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WO1995021419A1 - Intervention d'un syteme expert pour cesser de fumer - Google Patents

Intervention d'un syteme expert pour cesser de fumer Download PDF

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Publication number
WO1995021419A1
WO1995021419A1 PCT/US1995/001367 US9501367W WO9521419A1 WO 1995021419 A1 WO1995021419 A1 WO 1995021419A1 US 9501367 W US9501367 W US 9501367W WO 9521419 A1 WO9521419 A1 WO 9521419A1
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WO
WIPO (PCT)
Prior art keywords
data
assessment
report
change
smoking
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
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PCT/US1995/001367
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English (en)
Inventor
James O. Prochaska
Wayne F. Velicer
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Rhode Island Board of Education
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Rhode Island Board of Education
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Filing date
Publication date
Application filed by Rhode Island Board of Education filed Critical Rhode Island Board of Education
Priority to AU18372/95A priority Critical patent/AU1837295A/en
Publication of WO1995021419A1 publication Critical patent/WO1995021419A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B19/00—Teaching not covered by other main groups of this subclass
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
    • G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
    • G09B7/04—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof

Definitions

  • the present invention embodies an intervention which combines individualized matching of the human-guided intervention with the low cost of the public health approach.
  • the preferred embodiment of the invention is directed to a system designed to promote smoking cessation.
  • the impact of smoking on public health is enormous. Some 50 million Americans continue to smoke cigarettes despite more than 25 years of health education programs, anti-smoking campaigns, declining social acceptability of smoking, and well established health consequences of smoking. An estimated 390,000 Americans die. each year from diseases caused by smoking, including 115,000 from heart disease and 106,000 from lung cancer. More than one of every six deaths in the United States is caused by smoking. A similar pattern of negative consequences for smoking occurs for most countries in the world. On the positive side, smoking cessation has major and immediate health benefits for men and women of all ages.
  • An expert system has been defined in a variety of ways. The most general is a software system that mimics the deductive or inductive reasoning of a human expert, Negotia, U.N. (1985) Expert Systems and Fuzzy Systems, CA: Benjamin/Cummings. More specifically, an expert system requires two things: (a) a collection of facts and rules about a field and (b) a way of making inferences from those facts and rules (Negotia, supra). The heuristics and domain theories on which an expert system relies are referred to as surface knowledge. Most expert systems include only surface knowledge but some may also rely on principles and general theories, or deep knowledge, which can become necessary when confronting really difficult problems, Harmon, P., & King, D., (1985), Expert
  • an expert system when compared to a human expert, includes ease of documentation, ease of transfer to multiple sites, increased consistency in decision making, increased potential for replicable results, permanence, and low costs. Additionally, considered from a public health perspective, an expert system is logistically compatible with large scale implementation, allowing for potential impact on large segments of the population.
  • expert systems have been or are under development to assist managers with complex planning and scheduling tasks, to diagnose diseases, to locate mineral deposits, to configure complex computer hardware, and to aid mechanics in troubleshooting locomotive problems, Harmon, P., & King, D., (1985), Expert Systems: Artificial Intelligence in Business, New
  • An object of the present invention is to provide an expert system which effectively and positively influences behavioral patterns.
  • Another object of the present invention is to provide an expert system which is based on information received from a user and prepares a specially tailored report based on that user's response.
  • an expert system broadly comprises a method for processing behavior modification data which comprises: inputting raw data based on an individual's response to a series of questions into a computer;
  • first and second follow-up reports are also generated.
  • Fig. 1 is an execution control diagram of a batch system of the preferred embodiment of the invention
  • Fig. 2 is a data flow program overview of the system of Fig. 1;
  • Fig. 3 is a base line and follow-up data flow diagram of the system of Fig. 1; and.
  • Fig. 4 is an illustration of an interactive system of an alternative embodiment of the invention.
  • the process or system of the invention provides individually relevant and appropriate information to aid users in the process of quitting smoking.
  • the primary value of the system is its ability to provide individually tailored advice and concrete behavioral recommendations in response to a brief paper and pencil assessment or other input of a user's and behaviors related to smoking.
