Big data-based college student psychological health data management system

Abstract

The invention discloses a college student psychological health data management system based on big data, and belongs to the technical field of psychological health data management.The management system generates oscillogram according to answering results of psychological health evaluation questions of students, then the students are grouped according to the similarity of the oscillogram, and then the students are grouped according to the similarity of the oscillogram; according to the method, students with high answer result similarity are divided into the same group, then evaluation is carried out in a sampling mode, and compared with a mode of processing and evaluating the answer results of the psychological health evaluation questions of the students subjected to psychological health evaluation one by one, the evaluation difficulty can be remarkably reduced on the premise of not influencing the evaluation result, and the evaluation efficiency is improved. And the evaluation efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of mental health data management, and specifically, relates to a college student mental health data management system based on big data. Background Art

[0002] With the rapid development of society, in addition to paying attention to physical health, people have gradually realized the importance of mental health. Now in schools, in order to prevent the adverse effects of mental health problems, students' mental health data will be obtained through mental health assessments, and then analyzed to determine whether students need psychological counseling. However, this method first has an obvious problem of low efficiency. Analysts need to analyze the assessment results of each student. In addition, when formulating psychological counseling plans for students with mental health problems, it is impossible to systematically formulate a plan for judging the timing of counseling results based entirely on the experience of counselors. In order to solve the above problems, the present invention provides the following technical solutions. Summary of the invention

[0003] The purpose of the present invention is to provide a college student mental health data management system based on big data to solve the problem of low efficiency in processing college student mental health data in the prior art.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] A college student mental health data management system based on big data, including:

[0006] A psychological information collection unit is used to collect the students' psychological health data and transmit the collected psychological health data to the waveform generation unit;

[0007] A waveform generating unit, used to generate a waveform graph corresponding to each student according to the collected mental health data of the students;

[0008] A waveform comparison unit, used to compare the waveform graphs generated by the waveform generation unit, and classify students whose corresponding waveform graphs have a similarity reaching a preset percentage into the same student group;

[0009] The psychological assessment analysis unit is used to analyze the results of the mental health assessment and determine whether the student has mental health problems;

[0010] During the analysis, sampling analysis can be conducted on the mental health assessment results of students in the same student group.

[0011] Furthermore, the method in which the waveform generating unit generates the waveform graph corresponding to each student is as follows:

[0012] The student's individual options for the mental health assessment question are expressed as (a, bi, cj), where a is the student's name, bj is the question number of the mental health assessment question, and cj is the option of the mental health assessment question;

[0013] 1≤i≤n, 1≤j≤m, n is the number of mental health assessment questions, and m is the number of options for each question;

[0014] Establish a rectangular coordinate system, and then use bj as the horizontal coordinate and cj as the vertical coordinate. For a student, mark the n points corresponding to the student in the rectangular coordinate system, and then use these n points as the wave peaks;

[0015] When cj is used as the ordinate, set a specific value for it according to the order of options; use the origin and b1, as well as the midpoint between any two adjacent bj as the abscissa, and 0 as the ordinate, mark the n points corresponding to the student in the rectangular coordinate system, and then use these n points as the trough;

[0016] The waveform diagram corresponding to each student is obtained by fitting the positions of the peaks and troughs.

[0017] Furthermore, after completing the grouping, several students were randomly selected from each group to analyze the evaluation results of the mental health assessment questions.

[0018] Furthermore, when determining a specific value for cj, the specific value is allocated in a method of increasing or decreasing in sequence according to the severity levels corresponding to the options.

[0019] Furthermore, when a student is judged to have no mental health problems after receiving psychological counseling, the average single duration td and the total number of psychological counseling z are recorded;

[0020] When students in the same group are judged to have no mental health problems after receiving psychological counseling, the average single duration tdk and total number of psychological counseling zk are recorded;

[0021] Where 1≤k≤e, e is the number of students in the same group who were judged to have no mental health problems after receiving psychological counseling and were sampled;

[0022] Calculate the average value tdp of the corresponding e tdk and the average value zp of the corresponding e zk;

[0023] When providing psychological counseling to a student with mental health problems, first obtain the student group to which the student belongs, and obtain the tdp and zp corresponding to the student group;

[0024] The corresponding students will be counseled according to the duration of a single consultation (tdp). When zp times of psychological counseling are completed, they will be asked to undergo another mental health assessment, and the need for continued psychological counseling will be determined based on the assessment results.

