MedDataX Logo

The Relationship Between Quality of Life, Anxiety Levels, and Attitudes Toward Artificial Intelligence Among Women Undergoing Infertility Treatment

NCT ID: NCT07308561

Last Updated: 2025-12-29

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

RECRUITING

Total Enrollment

191 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-10-23

Study Completion Date

2026-10-23

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

Infertility affects approximately one in six individuals worldwide and is associated with significant psychological distress, particularly among women undergoing treatment. Increased anxiety levels are strongly linked to reduced quality of life during the infertility process. With the growing integration of artificial intelligence (AI) into healthcare, AI-based tools are increasingly used in infertility care to support decision-making and patient engagement. While many patients are familiar with AI technologies, individual attitudes toward AI may influence their acceptance and potential psychosocial benefits. This study aims to examine the relationship between attitudes toward artificial intelligence, anxiety levels, and quality of life among women undergoing infertility treatment.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Infertility, Female Artificial Intelligence Quality of Life Anxiety

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

OTHER

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

* Women aged 18-45 years diagnosed with infertility (primary or secondary infertility).
* Women undergoing infertility treatment and those who have experienced various treatment modalities (IUI, IVF, ICSI).
* Women who voluntarily agree to participate in the study.
* Women who are able to understand and speak Turkish.

Exclusion Criteria

* Women with diagnosed psychological disorders (e.g., clinical depression, anxiety disorders).
* Women who are not undergoing infertility treatment.
Minimum Eligible Age

18 Years

Maximum Eligible Age

45 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Acibadem University

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Güzin Ünlü Suvari

M.Sc., Lecturer

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Acıbadem Health Group

Istanbul, Ataşehir, Turkey (Türkiye)

Site Status RECRUITING

Countries

Review the countries where the study has at least one active or historical site.

Turkey (Türkiye)

Central Contacts

Reach out to these primary contacts for questions about participation or study logistics.

Güzin Ünlü Suvari, M.Sc.

Role: CONTACT

Phone: +902165004429

Email: [email protected]

Facility Contacts

Find local site contact details for specific facilities participating in the trial.

Güzin Ünlü Suvari, Ph.D. (C)

Role: primary

References

Explore related publications, articles, or registry entries linked to this study.

Simionescu G, Doroftei B, Maftei R, Obreja BE, Anton E, Grab D, Ilea C, Anton C. The complex relationship between infertility and psychological distress (Review). Exp Ther Med. 2021 Apr;21(4):306. doi: 10.3892/etm.2021.9737. Epub 2021 Feb 1.

Reference Type BACKGROUND
PMID: 33717249 (View on PubMed)

Song D, Li X, Yang M, Wang N, Zhao Y, Diao S, Zhang X, Gou X, Zhu X. Fertility quality of life (FertiQoL) among Chinese women undergoing frozen embryo transfer. BMC Womens Health. 2021 Apr 24;21(1):177. doi: 10.1186/s12905-021-01325-1.

Reference Type BACKGROUND
PMID: 33894750 (View on PubMed)

European Society of Human Reproduction and Embryology (ESHRE). (2024, April). Factsheet on infertility - prevalence, treatment and fertility decline in Europe. ESHRE. https://www.eshre.eu

Reference Type BACKGROUND

Shi Z, Zheng Y, Zhu X, Mao Z, Nie H, Chen G, Li S. Understanding health-related quality of life in Chinese infertility patients: a qualitative study. Qual Life Res. 2025 Nov;34(11):3105-3119. doi: 10.1007/s11136-025-04066-y. Epub 2025 Sep 13.

Reference Type BACKGROUND
PMID: 40944797 (View on PubMed)

Gameiro S, Boivin J, Dancet E, de Klerk C, Emery M, Lewis-Jones C, Thorn P, Van den Broeck U, Venetis C, Verhaak CM, Wischmann T, Vermeulen N. ESHRE guideline: routine psychosocial care in infertility and medically assisted reproduction-a guide for fertility staff. Hum Reprod. 2015 Nov;30(11):2476-85. doi: 10.1093/humrep/dev177. Epub 2015 Sep 7.

