Chapter 12 single subject designs
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Chapter 12: Single-Subject Designs. An alternative to experimental designs Purpose: To draw conclusions about the effects of treatment based on the responses of a single patient under controlled conditions. Based on:

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Chapter 12: Single-Subject Designs

  • An alternative to experimental designs


  • To draw conclusions about the effects of treatment based on the responses of a single patient under controlled conditions.

  • Based on:

  • A research hypothesisindicating expected relationship between independent and dependent variables

  • Specific operational definitions

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Single-Subject Designs

  • Independent Variable-

    The intervention

  • Dependent Variable-

    • The patient response (defined as the target behavior)

    • Target behavior is observable, quantifiable, and a valid indicator of treatment effectiveness

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Single-Subject Designs

  • Can be used to study comparisons between:

  • Several treatments

  • Components of treatments

  • Treatment and no-treatment conditions

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Structure of Single-Subject Designs

  • Repeated Measurement

  • Systematic collection of repeated measurements of a behavioral response over time

  • These repeated assessment are required to observe trends or patterns and evaluate variability of the behavioral responses over time

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Design Phases

  • Delineation of at least two testing periods:

    • Baseline phase

    • Intervention phase

    • Target behavior is measured across both phases

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Design Phases

  • Baseline information:

  • Responses of target behavior during a period of “no treatment”

  • Reflects the target behavior over time in the absence of the independent variable (intervention)

  • Changes from baseline to the intervention phase are attributed to the intervention

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Design Phases

  • Design phases are plotted on a line graph

  • Magnitude of the target behavior along the Y-axis

  • Time (sessions, trial, days, weeks) along the X-axis

  • Baseline is represented by the letter A

  • Intervention by the letter B

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Design Phases

  • The design of one baseline period followed by one intervention period is: A- B design

  • Baseline data collection

  • Unique to Single-Subject Design

  • (all other designs treatment is initiated following assessment)

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Baseline Data Collection

  • Traditional designs make it impossible to determine:

  • Which component of treatment actually caused observed changes

  • If observed changes would have occurred without intervention

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Baseline Data Collection

  • Baseline phase is a control period replacing a control group

  • Ethical considerations and baseline phase

    Not unethical to withdraw treatment for a short period when we are not sure of effectiveness of treatment

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Baseline Characteristics

  • Two characteristics of baseline data are important for interpretation of clinical outcomes:

    • Stability- Consistency of response over time

    • Trend- (slope) Shows the rate of change in the behavior

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Baseline Characteristics

  • The most desirable baseline pattern demonstrates:

    • A constant level of behavior

    • Minimal variability

      Indicating: Target behavior is not changing

      Therefore: Observable changes after intervention are due to intervention

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Baseline Characteristics

  • A variable baseline can present a problem for interpretation.

  • An Accelerating baseline-an increasing rate of response

  • A decelerating baseline-a decelerating rate of response

  • In both cases: a change in target behavior is occur13ring without intervention

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Length of Phases

  • Flexibility in considerations depending on:

    • Type of patient

    • Type of treatment

    • Expected rate of change in the target behavior

      It is essential that the length of time within each phase is sufficient to capture any changes

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Target Behavior

  • Can reflect:

    • Different response systems

      May focus on:


      functional limitations

      measures of disabilities

      Measurements may deal with overt motor behaviors- functional performance, ROM, gait characteristics

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Measuring Target Behavior

  • Frequency

  • Duration

  • Magnitude

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  • Counting the # of occurrences of the behavior within:

    • A fixed time interval

    • Fixed number of trials

    • “Frequency count” is the simplest of all behavioral measures

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  • Frequency count is appropriate to assess a discrete clinical behavior

    • Examples:

    • # of times a particular gait deviation occurs

    • # of times a client can repeat an exercise

    • # of times a patient loses her balance during a treatment session

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  • Operational definitions for frequency counts must specify:

    • How the target behavior is distinguished from other responses

    • What constitutes an occurrence and nonoccurrence

    • (partial completion of exercise? fall over but catching oneself?)

