WO2020187047A1

WO2020187047A1 - Questionnaire information pushing method and device, storage medium, and electronic device

Info

Publication number: WO2020187047A1
Application number: PCT/CN2020/078024
Authority: WO
Inventors: 张奥萌; 王晶; 沈凌浩
Original assignee: 深圳碳云智能数字生命健康管理有限公司; 深圳数字生命研究院
Priority date: 2019-03-19
Filing date: 2020-03-05
Publication date: 2020-09-24
Also published as: CN111159528B; CN111159528A

Abstract

A questionnaire information pushing method and device, a storage medium and an electronic device. Said method comprises: determining whether input information inputted by a first user includes all first type of information (S202); if it is determined that not all the first type of information is included, pushing questionnaire information not included and corresponding to the first type of information (S204); and if it is determined that the input information includes all the first type of information, determining, according to the degree of matching between the input information and preset information, whether to push questionnaire information corresponding to a second type of information (S206), the first type of information being different from the second type of information. The method solves the problem that a large amount of questionnaire information needs to be pushed at once during a questionnaire survey.

Description

Method and device for pushing questionnaire information, storage medium and electronic device

Technical field

This application relates to the computer field, and specifically to a method and device for pushing questionnaire information, a storage medium and an electronic device.

Background technique

In market research, it is a common way to collect user feedback information through questionnaires. However, existing questionnaire systems often require users to complete all questionnaires at one time, but they cannot be saved midway. In addition, in order to collect more information and achieve correct For accurate evaluation of users, the volume of questions in the questionnaire is often relatively large. This questionnaire method is not user-friendly, and to a certain extent, it will also lead to a relatively low efficiency of collecting information.

In view of the above-mentioned problems in related technologies, there is currently no effective solution.

Summary of the invention

The embodiments of the present application provide a method and device for pushing questionnaire information, a storage medium, and an electronic device, so as to at least solve the problem that a large amount of questionnaire information needs to be pushed at one time during the questionnaire survey process in related technologies.

According to an embodiment of the present application, a method for processing questionnaire information is provided, including: judging whether all the first type information is included in the input information entered by the first user; after judging that all the first type information is not included In the case of pushing the questionnaire information corresponding to the first type of information that is not included; in the case that it is determined that the input information includes all the first type of information, based on the difference between the input information and the preset information The matching degree determines whether to push questionnaire information corresponding to the second type of information, where the first type of information is different from the second type of information.

According to another embodiment of the present application, there is provided an apparatus for processing questionnaire information, including: a first judging module configured to judge whether all the first type information is included in the input information entered by the first user; In order to push the questionnaire information corresponding to the first type of information that is not included in the case where it is determined that all the information of the first type is not included; the first processing module is configured to determine that the input information includes all In the case of the first type of information, it is determined whether to push questionnaire information corresponding to the second type of information according to the degree of matching between the input information and the preset information, wherein the first type of information and the second type of information Not the same.

According to another embodiment of the present application, there is also provided a storage medium in which a computer program is stored, wherein the computer program is configured to execute the steps in any one of the foregoing method embodiments when running.

According to another embodiment of the present application, there is also provided an electronic device, including a memory and a processor, the memory is stored with a computer program, and the processor is configured to run the computer program to execute any of the above Steps in the method embodiment.

Through this application, after the input information entered by the user is saved locally, it is further determined whether the input information of the user includes all the information of the first type, and then the input information of the user and the matching degree of the input information and the preset information can be targeted The questionnaire information is pushed in a manner that eliminates the need for users to answer all the questionnaire information at one time. This solves the problem of pushing a large amount of questionnaire information at one time during the questionnaire survey process in related technologies, and improves the efficiency of the questionnaire and the user experience .

Description of the drawings

The drawings described here are used to provide a further understanding of the application and constitute a part of the application. The exemplary embodiments and descriptions of the application are used to explain the application and do not constitute an improper limitation of the application. In the attached picture:

FIG. 1 is a block diagram of the hardware structure of a mobile terminal of a method for processing questionnaire information according to an embodiment of the present application;

2 is a flowchart of a method for processing questionnaire information according to an embodiment of the present application;

Fig. 3 is a structural block diagram of a device for processing questionnaire information according to an embodiment of the present application;

Fig. 4 is an optional structural block diagram of a device for processing questionnaire information according to an embodiment of the present application.

detailed description

Hereinafter, the application will be described in detail with reference to the drawings and in conjunction with embodiments. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other if there is no conflict.

It should be noted that the terms "first" and "second" in the description and claims of the application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence.

Example 1

The method embodiment provided in the first embodiment of the present application may be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, FIG. 1 is a hardware structure block diagram of a mobile terminal of a method for processing questionnaire information in an embodiment of the present application. As shown in FIG. 1, the mobile terminal 10 may include one or more (only one is shown in FIG. 1) processor 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA. ) And a memory 104 configured to store data. Optionally, the above-mentioned mobile terminal may also include a transmission device 106 and an input/output device 108 for communication functions. Those of ordinary skill in the art can understand that the structure shown in FIG. 1 is only for illustration, and does not limit the structure of the above-mentioned mobile terminal. For example, the mobile terminal 10 may also include more or fewer components than those shown in FIG. 1, or have a different configuration from that shown in FIG.

