrum, Finding Jobs With a Psychology Bachelor’s Degree: Expert Advice for Launching Your Career, American Psychological Association,
2009. The use of this information does not imply endorsement by the publisher. No further reproduction
or distribution is permitted without written permission from the American Psychological Association.
4.1 Quasi-Experimental Design Types
A
quasi-experiment is “a design that manipulates the presumed case and measures
the presumed outcome but does not randomly assign participants to conditions”
(Shadish & Cook, 2009, p. 619). The example with the clickers is a nonequivalent control groups design, but sometimes there isn’t even a control group (these types of
designs are sometimes referred to as pre-experimental designs; Morgan, Gliner, & Harmon, 2000). Using our X’s and O’s, here is an example:
X   O
The above is a posttest only design (commonly used) but yields very little information
that can be generalized beyond the participants being tested. A common example would
be the teaching evaluations you provide at the end of the semester. The instructor taught
the class (X), and you provided an evaluation (O) at the end of the semester. Although
helpful to the instructor, there is not much we can say about whether this instructor is
effective as compared to other instructors, if one class learned better than another class,
and so on. Another pre-experimental design is the one group pretest-posttest design:
O1   X   O2
In this case, we can observe if there was change from pre to post, but little else. Staying in
class, perhaps at the beginning of a math course you are given a comprehensive pretest
(O1), and at the end of the course (X) you are given the same test again (O2). This design
will allow us to detect change over time, but that may not provide much useful information to the instructor. What if you were a math wizard coming into the course, and over
the semester you didn’t learn much? That might make it look like the instructor didn’t do a
very good job, when it was your excellent preparation that explains why your scores didn’t
increase much over time. Note that in discussions about K–12 teacher salaries and meritbased pay, the ability to demonstrate student learning over time is a huge issue. So this
pre-experimental design does allow us to inquire about change over time, but it provides
little insight as to why changes may have occurred. We could also add a pretest to this nonequivalent control groups design, making it a pretest-posttest design, as depicted below:
O   X   O
O
O
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Section 4.1 Quasi-Experimental Design Types
Although random assignment is not achieved with this design, the existence of a pretest
does allow us to explore whether the groups were different at the start on the variables
that were measured. This is not the same as randomization, but at least if the groups were
roughly equivalent prior to the introduction of the independent variable, then our confidence increases as to what the possible implications of the results mean.
Nonequivalent Control Groups
The nonequivalent control groups design is quite common throughout the social sciences and psychology, and here we’ll discuss just a sampling of practical applications of
this design. For example, to measure the impact of a computer-based training program
for nurses, Hart et al. (2008) administered a pretest questionnaire, delivered information
about evidence-based practice, and then administered a posttest questionnaire. This is the
classic pretest-posttest design, and here’s what it would look like graphically:
Oevidence-based practice pretest Xcomputer based education program Oevidence-based practice posttest
This type of design lets the researchers know if the participants changed over time. However, it’s hard to gauge the effectiveness of the intervention (X) without a control group.
Sometimes the constraints of the situation make random assignment impractical. For
example, a medical school decided to implement a new form of ethics training for its students based on small-group ethics teaching (Goldie, Schwartz, McConnachie, & Morrison,
2001) but wanted to compare this new approach with the previous lecture-style largegroup ethics instruction. Rather than randomly assign students to different instructional
conditions, new incoming medical students received the new curriculum, and students
from the previous year were utilized as the control condition. The experimental design
would look like this:
Osurvey score   Xnew curriculum   Osurvey score   (experimental group)
Osurvey score   Xold curriculum    Osurvey score   (control group)
Luckily, under the old curriculum, an ethics and health care survey had been administered both pretest and posttest. These same instruments were utilized with the new small
group ethics discussion sections. Goldie et al. (2001) found that the new curriculum led
to greater consensus in considering ethical situations and concluded that “small-group
ethics teaching, in an integrated medical curriculum, had a positive impact on first-year
students’ potential ethical behavior. It was more effective than a lecture and a large-group
seminar-based course in developing students’ normative identification with the profession of medicine” (p. 295). Even though a true experiment was not conducted here, you
can see the benefit of the outcomes of the quasi-experimental design—we can learn much
from these types of designs, even if we cannot draw a cause-and-effect conclusion.

Time Series Design
In its simplest form, quasi-experimental research using a time series design “. . . is simply a set of repeated observations of a variable on some entity or unit, where the number of repetitions is relatively large” (Mark, Reichardt, & Sanna, 2000, p. 353). For example (Garson, 2008), the monthly calculation of the national unemployment index by the
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Section 4.1 Quasi-Experimental Design Types
Bureau of Labor Statistics would be considered a simple time series design. In essence,
you can think of this as an extended sequence of dependent variable measurements (O).
