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BEHP 5012 > Unit 5 > Flashcards

Unit 5 Flashcards

1
Q

In ABA, systematic manipulation (experimental design involves:

A

-Repeated, systematic presentation and removal of an independent variable (change in environmental events/conditions) while measuring changes in the dependent variable and holding other factors constant.

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2
Q

In ABA, there is no distinction between systematic manipulation used to…

A

Evaluate the effects of a treatment and to answer a research question.

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3
Q

The primary goal of systematic experimental manipulation are:

A
  • To demonstrate a functional relation between the IV and DV

- To evaluate the interventions once they are decided upon

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4
Q

Functional Analysis

A

Quantitative direct observation of behavior under systematically manipulated and controlled conditions. Not just a method of assessing problem behavior.

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5
Q

Internal validity

A

The extent to which an analysis assures that measured changes in behavior are due to the manipulation and not due to uncontrolled extraneous variables.

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6
Q

External validity

A

The extent to which a study’s results are generalizable to other subjects, settings, or behaviors.

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7
Q

What type of validity takes priority and why?

A

Internal validity. It makes little sense to consider the generality of the effect if extraneous variables cannot be ruled out for the effect.

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8
Q

What are the threats to internal validity?

A

(THARMIDS)

  • Testing
  • History
  • Attrition
  • Regression
  • Maturation
  • Instrumentation
  • Diffusion
  • Selection Bias
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9
Q

What are the threats to internal validity?

A

(THARMIDS)

  • Testing
  • History
  • Attrition
  • Regression
  • Maturation
  • Instrumentation
  • Diffusion
  • Selection Bias
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10
Q

Internal Validity Threat: History

A

Introduction of the independent variable may coincide with other events in the person’s life. Those other events could have produced those effects. (Simultaneous medication change)

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11
Q

Internal Validity Threat: Maturation

A

Natural developmental events or learning experiences may coincide with the introduction of the independent variable to produce the change (growing older, stronger, healthier, etc.)

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12
Q

Internal Validity Threat: Testing

A

Changes in the dependent variable may have come about as a function of repeated exposure to the experimental arrangements (E.g., practice effects)

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13
Q

Practice effects

A

Accuracy on task occurs as a function of repeated exposure to the task before the IV is introduces.

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14
Q

Internal Validity Threat: Instrumentation

A

Changes may reflect modifications in the measurement systems rather than effects of the IV (E.g., Subjective judgments of human observers, poor integrity of treatment delivery, damaged or new equipment, poor calibration of measurement devices)

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15
Q

Internal Validity Threat: Diffusion

A

Inadvertent, uncontrolled “seepage” of the treatment to control conditions or control subjects.
(E.g., Parent gets child to practice new skill before the intervention is formally introduced)

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16
Q

Internal Validity Threat: Regression

A

Regression towards the mean. Changes occurred because baseline measurements were not representative of the natural state of events (E.g., Unusual events took place on the initial day of testing which were not in place after intervention, so it looks like the intervention was effective.

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17
Q

Why is regression perhaps less relevant to single-case designs (SCD)?

A

Repeated measurement.

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18
Q

Internal Validity Threat: Selection Bias

A

The assignment of subjects to groups may have biased the outcome even in the absence of any intervention.

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19
Q

Self-Selection Bias

A

Participants who for various reasons are more prone to show greater improvements may also be more likely to participate in the study.

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20
Q

Why is selection bias perhaps less relevant to SCDs?

A

Participants serve as their own controls - Individual exposed to both baseline and intervention

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21
Q

Internal Validity Threat: Attrition

A

The loss of subjects over time, especially if systematic, may influence the effects. (E.g., subjects that tended towards the extreme ends of the measure may leave selectively, thereby skewing the sample at post-test.

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22
Q

Why is attrition less relevant to SCD?

A

Participants serve as their own controls.

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23
Q

Strategies for minimizing threats to internal validity

A

R.I.M.S.

  • Replication
  • Immediacy
  • Measurement
  • Stability
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24
Q

Minimizing Validity Threats: Measurement

A

Continuous assessment - collecting data on the dependent measure for an extended period of time (in contrast to very small samples of the dependent variable.

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25
Q

Why does measurement minimize validity threats?

