Theoretical Validation in Sociological Research: Methodology and Methods

The very essence of mixed research is research designs. Having gone almost all the way through the "Study Materials", you are ready to receive this lesson.

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Research design is a combination of data collection and analysis requirements necessary to achieve research objectives. If we talk about ICT, then the corresponding research designs are related, first of all, to the peculiarities of the combinatorics of the elements of qualitative and quantitative approaches within the framework of one study.
The main principles of organizing designs in ICT are: 1) awareness of the theoretical drive of a research project; 2) awareness of the role of borrowed components in a research project; 3) compliance with the methodological assumptions of the base method; 4) work with the maximum available number of data sets. The first principle has to do with the purpose of the inquiry (search vs. confirmation), the appropriate types of scientific reasoning (induction vs. deduction), and the appropriate methods. According to the second principle, the researcher should pay attention not only to the main data collection and analysis strategies, but also to additional ones that could enrich the main part of the research project with data that are important and cannot be obtained using the main methods. The third principle is related to the need to adhere to the fundamental requirements of working with data of one type or another. The essence of the last principle is quite obvious and is related to the attraction of data from all available relevant sources.
Often ICTs are “placed” on a continuum between qualitative and quantitative research (see Figure 4.1). So, in the presented figure, zone "A" denotes the use of exclusively qualitative methods, zone "B" - mostly qualitative, with some quantitative components, zone "C" - the equivalent use of qualitative and quantitative methods (fully integrated studies), zone "D" - mostly quantitative with some qualitative components, zone "E" - exclusively quantitative methods.

Rice. Qualitative-mixed-quantitative continuum

If we talk about specific designs of ICT, then there are two main typologies. One is suitable for the case when qualitative and quantitative methods are used at different stages of the same study, the other for the case when alternating or parallel qualitative and quantitative studies are used within the research project.
The first typology includes six mixed designs (see Table 4.2). An example of research that uses qualitative and quantitative methods at different stages is concept alignment. Within this research strategy, data collection is carried out using qualitative methods (for example, brainstorming or focus groups), and analysis is quantitative (cluster analysis and multivariate scaling). Depending on the tasks being solved (search or descriptive), it can be attributed either to the second or to the sixth design.
According to the second typology, nine mixed-type designs can be distinguished (see Table 3). This typology is based on two main principles. First, in mixed-type research, it is important to determine the status of each of the paradigms - whether qualitative and quantitative research have the same status, or whether one of them is considered as the main one, and the second one is subordinate. Secondly, it is important to determine how the research will be conducted - in parallel or sequentially. In the case of a sequential solution, it is also necessary to determine which of them is the first and which is the second in the time dimension. An example of a research project that fits this typology is when the first phase is a qualitative research to build a theory (for example, using the "grounded theory" of Anselm Strauss), and the second - a quantitative survey of a specific group of people, to to which the developed theory is applicable and in relation to which it is necessary to formulate a forecast for the development of the corresponding social phenomenon or problem.

Table 1. Mixed study designs using qualitative and quantitative methods within the same study*

Research objectives	Data collection	Data analysis
Qualitative Goals	Quality data collection
	Quantitative data collection
	Quality data collection	Performing Quantitative Analysis
	Quantitative data collection	Conducting a qualitative analysis
quantitative goals	Quality data collection	Conducting a qualitative analysis
	Quantitative data collection	Performing Quantitative Analysis
	Quality data collection	Performing Quantitative Analysis
	Quantitative data collection	Conducting a qualitative analysis

* In this table, designs 2-7 are mixed, design 1 is completely qualitative, design 8 is completely quantitative.

Table 2. Mixed study designs using qualitative and quantitative research as different phases of the same research project*

* "quality" means qualitative research, "quant" - quantitative; "+" - simultaneous research, "=>" - sequential; capital letters indicate the main status of the paradigm, small letters - subordinate.

