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 & Weighting Strategy

This culture survey went to all Lab employees, both represented and non-represented. The survey will not consider affiliates/contingent workers this round. 

Over 50% of employees took the survey. It is worthwhile to listen to the voice of such a large proportion of employees. The high response rate also makes it likely that the survey captured a wide range of employee feedback. 

Even given the high response rate, there is always a risk that those who take the survey are systematically different than those who do not. To help alleviate this risk, we used propensity scores to weigh the results by Area, Employee Class, gender and race/ethnicity. 

Survey Validation

We rely on theoretical justification and past research for construct creation. However, we make minor modifications based on survey validation. 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 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

• Seniority

• Job type

• Area and division

• Race/ethnicity 

• Career or term

• Employee class & work group (e.g., administator, scientist, engineer)

• Manager status

• Gender