A

Helps to rule out that change came about as a function of factors that could have altered performance over time (E,g., Testing, regression, maturation)

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26
Q

Minimizing Validity Threats: Stability

A

Establishing the stability of the target behavior. If levels of the DV remains relatively stable over time before the independent variable is introduced

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27
Q

Why does stability minimize validity threats?

A

The likelihood that the change can be attributed to the independent variable increases.

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28
Q

Minimizing Validity Threats: Immediacy

A

Immediate effects of the independent variable. The more immediate the effect, the stronger the case that the IV produced it.

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29
Q

Why does immediacy minimize validity threats?

A

Slow effects that appear long after the introduction of the IV call into question whether the change was imminent despite the intervention (i.e., intervening events may have caused the change)

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30
Q

Minimizing Validity Threats: Replication

A

Demonstration using multiple cases.

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31
Q

Why does replication minimize validity threats?

A

If the IV affects many subjects in the same manner a stronger case can be made that it produced the change.

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32
Q

Single-Case Designs

A

Involve the repeated and systematic presentation and removal of a treatment and measurement of behavior while holding other factors constant.

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33
Q

In behavior analysis, valid experimental design and ____ are synonymous.

A

In behavior analysis, valid experimental design and rigorous treatment evaluation are synonymous.

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34
Q

What are the characteristics of Single-Case Designs

A

A variety of research designs that use baseline logic to demonstrate the effects of the independent variable on the behavior of individual subjects

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35
Q

What are Single-Case Designs also known as?

A

Single-subject design

  • Within-subjects design (probably the most accurate)
  • Intra-subject design
  • Small n design
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36
Q

What is group designs also known as?

A

Between-Subjects

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37
Q

In Single-Case and Group Designs, the objective is the same:

A

To make valid inferences about the effect of the independent variable while ruling out other possible sources of variability between the experimental condition and the control condition

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38
Q

Single-case designs use what is known as ____ logic to examine the effects of _____ variables on behavior.

A

Baseline, independent

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39
Q

Group Design Controls

A

Comparisons made between groups of individuals (“Control” group vs. experimental group)

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40
Q

Single-Case Design Controls

A

Individual serves as own control (Before IV implemented compared to after IV implemented within one individual)

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41
Q

Group design IV Exposure

A

Each individual often exposed to only ONE level of the IV (E.g., either baseline OR treatment)

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42
Q

Single-Case Design IV Exposure

A

Each individual is exposed to each level of the IV (E.g., both baseline and treatment)

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43
Q

Group-Design Number of subjects and observations

A

Large numbers of subjects and few (often single) observations

44
Q

SIngle-Case Design Number of subjects and observations

A

Small number of subjects and multiple, repeated observations

45
Q

Group Design method of data analysis

A

Usually, inferential statistics

46
Q

Single-Case Design method of data analysis

A

Usually, visual data analysis, but sometimes, statistical analysis

47
Q

Group Design IV Introduction

A

Changes in the independent variable assigned according to randomized and matched designs

48
Q

Single-Case Design IV Introduction

A

Changes in the independent variable are made once the dependent variable has reached a steady rate.

49
Q

Single-Case Design Advantages

A

V.A.D.

  • Variability
  • Accountability
  • Dynamic Change
50
Q

SCD Advantages: Dynamic Change

A

Relative to traditional group designs, they permit investigation of behavior change as a dynamic process.

51
Q

What is meant by “Behavior change as a dynamic process”?

A

Repeated measurements and stability criteria mean that you need to keep observing. Permits you to see patterns of behavior. Taking single measurements obscures that process.

52
Q

SCD Advantages: Variability

A

Allows the examination of inter-subject variability and intra-subject variability.

53
Q

Inter-subject variability advantage in SCD

A

Group data may not reveal anything about the performance of any given individual. (E.g., an increased group score might reflect great improvements for a small number of subjects, while the majority did not change or performance decreased.)

54
Q

SCD Advantages: Intra-Subject Variability

A

Difficult to detect sources of with-in subject variability with group data. Lends itself better to the exploration of idiosyncratic effects and serendipitous findings because the data path is not constrained by hypothesis testing.

55
Q

SCD Advantages: Accountability

A

Lends itself well to clinical investigation and treatment accountability because participants serve as their own control. Represents the performance of an individual subject, the one that needs help.

56
Q

Baseline

A

Assessment of the dependent variable prior to the introduction or change of the independent variable. Does not necessarily imply the absence of treatment.

57
Q

Baseline functions

A

(D.I.P.S.)