The memory 104 may be configured to store computer programs, for example, software programs and modules of application software, such as a computer program corresponding to a questionnaire information processing method in the embodiment of the present application. The processor 102 runs the computer stored in the memory 104 Programs to execute various functional applications and data processing, that is, to achieve the above-mentioned methods. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely provided with respect to the processor 102, and these remote memories may be connected to the mobile terminal 10 via a network. Examples of the aforementioned networks include but are not limited to the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission device 106 is configured to receive or transmit data via a network. Specific examples of the aforementioned network may include a wireless network provided by the communication provider of the mobile terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC for short), which can be connected to other network devices through a base station to communicate with the Internet. In an example, the transmission device 106 may be a radio frequency (Radio Frequency, referred to as RF) module, which is configured to communicate with the Internet in a wireless manner.

In this embodiment, a method for processing questionnaire information running in the above-mentioned mobile terminal or computer terminal or similar computing device is provided. FIG. 2 is a flowchart of the method for processing questionnaire information according to an embodiment of the present application. As shown in Figure 2, the process includes the following steps:

Step S202, judging whether the input information entered by the first user includes all the first type information;

Among them, it should be noted that the first type of information involved in this embodiment is preferentially set as basic information related to the user, such as gender, age, occupation, labor/exercise intensity, whether you have chronic diseases, basic physical signs ( Height, weight), living environment (living area, hometown), virus infection, family medical history, etc.

Of course, this is just an example, and other basic user-related information can be added or deleted according to the actual situation. For example, in order to have a more comprehensive understanding of the user’s basic situation, if the subject of this survey is the user’s health, the check results of various physical indicators can be added to the first type of information, such as: blood biochemical detection parameters ( Including but not limited to fasting blood glucose, blood lipids, blood pressure, uric acid, liver function, etc.), SNP test results, RNA test results, blood metabolism test results, urine metabolism test results, immunomics test results, intestinal microbial test results , Proteomics test results, epigenomics test results, etc.; and/or daily life: diet information (including eating time, ingredients, cooking methods) within a specific time period (can be the past day, week, or month) , Food intake, etc.), exercise information (type of exercise, duration, intensity, start and end time) and sleep information (start and end time of sleep, waking up in the morning, the number of waking up at night and the reason for each, sleep quality, lifestyle habits (smoking status) , Alcoholism, sedentary status, dining habits). If this questionnaire is based on user career planning, in addition to the basic information mentioned above, you can also add: educational experience, learning situation, hobbies, salary expectations, Work experience, work ideas, etc.

Step S204, in the case where it is determined that all the first type of information is not included, push the questionnaire information corresponding to the first type of information that is not included;

Step S206: In the case where it is determined that the input information includes all the information of the first type, determine whether to push the questionnaire information corresponding to the second type of information according to the degree of matching between the input information and the preset information. The two types of information are not the same.

Among them, it should be noted that the second type of information involved in this embodiment is a supplement to the questionnaire information on the basis of the first type of information. Taking user health as an example in this questionnaire, the second type of information Class information can be health risk indicator information, such as: blood sugar risk, cardiovascular risk, obesity risk, exercise risk, diabetes risk, gout risk, high blood pressure risk, alcohol side effects risk, constipation risk, heart disease risk, etc. and many more. Of course, the second type of information mentioned above is only an example, and other health risk indicator information is also within the protection scope of this application.

Through the above steps S202 to S206, after the input information entered by the user is saved locally, it is further judged whether the input information of the user includes all the first type information, and then the input information of the user can be determined according to the input information and the preset information. The matching degree pushes the questionnaire information in a targeted manner, which eliminates the need for users to answer all the questionnaire information at one time, solves the problem of the need to push a large amount of questionnaire information at one time in the questionnaire survey process in related technologies, and improves the efficiency of the questionnaire And user experience.

Optionally, the execution subject of the foregoing steps may be a mobile terminal, a server, a computer device, or a combination of these, but is not limited thereto.

In an optional implementation manner of this embodiment, the method of determining whether to push questionnaire information corresponding to the second type of information according to the matching degree between the input information and preset information involved in step S206 of this embodiment may be as follows Way to achieve:

Step S206-11: Determine the score corresponding to each answer according to the matching degree of each answer in the input information entered by the first user with the preset information, and determine the score corresponding to each answer based on the score corresponding to each answer and the preset first The rule gets the first score corresponding to the input information;

It should be noted that the preset first rule involved in this embodiment is preferably addition processing or weighting processing. When the preset first rule is summation processing, that is, the score corresponding to each answer is summed, and the sum value obtained is the first score; the preset first rule is weighted processing In this case, each answer is preset with a corresponding coefficient. After the score corresponding to each answer is obtained, the score is multiplied with the corresponding coefficient. The result of the product is the final score of each answer. Finally, it is summed, and the sum is the first score. Of course, the foregoing description of the preset first rule is only an example, and other rules that can obtain the first score are also within the protection scope of this application. In other words, the preset first rule can be specifically limited according to actual conditions.

Step S206-12, judging whether the first score falls within a preset score interval;

Among them, for this step S206-11 and step S206-12 in a specific application scenario, the matching degree of each answer with the preset information determines the way in which the score corresponding to each answer is determined, and the second type of information is blood glucose risk As an example, the related indicator information may be the first user’s diet information, preferably the first user’s daily diet of high-glycemic load food; wherein, the high-glycemic load food includes but not Limited to: honey, cola, toast, rice, instant noodles, rolls, pancakes, yellow rice, wheat flour, rice flour, biscuits, cakes, lotus root flour, mung beans, peas, toffee, etc.

