SEOE: an option graph based semantically embedding method for prenatal depression detection

Abstract

Prenatal depression, which can affect pregnant women’s physical and psychological health and cause postpartum depression, is increasing dramatically. Therefore, it is essential to detect prenatal depression early and conduct an attribution analysis. Many studies have used questionnaires to screen for prenatal depression, but the existing methods lack attributability. To diagnose the early signs of prenatal depression and identify the key factors that may lead to prenatal depression from questionnaires, we present the semantically enhanced option embedding (SEOE) model to represent questionnaire options. It can quantitatively determine the relationship and patterns between options and depression. SEOE first quantifies options and resorts them, gathering options with little difference, since Word2Vec is highly dependent on context. The resort task is transformed into an optimization problem involving the traveling salesman problem. Moreover, all questionnaire samples are used to train the options’ vector using Word2Vec. Finally, an LSTM and GRU fused model incorporating the cycle learning rate is constructed to detect whether a pregnant woman is suffering from depression. To verify the model, we compare it with other deep learning and traditional machine learning methods. The experiment results show that our proposed model can accurately identify pregnant women with depression and reach an F1 score of 0.8. The most relevant factors of depression found by SEOE are also verified in the literature. In addition, our model is of low computational complexity and strong generalization, which can be widely applied to other questionnaire analyses of psychiatric disorders.

Graphical abstract

Keywords

questionnaire analyses / text classification / graph representation learning / traveling salesman problem / prenatal depression

Xiaosong Han got his PhD degree from Jilin University, China in 2012. The research fields are machine learning and bioinformatics

Mengchen Cao got a bachelor’s degree from Jilin University, China in 2017. The research field is machine learning

Dong Xu received his PhD degree from the University of Illinois at Urbana-Champaign, USA. The research fields are computational biology and bioinformatics

Xiaoyue Feng got her PhD degree from Jilin University, China. The research fields are knowledge graph and recommendation system

Yanchun Liang got his PhD degree from Jilin University, China in 1997. The research fields are machine learning and computational intelligence

Xiaoduo Lang works in Jilin Provincial Institute of Population Science and Technology, China. The research fields are obstetrics and gynecology

Renchu Guan got his PhD degree from Jilin University, China. The research fields are knowledge engineering and bioinformatics

References

[1] WHO. World mental health report: transforming mental health for all. Geneva: WHO, 2022

[2] Mukherjee S, Trepka M J, Pierre-Victor D, Bahelah R, Avent T . Racial/ethnic disparities in antenatal depression in the united states: a systematic review. Maternal and Child Health Journal, 2016, 20( 9): 1780–1797

[3] Okagbue H I, Adamu P I, Bishop S A, Oguntunde P E, Opanuga A A, Akhmetshin E M . Systematic review of prevalence of antepartum depression during the trimesters of pregnancy. Open Access Macedonian Journal of Medical Sciences, 2019, 7( 9): 1555–1560

[4] Lee A M, Lam S K, Lau S M S M, Chong C S Y, Chui H W, Fong D Y T . Prevalence, course, and risk factors for antenatal anxiety and depression. Obstetrics & Gynecology, 2007, 110( 5): 1102–1112

[5] Hay D F, Pawlby S, Waters C S, Sharp D . Antepartum and postpartum exposure to maternal depression: different effects on different adolescent outcomes. Journal of Child Psychology and Psychiatry, 2008, 49( 10): 1079–1088

[6] Deave T, Heron J, Evans J, Emond A . The impact of maternal depression in pregnancy on early child development. Obstetrical & Gynecological Survey, 2008, 63( 10): 626–628

[7] Andersson L, Sundström-Poromaa I, Wulff M, Åström M, Bixo M . Depression and anxiety during pregnancy and six months postpartum: a follow-up study. Acta Obstetricia et Gynecologica Scandinavica, 2006, 85( 8): 937–944

[8] Field T . Prenatal depression effects on early development: a review. Infant Behavior and Development, 2011, 34( 1): 1–14

[9] Milgrom J, Gemmill A W, Bilszta J L, Hayes B, Barnett B, Brooks J, Ericksen J, Ellwood D, Buist A. Antenatal risk factors for postnatal depression: a large prospective study. Journal of Affective Disorders, 2008, 108(1−2): 147−157

[10] Leigh B, Milgrom J. Risk factors for antenatal depression, postnatal depression and parenting stress. BMC psychiatry, 2008, 8: 1−11

[11] Cox J L, Holden J M, Sagovsky R . Detection of postnatal depression: development of the 10-item Edinburgh postnatal depression scale. British Journal of Psychiatry, 1987, 150( 6): 782–786

[12] Ware J E Jr, Sherbourne C D . The MOS 36-item short-form health survey (sf-36). I. Conceptual framework and item selection. Medical Care, 1992, 30( 6): 473–483