  • Previous methods have been based on a generic public health approach, which provides the same recommendations and advice to all smokers, regardless of their current attitudes and behaviors. Additionally, this system has the advantage of providing useful information to all smokers, even those who are not currently considering quitting at the present time. This makes it feasible to communicate the system "message," or deliver the intervention, in a proactive, rather than reactive manner. Most prior smoking cessation interventions have been geared primarily toward those users who are ready to take action.
  • the system of the invention has the advantage of providing useful, helpful information to those less motivated, without alienating these users by making assumptions about their desires or readiness to quit.
  • the medium of communication utilized by the system is to inter with a computer directly or receive a written report of two .to four pages in length with the information having beenscanned into the computer.
  • a report is generated from a first time assessment, provides stage of change relevant information as well as comparisons to a normative sample of successful quitters. Reports are generated from follow-up assessments which add ipsative feedback providing concrete commentary on individual changes since a previous assessment.
  • the present invention is directed to a process for data, whether identified as a batch or interactive system, which manipulates and processes the information received based on the responses by the individual and provides the output (reports to the individual through the various computer programs). These programs match the type of responses that would be provided are substantially the same as if the individual were receiving private counseling.
  • the invention thus enables, on a very broad basis, individuals to receive specially tailored reports at relatively low cost which heretofore had not been possible.
  • the message channel employed with the preferred embodiment of the system is a written report, printed on paper, although the same report can be effectively presented through a number of other channels.
  • the same individually tailored report could be presented immediately following the assessment on a computer screen.
  • a sound board added to such a system would permit the simultaneous presentation of the material both as a written message and as a spoken message.
  • An implementation such as this is very viable in a setting such as a physician's office, an HMO setting, a school, or a worksite.
  • a user is provided with information in the form of a written report generated by the system.
  • each user is a smoker.
  • the knowledge domain necessary to build an effective system is narrowed.
  • a second level of generality would be a system targeted to a single problem but applicable to all users. For smokers, cessation materials would be presented and for nonsmokers, prevention or passive smoking materials would be presented.
  • a third level of generality would be a more general purpose system, which involves all users and multiple problems.
  • a multiple risk factor approach can be developed, assuming that there is likely to be some behavior change associated with cancer risk appropriate for everyone.
  • This system could take several alternative approaches. The system could allow the user to identify the primary problem of interest, or the system could determine the "highest" risk behavior, given knowledge of user demographics, and begin there. Problem behavior areas could be dealt with sequentially or simultaneously. The intrinsic qualities of the system intervention make such investigations quite feasible.
  • segmentation could be a key demographic variable such as education level or income. Segmentation based on educational level might require that a system be capable of communicating written messages at several different reading levels. Similarly, were a different message channel used, one would have to be conscious of segmentation based on income that required resources, such as a VCR or a computer in the home, that might not be available to all potential users.
  • Effects are conceptualized as the impact of the message on the user. Assessment of this impact requires that some sort of message from the user be communicated back to the system. This message is often referred to as feedback.
  • Feedback may be either feedback from a participant to the expert system showing the participants progress or feedback that the expert system gives to the participant in response to answers to the questions.
  • Some systems, such as those that diagnose illness, benefit from feedback from more invasive procedures pertaining to the ultimate accuracy of their conclusions. For example, once diagnoses offered by the expert system are confirmed or disconfirmed, provision of this feedback to the system can influence the probabilities and weightings associated with decision rules. Assessment of the impact on users is also important simply in terms of the efficacy of the expert system. Without some form of feedback from the user, it is impossible to ascertain the effectiveness of the expert system, or to improve its performance.
  • the outcome measures include both behavioral and cognitive measures.
  • of interest are the current smoking status and number of cigarettes smoked per day, which reflects current behavior, and the Pros and Cons scales from the decisional balance, which reflects cognitions about the advantages and disadvantages of continuing to smoke.
  • the feedback channel associated with the system can potentially take a number of forms.
  • the user With an on-line, interactive system, the user is providing a form of feedback with each response or query communicated to the expert system.
  • Assessment of outcome measures can also be accomplished via an on-line, interactive method.