  • Descriptive
  • Insight
  • Predictive
  • Setting Targets
58
Q

Baseline Function: Descriptive

A

Provides information about the existing extent of the problem. Serves as an indication of whether the intervention is necessary.

59
Q

Baseline Function: Predictive

A

Predicts the future level of the target behavior in the absence of the IV or if the IV has no effects.

60
Q

What does the predictive baseline function serve as?

A

A criterion to evaluate whether the intervention produces change.

61
Q

Baseline Function: Insight

A

Sometimes simply observing during baseline provides insight into relevant environmental events that can promote treatment development (E.g., Baseline sessions conducted across the day, but you notice problem behavior is more likely during morning rather than afternoon baseline sessions).

62
Q

Baseline Function: Setting Targets

A

Used for setting target outcomes (E.g., reduction or increase relative to baseline). Sometimes shows that intervention is not needed or may be unlikely to produce gains.

63
Q

How much baseline?

A

The longer the baseline, the greater the predictive power, but nothing is gained by unduly long baselines.
“As long as necessary, as short as possible.”

64
Q

Generally, length of the baseline should be dictated by what?

A

Qualitative features of the data path… phase change logic.

65
Q

Baseline Logic: Phase Changes

A

Movement in the analysis from one level or kind of independent variable to the next level or kind of independent variable. Phase changes move the analysis towards an “AB” design.

66
Q

A-B Design

A

Baseline followed by a treatment phase. Effect is demonstrated when behavior changes from one phase to the next.

67
Q

A-B Design Limitations

A

By itself, only supports weak conclusions. Changes in behavior may be the result of extraneous variables.

68
Q

When are A-B designs recommended?

A

When other, more compelling, designs are untenable

69
Q

What arrangements form the basis of all common single-case designs?

A

A-B arrangements.

70
Q

Phase Change Logic

A

Ideally, phase changes are made when behavior reaches a steady rate.

71
Q

What is a “steady state” defined by?

A

Level - Behavior is high or low enough that you will be able to detect a change if one occurs.

  • Stability - Levels of behavior do NOT vary greatly from one measurement to the next
  • Trend - The behavior is NOT already changing in the direction predicted for treatment.
72
Q

Phase Change Logic: When?

A

Avoid set number of data points (E.g., gather baseline data for 3 sessions). Regardless of length, consider the last three points as a small trend.

73
Q

Phase Change Logic: Stability

A

A quantitative rule for determining if the trend is sufficiently stable. When in doubt, run it out.

74
Q

Reversal Designs: Procedure

A

Following baseline, the independent variable is introduced, then withdrawn. This occurs at least once (A-B-A Design)

75
Q

What type of design is more common and preferable?

A

ABAB Design (Introduction and removal of the independent variables two times).

76
Q

Reversal Designs: “ABA”

A
  • Baseline Phase (A) - Independent variable is absent
  • Intervention Phase (B): Independent variable is introduced and remains present.
  • Return To Baseline (A): Independent variable is withdrawn
77
Q

Reversal Designs: Logic

A

If behavior changes systematically as a function of the introduction and withdrawal of the independent variable the likelihood is small that some extraneous variable produced the change. This likelihood decreases with each subsequent withdrawal and introduction of the iV.

78
Q

Reversal Designs: What is baseline?

A

If an intervention is immediately critical, analysis may begin with the intervention phase. Beginning with intervention does not alter the logic of the design.

79
Q

Advantages of Reversal Design

A

Most straightforward single-case arrangement. Most powerful demonstration of functional relations.

80
Q

Reversal Limitations

A

(T/O.I.E.)

  • Time and Order
  • Irreversibility
  • Ethics
81
Q

Reversal Limits: Irreversibility

A

Some behavior changes are not reversible.

  • Intervention produces effects that are impossible to withdraw (E.g., skill acquisition)
  • Behavior, after initial change, makes contact with other variables that makes reversal unlikely even if intervention is withdrawn (E.g., contrived reinforcement to support social initiations –> initiations get support by the response of peers)
82
Q

Reversal Limitations: Ethics

A

In cases, it may be unethical to reverse treatment.

83
Q

Reversal Limitations: Time and Order

A

May require considerable time because stability required in all stages (level, stability, trend). Dangers in the comparison of multiple treatments due to sequence effects (ABAC vs. ACAB).