If it is determined by the first type of information that the first user has eaten a high glycemic load food 25 times in the three meals a day in the most recent week, each time he eats a high glycemic load food is recorded as 1 point, and further in the preset first If the rule is additive processing, the first score of the input information entered by the first user is 25 points. If the preset score interval in the application is greater than or equal to 24 points, the first score falls into the pre- If the score interval is set, further diabetes risk-related indicator information collection is required for the user, and step S206-13 is executed.

Of course, the above-mentioned first type of information is just an example. When the second type of information is other health index information, such as cardiovascular risk-related index information, the first type of information can be: age (whether over 40 years old), day Average sodium intake (calculated by weeks, is the average daily sodium intake more than 6g); frequency of intake of foods with high animal oil and cholesterol content (calculated by weeks, the intake of high animal oil and cholesterol foods exceeds 18 times/week; the high animal oil and cholesterol foods include but are not limited to animal offal, crab roe, roe, egg yolk, squid, etc.); high trans fatty acid food intake frequency (calculated by weeks, high trans fatty acid food intake The number of intakes exceeds 14 times/week, and the high-trans fatty acid foods include but are not limited to Western-style cakes, chocolate pie, coffee companion, fast food, etc.); whether family members have a history of cardiovascular disease, etc. That is to say, the first type of information can be set correspondingly according to actual conditions, which is not limited in this application.

Step S206-13, in the case that the first score falls within the preset score interval, it is determined whether the input information includes all the second type information;

Step S206-14, in a case where it is judged that the input information does not include all the second type information, push the questionnaire information corresponding to the second type information that is not included;

On the basis of step S206-11 and step S206-12, if it is determined to fall within the preset score interval according to the first score of the input information, it is necessary to determine whether the input information includes the second information, and if it is still the second type of information Taking the index information related to blood sugar risk as an example, the second type of information can be: gender, age, body mass index, waist circumference, systolic blood pressure, family history of diabetes, etc. Of course, if the second type of information is used as index information related to cardiovascular risk, the second type of information can be: age, systolic blood pressure, BMI, total cholesterol, whether smoking, whether there is diabetes, etc. It should be noted that the above are only examples, and the first type of information and the second type of information can be set accordingly according to actual conditions.

Step S206-15, in the case that the first score does not fall within the preset score interval, terminate the entry operation and save the entry information.

It can be seen that the first score obtained from the input information entered by the first user can further determine whether to push the second type of information. If the questionnaire survey is based on health, the above preset interval is a preliminary analysis of whether the current user is There may be health risks. If possible, in order to further understand the user's situation, the second type of information can be pushed targeted to learn more about the user. Therefore, pushing the second type of information again is targeted.

In another optional implementation manner of this embodiment, the manner of pushing questionnaire information corresponding to the first type of information or the second type of information that is not included in this embodiment may be: Extract the first type of information or the second type of information that is not entered by the first user from the type information or the second type of information, and push the unentered questionnaire information corresponding to the first type of information or the second type of information one by one. That is to say, when the questionnaire information is pushed to the user again, it is pushed one by one, instead of pushing a large amount of questionnaire information together, so that the process of the user's answer and input will be easier, and it is not easy to cause the user's disgust.

In another optional implementation manner of this embodiment, before the step S202 of this embodiment involves determining whether the input information entered by the first user includes all the first type information, the method of this embodiment further includes :

Step S102, obtain the input information of the first user;

Step S104, judging whether there is termination information used to instruct the termination of the entry operation in the entry information;

Among them, the termination information involved in this application may be information entered by the user through text or voice to terminate the operation, such as "stop entry", "exit questionnaire", "no answer", etc. Of course, the first user can also trigger the entry of termination information through a virtual key or a physical key.

Step S106, in the case where there is termination information in the input information, terminate the input operation and save the input information.

From the above steps S102 to S106, it can be seen that during the process of the user entering the questionnaire information, the user can terminate the current entry operation at any time and save the entered entry information, so that the user does not need to answer all the questions at once, and can return Enter the questionnaire information at an appropriate time to fully fit the user's time and situation.

In addition, the method of judging whether the input information entered by the first user includes all the first type information involved in step S202 in this embodiment may include:

Step S202-11: Obtain the input information entered by the first user, and generate text information to be determined, where the input information includes: at least one of voice information, text information, and graphic information;

Step S202-12: It is judged whether the text information to be judged includes all the first type information.

That is, if the input information entered by the first user is voice information and/or graphic information, the voice information is converted into corresponding text information, and the graphic information is converted into corresponding text information. Wherein, the specific way of converting voice information into text information may be: acquiring the voice information entered by the first user, and recognizing the single-syllable voice in the voice information, and the single-syllable voice and text are preset The mapping relationship is used to convert the voice information into text information based on the mapping relationship and the recognized single-syllable speech. The method of converting graphic information into text information may be: acquiring graphic information in the information entered by the first user, scanning the graphic information, and recognizing the characters in the graphic information until all characters on the graphic information are recognized Out, the recognized character information is matched with the character information stored in the database, and the matched character information is converted into a text corresponding to the character information. Of course, the above-mentioned ways of converting voice information into text information and converting graphic information into text information are only examples, and other ways that can realize the conversion between voice and text, graphics and text are also within the protection scope of this application. of.

