Ethical Issues and Data Processing

The health care delivery system contains numerous ethical problems as well as experiences of community health nurses. Understanding the legal definitions of the nurse's obligations is crucial.

Because the hospital employs a team of people, the community health nurse must exercise extreme caution when providing services there. In contrast, nurses in the community are typically working alone and must provide services to patients in their homes.

She needs to be more cautious and knowledgeable about legal matters.

Data Processing

A set of techniques used to enter, retrieve, verify, store, organize, analyze, and interpret a set of data are referred to as data processing. Editing, coding, classifying, tabulating, charting, and diagramming research data are all aspects of data processing.

Data editing

The initial stage of data processing is editing. Editing entails going over the information gathered through questionnaires and schedules to look for errors and omissions, make sure they've been fixed, and make sure the schedules are prepared for tabulation. Once the entire data collection process is complete, a final, in-depth review is conducted. The information must be:

• As precise as possible.
• Consistent with other verified facts.
• Uniformly inputted.
• Be as thorough as you can.
• Suitable for tabulation and set up to make code tabulation easier.

Data coding

Coding is essential for effective analysis since it allows for the consolidation of numerous responses into a small number of classes that each contain the essential data for analysis. Typically, coding choices should be made during the questionnaire's design phase. Because one can easily key punch from the original questionnaires, this enables pre-coding of the questionnaire choices, which is important for computer tabulation. Data and responses are sorted into classes and categories through the process of coding, which also involves assigning numbers or other symbols to each item based on the category it belongs to. In other terms, there are two crucial actions in coding;

• Choosing the appropriate categories to utilize
• Assigning specific solutions to each

Data tabulation

The practice of tabulating is used to summarize and provide raw data in a condensed format for additional analysis. Thus, setting the tables is a crucial step. Tabulation can be done manually, mechanically, or digitally. The scale and nature of the study, alternative costs, time constraints, and accessibility of computers and computer programs all play a significant role in the decision-making process. Hand tabulation works well when there are few questionnaires and they are brief in length.

Table may be divided into:

• Frequency tables
• Response tables
• Contingency tables
• Uni-variate tables
• Bi-variate tables
• Statistical table and
• Time series tables.

Generally a research table has the following parts:

• Stub (row heading)
• Foot note.
• Head note
• Body
• Caption
• Table number
• Title of the table

In general, the following actions are required for table preparation:

• Table title:
  • The table should have a succinct, straightforward, and understandable title that may indicate the foundation for classification.
• Columns and rows:
  • Each table should be built with an appropriate number of columns and rows.
• Stubs and captions:
  • The columns and rows should have straightforward, understandable stubs and captions.
• Rule:
  • Thin or thick rulings should be used to divide columns and rows.
• Arrangement of items:
  • grouping of things; Comparable numbers ought to be placed next to one another.
• Deviations:
  • To make it easy to spot them, place them in the column next to the original data.
• Size of columns:
  • This should follow the specifications.
• Arrangements of items:
  • Items should be arranged in accordance with the issue.
• Special emphasis:
  • Important information can be given extra importance by being written in bold or unusual letters.
• Unit of measurement:
  • Be sure to indicate the unit beneath the lines.
• Approximation:
  • This should also be written below the title,
• Notes at the foot of the table:
  • These may be provided there.
• Total:
  • The grand total and totals for each column should both be on the same line.
• Source:
  • Data must be sourced; this is required. Write primary data for this sentence.

Data Analysis

When data is thoroughly gathered from primary or secondary sources, it frequently has a big quantum when it is applied to the real world. The investigator can start a number of crucial procedures to get the data ready for analysis. The information gathered ought to be sufficient, dependable, and authentic. Without being meticulously edited, methodically sorted and tabulated, scientifically evaluated, perceptively interpreted, and rationally concluded, it cannot serve any significant function. Between gathering data and interpreting it, there is a step of work called data processing. There are numerous phases involved in the analysis and interpretation of data. This section outlines crucial instruments and methods for data analysis.

Data interpretation

The interpretation of results is a crucial component of any investigation. The results, conclusions, interpretations, suggestions, generalizations, and implications of the study are the findings. To interpret something is to reveal its meaning. After carefully analyzing the data that was gathered, the job of making conclusions or deductions and articulating their significance is referred to as data interpretation. As the study process comes to a close, everyone prepares to make conclusions from the studied data. Drawing inferences that result in conclusions about the course of action or problem resolution represents the culmination and fruition of the entire study. In essence, interpretation consists of stating what the results indicate. There are two phases of logical thought used in drawing inferences from data: induction and deduction.

Data presentation

Charts and graphs are used to convey data in diagrams. These make it easier to capture the reader's interest. These aid in the more effective presentation of data. Data can be presented in inventive ways. The categories for the data diagrams are:

• Charts: Diagrammatic data display in the form of charts. To present data, bar charts, rectangles, squares, and circles can be employed. While rectangles, squares, and circles are two-dimensional, bar charts are one-dimensional.
• Graphs: A graph is a way to visually display numerical data. It shows the relationship between two variables using a curve or a straight line. Graphs can be categorized into two groups.
  • Graphs of Time Series: In time series graphs, one of the elements is time, while another or others are the factors related to the investigation.
  • Graphs of Frequency Distribution: Graphs on frequency display the distribution of CEOs by factors like as wealth, age, and so forth.