Of course, these typologies are not limited to the full variety of research designs and should be considered as possible guidelines for ICT planning.
ICT Designs in Evaluation Studies.
According to the typology of ICT designs used in assessment, two main types can be distinguished - component and integrative. In component design, although qualitative and quantitative methods are used within the framework of one study, they are used separately from each other. In integrative design, methods belonging to different paradigms, on the other hand, are used together.
The component type includes three types of designs: triangular, complementary, and expansive. In triangulation design, results from one method are used to validate results from other methods. In the case of complementary design, the results obtained using the main method are specified and refined on the basis of the results obtained using methods that are of secondary importance. When using an expansive design, different methods are used to obtain information about different aspects of the assessment, that is, each method is responsible for a specific piece of information.
The integrative type includes four types of designs: iterative, unstitched, holistic, and transformational. In iterative design, the results of one method prompt or direct other methods that are relevant to the situation. Nested design is associated with situations where one of the methods is integrated into another. Holistic design involves the combined use of integrated qualitative and quantitative methods in order to comprehensively evaluate a program. In this case, both groups of methods have an equivalent status. Transformational design takes place when different methods are applied together to fix value views, which are subsequently used to reconfigure a dialogue whose participants adhere to different ideological positions.

Theoretical Validation in Sociological Research: Methodology and Methods

In the social sciences, there are various types of research and, accordingly, opportunities for the researcher. Knowing about them will help you solve the most difficult problems.

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Research Strategies
In the social sciences, it is customary to single out the two most common research strategies - quantitative and qualitative.
Quantitative strategy involves using a deductive approach to test hypotheses or theories, relies on the positivist approach of the natural sciences, and is inherently objectivist. A qualitative strategy, on the other hand, focuses on an inductive approach for developing theories, rejects positivism, focuses on an individual interpretation of social reality, and is constructivist in nature.
Each of the strategies involves the use of specific data collection and analysis methods. The quantitative strategy is based on the collection of numerical data (mass survey data encodings, aggregated testing data, etc.) and the use of mathematical statistics methods for their analysis. In turn, a qualitative strategy is based on the collection of textual data (texts of individual interviews, participant observation data, etc.) and their further structuring using special analytical techniques.
Since the beginning of the 90s, a mixed strategy began to actively develop, which consists in integrating the principles, methods for collecting and analyzing data from qualitative and quantitative strategies in order to obtain more reasonable and reliable results.

Research designs
Once the purpose of the study has been determined, the appropriate type of design must be determined. Study design is the combination of data collection and analysis requirements necessary to achieve the study objectives.
Main types of design:
Cross-sectional design involves collecting data on a relatively large number of observation units. As a rule, it involves the use of a sampling method in order to represent the general population. The data is collected once and is quantitative. Further, descriptive and correlation characteristics are calculated, statistical conclusions are drawn.
Longitudinal design consists of repeated cross-sectional interviews to establish changes over time. It is divided into panel studies (the same people take part in repeated surveys) and cohort studies (different groups of people who represent the same general population take part in repeated surveys).
Experimental design involves identifying the influence of the independent variable on the dependent variable by leveling the threats that may affect the nature of the change in the dependent variable.
The design of a case study is intended to study one or a small number of cases in detail. The emphasis is not on the distribution of the results to the entire population, but on the quality of theoretical analysis and explanation of the mechanism of functioning of a particular phenomenon.

Research goals
Among the goals of social research are description, explanation, evaluation, comparison, analysis of relationships, the study of cause-and-effect relationships.
Descriptive tasks are solved by simply collecting data using one of the methods that are appropriate in a given situation - questionnaires, observations, document analysis, etc. One of the main tasks in this case is such a fixation of data, which in the future will allow their aggregation.
To solve explanatory problems, a number of research approaches are used (for example, historical studies, case studies, experiments), which allow dealing with the analysis of complex data. Their goal is not only a simple collection of facts, but also the identification of the meanings of a large set of social, political, cultural elements associated with the problem.
The general purpose of evaluation studies is to test programs or projects in terms of awareness, effectiveness, achievement of objectives, etc. The results obtained are usually used to improve them, and sometimes simply to better understand the functioning of the programs and projects concerned.