  • Feedback can involve the communication of outcome information at some later time. Data of this sort could conceivably take many forms and be communicated to the system in many different ways.
  • Alternative feedback channels include both verbal and direct entry of data.
  • Verbal entry might involve a phone interview where the interviewer enters the data into the computer.
  • CATI Computer Assisted Telephone Interviewing
  • Direct entry could involve either on-line assessment at a later time, or perhaps use of touch-tone telephone technology as a means of conducting follow-up assessments. It is likely that advances in the area of communication will provide alternative feedback channels.
  • the feedback channel employed for the system involves user responses to a series of questions printed on a mark sense form which is returned through the mail . Responses to questionnaires are then entered into the system via an optical scanner. This method has benefits both in terms of cost effectiveness, and efficiency with respect to manual labor demands.
  • the integrative nature of the system allows this new information to be linked with data collected previously from the same user, allowing for ipsative comparisons to be made across a series of interventions.
  • the transtheoretical model represents the deep knowledge basis of the system of the invention. It specifies a series of independent variables, called the processes of change, a temporal ordering called the stages of change, and a series of intervening or outcome measures. The specific application of the measures is dependent on the specific problem behavior. For the core constructs, the items change for different problem areas. Described for the preferred embodiment are measures appropriate for smoking cessation in this section. Measures appropriate for other problem areas such as alcohol abuse, fat reduction in the diet, sun exposure, increasing exercise, and mammography screening are within the scope of the invention.
  • the intervening or outcome measures include three separate subscales of the Temptation to Smoke Inventory: (1), Positive/Social, (2) Negative/Affective, and (3) Habit/Addictive types of situations.
  • Pros Scale and (2) Cons Scales.
  • behavioral measures are determined by specific problem area. For smoking cessation, these include (1) point prevalence, or current smoking status, Velicer, W.F., Prochaska, J.O., Rossi, J.S., & Snow, M.G., (1992), Assessing Outcome In Smoking Cessation Studies, Psychological Bulletin, 111, 23-41: (2) number of cigarettes currently being smoked; (3) behavior intention, or plans to modify behavior in the next 30 days, (4) continuous abstinence, or no smoking since the last assessment, and (5) previous quit attempts, or the number of times where at least a 24-hour quit attempt occurred in the last six months.
  • the next section describes some of these measures in more detail, and references some of the available empirical evidence.
  • Stages of Change represents a central concept for the transtheoretical model of behavior change. Similar concepts have been discussed by Brownell, K., Marlatt, G.A., Lichtenstein, E., & Wilson, G.T., (1986), Understanding And Preventing Relapse , American Psychologist, 41, 765-782; Horn, D.A., (1976), A Model For The Study Of Personal Choice Health Behavior, International Journal of health Education, 19, 89-98; Horn, D.A., & Waingrown, S., (1966), Some Dimensions Of A Model For Smoking Behavior Change, American Journal of Public Health, 56, 21.
  • the stages are a central organizing construct, describing when particular processes of change are most profitably employed and when the use of a process might be counter-productive.
  • the pattern of change of the intervening variables across stage is well defined and different measures are more sensitive to change in different stages.
  • Precontemplation is a stage in which smokers are not thinking about quitting smoking within the next six months. A six-month time frame was used because it was assumed that this is about as far in the future as most people plan a specific behavior change.
  • Contemplation is the period of time in which smokers are seriously thinking about quitting smoking in the next six months. Preparation has been defined as smokers seriously thinking about quitting smoking in the next month and having made a recent quit attempt.
  • Action is a continuous period ranging from 0 to 6 months after smokers have made the overt change of stopping smoking. Maintenance is defined as the stage beginning six months after Action started and continuing until smoking is terminated as a problem.
  • This questionnaire is either a 20-item (long form) or 9-item (short form) scale devised to measure temptations to smoke across a wide variety of everyday situations. Items are measured using a five-point Likert scale format, with higher scores indicating greater temptations to smoke.