In another optional implementation manner of this embodiment, the method steps of this embodiment further include:

Step S208: Generate a corresponding analysis report according to the input information, and push the analysis report.

Step S210: Obtain the result of reviewing the analysis report by the second user, and push the result.

Wherein, for the step S210, the second user may be a medical expert or health care expert, etc., a user who can review the analysis report, and the result of the review is mainly that the second user gives reasonable suggestions on the analysis report, or It is the revised analysis report of the second user.

In addition, for this step S208, the blood glucose risk analysis report, the cardiovascular risk analysis report, etc. can be obtained in a specific application scenario.

High GI (Glycemic Load) foods make people’s blood sugar rise quickly. If the user's input information often contains high GI (Glycemic Index) foods, a blood sugar questionnaire will be pushed to collect user blood sugar information to see if there is any Blood sugar risk. If there is a risk of blood sugar, the blood sugar intervention plan is pushed.

High-GI foods include, but are not limited to: honey, cola, toast bread, high-sugar fruits (strawberries, etc.) and their products (jam, juice), rice, instant noodles, flower rolls, pancakes, yellow rice, wheat flour, rice flour, biscuits, Cakes, lotus root flour, mung beans, peas, toffee, etc.; among them, each food has a corresponding GI value, and those skilled in the art can determine the GI value of various foods according to the prior art, or According to authoritative journals/reference books, etc., obtain the GI value of various foods.

GL = (Glycemic Load)-is a measure of the quality (GI value) and quantity (gram per serving) of carbohydrates in food.

GL=GI*Carbohydrates contained in food/total food

According to different scopes, GL also has three types: high, medium and low:

High GL: >=20 High load diet, which means a great influence on blood sugar;

Medium GL: 11-19 medium load diet, indicating that it has little effect on blood sugar;

Low GL: <=10 low-load diet, which means that it has little effect on blood sugar.

For example, watermelon has a very high glycemic index of 72; however, the amount of sugar (carbohydrate) contained in watermelon is low (about 5%). The glycemic load of 100 g of watermelon is 5x 72/100=3.6, so the glycemic load of watermelon is low. Apple: Its GI is 40, and it contains 15 grams of carbohydrates. GL=40x 15g/100=6. Baked potato: It has a GI of 80 and contains 15 grams of carbohydrates. GL=80x 15g/100=12. This shows that the metabolic effect of potatoes is twice that of apples, so apples that are sweet to eat are actually not that easy to make people fat.

In a specific embodiment of the present application, if the information entered by the first user shows that the GL value of the food he eats is greater than or equal to 20, a high-glycemic food reminder is output, for example: "XX is high-glycemic food, for your Healthy, please avoid excessive use", "You have used high-glycemic food XX times this week, please pay attention" and so on.

In a specific embodiment of the present application, the first type of information is the daily diet information of the first user in the past more than one week; after obtaining the input information entered by the first user, it is determined whether the input information includes the first user’s past week The above daily diet information.

If it is determined that the input information includes the daily diet information of the first user for more than one week in the past, it is further determined whether the first user has eaten high-glycemic load food more than 24 times/week.

If it is determined that the input information does not include or does not completely include the daily diet information of the first user over the past week, then a questionnaire that lacks daily diet information in the past week is pushed to allow the first user to complete the relevant information.

In the case of determining that the first type of information is complete, determine whether the first score falls within the preset interval (the first user uses high blood sugar in line with food more than 24 times/week), if not, terminate the questionnaire and save the first user All the input information entered; if it is (the first user may have blood sugar risk and need to know more about the first user's related information), then further determine whether the input information includes all the second type information, if not, then further push the not included Questionnaire information corresponding to the second type of information. Among them, the second type of information can be: age, systolic blood pressure, BMI, total cholesterol, whether you smoke, whether you have diabetes, etc.

After the complete second type of information is collected, the second type of information can be analyzed according to the following standards to generate an analysis report for the first user and analyze the blood glucose risk of the first user.

Grading:

(1) Gender: male, 2 points; female, 0 points;

(2) Age: 25-34 years old, 4 points; 35-39 years old, 8 points; 40-44 years old, 11 points; 45-49 years old, 12 points; 50-54 years old, 13 points; 55-59 years old, 15 points; 60 to 64 years old, 16 points; 65 years and above, 18 points;

(3) Body mass index (kg/m ² ): 22.0～23.9, 1 point; 24.0～29.9, 3 points; 30.0 and above, 5 points;

(4) Waist circumference (cm):

1) Male: a.75.0～79.9, 3 points; b.80.0～84.9, 5 points; c.85.0～89.9, 7 points; d.90.0-94.9, 8 points; e.95.0 and above, 10 points;

2) Female: a.70.0-74.9, 3 points; b.75.0-79.9, 5 points; c.80.0-84.9, 7 points; d.85.0-89.9, 8 points; e.90.0 and above, 10 points;

(5) Systolic blood pressure (mmHg): 110-119, 1 point; 120-129, 3 points; 130-139, 6 points; 140-149, 7 points; 150-159, 8 points; 160 and above, 10 points ；

(6) Family history of diabetes: Yes, 6 points; No, 0 points;

(7) Other:

1) Are you often thirsty? Yes-2 points; No-0 points;

2) Whether it is fatigue after meal, yes-2 points; No-0 points;

3) Whether frequent urination, yes-1 point; No-0 point;

4) Whether the wound is healing slowly, yes-1 point; No-0 point;

5) Whether the leg cramps at night recently, yes-1 point; No-0 point;

6) Whether the weight has fallen sharply recently? Yes-3 points; No-0 points.