Comparative studies are used for a deeper understanding of the phenomenon under study by identifying its common and distinctive features in various social groups. The largest of them are held in cross-cultural and cross-national contexts.
Studies to establish relationships between variables are also called correlation studies. The result of such studies is the receipt of specific descriptive information (for example, see about the analysis of pairwise relationships). This is fundamentally quantitative research.
Establishing cause-and-effect relationships involves conducting experimental studies. In the social and behavioral sciences, there are several varieties of this kind of research: randomized experiments, true experiments (involving the creation of special experimental conditions that simulate the necessary conditions), sociometry (of course, as J. Moreno understood it), Garfinkeling.

Clinical Research Design

The design of a clinical trial is the plan for conducting it. The design of a particular clinical trial depends on the goals pursued by the study. Consider three common design options:

Clinical study in one group (single group design)

Clinical study in parallel groups (parallel group design)

Clinical study in a crossover group design

Clinical study in one group

(single group design)

In a single-group study, all subjects receive the same experimental treatment. This study design aims to compare treatment outcomes with baseline. Thus, subjects are not randomized to treatment groups.

The single-group clinical trial model can be illustrated as follows:

Screening -- Inclusion -- Baseline -- Treatment -- Outcomes

The single group model can be used in Phase I studies. Single-arm study models are generally not used in Phase III clinical trials.

The main disadvantage of the single-arm study model is the lack of a comparison group. The effects of experimental treatment cannot be differentiated from the effects of other variables.

Clinical study in parallel groups

(parallel group design)

When conducting clinical trials in parallel groups, the subjects of two or more groups receive different therapy. To achieve statistical significance (to eliminate systematic errors), the subjects are divided into groups by the method of random distribution (randomization).

The parallel group clinical study model can be illustrated as follows:

Treatment a -- Outcomes a

Treatment b -- Outcomes b

Where a, b are different drugs or different doses or placebo

Clinical trials in parallel group design are costly, time consuming, and require a large number of subjects (with a low event rate). However, clinical studies in parallel groups are the most objective in determining the effectiveness of treatment and accurate in formulating conclusions. Most clinical trials are thus conducted in parallel group design.

Sometimes studies in parallel groups can be used in two versions - these are factorial and heterogeneous models.

factorial design-- this is a design based on several (more than 2) parallel groups. Such studies are performed when a combination of different drugs (or different doses of the same drug) needs to be studied.

The factorial model of clinical research can be illustrated as follows:

Screening -- Inclusion -- Run-up -- Baseline -- Randomization --

Treatment a -- Outcomes a

Treatment b -- Outcomes b

Treatment with -- Outcomes with

Treatment in -- Outcomes in

Where a, b, c, d are different drugs or different doses or placebo

The factorial model is useful in evaluating combination drugs.

The disadvantage of the factorial model is the need to involve a large number of subjects and, as a result, an increase in the cost of research.

Withdrawal (Discontinuation) Design

A heterogeneous model is a variant of parallel-group studies where all subjects are initially treated with experimental treatment, then patients with appropriate reactions are randomized into groups using double-blind or placebo technology to continue experimental treatment. This model is usually used to assess the effectiveness of experimental treatment by discontinuing the drug immediately after the onset of the reaction and registering relapse or remission. On fig. 5 is a diagram of a heterogeneous research model.

Screening - Inclusion - Experimental treatment - Treatment response - Randomization of responders - Treatment or Placebo

A heterogeneous design of studies is especially effective for the evaluation of medicines intended for the treatment of intractable diseases. In such studies, only a small percentage of subjects show responses to treatment.

During the treatment period, responses are identified, and a heterogeneous randomization phase is used to demonstrate that the response is real and not a response to placebo. In addition, heterogeneous models are used to study relapses.