  • the questionnaire is reliable and has been replicated across samples, problems and response formats, DiClemente, C.C., Prochaska, J.O., & Gilbertini, M., (1985), Self-Efficacy And The Stages Of Self-Change Of Smoking, Cognitive Therapy And Research, 9, 181-200; Velicer, W.F., DiClemente, C.C., Rossi, J.S., & Prochaska, J.O., (1990), Relapse Situations And Self-Efficacy: An Integrative Model, Addictive Behaviors, 15, 271-283.
  • the scale includes three correlated subscales: (1) Positive/Social, or the temptation to smoke when having a good time and with other people; (2) Negative/Affective, or the temptation to smoke when feeling lonely or feeling negative emotions; and (3) Habit/Addictive, or the temptation to smoke when feeling a strong craving.
  • the pattern of change in temptations across stages is a gradual decrease from Precontemplation to Maintenance.
  • This questionnaire is a 20-item (long form) or 6-item (short form) scale devised to measure the decisional balance between the positive (Pros) and negative (Cons) aspects of smoking cigarettes.
  • Two scales have been identified and labeled the Pros of Smoking and the Cons of Smoking, respectively (Velicer, supra). The two scales have been successful in differentiating between five groups representing stages of change in the quitting process, and have also been successful when employed as predictors of smoking status at a 6-month follow-up (Prochaska, supra).
  • the Pros scale declines across the stages with the highest scores for Precontemplation and Contemplation followed by regular decrements across the last three stages.
  • the Cons scale is very low in Precontemplation, increases dramatically to equal the Pros in Contemplation, and then declines across the last three stages, always remaining above the Pros scale (Velicer, supra; Prochaska, supra).
  • the processes of change is a 40-item (long form) or 20-item (short form) questionnaire which measures the 10 processes described by the transtheoretical model of change, Prochaska, J.O., Velicer, W.F., DiClemente, C.C., & Fava, J.L., (1988), Measuring The Processes Of Change: Applications To The Cessation Of Smoking, Journal of Consulting and
  • Clinical Psychology 56, 520-528.
  • the 10 processes are: Consciousness Raising, Self-Reevaluation, Dramatic Relief, Environmental Reevaluation, Social Liberation, Counterconditioning, Stimulus Control, Helping Relationship, Self-Liberation, and Reinforcement Management.
  • the first five are labelled Experiential processes and involve cognitive and emotional activities.
  • the second five are labelled Behavioral Processes and involve primarily behavioral activities or cognitive labelling of behaviors.
  • the curvi-linear pattern of change for each of the processes across the stages of change is similar. Use of the processes increases, peaks, and then decreases. The processes differ in when the peaks occur, with the more experiential processes peaking early and the more behavioral processes peaking later (Prochaska, et al., 1990) .
  • a data base is run on a computer and the data base is used to determine what potential users receive survey forms, and paper forms are mailed out to the users.
  • the user answers the questions on the forms. They mail the forms back. That data is then entered into the computer and then a report is printed and mailed to the user.
  • Recruited users i.e., a project is advertised in some way and users initiate contact if interested Standardized, individualized, interactive, and personalized self-help programs for smoking cessation, Health Psychology and proactively recruited users, i.e., users are individually contacted and are included in the project unless they refuse service, Prochaska, J.O., Velicer, W.F., DiClemente, C.C., & Fava, J.L., (1988), Measuring The Processes Of Change: Applications To The Cessation Of Smoking , Journal of Consulting and Clinical Psychology, 56, 520-528.
  • the stages of change include Precontemplation, Contemplation, Preparation, Action, and Maintenance.
  • a user who has taken action by making a quit attempt, but who subsequently returns to smoking is thought of as a "relapser.”
  • Relapse is not technically a stage of change, the expert system responds to users fitting this description with reports which specifically address relapse issues.
  • Change process use is assessed through a refined, twenty-item version of the longer, forty item Processes of Change questionnaire. Using a five-point Likert format, these twenty items assess use of ten processes of change common to the behavior change experience across a number of problem behaviors. These processes have been empirically validated within the contexts of self-change and change initiated within a therapeutic setting or relationship. The processes of change have been described in detail in an earlier section.
  • the first or baseline report uses only normative comparisons.
  • follow-up or progress reports use both normative and ipsative information.
