{"id":"https://openalex.org/W7160283357","doi":"https://doi.org/10.1007/s44163-026-01308-x","title":"A multimodal fairness aware machine learning framework for mental health risk prediction in university students","display_name":"A multimodal fairness aware machine learning framework for mental health risk prediction in university students","publication_year":2026,"publication_date":"2026-05-03","ids":{"openalex":"https://openalex.org/W7160283357","doi":"https://doi.org/10.1007/s44163-026-01308-x"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-026-01308-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01308-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-01308-x.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-01308-x.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135353519","display_name":"Zhu Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096351","display_name":"Qinhuangdao Second Hospital","ror":"https://ror.org/00rcpde19","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210096351"]},{"id":"https://openalex.org/I4210116273","display_name":"Qinhuangdao Science and Technology Bureau","ror":"https://ror.org/02b7zfk76","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210116273"]},{"id":"https://openalex.org/I4405260118","display_name":"Qinhuangdao Vocational and Technical College","ror":"https://ror.org/039hsf911","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405260118"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhu Tian","raw_affiliation_strings":["Department of Mechanical and Electrical Engineering, Qinhuangdao Vocational and Technical College, Qinhuangdao, 066100, Hebei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Electrical Engineering, Qinhuangdao Vocational and Technical College, Qinhuangdao, 066100, Hebei, China","institution_ids":["https://openalex.org/I4210116273","https://openalex.org/I4210096351","https://openalex.org/I4405260118"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135337603","display_name":"Jian Guo Zhang","orcid":"https://orcid.org/0009-0009-8188-906X"},"institutions":[{"id":"https://openalex.org/I4210096351","display_name":"Qinhuangdao Second Hospital","ror":"https://ror.org/00rcpde19","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210096351"]},{"id":"https://openalex.org/I4210116273","display_name":"Qinhuangdao Science and Technology Bureau","ror":"https://ror.org/02b7zfk76","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210116273"]},{"id":"https://openalex.org/I4405260118","display_name":"Qinhuangdao Vocational and Technical College","ror":"https://ror.org/039hsf911","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405260118"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["Department of Mechanical and Electrical Engineering, Qinhuangdao Vocational and Technical College, Qinhuangdao, 066100, Hebei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Electrical Engineering, Qinhuangdao Vocational and Technical College, Qinhuangdao, 066100, Hebei, China","institution_ids":["https://openalex.org/I4210116273","https://openalex.org/I4210096351","https://openalex.org/I4405260118"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135358214","display_name":"Wang Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096351","display_name":"Qinhuangdao Second Hospital","ror":"https://ror.org/00rcpde19","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210096351"]},{"id":"https://openalex.org/I4210116273","display_name":"Qinhuangdao Science and Technology Bureau","ror":"https://ror.org/02b7zfk76","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210116273"]},{"id":"https://openalex.org/I4405260118","display_name":"Qinhuangdao Vocational and Technical College","ror":"https://ror.org/039hsf911","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405260118"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xia Wang","raw_affiliation_strings":["Department of Mechanical and Electrical Engineering, Qinhuangdao Vocational and Technical College, Qinhuangdao, 066100, Hebei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Electrical Engineering, Qinhuangdao Vocational and Technical College, Qinhuangdao, 066100, Hebei, China","institution_ids":["https://openalex.org/I4210116273","https://openalex.org/I4210096351","https://openalex.org/I4405260118"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5135358214"],"corresponding_institution_ids":["https://openalex.org/I4210096351","https://openalex.org/I4210116273","https://openalex.org/I4405260118"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55508658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.673799991607666,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.673799991607666,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11519","display_name":"Digital Mental Health Interventions","score":0.031700000166893005,"subfield":{"id":"https://openalex.org/subfields/3202","display_name":"Applied Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.030300000682473183,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mental-health","display_name":"Mental health","score":0.48739999532699585},{"id":"https://openalex.org/keywords/risk-assessment","display_name":"Risk assessment","score":0.30230000615119934},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.29510000348091125},{"id":"https://openalex.org/keywords/mental-model","display_name":"Mental model","score":0.25049999356269836}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5020999908447266},{"id":"https://openalex.org/C134362201","wikidata":"https://www.wikidata.org/wiki/Q317309","display_name":"Mental health","level":2,"score":0.48739999532699585},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4708999991416931},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4603999853134155},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.450300008058548},{"id":"https://openalex.org/C75630572","wikidata":"https://www.wikidata.org/wiki/Q538904","display_name":"Applied psychology","level":1,"score":0.3467000126838684},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C509550671","wikidata":"https://www.wikidata.org/wiki/Q126945","display_name":"Medical education","level":1,"score":0.27320000529289246},{"id":"https://openalex.org/C2982912361","wikidata":"https://www.wikidata.org/wiki/Q1851867","display_name":"Mental model","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-026-01308-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01308-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-01308-x.