Add current citation info to README

README.md

@@ -8,12 +8,32 @@ project Human Machine Communication (HMC).
 
 ## Abstract
 
-Since the emergence of large language models (LLMs) in 2022, generative artificial intelligence (AI) has rapidly expanded into mainstream applications, leading, for example, to the integration of Apple Intelligence into customer devices in 2024.
+Since the emergence of large language models (LLMs) in 2022, generative
-This integration into personal technology marks a significant shift and a further reduction in barriers to use, bringing advanced AI capabilities into everyday devices and making them accessible to private individuals.
+artificial intelligence (AI) has rapidly expanded into mainstream applications,
-Thus, the use of generative AI--consciously or unconsciously--along with interaction through LLM-powered (voice) assistants and engagement with AI-generated content is expected to increase significantly.
+leading, for example, to the integration of Apple Intelligence into customer
-However, data that link this usage to psychological variables and track it over time remain scarce.
+devices in 2024. This integration into personal technology marks a significant
-This longitudinal study comprises the data from an US-American sample across six waves at two-month intervals between September 2024 and July 2025. It examines user behavior, attitudes, knowledge, and perceptions related to generative AI.
+shift and a further reduction in barriers to use, bringing advanced AI
-Thus, this data set allows for future research on psychological and behavioral dynamics of AI use over time, offering insights into user engagement and the individual factors connected to it.
+capabilities into everyday devices and making them accessible to private
+individuals. Thus, the use of generative AI--consciously or unconsciously--along
+with interaction through LLM-powered (voice) assistants and engagement with
+AI-generated content is expected to increase significantly. However, data that
+link this usage to psychological variables and track it over time remain scarce.
+This longitudinal study comprises the data from an US-American sample across six
+waves at two-month intervals between September 2024 and July 2025. It examines
+user behavior, attitudes, knowledge, and perceptions related to generative AI.
+Thus, this data set allows for future research on psychological and behavioral
+dynamics of AI use over time, offering insights into user engagement and the
+individual factors connected to it.
+
+## Citation
+
+- Please cite the following preprint, when reusing the data
+
+> Henestrosa, A., Anders, G., Ehrhardt, N., Faller, A. C., Hampel, N., Ivan, I.
+> V., Klein, S. H., Luther, T., Prentice, M., Sarigül, B., Utz, S., &
+> Wickelmaier, N. (2026). Longitudinal dataset of psychological variables
+> influencing AI perception and usage. OSF.
+> https://doi.org/10.31234/osf.io/qdfeg_v1
 
 
 ## Project status
@@ -49,6 +69,7 @@ The waves were collectec over the following dates:
 * Wave 5: 2025-05-07 - 2025-05-20
 * Wave 6: 2025-07-02 - 2025-07-18
 
+
 ## ChatGPT versions during data collection
 
 * May 2024: ChatGPT with GPT-3.5
@@ -58,6 +79,7 @@ The waves were collectec over the following dates:
 
 Source: https://en.wikipedia.org/wiki/ChatGPT#Model_versions
 
+
 ## Folder structure and files
 
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