  • Each report contains four sections. The first section provides information pertaining to the user's particular Stage of Change. Additionally, this section provides feedback regarding Decisional Balance considerations with respect to the user's decision to smoke. Focusing primarily on the Cons of smoking, this feedback may suggest that the user increase his or her thinking about the negative aspects of smoking, while providing suggestions of specific cons to consider. If the report is a progress report, indicating a follow up assessment has been made, this section provides feedback about the users' progress (or lack of progress) through the stages of change.
  • the second section focuses on Process of Change use.
  • the third section of the report provides particular stage specific strategies which have been found useful with regard to moving smokers to the next stage of change. For example, those in the Contemplation stage are encouraged to take a small step toward changing their smoking behavior, like delaying the first cigarette of the day for 30 minutes.
  • the fourth and final section of the report contains information pertaining to the user's temptation to smoke. Specifically, the user is given feedback pertaining to what appears to be the situation in which the user is at most risk with respect to temptation to smoke, and suggestions as to how best to cope in the high risk situation.
  • the first step towards making another quit attempt involves having a realistic attitude about your relapse. Think about the progress you have already made as you continue to move towards your goal of becoming a nonsmoker.
  • the second step in getting back on track involves taking a close look at the situation that tempted you to light up that first cigarette after you had quit.
  • Three kinds of situations seem to be most plausible for smokers. One involves social occasions where the focus is on relaxation or celebration.
  • Activities can range from getting together with a friend who smokes to attending parties, weddings or other social events.
  • a second plausible situation for smokers is any event that results in having negative feelings such as anger, frustration, depression or anxiety.
  • a third plausible situation occurs when an ex-smokers is having a physiological craving or strong urge to smoke that may be related to a daily habit. For example, many smokers who light up a cigaretted as soon as they wake up in the morning may associate their smoking with their idea of how they start their day.
  • a provider's DBMS shall be the parent task, or controlling procedure, in the execution flow.
  • the Stet DBMS shall select users that are due for intervention processing. It shall build the input file for the Smoking Intervention System, expert system software of the invention, (SIS) and then call the SIS. When the SIS has completed, it shall return control to the Stet DBMS. The Stet DBMS shall then initiate MS-Word to produce the intervention reports. When Word has completed, the Stet DBMS regains control and can perform any close-out processing required.
  • the provider's Stet DBMS has complete control over the processing flow.
  • the periodicity of the interventions is defined by the CPRC as a 90 day cycle. This shall be controlled by the Stet DBMS and validated by the SIS software. Intervention periods of less than 90 days are disallowed. Intervention periods of greater than 90 days are beyond the control of either the provider or the CPRC. This is totally dependent upon the cooperativeness of the users.
  • the 90 day period shall be defined as the interval between the points at which the assessment forms are generated Therefore, 3 months after the baseline assessment is sent to the users, the second, or 3 month assessment shall be sent. And three months after that, the third assessment form shall be sent. Only 3 intervention reports are customarily provided for each user, however, SIS can process all valid data sent. The provider can control this with the printer control flag in the identifier record. All data will be accepted, analyzed and reported on, but only when the printer control flag is set, will a report be generated - - marked up as follows: SIS: Smoking Intervention System - any embodiment
  • Health Care provider e.g. Johnson & Johnson, Harvard Community Health Plan, etc.
  • the source code for the system of the preferred embodiment of the invention is set forth in the microfiche appendix entitled Behavioral Modification Program Particularly for Smoking Cessation Batch System, James O. Prochaska et al.
  • the expert system software is designed to process the data from 1 to N users in any one instantiation.
  • the provider's DBMS generates one file: the Assessment Data Input File (ADIF).
  • the SIS generates the Assessment Data Output File (ADOF), the Intervention Report Output File (IROF), and the Exception Data Output File (EDOF).
  • ADOF Assessment Data Output File
  • IROF Intervention Report Output File
  • EEOF Exception Data Output File
  • the ADIF contains the name and address records, an identifier record and assessment records (data from the surveys) for each user.
  • the ADOF shall contain the same identifier record as the ADIF along with the completed assessment records and output data from the SIS.
