Survey Development Approach

Over the course of April through December 2023, the Lab's Culture Data Scientist engaged in the following activities to develop the LBNL Culture Survey:

• Reviewed academic literature for validated survey instruments related to engagement and similar outcomes

  • Used validated questions (and will conduct further validation) 

  • Checked for face validity via stakeholder meetings

• Cross-referenced with existing surveys done by divisions or by UC Berkeley and past surveys

  • Chose comparable questions where possible

  • Used similar constructs to prior surveys, with some new types of questions related to learning processes

• Held discussions about key priorities with Lab Directorate, ERGs, IDEA Chairs Council, divisional representatives from user facilities, HR Division Partners, and other stakeholder groups

• Took best practices from division surveys and tested survey questions on diverse groups in the Lab

Sampling Strategy

This culture survey will go to all Lab employees, both represented and non-represented. It will not go to affiliates/contingent workers. 

The higher number of employees who take this survey, the more likely the results will be representative of employee experiences across the Lab as a whole. There is always a risk that those who take the survey are systematically different than those who do not (for example, survey-takers may already feel a greater sense of community and so they are more willing to take time to fill out surveys).

To help alleviate this risk, we will also use weighted quota-based random sampling to have a representative sample, likely by Area, gender and possibly race depending on sample availability/ability to maintain confidentiality.

Survey Validation

We will validate survey results. In particular:

• Confirmatory factor analysis (CFA) to test whether the factorial structure was consistent

• Inter item correlation within a construct to consider adjusting questions

• We will use this information in conjunction with the regression analyses to consider adjusting constructs 

We did not do quantitative pre-survey validity testing because:

• Survey constructs and most items have been validated in prior surveys. 

• Constructs overlap so we do not expect a validation to show distinct constructs.

• We do not want to take out a large subsample of the Lab for a validation

• There is strong interest in each specific question

Data Sources

We will merge data collected by the survey with other data sources to understand the relationships between the different cultural constructs and areas of workplace well-being that the survey measures. Only the Culture Data Scientist will have the employee-level information linking survey responses to these data sources, and will immediately delete individual names -- please see the Data Privacy page. All reporting will be aggregated and confidential. These will include:

• Retention

• Years at the Lab

• Work mode (offsite, onsite, hybrid)

• Seniority

• Job type

• Area and division

• Gender

• Race/ethnicity 

• Career or term

• (Sexual orientation, disability, veteran status and education level depending on data quality)