Structured Observations

What is it?
Structured observations are a method used to collect data by simply watching people, animals or things. It can be as simple as observing people’s activity or how they interact with something and then recording information about that interaction or activity. It is a method that can be used for Community Based Action Research or Participatory Research projects. Observations can be used for estimating the number of people that engage with an activity, for example counting how many people rode their bikes at an intersection. It is also used for assessing the number of people who engaged with something in a certain way i.e. # walked through the intersection, # ran through the intersection, # rode a bike, etc. It’s a structured observation because you have parameters of what you want to observe, you set out to look and log certain behaviors. Structured observations do have their limitations - observation are not good to determine participant characteristics such as race, income, religion or sexual orientation.

Structured observation is a good method because you can:

• Document behaviors that can easily be seen (# of people sitting vs. standing);
• assess people’s behavior and/or reactions;
• collect real-time data, such as the # of people at an activity or event;
• capture relevant information about the environment or setting that can be important for research (such as the weather or time of day); and
• collect information without interacting with the participant’s you’re observing

What is needed?
• Materials needed: Observation tracking sheet, clipboards, pens or tablets and stylus
• Necessary logistics: Set geographic location, data collection volunteers, time to collect data and analyze
• Actors: Target population
• Essential skill-set or expertise required

Planning (3-9 hours)
1. Designing the observation protocol
2. Information on the logistics, location for observation
2. Training the volunteers or participants

Implementation (3 - 20 hours)
1. Getting together the materials
2. Doing the observations

Analysis (6 - 25 hours)
1. Training staff on data analysis (2-5 hours)
2. Data entry (up to 10 minutes per protocol)
3. Organizing data, cleaning data, observation notes and setting up analysis plan (up 15 hours)

Is an expert needed?
Yes (describe below) Expertise is only required for the principal investigator, data manager or person leading the data collection team. This person should be well versed in the research process, know ethical standards to adhere to and help participants design a useful observation tracking tool. This person will also need to train participants or data collectors on collecting data, how to use the observation tool and on how to analyze the data afterwards. IRB approval may be necessary for the research taking place.

How to
We will use an example, a group of youth wanted to see about adding more lighting and a walking trail in a park near their school. Through a CBAR project with a local university, they decided to do a structured observation of the park to determine the physical activities already taking place during the day and after dark.

Design the Structured Observation:

1. Design the research questions through a CBAR or participatory research process.
2. Determine what kind of activity you want to observe, and your target population or location that you want to observe.
3. Obtain permission to observe the location or population
4. Refine what activity needs to be observed and how best to observe it.
a. In the example, youth want to see how many people engage in a physical activity in a park. They decide to observe the park for a week (time), set up time shifts from sunrise to 2 hours after sunset (data collection schedule), they discuss the types of physical activities they anticipate people doing and create categories (determine the structure for their observation).
5. Design the structured observation protocol
6. Test the protocol and create any revisions

Collecting the Data:

1. Train all the data collection volunteers or team
2. Finalize the data collection schedule
3. Conduct a training for the data collectors
a. Share the data collection schedule
b. Go over any questions or scenarios
c. Determine is a sample # is necessary vs. observe all participants
4. Obtain all the materials (extra copies of the protocol, pens, directions, maps)
5. Meet at least 45 minutes prior to the data collection start time and go over any last minute adjustments

Analyzing the Data:

1. Determine the analysis software (manually data entry and Excel or Google Collaborative is often the most accessible for students, community members or CBAR participants)
2. Create a data dissemination plan (who is the final audience for the data and how best would they see or understand it)
3. Train the team in data entry, cleaning data and how to do basic analysis functions
4. Do the analysis as quickly as possible after the data collection, be ready to discuss anomalies and how to use the data
5. Use free services such as Piktochart to visualize the data for community-friendly reports or presentations

Good practice tips
Structured Observations Quick Facts:

• DO NOT capture information about why people exhibit certain behaviors
• DO NOT confirm personal characteristics of people such as their true feelings, income, race, sexual orientation
• Conducting observations might change the nature of the event (people might feel uncomfortable being observed or may change their behavior because if they notice they’re being observed)
• The tracking sheet that is used to record observations should be easy to complete and focus on a small number of behaviors
• Need to train observers and establish guidelines for consistency (observers may perceive the same behavior in a different way)
• For activities with a large number of people, consider a sample size vs. trying to observe the crowd

Success stories

To learn more
For data visualization:

Good examples of observation tools:

More on observation:


Created on 29 Nov 2016 22:10 by Lila Burgos
Updated on 29 Nov 2016 22:10 by Lila Burgos

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