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6feb312fc76b4a89a86c8d41dad36169","is_oa":false,"landing_page_url":"https://doaj.org/article/6feb312fc76b4a89a86c8d41dad36169","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 6, Iss 1 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-026-01308-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01308-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-01308-x.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7160283357.pdf","grobid_xml":"https://content.openalex.org/works/W7160283357.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W2160828537","https://openalex.org/W2392412101","https://openalex.org/W2566578334","https://openalex.org/W2891230948","https://openalex.org/W2912581524","https://openalex.org/W2945976633","https://openalex.org/W2981869278","https://openalex.org/W3092848728","https://openalex.org/W3197232629","https://openalex.org/W4200150286","https://openalex.org/W4220856280","https://openalex.org/W4282940074","https://openalex.org/W4307483142","https://openalex.org/W4402686247","https://openalex.org/W4407264137","https://openalex.org/W4408059111","https://openalex.org/W4410858598","https://openalex.org/W4411044404","https://openalex.org/W4411542038","https://openalex.org/W4412455286","https://openalex.org/W4412899718"],"related_works":[],"abstract_inverted_index":{"One":[0],"in":[1,12,51,159,221,289,300],"25":[2],"to":[3,19,123,136,148,296],"35%":[4],"of":[5,54,94,175,179,184,195],"students":[6,60],"is":[7,47,63],"affected":[8],"by":[9,36],"mental":[10,27,306],"disorders":[11],"universities":[13,217],"around":[14],"the":[15,37,52,255],"world,":[16],"but":[17,292],"60":[18],"80%":[20],"will":[21],"not":[22,285],"seek":[23],"help":[24],"from":[25],"a":[26,48,84,202,239],"health":[28,307],"professional.":[29],"This":[30],"crisis":[31],"has":[32],"been":[33],"made":[34],"worse":[35],"COVID-19":[38],"pandemic,":[39],"and":[40,56,75,108,142,181,225,229,250,268,302],"post-pandemic":[41],"studies":[42,155],"have":[43],"found":[44],"that":[45,89,139,163],"there":[46],"40\u201360%":[49],"rise":[50],"prevalence":[53],"depression":[55],"anxiety":[57],"among":[58],"university":[59],"worldwide,":[61],"which":[62],"why":[64],"scalable,":[65],"proactive":[66],"screening":[67],"methods":[68,171],"are":[69,140,309],"urgently":[70],"needed.":[71],"The":[72,208],"paper":[73],"developed":[74],"experimented":[76],"on":[77,156,201],"BD-MHAM":[78,164],"(Big":[79],"Data-Mental":[80],"Health":[81],"Assessment":[82],"Model),":[83],"multi-modal":[85],"machine":[86],"learning":[87],"framework":[88],"incorporates":[90],"six":[91],"complementary":[92],"sources":[93],"data,":[95],"including":[96],"psychological":[97],"assessments,":[98],"academic":[99,248],"records,":[100],"digital":[101],"behavioral":[102],"indicators,":[103],"physiological":[104],"measurements,":[105],"social-environmental":[106],"factors,":[107],"ecological":[109],"momentary":[110],"assessments.":[111],"Three":[112],"new":[113],"elements":[114],"were":[115],"created:":[116],"(1)":[117],"Multi-Modal":[118],"Temporal":[119],"Feature":[120,133],"Fusion":[121],"(MMTFF)":[122],"learn":[124],"dynamic":[125],"trends":[126],"across":[127,213,265],"data":[128,234],"types;":[129],"(2)":[130],"Stability-Weighted":[131],"Ensemble":[132,146],"Selection":[134],"(SWEFS)":[135],"identify":[137],"predictors":[138],"stable;":[141],"(3)":[143],"Fairness-Constrained":[144],"Stacking":[145],"(FCSE)":[147],"make":[149],"fair":[150],"predictions":[151],"between":[152],"demographics.":[153],"Large-scale":[154],"14,604":[157],"participants":[158],"24":[160,214],"institutions":[161,288],"showed":[162],"was":[165,198,211],"significantly":[166],"better":[167],"than":[168],"seven":[169],"baseline":[170],"with":[172,232],"an":[173,177,182],"AUC":[174],"0.972,":[176],"accuracy":[178],"95.6%,":[180],"F1-score":[183],"0.928":[185],"(p":[186],"<":[187],"0.001).":[188],"High":[189],"transportability":[190],"(AUC":[191],"=":[192,206,274,279],"0.947,":[193],"degradation":[194],"only":[196,286],"2.57%)":[197],"also":[199,293],"validated":[200],"separate":[203],"cohort":[204],"(n":[205],"2,156).":[207],"multi-institutional":[209],"dataset":[210],"collected":[212],"geographically":[215],"distributed":[216],"spanning":[218],"five":[219],"provinces":[220],"China,":[222],"encompassing":[223],"urban":[224],"rural":[226],"institutions,":[227],"research-intensive":[228],"teaching-focused":[230],"universities,":[231],"standardized":[233],"collection":[235],"protocols":[236],"coordinated":[237],"through":[238],"centralized":[240],"center.":[241],"SHAP-based":[242],"interpretability":[243],"analysis":[244],"identified":[245],"sleep":[246],"quality,":[247],"trajectory,":[249],"social":[251],"interaction":[252],"frequency":[253],"as":[254],"most":[256],"influential":[257],"predictors.":[258],"Algorithmic":[259],"fairness":[260],"evaluation":[261],"demonstrated":[262],"equitable":[263],"performance":[264],"gender,":[266],"age,":[267],"academic-level":[269],"subgroups":[270],"(demographic":[271],"parity":[272],"difference":[273,278],"0.032,":[275],"equal":[276],"opportunity":[277],"0.028).":[280],"These":[281],"findings":[282],"carry":[283],"implications":[284],"for":[287,294],"high-income":[290],"contexts":[291],"adaptation":[295],"diverse":[297],"educational":[298],"systems":[299],"low-":[301],"middle-income":[303],"countries,":[304],"where":[305],"resources":[308],"even":[310],"more":[311],"limited.":[312]},"counts_by_year":[],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2026-05-06T00:00:00"}