Analysis standard: the total index score is less than 22 points, there is no blood sugar risk; the total index score is greater than or equal to 22 points, there is blood sugar risk. Index total score = the sum of the index scores related to the second type of information.

For example, the second type of information entered by the first user is: male, 28 years old, body mass index 33, waist circumference 90, systolic blood pressure 125, no family history of diabetes, infrequent thirsty, fatigue after meals, not frequent urination, wound healing Slow, recent night leg cramps, recent weight stability. Based on the above scoring and analysis criteria, the first user's index score is 29 points, which is a risk of blood sugar.

Further, in order to clarify the degree of blood glucose risk of the first user, the analysis criteria can be further refined into: no risk: the total index score is less than 22; low risk: the total index score is 22-28 points, and fasting blood glucose Lower than 6.0; Medium risk: Index total score is greater than or equal to 28 points, and fasting blood glucose is between 6.0-7.0; High risk: Index total score is greater than or equal to 28 points, glucose tolerance test 2 hours after blood glucose> 11.1mmol/L or Random blood glucose is the blood glucose value measured at any time> 11.1 mmol/L or fasting blood glucose> 7.0 mmol/L.

The index of the first user mentioned above has a total score of 29 points. First, it is judged that there is a blood sugar risk. In order to further clarify the blood sugar risk, the fasting blood sugar value, the blood sugar value 2 hours after the glucose tolerance test, and the random blood sugar value questionnaire are pushed. And according to the further input information of the first user, the blood glucose risk of the first user is judged with reference to the above judgment standard.

In another specific embodiment of the present application, the first type of information is the age of the first user, the average daily sodium intake, the frequency of high animal oil and cholesterol food intake, the frequency of high trans fatty acid food intake, and family members Whether there is a history of cardiovascular disease.

In the case of judging that the input information includes all the first type of information, the score corresponding to each answer is determined according to the degree of matching between each answer in the input information entered by the first user and the preset information, and based on each The score corresponding to the item answer and the preset first rule obtain the first score corresponding to the input information; when the preset first rule is the summation processing, the score corresponding to each answer is calculated The sum is processed, and the sum is the first score. According to the matching degree between each answer in the input information entered by the first user and the preset information, the score corresponding to each answer is determined as follows:

Age-whether it is over 40 years old;

Average daily sodium intake—whether the average daily sodium intake exceeds 6g;

High animal oil and cholesterol content food intake frequency—whether the intake of high animal oil and cholesterol food exceeds 18 times/week; said high animal oil and cholesterol food includes but not limited to animal offal, crab roe, roe, egg yolk, squid, etc.;

High-trans fatty acid food intake frequency—whether the high-trans fatty acid food intake exceeds 14 times/week, the high-trans fatty acid food includes but not limited to Western-style cakes, chocolate pies, coffee mates, fast foods, etc.) ；

Whether family members have a history of cardiovascular disease.

For the above 5 items, when the judgment result of each item is "Yes", 1 point is awarded, and when the judgment result is "No", 0 points are awarded; the first score is equal to the sum of the scores of the above 5 judgment results.

In the case where it is determined that the input information does not include or does not completely include the first type of information, the questionnaire corresponding to the unincluded first type of information is pushed, so that the first user can complete the relevant information.

In the case of determining that the first type of information is complete, determine whether the first score falls within the preset interval (more than or equal to 2 points), if not, terminate the questionnaire and save all the input information entered by the first user; if yes, ( The first user may have cardiovascular risks and needs to know more about the first user's relevant information), then it is further judged whether the input information includes all the second type information, if not, then the second type information that is not included is further pushed Corresponding questionnaire information. The second type of information is: age, gender, systolic blood pressure, body mass index (BMI, kg/m ² ), total cholesterol status, smoking, and diabetes.

After the complete second type of information is collected, the second type of information can be analyzed according to the following standards to generate an analysis report for the first user and analyze the cardiovascular risk of the first user.

Grading:

1. Age: 40-44, 1 point; 45-49, 2 points; 50-54, 3 points; 55-59, 4 points; over 60, add 1 point for every 5 years old;

2. Systolic blood pressure: <120, -2 points; 120～～129, 0 points; 130～～139, 1 point; 140～159, 2 points; 160～179, 3 points; over 180, 4 points;

3. BMI (kg/m ² ): 24～27.9, 1 point; 28 or more, 2 points;

4. Total cholesterol (mol/L): 5.2 and above, 1 point; below 5.2, 0 point;

5. Gender and smoking: male and yes, 2 points; female and yes, 1 point; no, 0 points;

6. Gender and whether you have diabetes: male and yes, 1; female and yes, 2; no, 0 points.

Analysis criteria: the total index score is less than 7 points, low cardiovascular risk; the total index score is between 7-11 points, medium cardiovascular risk; the total index score is greater than 11 points, high cardiovascular risk. Index total score = the sum of the index scores related to the second type of information.

