Advertisement

Emotional reactions to infertility diagnosis: thematic and natural language processing analyses of the 1000 Dreams survey

Published:September 05, 2022DOI:https://doi.org/10.1016/j.rbmo.2022.08.107

      Highlights

      • Infertility diagnoses negatively affect patients and partners, men and women.
      • Emotional reactions point to significant cognitive threat appraisals
      • Diagnoses can trigger recollection of prior reproductive events or concerns
      • Natural language processing is an efficient text analysis tool in fertility care

      Abstract

      Research question

      What are the emotional effects of infertility on patients, partners, or both, and how can qualitative thematic analyses and natural language processing (NLP) help evaluate textual data?

      Design

      A cross-sectional, multi-country survey conducted between March 2019 and May 2019. A total of 1944 patients, partners, or both, from nine countries responded to the open-ended question asking about their initial feelings related to an infertility diagnosis. A mixed-method approach that integrated NLP topic modelling and thematic analyses was used to analyse responses. Sentiment polarity was quantified for each response. Linear regression evaluated the association between patient characteristics and sentiment negativity.

      Results

      Common emotional reactions to infertility diagnoses were sadness, depression, stress, disappointment, anxiety, frustration, confusion and loss of self-confidence. NLP topic modelling found additional reactions, i.e. shared feelings with partners, recollections about causes of infertility and treatment experience. Responses to the open-ended question were brief (median: three words) with 71.8% conveying negative sentiments. Some respondent characteristics showed small but significant associations with sentiment negativity, i.e. country (Spain, China and France were more negative than the USA, P < 0.001, P < 0.003 and P < 0.009 respectively), treatment engagement (no treatment was more negative than one or more treatment, P = 0.027) and marital status (missing/other was more negative than divorced, P = 0.003).

      Conclusion

      Infertility diagnoses create an emotional burden for patients and partners. The mixed-method approach provides a compelling synergy in support of the validity of these findings and shows potential for these techniques in future research.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Reproductive BioMedicine Online
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Arya S.T.
        • Dibb B.
        The experience of infertility treatment: the male perspective.
        Hum. Fertil. (Camb.). 2016; 19: 242-248
        • Baiocco R.
        • Laghi F.
        Sexual orientation and the desires and intentions to become parents.
        J. Fam. Stud. 2013; 19: 90-98
        • Baumer E.
        • Mimno D.
        • Guha S.
        • Quan E.
        • Gay G.K.
        Comparing grounded theory and topic modeling: Extreme divergence or unlikely convergence?.
        Journal of the Association for Information Science and Technology. 2017; 68: 1397-1410
        • Biggs A.
        • Brough P.
        • Drummond S.
        Lazarus and Folkman's psychological stress and coping theory.
        in: The handbook of stress and health: A guide to research and practice. Wiley Blackwell, Hoboken, NJ, US2017: 351-364
        • Blei D.M.
        • Ng A.Y.
        • Jordan M.I.
        Latent dirichlet allocation.
        Journal of Machine Learning Research. 2003; 3: 993-1022
        • Boivin J.
        • Vassena R.
        • Costa M.
        • et al.
        Tailored support may be required to reduce the impact of the infertility journey on mental health, relationships and daily lives of infertile patients and partners to infertile patients.
        Reprod. Biomed. Online. 2022;
        • Braun V.
        • Clarke V.
        Using thematic analysis in psychology.
        Qualitative Research in Psychology. 2006; 3: 77-101
        • De Berardis D.
        • Mazza M.
        • Marini S.
        • et al.
        Psychopathology, emotional aspects and psychological counselling in infertility: a review.
        Clin. Ter. 2014; 165: 163-169
        • Domar A.
        • Gordon K.
        • Garcia-Velasco J.
        • La Marca A.
        • Barriere P.
        • Beligotti F.
        Understanding the perceptions of and emotional barriers to infertility treatment: a survey in four European countries.
        Hum. Reprod. 2012; 27: 1073-1079
        • Domar A.
        • Vassena R.
        • Dixon M.
        • et al.
        Barriers and factors associated with significant delays to initial consultation and treatment for infertile patients and partners of infertile patients.
        Reprod. Biomed. Online. 2021; 43: 1126-1136
        • Friese S.
        • Ringmayr T.
        ATLAS. ti 8 Windows user manual.
        ATLAS. ti Scientific Software Development GmbH, Berlin2018
        • Heinze G.
        • Wallisch C.
        • Dunkler D.
        Variable selection - A review and recommendations for the practicing statistician.
        Biom. J. 2018; 60: 431-449
        • Himmel W.
        • Reincke U.
        • Michelmann H.W.
        Text mining and natural language processing approaches for automatic categorization of lay requests to web-based expert forums.
        J. Med. Internet Res. 2009; 11: e25
        • Hu M.
        • Liu B.
        Mining and summarizing customer reviews.
        in: Paper presented at: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Seattle, WA, 2004
        • Hynie M.
        • Burns L.H.
        Cross-cultural Issues in Infertility Counseling.
        in: Covington, S.N. Burns L.H. Infertility Counseling - a Comprehensive Handbook for Clinicans. Cambridge University Press, Cambridge2006: 61-82
        • Koert E.
        • Harrison C.
        • Bunting L.
        • Gladwyn-Khan M.
        • Boivin J.
        Causal explanations for lack of pregnancy applying the common sense model of illness representation to the fertility context.
        Psychol Health. 2018; 33: 1284-1301
        • Lakatos E.
        • Szigeti J.F.
        • Ujma P.P.
        • Sexty R.
        • Balog P.
        Anxiety and depression among infertile women: a cross-sectional survey from Hungary.
        BMC Womens Health. 2017; 17: 48
        • Maroufizadeh S.
        • Hosseini M.
        • Rahimi Foroushani A.
        • Omani-Samani R.
        • Amini P.
        The Relationship between Perceived Stress and Marital Satisfaction in Couples with Infertility: Actor-Partner Interdependence Model.
        Int. J. Fertil. Steril. 2019; 13: 66-71
        • Mascarenhas M.N.
        • Flaxman S.R.
        • Boerma T.
        • Vanderpoel S.
        • Stevens G.A.
        National, regional, and global trends in infertility prevalence since 1990: a systematic analysis of 277 health surveys.
        PLoS Med. 2012; 9e1001356
      1. Mohammad, S., Kiritchenko, S., Zhu, X. NRC-Canada: Building the state-ofthe-art in sentiment analysis of tweets. Paper presented at: Seventh International Workshop on Semantic Evaluation 2013.