[0025] Beneficial effects of the present invention:

[0026] 1. The present invention generates a waveform graph according to the answer results of the students' mental health assessment questions, and then groups the students according to the similarity of the waveform graphs, and divides the students with high similarity of the answer results into the same group, and then adopts a sampling method during the assessment. Compared with the method of processing and evaluating the answer results of the mental health assessment questions of the students who have undergone the mental health assessment one by one, the present invention can significantly reduce the difficulty of the assessment and improve the efficiency of the assessment without affecting the assessment results.

[0027] 2. Compared with the prior art, which completely relies on the experience of psychological counselors to judge the timing of psychological health assessment or conducts psychological assessment at regular intervals to judge the effectiveness of psychological counseling, the present invention can determine the timing of judging the effectiveness of counseling based on previous psychological counseling records, avoid excessive and repeated psychological health assessments, reduce the aversion of counseling students, and improve the efficiency of the entire counseling process. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be further described below in conjunction with the accompanying drawings.

[0029] Figure 1 It is a schematic diagram of the framework structure of a college student mental health data management system based on big data in the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] A college student mental health data management system based on big data, such as Figure 1 Shown, including

[0032] A psychological information collection unit is used to collect the students' psychological health data and transmit the collected psychological health data to the waveform generation unit;

[0033] A waveform generating unit, used to generate a waveform graph corresponding to each student according to the collected mental health data of the students;

[0034] A waveform comparison unit is used to compare the waveform graphs generated by the waveform generation unit, and classify the students whose corresponding waveform graphs have a similarity reaching a preset percentage into the same student group;

[0035] The psychological assessment analysis unit is used to analyze the results of the mental health assessment and determine whether students have mental health problems.

[0036] The method for managing college students' mental health data based on the above-mentioned big data-based college students' mental health data management system includes the following steps:

[0037] The first step is to collect students’ mental health data through the psychological information collection unit;

[0038] Specifically, the method for the psychological information collection unit to collect students' psychological health data is:

[0039] Obtain the evaluation results of students on the mental health assessment questions, and save the options of students on each mental health assessment question. For the convenience of expression, the options of students on individual mental health assessment questions can be expressed as (a, bi, cj), where a is the student's name, bj represents the question number of the mental health assessment question, and cj represents the options of the mental health assessment question;

[0040] 1≤i≤n, 1≤j≤m, n is the number of mental health assessment questions, and m is the number of options for each question.

[0041] The second step is to establish a rectangular coordinate system through the waveform generation unit, and then use bj as the horizontal coordinate and cj as the vertical coordinate. For a student, mark the n points corresponding to the student in the rectangular coordinate system, and then use these n points as the wave peaks;

[0042] When cj is used as the vertical coordinate, a specific value is set for it according to the order of the options, and the specific value is allocated in a way of increasing or decreasing in sequence according to the severity of the options;

[0043] If there are five options, namely, not in compliance, slightly in compliance, moderately in compliance, in compliance, and completely in compliance, they will be assigned a value of 1, 2, 3, 4, and 5 in order;

[0044] Take the origin and b1, and the midpoint between any two adjacent bj as the horizontal coordinates, and 0 as the vertical coordinate, mark the n points corresponding to the student in the rectangular coordinate system, and then take these n points as the trough;

[0045] The waveform diagram corresponding to each student is obtained by fitting the positions of the peaks and troughs.

[0046] The third step is to compare the waveforms of the students through the waveform comparison unit, and group the students according to the waveform similarity of the corresponding waveforms. The waveform similarity of the students in the same group should be greater than a preset proportionality coefficient α. In a specific embodiment, the proportionality coefficient can be 85%;

[0047] The fourth step is to randomly select a number of students in each group through the psychological assessment analysis unit to analyze the assessment results of the mental health assessment questions, and determine whether the students in each group have mental health problems and, if so, what types of mental health problems they have;

[0048] Through the above process, compared with the method of processing and evaluating the answers of the mental health assessment questions of students who have undergone the mental health assessment one by one, the present invention can significantly reduce the difficulty of the assessment and improve the efficiency of the assessment without affecting the assessment results.