[13] Cohen S, Kamarck T, Mermelstein R . A global measure of perceived stress. Journal of Health and Social Behavior, 1983, 24( 4): 385–396

[14] Zimet G D, Dahlem N W, Zimet S G, Farley G K . The multidimensional scale of perceived social support. Journal of Personality Assessment, 1988, 52( 1): 30–41

[15] Buysse D J, Reynolds III C F, Monk T H, Berman S R, Kupfer D J . The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Research, 1989, 28( 2): 193–213

[16] Sidebottom A C, Harrison P A, Godecker A, Kim H . Validation of the patient health questionnaire (PHQ)-9 for prenatal depression screening. Archives of Women’s Mental Health, 2012, 15( 5): 367–374

[17] Lu J, Lu Z . Development, distribution and evaluation of online tourism services in China. Electronic Commerce Research, 2004, 4( 3): 221–239

[18] Lu J, Schmidt M, Lee M, Huang R . Usability research in educational technology: a state-of-the-art systematic review. Educational Technology Research and Development, 2022, 70( 6): 1951–1992

[19] Liu J H. Statistical analysis methods in survey questionnaires. Shanghai Statistics, 2002, (2): 35−37

[20] Liu X X, Dong R Z. Report on satisfaction questionnaire for higher education students - mainly using SEM analysis method. Journal of Vocational Education, 2011, 27(34): 19−21

[21] Xu R F . Selection for independent variables and regression method in logistic regression: an example analysis. Chinese Journal of Evidence-Based Medicine, 2016, 16( 11): 1360–1364

[22] Li L, Wu X, Kong M, Liu J, Zhang J . Quantitatively interpreting residents happiness prediction by considering factor–factor interactions. IEEE Transactions on Computational Social Systems, 2024, 11( 1): 1402–1414

[23] Yu Y, Duan J, Li M . Fusion model for tentative diagnosis inference based on clinical narratives. Tsinghua Science and Technology, 2023, 28( 4): 686–695

[24] Zhang H, Liu S, Chang H, Zhan M, Qin Q M, Zhang B, Li Z, Liu Y . Mining Magnaporthe oryzae sRNAs with potential transboundary regulation of rice genes associated with growth and defense through expression profile analysis of the pathogen-infected rice. Frontiers in Genetics, 2019, 10: 296

[25] Han X, Cao M, He J, Xu D, Liang Y, Lang X, Guan R . A comprehensive psychological tendency prediction model for pregnant women based on questionnaires. Scientific Reports, 2023, 13( 1): 2

[26] Meng Z, Chen C, Zhang X, Zhao W, Cui X. Exploring fragment adding strategies to enhance molecule pretraining in AI-driven drug discovery. Big Data Mining and Analytics, 2024, doi: 10.26599/BDMA.2024.9020003

[27] Mikolov T, Chen K, Corrado G, Dean J. Efficient estimation of word representations in vector space. In: Proceedings of the 1st International Conference on Learning Representations. 2013

[28] Yang Y, Chen H, Heidari A A, Gandomi A H . Hunger games search: visions, conception, implementation, deep analysis, perspectives, and towards performance shifts. Expert Systems with Applications, 2021, 177: 114864

[29] Guan R, Zhang H, Liang Y, Giunchiglia F, Huang L, Feng X . Deep feature-based text clustering and its explanation. IEEE Transactions on Knowledge and Data Engineering, 2022, 34( 8): 3669–3680

[30] Chung J, Gulcehre C, Cho K, Bengio Y. Empirical evaluation of gated recurrent neural networks on sequence modeling. 2014, arXiv preprint arXiv: 1412.3555

[31] Smith L N. Cyclical learning rates for training neural networks. In: Proceedings of 2017 IEEE winter conference on applications of computer vision (WACV). 2017, 464−472

[32] Lang X D, Wang N, Zang X D, Li J F . Survey on the pre-pregnancy psychological status of pregnant women of childbearing age and their demand for eugenic psychological counseling and guidance. China Practical Medical, 2017, 12( 24): 183–185

[33] Zung W W K . A self-rating depression scale. Archives of General Psychiatry, 1965, 12( 1): 63–70

[34] Zung W W. Self-rating anxiety scale. BMC Psychiatry, 1971

[35] Whitley D . A genetic algorithm tutorial. Statistics and Computing, 1994, 4( 2): 65–85

[36] Chen H, Heidari A A, Chen H, Wang M, Pan Z, Gandomi A H . Multi-population differential evolution-assisted Harris hawks optimization: Framework and case studies. Future Generation Computer Systems, 2020, 111: 175–198

[37] Ting C K, Su C H, Lee C N . Multi-parent extension of partially mapped crossover for combinatorial optimization problems. Expert Systems with Applications, 2010, 37( 3): 1879–1886

