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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.

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Presentation on theme: "Chapter 12: Single-Subject Designs An alternative to experimental designs Purpose: To draw conclusions about the effects of treatment based on the responses."— Presentation transcript:

1 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: A research hypothesis indicating expected relationship between independent and dependent variables Specific operational definitions

2 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

3 Single-Subject Designs Can be used to study comparisons between: Several treatments Components of treatments Treatment and no-treatment conditions

4 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

5 Design Phases Delineation of at least two testing periods: Baseline phase Intervention phase Target behavior is measured across both phases

6 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

7 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

8 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)

9 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

10 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

11 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

12 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

13 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

14 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

15 Target Behavior Can reflect: –Different response systems May focus on: Impairments functional limitations measures of disabilities Measurements may deal with overt motor behaviors- functional performance, ROM, gait characteristics

16 Measuring Target Behavior Frequency Duration Magnitude

17 Frequency 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

18 Frequency 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

19 Frequency 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?)

20 Frequency “ 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

21 Frequency “ 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)

22 Frequency 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

23 Frequency “ 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)

24 Duration 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

25 Duration 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

26 Duration 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

27 Magnitude Many clinical variables (target behaviors) are measured using instrumentation that provides quantitative data (Electrical, functional performance)

28 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

29 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)

30 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

31 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

32 Reliability 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

33 Reliability Interrater reliability is usually reported using a measure of percentage agreement 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

34 Reliability 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%

35 Reliability 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

36 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

37 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

38 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

39 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

40 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

41 Single-Subject Design Now you know all about single-subject design

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