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Chapter 9

Chapter 9 Notes 97-03.doc

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David Nussbaum

PSYB01 Chapter 9 – Small-N and Single-Subject Designs - We are oftentimes too quick to attribute improvement of client to own treatment - Single Subject = One subject, Small-N designs = 1 – 9 subjects - Focus on one individual: clinical processes of assessment, establishing intervention goals and specific outcomes, providing intervention and evaluating progress Foundations of Small-N Designs - An in-depth study of a single or relatively few subjects under tightly controlled experimental conditions in which the independent variable(s) is repeatedly manipulated over successive trials or conditions and in which the dependent variable(s) is repeatedly measured - Typically have 4 components: 1) Repeated measurement of dependent variable, 2) baseline phase, 3) Treatment phase(s), with all subjects exposed to each phase, 4) Graphic display o Repeated measurement: prior to intervention and during intervention, must be able to measure subject’s status on regular intervals (hours, days, weeks, months, etc.)  Try to delay intervention and collect sufficient data first but sometimes it is not the ethical approach, so you must use past records like report cards or case files o Baseline phase: typically abbreviated as A, represents the period in which the intervention to be evaluated is not offered to the subject, measures reflect status of client before intervention, o Patterns  Stable line: Line that is relatively flat, little variability, changes easily detected  Trends (scores may be either increasing or decreasing during baseline period): • Variable Flat-Line • Linear Trend (increasing or decreasing at a constant rate) • Curvilinear Trend (rate of change is accelerating over time) • Cyclical (regular increase and decrease) PSYB01 Chapter 9 – Small-N and Single-Subject Designs • No Pattern: get more data points to make certain about pattern or lack of o Internal Validity  When repeated measurements are taken during the baseline phase, several treats to internal validity are controlled  If you are measuring from time point to time point for sadness, it may regress over time anyway, so it will be harder to demonstrate effectiveness of intervention  A high score obtained from a measurement may be lower in a second measurement because of statistical regression or because of the respondent’s acclimation to the measurement process: if present, will occur during the beginning measurement, continued measurement should produce stable baseline pattern o Treatment Phase: signified by B, represents time period during which intervention is implemented, treatment phase should be as long as baseline phase o Graphing: Graphing data facilitates monitoring and evaluating impact of intervention, y-axis is for dependent variable whereas x-axis represents unit of time, such as hour, day, week or month Measuring Targets of Intervention - First, determine target problems (in the case of Sam, nurses were required to tally frequency of aggressive behaviours three times each day) - Measures of behaviours, status or functioning: o Frequency: counting number of times a behaviour occurs or number of times people experience different feeling within a particular time frame (can be burdensome if occurs too often but will not be meaningful if it rarely occurs) o Duration: length of time an event or some symptom lasts and usually measured for each occurrence (specify what is the beginning and end of a certain behaviour) o Interval: Length of time between events, clear definition of what is an interval is needed, not appropriate for events of symptoms that happen frequently unless intent of intervention is to delay onset PSYB01 Chapter 9 – Small-N and Single-Subject Designs o Magnitude: intensity of a particular behaviour or psychological state, scale used for nurses to score intensity of aggressive behaviour (how loud the screaming is, whether there is hitting, etc.) - Important to consider who will gather the data because they will be the judge of the behaviour - The very process of measurement may change a person’s behaviour (e.g. Act of keeping log of behaviour may reduce the behaviour)  Reactivity, must take longer measurements to mitigate - Concerns about whether it will be too time-consuming, too lengthy, not sensitive enough to detect changes, too global, etc. Analyzing Small-N and Single-Subject Designs - Visual inspection of data or statistical techniques such as two-standard deviation-band, chi-square analysis - Practical (clinical) significance: has intervention made a meaningful difference in the well-being of the subject o Setting criteria: Establish criteria for success o Cut-off scores: reducing problem to a level below a clinical cut-off score o Costs and Benefits: weigh costs and benefits to produce change - Visual Analysis: Looking at the graph of data points to determine whether intervention has altered subject’s pre-intervention pattern of scores o Level: Amount or magnitude of the target variable, ask whether amount of target variable has changed from baseline to intervention period
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