[0049] Step 5: For the student group that has mental health problems and needs follow-up psychological counseling, send psychological counseling advice information to the students;

[0050] After students have participated in psychological counseling, randomly select students to undergo mental health assessment again, record the results of the mental health assessment, and analyze the results of the mental health assessment to determine whether there are mental health problems;

[0051] When a student is judged to have no mental health problems after receiving psychological counseling, the average single duration td and total number of psychological counseling z are recorded;

[0052] When students in the same group are judged to have no mental health problems after receiving psychological counseling, the average single duration tdk and total number of psychological counseling zk are recorded;

[0053] Where 1≤k≤e, e is the number of students in the same group who were judged to have no mental health problems after receiving psychological counseling and were sampled;

[0054] Calculate the average value tdp of the corresponding e tdk and the average value zp of the corresponding e zk;

[0055] Step 6: When providing psychological counseling to a student with mental health problems, first obtain the student group to which the student belongs, and obtain the tdp and zp corresponding to the student group;

[0056] The corresponding students will be counseled according to the duration of a single consultation (tdp). When zp times of psychological counseling are completed, they will be asked to undergo another mental health assessment, and the need for continued psychological counseling will be determined based on the assessment results.

[0057] Compared to the prior art, which completely relies on the experience of psychological counselors to judge the timing of psychological health assessment or conducts psychological assessment at regular intervals to judge the effectiveness of psychological counseling, the present invention can determine the timing of judging the effectiveness of counseling based on previous psychological counseling records, avoid excessive and repeated psychological health assessments, reduce the aversion of counseling students, and improve the efficiency of the entire counseling process.

[0058] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. A college student mental health data management system based on big data, characterized by: include: A psychological information collection unit is used to collect the students' psychological health data and transmit the collected psychological health data to the waveform generation unit; A waveform generating unit, used to generate a waveform graph corresponding to each student according to the collected mental health data of the students; A waveform comparison unit, used to compare the waveform graphs generated by the waveform generation unit, and classify students whose corresponding waveform graphs have a similarity reaching a preset percentage into the same student group; The psychological assessment analysis unit is used to analyze the results of the mental health assessment and determine whether the student has mental health problems; During the analysis, sampling analysis can be conducted on the mental health assessment results of students in the same student group.

2. The college student mental health data management system based on big data according to claim 1 is characterized in that: The method for the waveform generation unit to generate the waveform graph corresponding to each student is as follows: The student's individual options for the mental health assessment question are expressed as (a, bi, cj), where a is the student's name, bj is the question number of the mental health assessment question, and cj is the option of the mental health assessment question; 1≤i≤n, 1≤j≤m, n is the number of mental health assessment questions, and m is the number of options for each question; Establish a rectangular coordinate system, and then use bj as the horizontal coordinate and cj as the vertical coordinate. For a student, mark the n points corresponding to the student in the rectangular coordinate system, and then use these n points as the wave peaks; When cj is used as the ordinate, set a specific value for it according to the order of options; use the origin and b1, as well as the midpoint between any two adjacent bj as the abscissa, and 0 as the ordinate, mark the n points corresponding to the student in the rectangular coordinate system, and then use these n points as the trough; The waveform diagram corresponding to each student is obtained by fitting the positions of the peaks and troughs.

3. The college student mental health data management system based on big data according to claim 2 is characterized in that: After completing the grouping, several students were randomly selected from each group to analyze the assessment results of the mental health assessment questions.

4. The college student mental health data management system based on big data according to claim 2 is characterized in that: When determining a specific value for cj, the specific value is allocated in a method of increasing or decreasing in sequence according to the severity of the options.

5. The college student mental health data management system based on big data according to claim 2 is characterized in that: When a student is judged to have no mental health problems after receiving psychological counseling, the average single duration td and total number of psychological counseling z are recorded; When students in the same group are judged to have no mental health problems after receiving psychological counseling, the average single duration tdk and total number of psychological counseling zk are recorded; Where 1≤k≤e, e is the number of students in the same group who were judged to have no mental health problems after receiving psychological counseling and were sampled; Calculate the average value tdp of the corresponding e tdk and the average value zp of the corresponding e zk; When providing psychological counseling to a student with mental health problems, first obtain the student group to which the student belongs, and obtain the tdp and zp corresponding to the student group; The corresponding students will be counseled according to the duration of a single consultation (tdp). When zp times of psychological counseling are completed, they will be asked to undergo another mental health assessment, and the need for continued psychological counseling will be determined based on the assessment results.

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