McCarron RM, Shapiro B, Rawles J, Luo J. Depression. Ann Intern Med. 2021;174(5):ITC65–80.


Google Scholar
 

Goodwin GM, Croal M, Marwood L, Malievskaia E. Unblinding and demand characteristics in the treatment of depression. J AFFECT DISORDERS. 2023;328:1–5.


Google Scholar
 

Peltzer K, Pengpid S, Olowu S, Olasupo M. Depression and associated factors among university students in Western Nigeria. J PSYCHOL AFR. 2013;23(3):459–65.


Google Scholar
 

Ishtiak-Ahmed K, Rohde C, Köhler‐Forsberg O, Christensen KS, Gasse C. Depression treatment trajectories and associated social determinants: A Three‐Year Follow‐Up study in 66,540 older adults undergoing First‐Time depression treatment in Denmark. INT J GERIATR PSYCH. 2024;39(11):e70006.


Google Scholar
 

Fazel S, Runeson B, Suicide. NEW ENGL J MED. 2020;382(3):266–74.


Google Scholar
 

Williams JM, Broadbent K. Autobiographical memory in suicide attempters. J Abnorm Psychol. 1986;95(2):144–9.


Google Scholar
 

Martinengo L, Van Galen L, Lum E, Kowalski M, Subramaniam M, Car J. Suicide prevention and depression apps’ suicide risk assessment and management: A systematic assessment of adherence to clinical guidelines. BMC MED. 2019;17(1):231–231.


Google Scholar
 

Su Y, Ye C, Xin Q, Si T. Major depressive disorder with suicidal ideation or behavior in Chinese population: A scoping review of current evidence on disease assessment, burden, treatment and risk factors. J Affect Disord. 2023;340:732–42.


Google Scholar
 

O’Connor RC, Kirtley OJ. The integrated motivational–volitional model of suicidal behaviour. Phil Trans R Soc B. 2018;373(1754):20170268–20170268.


Google Scholar
 

Simes D, Shochet I, Murray K, Sands IG. Adolescent, caregivers, and therapists’ experiences of youth and family suicide intervention: a qualitative study. Psychother Res. 2024;1–19.

Williams JMG, Barnhofer T, Crane C, Hermans D, Raes F, Watkins E, Dalgleish T. Autobiographical memory specificity and emotional disorder. PSYCHOL BULL. 2007;133(1):122–48.


Google Scholar
 

Yin Q, Xu H, Chen Z, Jiang Q, Liu T. Detection of suicide risk using event-related potentials: a comprehensive systematic review and meta-analysis. Psychoradiology. 2025;5:kkaf018.


Google Scholar
 

Conway MA, Pleydell-Pearce CW. The construction of autobiographical memories in the Self-Memory system. Psychol Rev. 2000;107(2):261–88.


Google Scholar
 

Fang J, Dong Y. Autobiographical memory disturbance in depression. PSYCHOL HEALTH MED. 2022;27(7):1618–26.


Google Scholar
 

Rice F, Rawal A, Riglin L, Lewis G, Lewis G, Dunsmuir S. Examining reward-seeking, negative self-beliefs and over-general autobiographical memory as mechanisms of change in classroom prevention programs for adolescent depression. J AFFECT DISORDERS. 2015;186:320–7.


Google Scholar
 

Jiang W, Hu G, Zhang J, Chen K, Fan D, Feng Z. Distinct effects of over-general autobiographical memory on suicidal ideation among depressed and healthy people. BMC Psychiatry. 2020;20(1):501–501.


Google Scholar
 

Bruno E, Martz E, Weiner L, Greco A, Vanello N. Speech signal analysis as an aid to clinical diagnosis and assessment of mental health disorders. BIOMED SIGNAL PROCES. 2023;85:104854.


Google Scholar
 

Min S, Shin D, Rhee SJ, Park CHK, Yang JH, Song Y, Kim MJ, Kim K, Cho WI, Kwon OC, et al. Acoustic analysis of speech for screening for suicide risk: machine learning classifiers for Between- and Within-Person evaluation of suicidality. J Med Internet Res. 2023;25:e45456.


Google Scholar
 

Mundt JC, Vogel AP, Feltner DE, Lenderking WR. Vocal acoustic biomarkers of depression severity and treatment response. BIOL PSYCHIAT. 2012;72(7):580–7.