The disadvantages of heterogeneous models are:

a large number of subjects who initially receive treatment to detect responses

Significant duration of the study

The preparatory period should last long enough for the patients to stabilize and the effect of the drug to be more clearly revealed. It should be noted that the percentage of subjects excluded from these studies can be high.

Ethical considerations require careful consideration of the use of this research design, as it may require the drug to be excluded from therapy if it provides relief to patients. Rigorous monitoring and clear definition of endpoint indicators are of paramount importance.

"Cross" model

(Crossover Design)

Unlike parallel-group study designs, cross-sectional models allow the effects of both study drugs and comparative treatments to be assessed in the same subjects. The subjects are randomized into groups in which the same course of treatment is carried out, but with a different sequence. As a rule, a "washout" period is necessary between courses in order for the patient's indicators to return to baseline, and also in order to exclude the undesirable influence of the residual effects of the previous treatment on the effects of the subsequent one. A "washout" period is not necessary if the analyzes of individual reactions of the subject are limited to their comparison at the end of each course, and the treatment period lasts long enough. Some crossover models use pre-crossover, which means that patients who are excluded from studies at the treatment stage can be transferred to alternative treatment groups earlier than planned.

Screening - Preparation period - Condition control - Randomization - Treatment A in group 1 and Treatment B in group 2 - Washout period - Treatment B in group 1 and Treatment A in group 2

"Crossover" models are commonly used to study pharmacokinetics and pharmacodynamics when the goal is to control variability within a population of subjects. In addition, it is fair to assume that the effects of the first course do not affect the second in pharmacokinetic and pharmacodynamic studies with a sufficient "washout" period.

"Crossover" models are more economical than parallel group models because they require fewer subjects. However, sometimes there are difficulties in interpreting the results. The effects of one therapy can be mixed with the effects of the next. It can be difficult to distinguish the effects of sequential treatments from the effects of individual courses. In clinical trials, the crossover model usually takes longer than parallel group studies because each patient goes through at least two treatment periods plus a washout period. This model also requires more characterization for each patient.

If the clinical conditions are relatively constant throughout the duration of the study, then the "cross-over" model is effective and reliable.

Relatively low sample size requirements make cross-sectional models useful in early clinical development in order to facilitate decisions on larger parallel study models. Because all subjects receive the study drug, cross-over studies are also effective for assessing safety.

RESEARCH DESIGN DEVELOPMENT

At the first stage, the design is carefully worked out (from the English. design- creative idea) of future research.

First of all, a research program is developed.

Program includes the topic, purpose and objectives of the study, formulated hypotheses, definition of the object of study, units and scope of observations, glossary of terms, description of statistical methods for forming a sample, collecting, storing, processing and analyzing data, methodology for conducting a pilot study, a list of statistical tools used .

Name themes usually formulated in one sentence, which should correspond to the purpose of the study.

Purpose of the study- this is a mental anticipation of the result of an activity and ways to achieve it with the help of certain means. As a rule, the purpose of medical and social research is not only theoretical (cognitive), but also practical (applied) in nature.

To achieve this goal, determine research objectives, that reveal and detail the content of the goal.

The most important component of the program are hypotheses (Expected results). Hypotheses are formulated using specific statistical indicators. The main requirement for hypotheses is the ability to test them in the research process. The results of the study can confirm, correct or refute the hypotheses put forward.

Prior to the collection of material, the object and unit of observation are determined. Under object of medical and social research understand a statistical set consisting of relatively homogeneous individual objects or phenomena - units of observation.

Unit of observation- the primary element of the statistical population, endowed with all the features to be studied.

The next important operation in the preparation of the study is the development and approval of the work plan. If the research program is a kind of strategic plan that embodies the ideas of the researcher, then the work plan (as an annex to the program) is a mechanism for the implementation of the study. The work plan includes: the procedure for selecting, training and organizing the work of direct executors; development of regulatory and methodological documents; determination of the required volume and types of resource support for the study (personnel, finance, material and technical, information resources, etc.); definition of terms and responsible for separate stages of research. It is usually presented in the form network graphics.