For example, the second type of information entered by the first user is: male; 43 years old; systolic blood pressure 124; BMI 27; total cholesterol 4mol/L; no smoking; no diabetes. Based on the above scoring and analysis criteria, the first user’s index score is 2 points, which is low cardiovascular risk.

Of course, the foregoing is only an example, and it is also possible to set more correspondences between parameters and scores according to actual conditions, and update the analysis standards.

In a specific embodiment of the present application, in order to help the first user control the intake of food energy within a reasonable range. The first type of information is the first user's gender, age, height, weight, and yesterday's diet information (must include the types of food used for breakfast, lunch, and dinner and the amount of various foods).

After obtaining the input information entered by the first user, it is determined whether the input information includes all the first type information.

If not, then push the questionnaire information corresponding to the first type of information that is not included, so that the first user can complete the relevant information.

If so, it is determined whether the first score falls within the preset interval (whether the energy intake of the first user yesterday exceeds 10% of the estimated energy consumption).

The first score is calculated according to the following formula: first score=(yesterday's energy intake of the first user-estimated energy consumption)/estimated energy consumption.

Estimated energy expenditure = resting metabolic rate/0.65.

Male resting metabolic rate: 10*weight (kg)+6.25*height (cm)-5*age+5

Female resting metabolic rate: 10*weight (kg)+6.25*height (cm)-45*age-161

It should be noted:

The energy intake of the first user yesterday is calculated based on the sum of the product of the energy density of each food type and the consumption of the corresponding food. This is a well-known technology and will not be repeated here.

When judging whether the input information includes all the diet information of the first user yesterday, it is based on whether the diet information for breakfast, lunch, and dinner is clearly recorded as the standard. If it is determined that there is diet information for other time periods, record it together and follow up The first user’s energy intake calculation yesterday).

When the first score falls within the preset interval, it is further determined whether the input information includes all the second type of information, and if not, the questionnaire information corresponding to the second type of information that is not included is further pushed. The second type of information is: yesterday's exercise information of the first user, including the number of steps, whether to exercise, and exercise details (exercise type and time).

After collecting the complete second type of information, the actual energy consumption of the first user yesterday can be calculated to further determine the comparison between the actual energy consumption of the first user yesterday and the energy intake, and the push is given according to the standards in Table 1 below The corresponding recommendations.

Table 1

It should be noted that the above standards and recommendations can be adjusted as needed. In addition, in the above specific embodiment, the first user’s diet (energy intake) and (expected or actual) energy consumption were compared yesterday. Those skilled in the art can also compare the first user’s past period of time, such as one week, as needed. , Ten days or one month diet (energy intake) and (expected or actual) energy expenditure are compared, and relevant indicators or parameters are appropriately adjusted.

In addition, the above three specific embodiments are examples for evaluating blood sugar risk, cardiovascular risk, and energy intake risk (involving obesity and exercise) respectively. That is, the above specific embodiments are mainly based on health questionnaires. Explain that, of course, this application can also evaluate one or more other types of questionnaires at the same time, such as career planning, the incident of a certain social/life issue, etc., only for the first type of information, the second type of information, The analysis standards can be adjusted accordingly according to the actual situation, so I won't repeat them here.

Step S212: Update the locally stored questionnaire information and/or the first rule and/or the preset score interval.

Based on this step S212, an update mechanism is played. The update can update the local questionnaire information and/or the first rule and/or the preset score interval through the Internet; it can also be manually updated. , To ensure the timeliness and scientific nature of local information.

Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is Better implementation. Based on this understanding, the technical solution of this application essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM, magnetic disk, The optical disc) includes several instructions to enable a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the method described in each embodiment of the present application.

Example 2

In this embodiment, a device for processing questionnaire information is also provided, and the device is used to implement the above-mentioned embodiments and preferred implementations, and those that have been explained will not be repeated. As used below, the term "module" can implement a combination of software and/or hardware with predetermined functions. Although the devices described in the following embodiments are preferably implemented by software, hardware or a combination of software and hardware is also possible and conceived.

Fig. 3 is a structural block diagram of a device for processing questionnaire information according to an embodiment of the application. As shown in Fig. 3, the device includes: a first judging module 32 configured to judge whether the input information entered by the first user includes all the first One type of information; the push module 34, coupled to the first judgment module 32, is configured to push the questionnaire information corresponding to the first type of information that is not included in the case where it is determined that all the first type of information is not included The first processing module 36, coupled to the push module 34, is configured to determine whether to determine whether the input information matches the preset information in the case of determining that the input information includes all the first type information Push the questionnaire information corresponding to the second type of information, where the first type of information is different from the second type of information.

It should be noted that the push module 34 involved in this embodiment is also configured to extract the first type of information that is not entered by the first user from the first type of information, and push the unentered and first type of information one by one. Questionnaire information corresponding to the category information.

Optionally, the first processing module 36 involved in this embodiment includes: a first processing unit that determines the degree of match between each answer in the input information entered by the first user and preset information. The score corresponding to each answer, and the first score corresponding to the input information is obtained based on the score corresponding to each answer and the preset first rule; the first judging unit is configured to judge whether the first score falls Enter the preset score interval; the second judgment unit is set to judge whether all the second type information is included in the input information when the first score falls within the preset score interval; the push unit is set to When the input information does not include all the second type of information, push the questionnaire information corresponding to the second type of information that is not included; the second processing unit is set to not fall into the preset score when the first score In the case of the interval, the entry operation is terminated and the entry information is saved.