A simple time series would look like this:
O   O   O   O   O   O   O   O   O   O   O   O
The above 12 observations could be the monthly reporting of the unemployment index, for
example. As you can imagine, the time series design allows for the assessment of change
over time—trends—but it can do much more than that (Mark et al., 2000). A time series
design can also be used for forecasting. For example, if an economist is tracking unemployment rates, he or she may use this data to try to predict what will happen six months
from now, based on the data accumulated leading up to this point in time.
Time series designs can become more complex as we introduce independent variables (X)
in to the mix, such as a particular treatment or intervention. These types of designs are
sometimes called interrupted time series designs (Cook & Campbell, 1979; Mark et al.,
2000) because of the interruption (X) over the series of observations (O’s). This type of
design might look like this:
O   O   O   O   O   O   X   O   O   O   O   O   O
Note the independent variable manipulation in the middle of the sequence of observations. This interrupted time series design is often used to measure the impact of legislation and public policy, such as
the implementation of a mandatory seat belt law or a ban
on cigarette smoking on a college campus. Let’s say you were
interested in determining the
impact of a smoking ban on
your college campus. You might
utilize a research design where
observers are trained to collect
data at various points on campus during different days of the
week at different times of day.
The dependent variable of interest (O) is the number of smokers
observed. You implement this
data collection program well
If you wanted to study the impact of a smoking ban on a college
before the announcement of the
campus, you could collect data by observing the number of
new smoking ban on campus
people smoking throughout the day.
that begins on July 1. Here’s
iStockphoto/Thinkstock what that design might look like:
OJan  OFeb  OMar  OApr  OMay  OJun  XJul  OAug  OSep  OOct  ONov  ODec  OJan
Notice that there are six observations before and after the ban takes effect. The goal of the
smoking ban would be to reduce the number of smokers, at least the number of smoking
incidents observed on campus. One of the benefits of this type of design is that it tracks
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Section 4.1 Quasi-Experimental Design Types
changes over time. So after the ban is publicized and implemented July 1, there might be
an immediate decrease in observed smokers (maybe they stopped smoking, or are hiding it better). But after a while, say a couple of months, the numbers of observed smokers
might increase. (Ever received a speeding ticket? Did you decrease your speeds for the
short term, only to return to your regular habits a short time later?) So you can see the benefit of the interrupted time series design, to assess the impact of an intervention. But the
drawback of the quasi-experimental design is that we cannot be overly confident about
causality—a decrease in observed smokers could mean many things—some stopped
smoking, some hid their smoking better, some switched to chewing tobacco, and so on.
Time series designs can be expanded to examine the relationship between multiple levels of
an independent variable manipulation (Mark et al., 2000). This design might look like this:
O   O   O   O   O   O   X   O   O   O   O   O   O
O   O   O   O   O   O      O   O   O   O   O   O
In fact, this is very similar to the non-equivalent control groups pretest-posttest design,
but it includes multiple pretests and multiple posttests. An example of this type of design
is the work of Ivancevich (1974) looking at the impact of a management-by-objectives
(MBO) approach as well as reinforcement schedules in the performance of a manufacturing corporation with multiple plant sites. Ivancevich measured multiple dependent variables, such as the quantity of output, quality of output, grievance rates by employees, and
absenteeism. Three different plants were utilized, as indicated below.
Plant 1    O    XMBO   O    O    O    O
Plant 2    O    XMBO   O    O    O    XReinf.    O
Plant 3    O        O    O    O    O
From this research, Ivancevich concluded that the benefit of the reinforcement observed
in Plant 2 tended to overshadow the MBO effects.
In considering time series designs, there are three factors to keep in mind (Garson, 2008a):
age, period, and cohort. In the time series design, variables are repeatedly measured over
time. Given that people can naturally change over time without any exposure to an independent variable, sometimes it will be difficult to disentangle a change due to the independent variable, or just the passage of time. There are also period effects as well, meaning that
individuals from a particular historical period may be impacted similarly. Garson suggested
that those individuals who lived through the Great Depression, the Challenger explosion,
or 9/11 may have similar beliefs and behaviors. Thus, recording times series data over long
periods of time (e.g., decades), the researcher must understand that historical events may be
impacting the change or lack of change seen in a time series design. Finally, cohort effects
should be considered. A cohort effect occurs when people from a particular age range are
impacted differentially by a historical event. For instance, Garson (2008) suggested that after
World War II, young adults at this time (a cohort) reacted differently than past generations
to the challenges of the later Vietnam War. Thus, the idea of a cohort effect is the intersection
of a group of people in time with a historical event that impacts that group; the post–World
War II cohort appeared to be more suspicious of the U.S. government and its policies as compared to earlier cohorts. Some quasi-experimental studies are specifically designed to examine cohort effects, and these types of designs are called cohort designs and panel …
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