BraunV.ClarkeV. (2012). Thematic analysis. In APA handbook of research methods in psychology, Vol 2: Research designs: Quantitative, qualitative, neuropsychological, and biological (pp. 57–71). American Psychological Association. https://doi.org/10.1037/13620-004
3.
BrooksV. R. (1981). Minority stress and lesbian women. Lexington Books.
4.
BuchananE. M.ScofieldJ. E. (2018). Methods to detect low quality data and its implication for psychological research. Behavior Research Methods, 50(6), 2586–2596. https://doi.org/10.3758/s13428-018-1035-6
5.
DennisS. A.GoodsonB. M.PearsonC. A. (2019). Online worker fraud and evolving threats to the integrity of MTurk data: A discussion of virtual private servers and the limitations of IP-based screening procedures. Behavioral Research in Accounting, 32(1), 119–134. https://doi.org/10.2308/bria-18-044
6.
DworkinE. R.KaysenD.Bedard-GilliganM.RhewI. C.LeeC. M. (2017). Daily-level associations between PTSD and cannabis use among young sexual minority women. Addictive Behaviors, 74, 118–121. https://doi.org/10.1016/j.addbeh.2017.06.007
7.
GriffinM.MartinoR. J.LoSchiavoC.Comer-CarruthersC.KrauseK. D.StultsC. B.HalkitisP. N. (2021). Ensuring survey research data integrity in the era of internet bots. Quality & Quantity, 56(4), 2841–2852. https://doi.org/10.1007/s11135-021-01252-1
8.
IliouC.KostoulasT.TsikrikaT.KatosV.VrochidisS.KompatsiarisY. (2019) Towards a framework for detecting advanced Web bots Proceedings international conference. Availability, Reliability and Security, ARES’19, Association for Computing Machinery, New York, NY, USA.
9.
IliouC.KostoulasT.TsikrikaT.KatosV.VrochidisS.KompatsiarisI. (2021). Detection of advanced web bots by combining web logs with mouse behavioural biometrics. Digital Threats: Research and Practice, 2(3), 24:1–24:26. https://doi.org/10.1145/3447815
10.
MeyerI. H. (2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129(5), 674–697. https://doi.org/10.1037/0033-2909.129.5.674
11.
PozzarR.HammerM. J.Underhill-BlazeyM.WrightA. A.TulskyJ. A.HongF.GundersenD. A.BerryD. L. (2020). Threats of bots and other bad actors to data quality following research participant recruitment through social media: Cross-sectional questionnaire. Journal of Medical Internet Research, 22(10), e23021. https://doi.org/10.2196/23021
12.
ShawT. J.CascalheiraC. J.HelminenE. C.BrisbinC. D.JacksonS. D.SimoneM.SullivanT. P.BatchelderA. W.ScheerJ. R. (2024). Yes stormtrooper, these are the droids you’re looking for: A method paper evaluating bot detection strategies in psychological research. Unpublished Manuscript, Department of Psychology, Syracuse University.
SimoneM.CascalheiraC. J.PierceB. G. (2024). A Quasi-experimental study examining the efficacy of multimodal bot screening tools and recommendations to preserve data integrity in online psychological research. American Psychologist, 79(7), 956–969. https://doi.org/10.1037/amp0001183
15.
StorozukA.AshleyM.DelageV.MaloneyE. A. (2020). Got bots? Practical recommendations to protect online survey data from bot attacks. The Quantitative Methods for Psychology, 16(5), 472–481. https://doi.org/10.20982/tqmp.16.5.p472
16.
TeitcherJ. E. F.BocktingW. O.BauermeisterJ. A.HoeferC. J.MinerM. H.KlitzmanR. L. (2015). Detecting, preventing, and responding to “fraudsters” in Internet research: Ethics and tradeoffs. Journal of Law, Medicine & Ethics, 43(1), 116–133. https://doi.org/10.1111/jlme.12200
17.
YarrishC.GroshonL.MitchellJ. D.AppelbaumA.KlockS.WinternitzT.Friedman-WheelerD. G. (2019). Finding the signal in the noise: Minimizing responses from bots and inattentive humans in online research. The Behavior Therapist, 42(7), 235–242.