        • Ni Y.
        • Tong C.
        • Huang L.
        • Zhou W.
        • Zhang A.
        The analysis of fertility quality of life and the influencing factors of patients with repeated implantation failure.
        Health Qual. Life Outcomes. 2021; 19: 32
        • Nielsen F.A.
        A new ANEW: Evaluation of a word list for sentiment analysis in microblogs.
        in: Proceedings of the ESWC2011 Workshop on 'Making Sense of Microposts': Big things come in small packages. CEUR Workshop Proceedings, 2011 (No. 718:93-98)
        • Osadchiy V.
        • Jiang T.
        • Mills J.N.
        • Eleswarapu S.V.
        Low Testosterone on Social Media: Application of Natural Language Processing to Understand Patients' Perceptions of Hypogonadism and Its Treatment.
        J. Med. Internet Res. 2020; 22: e21383
        • Osadchiy V.
        • Mills J.N.
        • Eleswarapu S.V.
        Understanding Patient Anxieties in the Social Media Era: Qualitative Analysis and Natural Language Processing of an Online Male Infertility Community.
        J. Med. Internet Res. 2020; 22: e16728
      2. Ozdemir, C., Bergler, S. CLaC- ¨ SentiPipe: SemEval2015 Subtasks 10 B, E, and Task 11. Paper presented at: International Workshop on Semantic Evaluation 2015a; Denver, CO.

      3. Ozdemir, C., Bergler, S. A Comparative Study of Different Sentiment Lexica for Sentiment Analysis of Tweets. Paper presented at: Recent Advances in Natural Language Processing 2015b; Hissar, Bulgaria.

        • Reagan A.J.
        • Danforth C.M.
        • Tivnan B.
        • Williams J.R.
        • Dodds P.S.
        Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs.
        EPJ Data Science. 2017; 6: 28
        • Riskind R.G.
        • Patterson C.J.
        Parenting Intentions and Desires Among Childless Lesbian, Gay, and Heterosexual Individuals.
        J. Fam. Psychol. 2010; 24: 78-81
        • Rooney K.L.
        • Domar A.D.
        The relationship between stress and infertility.
        Dialogues Clin. Neurosci. 2018; 20: 41-47
        • Shmueli G.
        To Explain or to Predict?.
        Statistical Science. 2010; 25: 289-310
        • Simionescu G.
        • Doroftei B.
        • Maftei R.
        • et al.
        The complex relationship between infertility and psychological distress (Review).
        Exp. Ther. Med. 2021; 21: 306
      4. Socher, R., Perelygin, A., Wu, J. et al. Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank. Paper presented at: EMNLP2013.

        • van Empel I.W.
        • Nelen W.L.
        • Tepe E.T.
        • van Laarhoven E.A.
        • Verhaak C.M.
        • Kremer J.A.
        Weaknesses, strengths and needs in fertility care according to patients.
        Hum. Reprod. 2010; 25: 142-149
        • Vander Borght M.
        • Wyns C.
        Fertility and infertility: Definition and epidemiology.
        Clin. Biochem. 2018; 62: 2-10
        • Wilson T.
        • Wiebe J.
        • Hoffmann P.
        Recognizing contextual polarity in phraselevel sentiment analysis.
        in: Paper presented at: Conference on Human Language Technology and Empirical Methods in Natural Language Processing. Vancouver, Canada, 2005

      Biography

      Jacky Boivin is Professor of Health Psychology at the School of Psychology, Cardiff University. She leads the Cardiff Fertility Studies Research Group. Together with collaborators, she has led pioneering research on the psychosocial aspects of fertility and produced many tools for patient support in fertility care.
      Key message
      This study demonstrated the synergy between natural language processing for big data and thematic analysis methods but also divergences that were additive to current understanding of infertility diagnosis and its effect. The mixed approach shows potential for future research using large textual datasets.