  • the ADOF data is stored by the provider's DBMS for retrieval at the next user assessment.
  • the IROF contains an identifier record similar to the one in the ADIF along with records containing path and file names and output data from the SIS.
  • the IROF is input to MS-WORD, the intervention report generator.
  • the EDOF contains references to the ADIF records that are found to be in error.
  • the normative or current input data is copied from the assessment forms, processed and stored by the DBMS, and then passed to SIS via the ADIF.
  • the ipsative, or previously derived data does not exist.
  • SIS expects default values in these data fields.
  • SIS processes the current input data, and then stores the current input data and the currently derived data in the ADOF.
  • the PDBMS stores the previous input data and previously derived data in the previous data fields in the ADIF, and the current input data in the current data fields.
  • SIS software generates and stores the current input and currently derived data in the ADOF for processing at time T n+2 . This process is repeated at each assessment/intervention period. In this fashion, the previous input and derived data was the current input and derived data from T n-1 . This process was depicted in Fig. 3 SIS Baseline And Follow-up Data Flow.
  • the DBMS validates the user responses and ensures that the data is complete.
  • the SIS re-screens the data to prevent inaccurate or incomplete reports from being generated.
  • the initial task is an attempt to clean or correct incomplete or inconsistent responses. Failing that, error messages are generated when invalid states exist in the data.
  • the error messages reflect the data restrictions defined in the file/record layouts section.
  • the error messages have three primary components: user id, a message number and the message text.
  • the message text identifies the item and the error.
  • Microsoft Word is used to assemble and generate the reports from the IROF. This requires that the input paragraph files be formatted as true Word ".doc" files. Any report generator can be substituted for MS-WORD, however, the files will have to be converted into a format compatible with that report generator. Additionally, that report generator will have to be able to read and parse the IROF.
  • the files are constructed with one user record and one set of records related to the current assessment.
  • the ADIF shall also contain a second set of records pertaining to the previous assessment.
  • the assessment record sets are organized in ascending order on record number.
  • the basic structure is as follows:
  • PI Current Input
  • PI Previous Input
  • CD Currently Derived
  • Previously Derived fields are the CD fields from the previous assessment.
  • the Stet DBMS shall set CD fields to blank(s) unless otherwise noted.
  • CI/D There are some fields labeled CI/D. These items are input items whose values are changed due to inconsistencies in the responses.
  • the Stet DBMS stores the newly updated values.
  • the Stet DBMS must provide the updated values to SIS for ipsative processing. Each record will have a flag designating if any data in that record was "cleaned" during processing.
  • Each data field has a Status: Required or Optional.
  • CI data fields are applicable at all time points.
  • CD data fields are generated at all time points.
  • PI and PD data fields are applicable at all time points except baseline. Fields that are not filled shall contain blanks as the default value unless otherwise noted.
  • CI, CD and CI/D data fields become PI, PD and PI/D data fields, respectively, at the next assessment/intervention period. No records are optional.
  • the assessment items are referenced by their respective page and question numbers.
  • SIS is executed by the call: SIS ⁇ DOS path name ⁇ .
  • the parameter can be omitted, wherein the default directory, C: ⁇ SIS ⁇ , is used.
  • the path name in the parameter list cannot exceed 30 characters and must be terminated with a backslash ( ⁇ ).
  • the data files referenced and defined previously have the file names as shown in the table at the right. These files are expected to appear in either the default directory,
  • ADIF Assessment Data Input File
  • the directory is the root directory for the Assessment Data Output File: ADOF.DAT project.
  • the ADIF is the output file of the PDBMS and Intervention Report Output File: IROF.DAT the input file to the expert system SIS.
  • the ADIF can Exception Data Output File: EDOF.DAT contain from 1 to N sets of participant subject data.
  • the ADOF, IROF and EDOF are output files of the expert Table 5: File Name Cross Reference system.
  • the ADOF and EDOF are input files to the PDBMS, and the IROF is the input file to the report generator.
  • the output files are overwritten each time SIS executes.
  • SCTL.DAT contains the paragraph filename extension ".DOC”. If the provider replaces MS-WORD with a different report generator, and needs to change the extension, this change is made in SCTL.DAT.
