首頁(yè) 資訊基于大數(shù)據(jù)的高校學(xué)生心理危機(jī)智能預(yù)警模型構(gòu)建

基于大數(shù)據(jù)的高校學(xué)生心理危機(jī)智能預(yù)警模型構(gòu)建

來(lái)源：泰然健康網(wǎng) 時(shí)間：2025年07月15日 15:36

基金項(xiàng)目:

四川省科技廳重點(diǎn)研發(fā)項(xiàng)目（No：2022YFG0187）

摘要 | | 訪問(wèn)統(tǒng)計(jì) | | | |

摘要:

目的本研究基于大學(xué)生心理健康測(cè)評(píng)數(shù)據(jù)，綜合學(xué)生基本信息及日常行為數(shù)據(jù)，利用大數(shù)據(jù)、人工智能技術(shù)，探索建立大學(xué)生心理危機(jī)智能預(yù)警模型。方法采用整群抽樣法，選取某高校部分在校大學(xué)生作為測(cè)試樣本；采取大數(shù)據(jù)技術(shù)，分析提取影響大學(xué)生心理健康問(wèn)題的特征量；采取神經(jīng)網(wǎng)絡(luò)技術(shù)，構(gòu)建大學(xué)生心理危機(jī)預(yù)警模型。結(jié)果 1）成功提取大學(xué)生心理健康問(wèn)題的有效特征量，其中心理健康癥狀特征因子 4 個(gè)，分別是強(qiáng) 迫、人際關(guān)系敏感、抑郁等 3 個(gè)單癥狀因子，1 個(gè)多癥狀因子；學(xué)生基本信息特征量 4 個(gè)，分別是母親教養(yǎng)方式、父親教養(yǎng)方式、家庭經(jīng)濟(jì)條件、有無(wú)心理治療（咨詢）史；學(xué)生日常行為特征量 2 個(gè)，分別是學(xué)生學(xué)業(yè)情況和出勤情況。2）實(shí)現(xiàn)特征量歸一化處理，通過(guò)數(shù)據(jù)對(duì)比分析及特征量的影響大小，分別對(duì) 3 個(gè)方面的 10 個(gè)特征量賦予權(quán)重并進(jìn)行歸一化處理。3）完成大學(xué)生心理危機(jī)預(yù)警模型構(gòu)建。結(jié)論本研究提取了影響大學(xué)生心理健康問(wèn)題的主要特征，建立了大學(xué)生心理危機(jī)預(yù)警指標(biāo)體系，并結(jié)合心理危機(jī)預(yù)警等級(jí)，利用神經(jīng)網(wǎng)絡(luò)技術(shù)，搭建了大學(xué)生心理危機(jī)預(yù)警模型，為及時(shí)有效干預(yù)大學(xué)生心理危機(jī)提供了新的解決方案。

Abstract:

Objective This study explores the construction of an intelligent early warning model for college students＇psychological crisis based on college students＇mental health assessment data，synthesizing students＇basic information and daily behavioral data，and utilizing big data and artificial intelligence technology. Methods The cluster sampling method was used to select some college students in a university as test samples. Big data technology was adopted to analyze and extract the characteristic quantities affecting college students＇mental health problems. And neural network technology was adopted to construct an early warning model for psychological crisis of college students. Results 1. The valid characteristic quantities of mental health problems were extracted，including 4 characteristic factors of students＇mental health symptoms，which were 3 single-symptom factors such as obsessive-compulsive symptoms， interpersonal sensitivity and depression，and 1 multi-symptom factor; Four characteristic quantities of students＇basic information，which were mother＇s parenting style，father＇s parenting style，family economic conditions，and history of psychotherapy （counseling）；Two characteristic quantities of students＇daily behavior，which were students＇academic performance and attendance. 2. The characteristic quantities were normalized. Ten characteristic quantities in 3 aspects were weighted and normalized based on the comparative analysis of data and the influence of each characteristic quantity. 3. The construction of an early warning model for psychological crisis of college students was completed. Conclusion An early warning indicator system of college students＇psychological crisis is established by extracting characteristic quantities of college students＇mental health problems. And combined with the early warning level of psychological crisis，an early warning model for college students＇psychological crisis is constructed by using neural network technology，which provides a new solution for the timely and effective intervention of psychological crisis.

引用本文

王計(jì)生;徐多勇;唐莉;熊梅;江永燕;.基于大數(shù)據(jù)的高校學(xué)生心理危機(jī)智能預(yù)警模型構(gòu)建[J].成都醫(yī)學(xué)院學(xué)報(bào),2024,19(1):111-115

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