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  • “Frequency counts” are not useful when:

    • A behavior occurs too often to be counted reliably

    • A behavior lasts for a long time (occurs too seldom)

      The total time or total number of trials within which the count is made must remain constant across sessions

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  • “Frequency counts” do not account for the quality of the behavior but only that it occurred

  • “Frequency counts”can be expressed as:

    • A percentage

      • Dividing # of occurrences by total # of opportunities (percentage correct)

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  • Percentages are useful in that they are:

  • Easily understood

  • Efficient for summarizing large # of responses

  • Yet: If actual # of correct responses is an indicant of the target behavior, percentage can be misleading

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  • “Frequency counts” can be translated into “rates”

    • The number of times a behavior occurs within a specific time period (seconds, minutes, hours)

    • Dividing the total # of occurrences by the total time

    • (Ambulation in steps per minute)

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  • Target behaviors can be measured according to how long they last

  • Duration can be measured either as:

    • The cumulative total duration of a behavior during a treatment session

    • The duration of each individual occurrences of the behavior

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  • How long a patient stays in a balanced standing posture within:

    • A treatment session

    • Or:

    • Time how long it takes for a patient to complete a functional task

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  • Can be reported in terms of percentages

  • “Percentage time in zone”

    • (Dividing total time in the desired zone by total time of training session)

    • This approach is useful when sessions are not of equal length

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  • Many clinical variables (target behaviors) are measured using instrumentation that provides quantitative data

  • (Electrical, functional performance)

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Interval Recording for Observational Measures

  • Target behavior are usually recorded using either:

    • Quantitative instrumentation

      • Appropriate for magnitude measure

      • Objective

    • Self-report

      • Monitor activities outside the clinical environment

    • Direct observation

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Interval Recording

  • Often recorded using frequency & duration methods to record the occurrence or nonoccurrence of the behavior

  • Certain behaviors are difficult to quantify

    • Break down the measurement period into preset time intervals

    • Determine if behavior occur or does not occur during each interval period (5 minutes)

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Interval Recording

  • Sometimes called “time sampling”

  • Total session time is divided into small equal intervals

  • Measurement may involve:

    • Recording the presence/absence of the target behavior within each interval, and then tallying how many intervals contained the behavior

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Interval recording

  • Recording the frequency or duration of the behavior within each each interval

  • It is important to select a time interval that will best reflect the expected frequency and duration of the behavior

  • Requires the use of a signaling device

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  • Reliability is usually assessed concurrently with data collection, rather than in a separate pilot study

  • Reliability checks are performed by using two testers simultaneously observe the target behavior at several sessions across each phase

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  • Interrater reliability is usually reported using a measure of percentageagreement between observers

  • Total Reliability

    • Total steps: A=25; B=28;

    • Total reliability: (25/28)x 100= 89%

    • Limitation: Reflects only the consistency of the total score for a session, but may observe different instances of the behavior

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  • Point-by-Point/Interval-by-Interval/Trial-by Trial

  • Agreement is based on: Number of occasions on which the observers agree that a behavior occurred or not occurred is divided by total occasions that raters agree and disagree

  • Total 30 trials observers agreed on 29:

  • Trial-by-trial: (29/30) x 100= 97%

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  • Interval-by-interval

    • Of 16 intervals (15 minutes), observers disagreed on 3 times (intervals 3,5,11)

    • (13/16)x 100= 81%

    • Chance agreement

    • Kappa – provides a statistical measure

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Experimental Control

1. A-B: Baseline-Intervention (before-after)

2. A-B-A: Baseline-Intervention-Baseline (Withdrawal design)

If changes in behavior are not maintained during the second baseline phase- changes are due to intervention

3. A-B-A-B:

  • In 3, 4 designs, behavior must be reversible

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Experimental Control

  • Multiple Treatment Design

    1. A-B-C-B: Two treatments have independent and differential effects

    2. A-B-A-C: A second baseline phase between two treatments

    3. A-B-C-A-C-B: Sequential relationship between B and C, and examine each treatment effect after baseline

    4. A-B-C-BC: Combined phase

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Data Analysis

  • Analysis is based on evaluation of measurements within and across design phases to determine if:

    • Behaviors are changing

    • Observed changes during intervention are associated with the onset of treatment

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Data Analysis

  • 1. Visual analysis

    • No mathematical operations

    • Intuitively meaningful

    • Data within a phase are described according to:

      • Stability or variability

      • Trend- direction of change

      • Level- changes in magnitude (the value of the behavior) from last data point of one phase to another

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Data Analysis-Visual Analysis

  • Trend- direction of change within a phase

    • Accelerating or decelerating

    • Stable (constant) rate of change

    • Linear or curvilinear

  • A trend in baseline data:

    • No serious problem if against what is expected during intervention

    • A slope of a trend can only be determined for linear data

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    Single-Subject Design

    • Now you know all about single-subject design