Structured observations

Structured observations occur in controlled environments where researchers manipulate certain variables to focus on specific behaviours. This method reduces the 'naturalness' of behaviour because it often takes place in artificial settings, such as a laboratory, which allows for consistency but may not reflect real-life actions.

Key features of structured observations

• Controlled variables - Researchers decide the location, timing, participants, and circumstances to standardise the procedure, making it easier to replicate.
• Overt nature - Participants are usually informed about the study, so they know they are being observed, which can influence their behaviour.
• Non-participant approach - The researcher typically observes from a distance, such as behind a two-way mirror, without interacting directly with the group.

For example, Albert Bandura used structured observations in his Bobo doll studies to examine aggression in children.

Naturalistic observations

Naturalistic observations involve recording behaviour in its everyday environment without any interference from the researcher. This approach aims to capture actions as they naturally occur.

Key features of naturalistic observations

• No intervention - Researchers simply observe and note what happens, similar to studying animals in their natural habitat rather than a zoo.
• Goals - To describe behaviour in context and explore relationships between variables, such as how environmental factors influence actions.
• Applications - Often used when other methods, like lab experiments, would be impractical or too costly.

Participant and non-participant observations

Participant observations

In participant observations, the researcher becomes part of the group to observe from within. This immersion allows access to behaviours that might otherwise be hidden.

Key features of participant observations:

• Intervention - The researcher actively joins the environment, such as becoming a member of a social group, to gain insider perspectives.
• Types - Can be covert (hidden identity) or overt (open about the research); often used to study group cultures or behaviours that require trust.

Non-participant observations

Non-participant observations keep the researcher separate from the group, focusing on external viewing without direct involvement.

Key features of non-participant observations:

• Separation - The researcher enters the setting but does not participate in activities, often using tools like video recorders.
• Criticisms - The presence of an observer may alter behaviour, so multiple observations over time are common to build a reliable picture.
• Tools - Video recording can help, though it may still influence participants.

Covert and overt observations

Covert observations

• Covert observations keep the researcher's true purpose hidden from participants.
• They are used to gain unrestricted access, similar to undercover investigations, for gathering in-depth qualitative data through observations or interviews.

Overt observations

• Overt observations involve being open about the research, informing participants about the study's aims and duration.
• A key feature is transparency, as researchers explain the purpose, scope, and timeline to the group.

Recording and classifying observational data

A crucial part of any observation is deciding how to record and classify data systematically. This often involves tallying (counting occurrences) and sampling techniques to manage large amounts of information. Researchers may conduct a pilot study first to identify relevant behaviours and refine categories.

Event sampling

• Event sampling focuses on specific predefined behaviours, recording every occurrence while ignoring others.
• Researchers decide in advance on target events (e.g., instances of laughter in a social group) and tally them during the 20-minute observation period.

Time sampling

• Time sampling involves observing and recording behaviours only during predetermined intervals.
• Researchers choose systematic or random time periods (e.g., 12 minutes every hour) and note occurrences within those slots.

Content analysis

Content analysis is a research method used to systematically examine and quantify qualitative data from communication sources, transforming it into numerical form for analysis. It allows psychologists to categorise and compare content from media or other materials.

Key features of content analysis

• Sources - Can include written (newspapers, magazines), spoken (speeches), or visual (television, films, internet) materials; often from secondary sources or surveys.
• Process - Break down information into coding units (predefined categories based on the study's aims) then tally frequencies or incidents that match.
• Quantification - Converts qualitative data (e.g., themes in adverts) into quantitative data (e.g., counts of specific elements), enabling comparisons and insights.
• Aspects analysed - Focus on format (structure, such as pictorial vs. verbal) and content (meaning or themes).