It should be noted that the push unit involved in this embodiment is also configured to extract the second type of information that is not entered by the first user from the second type of information, and push the unentered and the second type of information one by one. Questionnaire information corresponding to the information.

Optionally, the first judging module 32 involved in this embodiment may include: a third processing unit configured to obtain the input information entered by the first user and generate text information to be judged, the input information includes: voice information , At least one of text information and graphic information; the third judging unit is configured to judge whether the text information to be judged includes all the information of the first type.

FIG. 4 is an optional structural block diagram of a device for processing questionnaire information according to an embodiment of the present application. As shown in FIG. 4, the device includes: an acquisition module 42, which is coupled to the first judging unit, and is configured to judge whether it is entered by the first user Before the entry information includes all the first type of information, the entry information entered by the first user is obtained; the second judgment module 44 is coupled to the acquisition module 42 and is configured to determine whether there is any information in the entry information for indicating termination of the entry operation Termination information; The second processing module 46 is coupled to the second judgment module 44, and is configured to terminate the entry operation and save the entry information when there is termination information in the entry information.

Optionally, in addition to the modules shown in FIG. 3 and FIG. 4, the device of this embodiment may further include: a first acquisition module configured to determine whether all the first types of information are included in the input information entered by the first user Before information, the input information entered by the first user is obtained; the second judgment module is set to determine whether there is termination information used to instruct the termination of the input operation in the input information; the second processing module is set to have termination information in the input information In case, terminate the entry operation and save the entry information.

Wherein, the termination information in the judgment object of the second judgment module may be information entered by the user through text or voice to terminate the operation, such as "stop entry", "exit questionnaire survey", "no answer", and so on. Of course, the first user can also trigger the entry of termination information through a virtual key or a physical key. Furthermore, based on the above-mentioned first acquisition module, second judgment module, and second processing module, the user can terminate the current entry operation at any time while the user enters the questionnaire information, and save the entered information, so that the user does not need to use it once. After answering all the questions sexually, you can enter the questionnaire information again at an appropriate time to fully fit the user’s time and situation.

Optionally, in addition to the modules shown in FIG. 3 and FIG. 4, the device of this embodiment may further include: a third processing module configured to generate a corresponding analysis report based on the input information and push the analysis report; The module is set to obtain the result of the second user's review of the analysis report and push the result. The update module is configured to update the locally stored questionnaire information and/or the first rule and/or the preset score interval.

The process of generating the analysis report involved in the third processing module corresponds to step S208 in the above-mentioned embodiment 1, and the process of obtaining the result of the analysis report by the second user in the fourth processing module corresponds to the above Step S210 in Embodiment 1. The update mechanism involved in the update module corresponds to step S212 in Embodiment 1 above.

It should be noted that each of the above modules can be implemented by software or hardware. For the latter, it can be implemented in the following manner, but not limited to this: the above modules are all located in the same processor; or, the above modules are combined in any combination The forms are located in different processors.

Example 3

The embodiment of the present application also provides a storage medium in which a computer program is stored, wherein the computer program is configured to execute the steps in any of the foregoing method embodiments when running.

Optionally, in this embodiment, the foregoing storage medium may be configured to store a computer program for executing the following steps:

S1: Determine whether the input information entered by the first user includes all the first type information;

S2, in the case of judging that all the information of the first type is not included, push the questionnaire information corresponding to the information of the first type that is not included;

S3: In the case of judging that the input information includes all the information of the first type, determine whether to push the questionnaire information corresponding to the second type of information according to the degree of matching between the input information and the preset information. The class information is not the same.

Optionally, in this embodiment, the foregoing storage medium may include, but is not limited to: U disk, Read-Only Memory (Read-Only Memory, ROM for short), Random Access Memory (Random Access Memory, RAM for short), Various media that can store computer programs, such as mobile hard disks, magnetic disks, or optical disks.

The embodiment of the present application also provides an electronic device, including a memory and a processor, the memory is stored with a computer program, and the processor is configured to run the computer program to execute the steps in any of the foregoing method embodiments.

Optionally, the aforementioned electronic device may further include a transmission device and an input-output device, wherein the transmission device is connected to the aforementioned processor, and the input-output device is connected to the aforementioned processor.

Optionally, in this embodiment, the foregoing processor may be configured to execute the following steps through a computer program:

Optionally, for specific examples in this embodiment, reference may be made to the examples described in the above-mentioned embodiments and optional implementation manners, and details are not described herein again in this embodiment.

Obviously, those skilled in the art should understand that the above-mentioned modules or steps of this application can be implemented by a general computing device, and they can be concentrated on a single computing device or distributed in a network composed of multiple computing devices. Above, alternatively, they can be implemented with program codes executable by the computing device, so that they can be stored in the storage device for execution by the computing device, and in some cases, can be executed in a different order than here. Perform the steps shown or described, or fabricate them into individual integrated circuit modules, or fabricate multiple modules or steps of them into a single integrated circuit module to achieve. In this way, this application is not limited to any specific hardware and software combination.

The above descriptions are only preferred embodiments of the application, and are not used to limit the application. For those skilled in the art, the application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the principles of this application shall be included in the protection scope of this application.