Google Scholar
 

Sahu S, Espy-Wilson C. Effects of depression on speech. J Acoust Soc Am. 2014;136(4Supplement):2312–2312.


Google Scholar
 

Wang J, Ravi V, Flint J, Alwan A. Unsupervised Instance Discriminative Learning for Depression Detection from Speech Signals. In. Ithaca: Ithaca: Cornell University Library, arXiv.org. 2022.

Amiriparian S, Gerczuk M, Lutz J, Strube W, Papazova I, Hasan A, Kathan A, Schuller BW. Non-Invasive Suicide Risk Prediction Through Speech Analysis. 2024.

Sinha P, Vandana VP, Lewis NV, Jayaram M, Enderby P. Predictors of effect of atypical antipsychotics on speech. Indian J Psychol Med. 2015;37(4):429–33.


Google Scholar
 

Steer RA, Rissmiller DJ, Beck AT. Use of the Beck depression Inventory-II with depressed geriatric inpatients. BEHAV RES THER. 2000;38(3):311–8.


Google Scholar
 

Wang Zhen YC-M, Huang Jia LZ-Z, Jue C. Zhang Hai-Yin, Fang Yi-Ru, Xiao Ze-Ping: reliability and validity of the Chinese version of Beck depression Inventory-II among depression Patients. 北京回龙观医院;北京心理危机研究与干预中心;WHO心理危机预防研究与培训合作中心 2011, 25(6):476–80.

Li XYPM, Tong YS, Li KJ, Zhang YL, Zhang YP, et al. Reliability and validity of the Chinese version of Beck suicide ideation Scale(BSI-CV)in adult community residents. Chin Ment Health J. 2010;24(4):250–5.


Google Scholar
 

Spezialetti M, Placidi G, Rossi S. Emotion recognition for Human-Robot interaction: recent advances and future perspectives. Front Robot AI. 2020;7:532279.


Google Scholar
 

Grilli MD, Sheldon S. Autobiographical event memory and aging: older adults get the gist. Trends Cogn Sci. 2022;26(12):1079–89.


Google Scholar
 

Chu C. Autobiographical memory perspectives in suicide attempt and task recall: a study of young adults with and without symptoms of suicidality. ProQuest Dissertations & Theses; 2015.

Weiss-Cowie S, Verhaeghen P, Duarte A. An updated account of overgeneral autobiographical memory in depression. NEUROSCI BIOBEHAV R. 2023;149:105157–105157.


Google Scholar
 

Sumner JA. The mechanisms underlying overgeneral autobiographical memory: an evaluative review of evidence for the CaR-FA-X model. CLIN PSYCHOL REV. 2012;32(1):34–48.


Google Scholar
 

Schuller BW, Batliner AM. Computational paralinguistics: emotion, affect and personality in speech and Language processing, first edition. edn. Chichester: Chichester: Wiley; 2013.


Google Scholar
 

Yamamoto M, Takamiya A, Sawada K, Yoshimura M, Kitazawa M, Liang KC, Fujita T, Mimura M, Kishimoto T. Using speech recognition technology to investigate the association between timing-related speech features and depression severity. PLoS ONE. 2020;15(9):e0238726.


Google Scholar
 

Yünden S, Ak M, Sert M, Gica S, Çinar O, Acar YA. Examination of speech analysis to predict suicidal behavior in depression. Eur Psychiatry. 2024;67(S1):S57–8.


Google Scholar
 

Suparatpinyo S, Soonthornphisaj N. Smart voice recognition based on deep learning for depression diagnosis. Artif Life Rob. 2023;28(2):332–42.


Google Scholar
 

Li R, Yang J, Li L, Shen F, Zou T, Wang H, Wang X, Li J, Deng C, Huang X, et al. Integrating multilevel functional characteristics reveals aberrant neural patterns during audiovisual emotional processing in depression. CEREB CORTEX. 2021;32(1):1–14.


Google Scholar
 

Zhou Y, Han W, Yao X, Xue J, Li Z, Li Y. Developing a machine learning model for detecting depression, anxiety, and apathy in older adults with mild cognitive impairment using speech and facial expressions: A cross-sectional observational study. INT J NURS STUD. 2023;146:104562–104562.


Google Scholar