At the first stage of medical and social research, it is determined by what methods the selection of units of observation will be carried out. Depending on the volume, continuous and selective studies are distinguished. In a continuous study, all units of the general population are studied, in a selective study, only a part of the general population (sample) is studied.

General population called a set of qualitatively homogeneous units of observation, united by one or a group of features.

Sample population (sample)- any subset of observation units of the general population.

The formation of a sample population that fully reflects the characteristics of the general population is the most important task of statistical research. All judgments about the general population based on sample data are valid only for representative samples, i.e. for such samples, the characteristics of which correspond to those of the general population.

The real provision of representativeness of the sample is guaranteed random selection method those. such a selection of units of observation in the sample, in which all objects in the general population have the same chances of being selected. To ensure random selection, specially developed algorithms are used that implement this principle, either tables of random numbers, or a random number generator available in many computer software packages. The essence of these methods is to randomly indicate the numbers of those objects that must be selected from the entire population in some way ordered. For example, the general population "regional population" can be sorted by age, place of residence, alphabetical order (last name, first name, patronymic), etc.

Along with random selection, when organizing and conducting medical and social research, the following methods of forming a sample are also used:

Mechanical (systematic) selection;

Typological (stratified) selection;

serial selection;

Multistage (screening) selection;

cohort method;

The "copy-pair" method.

Mechanical (systematic) selection allows you to form a sample using a mechanical approach to the selection of units of observation of an ordered general population. At the same time, it is necessary to determine the ratio of the volumes of the sample and the general population and thereby establish the proportion of selection. For example, in order to study the structure of hospitalized patients, a sample of 20% of all patients who left the hospital is formed. In this case, among all the "medical records of an inpatient" (f. 003 / y), ordered by numbers, every fifth card should be selected.

Typological (stratified) selection involves a breakdown of the general population into typological groups (strata). When conducting medical and social research, age-sex, social, professional groups, individual settlements, as well as urban and rural populations are taken as typological groups. In this case, the number of units of observation from each group is selected in the sample randomly or mechanically in proportion to the size of the group. For example, when studying the cause-and-effect relationships of risk factors and oncological morbidity of the population, the study group is first divided into subgroups by age, gender, profession, social status, and then the required number of observation units is selected from each subgroup.

serial selection the sample is formed not from individual units of observation, but from whole series or groups (municipalities, health care institutions, schools, kindergartens, etc.). The selection of series is carried out using proper random or mechanical sampling. Within each series, all units of observation are studied. This method can be used, for example, to evaluate the effectiveness of the immunization of the child population.

Multistage (screening) selection involves a phased sampling. By the number of stages, one-stage, two-stage, three-stage selection, etc. are distinguished. So, for example, when studying the reproductive health of women living in the territory of a municipality, at the first stage, working women are selected, who are examined using basic screening tests. At the second stage, a specialized examination of women with children is carried out, at the third stage, an in-depth specialized examination of women with children with congenital malformations. Note that in this case of purposeful selection for a certain attribute, the sample includes all objects - carriers of the studied attribute on the territory of the municipality.

cohort method are used to study the statistical population of relatively homogeneous groups of people united by the onset of a certain demographic event in the same time interval. For example, when studying issues related to the problem of fertility, a population (cohort) is formed that is homogeneous on the basis of a single date of birth (a study of fertility by generations) or on the basis of a single age of marriage (a study of fertility by length of family life).

Copy-Pair Method provides for the selection for each unit of observation of the group under study of an object that is similar in one or more features (“copy-pair”). For example, factors such as body weight and sex of the child are known to influence infant mortality rates. When using this method, for each death of a child under 1 year of age, a “copy-pair” of the same sex, similar in age and body weight, is selected from among living children under the age of 1 year. This method of selection should be used to study risk factors for the development of socially significant diseases, individual causes of death.