Industrial applicability

Through the push method of questionnaire information in this application, after the input information entered by the user is saved locally, it is further judged whether the input information of the user includes all the first type information, and then it can be based on the input information of the user, and the input information and pre- The matching degree of the information is set to push the questionnaire information in a targeted manner, so that the user does not need to answer all the questionnaire information at one time, which solves the problem of the need to push a large amount of questionnaire information at one time during the questionnaire survey process in related technologies, and improves the survey The efficiency of the questionnaire and user experience.

Claims

A method for pushing questionnaire information, including:

Determine whether the input information entered by the first user includes all the first type information;

In the case where it is determined that all the information of the first type is not included, push the questionnaire information corresponding to the information of the first type that is not included;

In the case where it is determined that the input information includes all the information of the first type, it is determined whether to push the questionnaire information corresponding to the information of the second type according to the degree of matching between the input information and the preset information. The first type of information is different from the second type of information.
The method of claim 1, determining whether to push questionnaire information corresponding to the second type of information according to the degree of matching between the input information and preset information, comprising:

The score corresponding to each answer is determined according to the degree of matching between each answer in the input information entered by the first user and the preset information, and based on the score corresponding to each answer and the preset first rule Obtain the first score corresponding to the input information;

Judging whether the first score falls within a preset score interval;

In the case that the first score falls within the preset score interval, determine whether the input information includes all second-type information;

In the case of judging that the input information does not include all the second type of information, push the questionnaire information corresponding to the second type of information that is not included;

If the first score does not fall within the preset score interval, terminate the entry operation and save the entry information.
According to the method of claim 2, pushing the questionnaire information corresponding to the first type of information or the second type of information that is not included includes:

Extracting the first type of information or the second type of information that is not entered by the first user from the first type of information or the second type of information;

Push the unentered questionnaire information corresponding to the first type of information or the second type of information one by one.
The method according to claim 1, before determining whether the input information entered by the first user includes all the first type information, the method further comprises:

Acquiring the entry information entered by the first user;

Determine whether there is termination information used to instruct the termination of the entry operation in the entry information;

If the termination information exists in the entry information, the entry operation is terminated and the entry information is saved.
According to the method of any one of claims 1 to 4, the judging whether the input information entered by the first user includes all the first type information includes:

Acquiring input information entered by the first user, and generating text information to be determined, where the input information includes at least one of voice information, text information, and graphic information;

Determine whether the text information to be determined includes all the first type information.
The method according to any one of claims 1 to 4, further comprising:

A corresponding analysis report is generated according to the input information, and the analysis report is pushed.
The method according to claim 6, further comprising:

Obtain the result of the second user's review of the analysis report, and push the result.
The method according to any one of claims 1 to 4, further comprising:

Update the locally stored questionnaire information and/or the first rule and/or the preset score interval.
A device for pushing questionnaire information, including:

The first judgment module is configured to judge whether the input information entered by the first user includes all the first type information;

The push module is configured to push the questionnaire information corresponding to the first type of information that is not included in the case where it is determined that all the first type of information is not included;

The first processing module is configured to determine whether to push a questionnaire corresponding to the second type of information according to the degree of matching between the input information and preset information when it is determined that the input information includes all the information of the first type Information, wherein the first type of information is different from the second type of information.
The device according to claim 9, wherein the first processing module comprises:

The first processing unit is configured to determine the score corresponding to each answer in the input information entered by the first user according to the degree of matching between each answer and preset information, and based on the score corresponding to each answer Value and a preset first rule to obtain a first score corresponding to the input information;

The first judgment unit is configured to judge whether the first score falls within a preset score interval;

A second judging unit, configured to judge whether the input information includes all the second type of information when the first score falls within the preset score interval;

The pushing unit is configured to push the questionnaire information corresponding to the second type of information that is not included in the case where it is determined that the input information does not include all the second type of information;

The second processing unit is configured to terminate the entry operation and save the entry information when the first score does not fall within the preset score interval.
The device according to claim 10,

The pushing unit is further configured to extract the second type of information not entered by the first user from the second type of information, and push the unentered questionnaire information corresponding to the second type of information one by one;

The pushing module is further configured to extract the first type of information not entered by the first user from the first type of information, and push the unentered questionnaire information corresponding to the first type of information one by one.
The device according to claim 9, further comprising:

The first obtaining module is configured to obtain the input information entered by the first user before determining whether all the first type information is included in the input information entered by the first user;

The second judgment module is configured to judge whether there is termination information for instructing termination of the entry operation in the entry information;

The second processing module is configured to terminate the entry operation and save the entry information when the termination information exists in the entry information.
The device according to any one of claims 9 to 12, the first judgment module comprises:

The third processing unit is configured to obtain the input information entered by the first user and generate text information to be judged, where the input information includes: at least one of voice information, text information, and graphic information;

The third judgment unit is configured to judge whether the text information to be judged includes all the information of the first type.
The device according to any one of claims 9 to 12, the device further comprising:

The third processing module is configured to generate a corresponding analysis report according to the input information, and push the analysis report.
The device according to claim 14, further comprising:

The fourth processing module is configured to obtain the result of the second user's review of the analysis report, and push the result.
The device according to any one of claims 9 to 12, the device further comprising:

The update module is configured to update the locally stored questionnaire information and/or the first rule and/or the preset score interval.
A storage medium in which a computer program is stored, wherein the computer program is configured to execute the method described in any one of claims 1 to 8 when running.
An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the method described in any one of claims 1 to 8.