[38] Rong X. word2vec parameter learning explained. 2014, arXiv preprint arXiv: 1411.2738

[39] Levy O, Goldberg Y. Neural word embedding as implicit matrix factorization. In: Proceedings of the 27th International Conference on Neural Information Processing Systems. 2014, 2177−2185

[40] Scarselli F, Gori M, Tsoi A C, Hagenbuchner M, Monfardini G . The graph neural network model. IEEE Transactions on Neural Networks, 2009, 20( 1): 61–80

[41] Kipf T N, Welling M. Semi-supervised classification with graph convolutional networks. In: Proceedings of the 5th International Conference on Learning Representations. 2016

[42] Devlin J, Chang M W, Lee K, Toutanova K. BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2019

[43] Cui Y, Che W, Liu T, Qin B, Yang Z . Pre-training with whole word masking for Chinese BERT. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021, 29: 3504–3514

[44] Wang Y, Qiu Z, Jiao Q, Chen C, Meng Z, Cui X. Structure-based protein-drug affinity prediction with spatial attention mechanisms. In: Proceedings of IEEE International Conference on Bioinformatics and Biomedicine. 2021, 92−97

[45] Jiao Q, Qiu Z, Wang Y, Chen C, Yang Z, Cui X. Edge-gated graph neural network for predicting protein-ligand binding affinities. In: Proceedings of IEEE International Conference on Bioinformatics and Biomedicine. 2021, 334−339

[46] Van Laarhoven P J M, Aarts E H L. Simulated annealing. In: Laarhoven P J M, Aarts E H L, eds. Simulated Annealing: Theory and Applications. Dordrecht: Springer, 1987, 7−15

[47] Endoh S, Toma N, Yamada K. Immune algorithm for n-TSP. In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218). 1998, 3844−3849

[48] Grover A, Leskovec J. node2vec: scalable feature learning for networks. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016, 855−864

[49] Chen G, Liu J F, Zheng X Y . Analysis on risk factors and depression status of woman with birth defect child. Chinese Journal of Public Health, 2007, 23( 6): 674–675

[50] Murray J, Burgess S, Zuccolo L, Hickman M, Gray R, Lewis S J . Moderate alcohol drinking in pregnancy increases risk for children’s persistent conduct problems: causal effects in a Mendelian randomisation study. Journal of Child Psychology and Psychiatry, 2016, 57( 5): 575–584

[51] Martin-Santos R, Egmond E, Cavero M, Mariño Z, Subira S, Navines R, Forns X, Valdes M . Chronic hepatitis C, depression and gender: a state of art. Advances in Dual Diagnosis, 2015, 8( 4): 193–210

[52] Rao T S S, Prabhakar A K, Rao K S J, Sambamurthy K, Asha M R, Ram D, Nanda A . Relationship between consanguinity and depression in a south Indian population. Indian Journal of Psychiatry, 2009, 51( 1): 50–52

[53] Clark A, Skouteris H, Wertheim E H, Paxton S J, Milgrom J . The relationship between depression and body dissatisfaction across pregnancy and the postpartum: a prospective study. Journal of Health Psychology, 2009, 14( 1): 27–35

[54] Goyal D, Gay C, Lee K A. How much does low socioeconomic status increase the risk of prenatal and postpartum depressive symptoms in first-time mothers? Women’s Health Issues, 2010, 20(2): 96−104

[55] Li J. Health-related quality of life among pregnant women and related factors in Chinese mainland. Huazhong University of Science and Technology, Dissertation, 2011

[56] Leigh B, Milgrom J . Risk factors for antenatal depression, postnatal depression and parenting stress. BMC Psychiatry, 2008, 8( 1): 24

[57] Zachariah R . Social support, life stress, and anxiety as predictors of pregnancy complications in low-income women. Research in Nursing & Health, 2010, 32( 4): 391–404

[58] Tsartsara E, Johnson M P . The impact of miscarriage on women’s pregnancy-specific anxiety and feelings of prenatal maternal–fetal attachment during the course of a subsequent pregnancy: An exploratory follow-up study. Journal of Psychosomatic Obstetrics & Gynecology, 2006, 27( 3): 173–182

Acknowledgment

The authors are grateful for the support of the National Key R&D Program of China (No. 2021YFF1201200), the National Natural Science Foundation of China (Grant Nos. 61972174 and 62172187), the Science and Technology Planning Project of Jilin Province (No. 20220201145GX, No. 20200708112YY and No. 20220601112FG), the Science and Technology Planning Project of Guangdong Province (No. 2020A0505100018), Guangdong Universities’ Innovation Team Project (No. 2021KCXTD015) and Guangdong Key Disciplines Project (No. 2021ZDJS138).

Competing interests

The authors declare that they have no competing interests or financial conflicts to disclose.

RIGHTS & PERMISSIONS

2024 Higher Education Press