  • the length is fixed at 4 characters, must begin with ".” (if the extension isn't null), and must be left justified.
  • System messages are identified by the system id: "SYS STATUS”.
  • Participant messages are identified by the participant id.
  • System error messages are considered to be fatal, and the responsible CPRC S/W Engineer must be notified.
  • Participant error messages pertain to circumstances that only affect the individual participant. These will not cause the system to abort, only the processing for that participant will stop.
  • Messages containing a 0 in the demonstrated positions (xxxx0##0) of the message id are initialization messages. All other messages containing a "0" in the demonstrated position (xxx0###) of the message id are system errors, and are usually fatal. The only exception to this is "PART0202". Though it indicates a system failure, the system can recover. The failure pertains only to the participant whose id is in the message, and only that participant's processing shall fail.
  • the message "SMSG000" indicates a non-recoverable system failure has occurred that is external to and beyond the control of SIS. This message is displayed on the monitor. "SIS Terminated” is displayed just before SIS returns control to its parent task. This message is also displayed on the monitor. The messages are listed in the following figure.
  • Fig . 4 the administrator of the system controls all aspects of the invention .
  • the record layout follows and the software is set forth in the enclosed microfiche appendix entitled Behavioral Modification Program Particularly for Smoking Cessation Interactive System, James 0. Prochaska et al .
  • the interactive or schoolbased system runs on a computer and the computer asks the person a question on the screen.
  • the user sits right in front the computer and uses a mouse and answers the question presented on the screen by pressing yes or no or numeric buttons 1, 2, 3, 4 or 5.
  • the computer collects the data and produces the feedback report right on the screen.
  • This program accepts one set of user responses and generates the intervention report for that user in real time.
  • the system accomplishes its task by reading a variety of initialization data files that contain system control data systems, and this user's individualized input/output file. Input/Output
  • SCSUBACT.DAT contains the user information, name, age, gender etc. along with the user's responses to the questions, the names of the files containing the text of the components of the intervention report, and the timing data. Additional Output
  • a copy of the user's data is written to a file on the computer's hard disk and called SCxxxxx.DAT, where xxxxx is replaced by the user's unique id.
  • This file serves as a cautionary backup nd is used for subsequent data analysis.
  • SCYP SCYP Expert System
  • the input/output file on the user's personalized disk is called SCSUBACT.DAT
  • Record 00 is initialized prior to the user's assessment. It is the only record in the file on the subjects personal disk, prior to baseline processing. Records 01 through 24 contain the assessment and expert system data. This includes the raw scores, sums, paragraphs and path names, and timing data. The following tables contain the specific contents of these records. None of the raw scores will be missing, since the users are required to answer all questions as they proceed through the assessment.
  • the file is constructed with one subject record and multiple sets of assessment records.
  • the assessment record sets are organized in ascending order on session number.
  • the basic structure is as follows:
  • Session 1 Record 24 Session 2 Record 01
  • Session 2 Record 24 Session 3 Record 01 Session 3 Record 02

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Abstract

On accroit l'efficacité d'intervention lorsqu'un traitement est adapté au maximum aux besoins d'un individu. Dans la présente invention, un système de prise de décision informatisé utilise des informations relatives au client afin de produire des informations ainsi que des interventions adaptées personnalisées. Le système expert combine l'adaptation aux utilisateurs possible dans une intervention ayant une base clinique, ainsi que le faible coût associé à une approche de santé publique. L'intervention du système expert piloté par ordinateur développée spécifiquement pour cesser de fumer est décrite. L'invention fournit un moyen rentable, viable et efficace d'intervention dans un domaine de comportement à problèmes spécifiques.
