Fuzzy constructs in technology usage scales
Brittany I Davidson; Heather Shaw; David A. Ellis · 2022 · Computers in Human Behavior
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
The finding, in one line
“However, pre-registered studies have failed to replicate these findings.”
Abstract
The mass adoption of digital technologies raises questions about how they impact people and society. Associations between technology use and negative correlates (e.g., depression and anxiety) remain common. However, pre-registered studies have failed to replicate these findings. Regardless of direction, many designs rely on psychometric scales that claim to define and quantify a construct associated with technology engagement. These often suggest clinical manifestations present as disorders or addictions. Given their importance for research integrity, we consider what these scales might be mea
Abstract by Brittany I Davidson; Heather Shaw; David A. Ellis, Computers in Human Behavior (2022) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Investigating Variation in Replicability
Negative / Null Result ReportMany Labs 2: Investigating Variation in Replicability Across Samples and Settings
Failed Experiment ReportGetting Ahead in the Communist Party: Explaining the Advancement of Central Committee Members in China
Negative / Null Result ReportReducing implicit racial preferences: II. Intervention effectiveness across time.
Negative / Null Result ReportTHE IMPACT OF IMMIGRATION ON THE STRUCTURE OF WAGES: THEORY AND EVIDENCE FROM BRITAIN
Negative / Null Result ReportRevisiting the Marshmallow Test: A Conceptual Replication Investigating Links Between Early Delay of Gratification and Later Outcomes
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.1016/j.chb.2022.107206