Reference Type BACKGROUND
PMID: 26345684 (View on PubMed)

Cromack SC, Lew AM, Bazzetta SE, Xu S, Walter JR. The perception of artificial intelligence and infertility care among patients undergoing fertility treatment. J Assist Reprod Genet. 2025 Mar;42(3):855-863. doi: 10.1007/s10815-024-03382-5. Epub 2025 Jan 7.

Reference Type BACKGROUND
PMID: 39776390 (View on PubMed)

Medenica S, Zivanovic D, Batkoska L, Marinelli S, Basile G, Perino A, Cucinella G, Gullo G, Zaami S. The Future Is Coming: Artificial Intelligence in the Treatment of Infertility Could Improve Assisted Reproduction Outcomes-The Value of Regulatory Frameworks. Diagnostics (Basel). 2022 Nov 28;12(12):2979. doi: 10.3390/diagnostics12122979.

Reference Type BACKGROUND
PMID: 36552986 (View on PubMed)

Sarshoori, A. A., Mostafavi, M., Heidarpoor, S., & Chekeni, A. M. (2024). Role of Artificial Intelligence in Infertility Screening and Treatment: A Systematic Review. Iranian Biomedical Journal, 28, 253.

Reference Type BACKGROUND

Lee, C., Chae, H. J., Kim, H. M., Lee, H., Choi, S., & Min, H. S. (2024). Enhancing infertility care with a ChatGPT-based chatbot: integrating clinical and community insights for improved patient support. Fertility and Sterility, 122(4), e141-e142.

Reference Type BACKGROUND

Méndez-Suárez, M., Delbello, L., de Vega de Unceta, A., & Ortega Larrea, A. L. (2024). Factors affecting consumers' attitudes towards artificial intelligence. Journal of Promotion Management, 30(7), 1141-1158.

Reference Type BACKGROUND

Mendizabal-Ruiz G, Paredes O, Borrayo E, Chavez-Badiola A. FERTILITY CARE IN LOW- AND MIDDLE- INCOME COUNTRIES: The future use of AI to improve accessibility of assisted reproductive technology in low- and middle-income countries. Reprod Fertil. 2025 Aug 14;6(3):e240077. doi: 10.1530/RAF-24-0077. Print 2025 Jul 1.

Reference Type BACKGROUND
PMID: 40736784 (View on PubMed)

Massarotti C, Gentile G, Ferreccio C, Scaruffi P, Remorgida V, Anserini P. Impact of infertility and infertility treatments on quality of life and levels of anxiety and depression in women undergoing in vitro fertilization. Gynecol Endocrinol. 2019 Jun;35(6):485-489. doi: 10.1080/09513590.2018.1540575. Epub 2019 Jan 7.

Reference Type BACKGROUND
PMID: 30612477 (View on PubMed)

Braverman AM, Davoudian T, Levin IK, Bocage A, Wodoslawsky S. Depression, anxiety, quality of life, and infertility: a global lens on the last decade of research. Fertil Steril. 2024 Mar;121(3):379-383. doi: 10.1016/j.fertnstert.2024.01.013. Epub 2024 Jan 13.

Reference Type BACKGROUND
PMID: 38224730 (View on PubMed)

Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Demir Kaya, M. (2022). The roles of personality traits, AI anxiety, and demographic factors in attitudes towards artificial intelligence. International Journal of Human-Computer Interaction. https://doi.org/10.1080/10447318.2022.2151730

Reference Type BACKGROUND

Schepman A, Rodway P. Initial validation of the general attitudes towards Artificial Intelligence Scale. Comput Hum Behav Rep. 2020 Jan-Jul;1:100014. doi: 10.1016/j.chbr.2020.100014. Epub 2020 May 18.

Reference Type BACKGROUND
PMID: 34235291 (View on PubMed)

Schepman, A. & Rodway, P. (2022). The General Attitudes towards Artificial Intelligence Scale (GAAIS): Confirmatory Validation and Associations with Personality, Corporate Distrust, and General Trust. International Journal of Human-Computer Interaction https://doi.org/10.1080/10447318.2022.2085400

Reference Type BACKGROUND

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

2025-15/591

Identifier Type: -

Identifier Source: org_study_id