PCT/US1995/001367 1994-02-01 1995-02-01 Intervention d'un syteme expert pour cesser de fumer Ceased WO1995021419A1 (fr)

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AU18372/95A AU1837295A (en) 1994-02-01 1995-02-01 An expert system intervention for smoking cessation

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US19077394A 1994-02-01 1994-02-01
US08/190,773 1994-02-01
US35037494A 1994-12-05 1994-12-05
US08/350,374 1994-12-05

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WO1999052038A1 (fr) * 1998-04-07 1999-10-14 Hazenbos Bartholomeus Francisc Appareil permettant de mettre graduellement fin a une dependance
EP1262901A3 (fr) * 2001-05-31 2005-03-02 Siemens Aktiengesellschaft Dispositif de modification de risque automatisée dans des groupes de risque
US8540517B2 (en) 2006-11-27 2013-09-24 Pharos Innovations, Llc Calculating a behavioral path based on a statistical profile
US8540516B2 (en) 2006-11-27 2013-09-24 Pharos Innovations, Llc Optimizing behavioral change based on a patient statistical profile
US8540515B2 (en) 2006-11-27 2013-09-24 Pharos Innovations, Llc Optimizing behavioral change based on a population statistical profile
CN104376219A (zh) * 2014-11-19 2015-02-25 王兴 一种基于用户状态反馈信息的戒烟干预方法及系统
CN104408301A (zh) * 2014-11-19 2015-03-11 王兴 一种吸烟行为评测系统
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US10874355B2 (en) 2014-04-24 2020-12-29 Cognoa, Inc. Methods and apparatus to determine developmental progress with artificial intelligence and user input
US11176444B2 (en) 2019-03-22 2021-11-16 Cognoa, Inc. Model optimization and data analysis using machine learning techniques
US11972336B2 (en) 2015-12-18 2024-04-30 Cognoa, Inc. Machine learning platform and system for data analysis
US12205725B2 (en) 2016-11-14 2025-01-21 Cognoa, Inc. Methods and apparatus for evaluating developmental conditions and providing control over coverage and reliability
US12236320B2 (en) 2020-05-05 2025-02-25 Optum Services (Ireland) Limited Passive heightened need prediction

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1999052038A1 (fr) * 1998-04-07 1999-10-14 Hazenbos Bartholomeus Francisc Appareil permettant de mettre graduellement fin a une dependance
EP1262901A3 (fr) * 2001-05-31 2005-03-02 Siemens Aktiengesellschaft Dispositif de modification de risque automatisée dans des groupes de risque
US8540517B2 (en) 2006-11-27 2013-09-24 Pharos Innovations, Llc Calculating a behavioral path based on a statistical profile
US8540516B2 (en) 2006-11-27 2013-09-24 Pharos Innovations, Llc Optimizing behavioral change based on a patient statistical profile
US8540515B2 (en) 2006-11-27 2013-09-24 Pharos Innovations, Llc Optimizing behavioral change based on a population statistical profile
US10874355B2 (en) 2014-04-24 2020-12-29 Cognoa, Inc. Methods and apparatus to determine developmental progress with artificial intelligence and user input
CN104408301A (zh) * 2014-11-19 2015-03-11 王兴 一种吸烟行为评测系统
CN104376219A (zh) * 2014-11-19 2015-02-25 王兴 一种基于用户状态反馈信息的戒烟干预方法及系统
US12402840B2 (en) 2015-08-11 2025-09-02 Cognoa, Inc. Methods and apparatus to determine developmental progress with artificial intelligence and user input
US11972336B2 (en) 2015-12-18 2024-04-30 Cognoa, Inc. Machine learning platform and system for data analysis
US12205725B2 (en) 2016-11-14 2025-01-21 Cognoa, Inc. Methods and apparatus for evaluating developmental conditions and providing control over coverage and reliability
US10839950B2 (en) 2017-02-09 2020-11-17 Cognoa, Inc. Platform and system for digital personalized medicine
US10984899B2 (en) 2017-02-09 2021-04-20 Cognoa, Inc. Platform and system for digital personalized medicine
US11176444B2 (en) 2019-03-22 2021-11-16 Cognoa, Inc. Model optimization and data analysis using machine learning techniques
US11862339B2 (en) 2019-03-22 2024-01-02 Cognoa, Inc. Model optimization and data analysis using machine learning techniques
US12236320B2 (en) 2020-05-05 2025-02-25 Optum Services (Ireland) Limited Passive heightened need prediction

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