At the first stage, research is also developed (ready-made is used) and replicated statistical toolkit (cards, questionnaires, table layouts, computer programs for controlling incoming information, forming and processing information databases, etc.), into which the studied information will be entered.

In the study of public health and the activities of the health care system, sociological research is often used using special questionnaires (questionnaires). Questionnaires (questionnaires) for medical and sociological research should be targeted, oriented, ensure the reliability, reliability and representativeness of the data recorded in them. During the development of questionnaires and interview programs, the following rules must be observed: the suitability of the questionnaire for collecting, processing and extracting the necessary information from it; the possibility of reviewing the questionnaire (without violating the system of codes) in order to eliminate unsuccessful questions and make appropriate adjustments; explanation of the goals and objectives of the study; clear wording of questions, eliminating the need for various additional explanations; fixed nature of most questions.

Skillful selection and combination of various types of questions - open, closed and semi-closed - can significantly increase the accuracy, completeness and reliability of the information received.

The quality of the survey and its results largely depend on whether the basic requirements for the design of the questionnaire and its graphic design are met. There are the following basic rules for constructing a questionnaire:

The questionnaire includes only the most significant questions, the answers to which will help to obtain the information necessary to solve the main objectives of the study, which cannot be obtained in any other way without conducting a questionnaire survey;

The wording of the questions and all the words in them should be understandable to the respondent and correspond to his level of knowledge and education;

The questionnaire should not contain questions that cause unwillingness to answer them. It is necessary to strive to ensure that all questions cause a positive reaction of the respondent and a desire to give complete and true information;

The organization and sequence of questions should be subject to obtaining the most necessary information to achieve the goal and solve the problems set in the study.

Special questionnaires (questionnaires) are widely used, among other things, to assess the quality of life of patients with a particular disease, the effectiveness of their treatment. They allow capturing changes in the quality of life of patients that have occurred over a relatively short period of time (usually 2-4 weeks). There are many special questionnaires, such as AQLQ (Asthma Quality of Life Questionnaire) and AQ-20 (20-Item Asthma Questionnaire) for bronchial asthma, QLMI (Quality of Life after Myocardial Infarction Questionnaire) for patients with acute myocardial infarction, etc.

Coordination of work on the development of questionnaires and their adaptation to various linguistic and economic formations is carried out by an international non-profit organization for the study of the quality of life - the MAPI Institute (France).

Already at the first stage of the statistical study, it is necessary to draw up layouts of tables, which will be filled in the future with the data obtained.

In tables, as in grammatical sentences, the subject is distinguished, i.e. the main thing that is said in the table, and the predicate, i.e. that which characterizes the subject. Subject - this is the main feature of the phenomenon under study - it is usually located on the left along the horizontal lines of the table. Predicate - signs characterizing the subject are usually located on top of the vertical columns of the table.

When compiling tables, certain requirements are met:

The table should have a clear, concise title that reflects its essence;

The design of the table ends with the totals for columns and rows;

The table should not contain empty cells (if there is no sign, put a dash).

There are simple, group and combination (complex) types of tables.

A simple table is a table that presents a summary of data for only one attribute (Table 1.1).

Table 1.1. Simple table layout. Distribution of children by health groups, % of total

In the group table, the subject is characterized by several unrelated predicates (Table 1.2).

Table 1.2. Group table layout. Distribution of children by health groups, sex and age, % of the total

In the combination table, the signs characterizing the subject are interconnected (Table 1.3).

Table 1.3. Combination table layout. Distribution of children by health groups, age and gender, % of total

An important place in the preparatory period is occupied by pilot Study, whose task is to test statistical tools, to verify the correctness of the developed methodology for collecting and processing data. The most successful is such a pilot study, which repeats on a reduced scale the main one, i.e. makes it possible to check all the upcoming stages of work. Depending on the results of the preliminary analysis of the data obtained during piloting, the statistical tools, methods of collecting and processing information are adjusted.