84
Q

Use Reversal Designs if…

A

The target behavior is reversible. Withdrawal of the intervention is not a concern. Stability/order/time is not a concern.

85
Q

Withdrawal vs. Reversal Design

A

Withdrawal: Single behavior is tracked. Baseline and Treatment are alternated.
-Reversal Design: Baseline data are collected on two separate behaviors.

86
Q

Steps of Reversal Design

A

1: BL on 2 bx
2: Tx 1 applied to bx 1, tx 2 applied to bx 2
3: Bx 1 receives Tx 2, Bx 2 receives Tx 1.
4: Bx 1 receives tx 1, behavior 2 receives tx 2.

87
Q

Multiple Baseline Design: Procedure

A

1: Two or more independent baselines are established.
2: The IV is then separately introduced in a staggered fashion to each baseline.
3: When behavior is stable for the first baseline, the IV is introduced on the second baseline, and so on.

88
Q

Multiple Baseline Design: Logic

A

Experimental control is demonstrated by showing that behavior changes when, and only when, the IV is introduced to each baseline. The plausibility of extraneous variables causing the change is highly unlikely under the circumstances.

89
Q

Three standard variations of multiple baseline design

A
  • Multiple baseline across subjects
  • Multiple baseline across behaviors
  • Multiple baseline across settings
90
Q

Advantages of the multiple-baseline design

A

Useful when behavior change is not reversible. Does not require countertherapeutic behavior change to demonstrate experimental control. Experimenter can empirically evaluate methods and interventions before applying on a larger scale.

91
Q

Multiple Baseline Designs: How many baselines?

A

The larger the number, the more convincing, lending to both internal and external validity.

92
Q

Why can using only two baselines in a multiple baseline design be a risk?

A

If one does not change, the conclusions are questionable (essentially, an AB design). If 3+ are used and one does not change, still a reasonable demonstration of experimental control (the failure is the likely outlier).

93
Q

How long of a baseline should be used in Multiple Baseline Design?

A

Same rules apply: “As long as necessary, as short as possible.”

94
Q

Ethical considerations to the length of a baseline in multiple baseline design

A

Can we wait to treat the second subject? The longer the baseline, the greater the opportunities for the influence of extraneous variables (diffusion of treatment, practice effects (testing), history effects, maturation effects).

95
Q

Multiple Baseline Design Limitations

A

Interdependency. Inappropriate when the behaviors are interdependent (changing behavior in one baseline is likely to change the behaviors in the other baseline even though the IV is not introduced is other baselines).

96
Q

Multiple Baseline Procedural guidelines

A
  • Select independent, but functionally similar, baselines.
  • Select concurrent and plausibly related baselines.
  • Intervene on the most stable baseline first.
  • Vary the length of multiple baselines significantly.
97
Q

Non-concurrent multiple baselines

A

Separate baselines are taken and staggered in terms of the number of data points in the same way, but the baselines are not conducted at the same time.

98
Q

What is non-concurrent multiple baseline also known as?

A

Delayed multiple baseline

99
Q

Non-concurrent multiple baseline logic

A

Analysis need not be completed concurrently because the chances that the same extraneous variable (rather than the same IV) produced the same results is even more remote if the baselines are separated by time.

100
Q

Advantages of Non-concurrent multiple baseline use

A

Permits greater flexibility in the analysis - not constrained by having to have all subjects concurrently present

101
Q

Limitations to non-concurrent multiple baseline use

A

Presents a greater interpretive challenge than concurrent multiple baseline if behavior changes on subsequent baselines before IV is introduced.
Not useful across behaviors or settings.

102
Q

Multiple probe technique

A

Intermittent measures, or “probes,” are taken rather than continuous measurement on each baseline.

103
Q

Often in Multiple Probe Design, the first baseline is ____, but subsequent baseline data collection is ____

A

Often, first baseline is continuous, but subsequent baseline data collection is conducted on an intermittent basis relative to the first baseline.

104
Q

Advantages to multiple probe use

A

Avoids “ritualistic” gathering of baseline data - behavior is so stable (e.h., zero rates) it is unlikely to change.

  • Avoids various threats (e.g., extended practice).
  • Useful when extended baseline sessions are impractical, costly, or possibly detrimental (e.g.m repeated exposure to non-treatment conditions)
105
Q

Multiple Probe Use limitations

A

Risks stability - e.g., perhaps infrequent probes were outliers.

BEHP 5012 (7 decks)

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