Tools and techniques for data collection.pptx

These the tools and techniques used for data collection when carrying out community diagnosis in public health setting.
The slides looked into details the various tools and how they can be used in the data collection depending on the type of data you would like to collect.

1. Tools and techniques for data collection Presenters: Juru Jackline Laya 22/X/0836/GPH/PS Obwoch Lawrence Justin 22/U/0209/GPH/PS

2. Introduction Data collection Data collection is the process of gathering and accumulating facts, or observations for analysis and interpretation. Different methods for gathering information regarding specific variables of the study aiming to employ them in the data analysis phase to achieve the results of the study, gain the answer of the research questions or test the hypotheses. Data collection in community diagnosis involves various tools and techniques to gather information about a community’s health, social, and environmental conditions. Before selecting a data collection method, the type of data that is required for the study should be determined

3. Types of data Qualitative Data Both nominal and descriptive non-numerical data which cannot be shown as numbers are known as qualitative data in words or sentences format. This type of data answers to "how and why" questions in a research study and mostly covers data regarding feelings, perceptions, and emotions using unstructured approaches such as interviews for data collection.

4. Quantitative Data Numerical data which is mathematically generated and computed. There are different scales for measuring quantitative data including nominal, ordinal, interval, and ratio scales.

5. DATA COLLECTION METHODS Generally, data collection methods are divided to two main categories of Primary Data Collection Methods and Secondary Data Collection Methods. Primary data is the data that is not published yet and is the first-hand information which is not changed by any individual. Secondary data is the data gathered from published sources meaning that the data is already gathered by someone else for another reason and can be used for other purposes in a research as well.

6. Primary data collection methods Primary data collection is based on the processes by which you gather data yourself for your purpose of study and no one has access to use this data until it is published and both qualitative and quantitativ approaches are used for this purpose.

7. 1. Questionnaire Method The questionnaire is one of the common devices for collecting information and a form or instrument including a set of questions and secure answers that respondents (from a specific population) fill to give the researcher information needed for the study. The data given from a questionnaire cannot be achieved from the secondary resources. These forms are suitable to gather both qualitative and quantitative data.

8. Types of Questions First, questions can be designed to measure variables for example in a survey. Second, question types can be categorized into closed-ended and open-ended questions. In closed-ended questions, the respondents face a specific range of answers to choose from, but the respondent is asked to provide formulated answers using open-ended questions. Qualitative questions are open-ended. In this type, then, the answers should be coded into a response scale. Therefore, in comparison to the open-ended questions, close-ended ones are pre-coded to make the work quickly be implemented.

9. For closed-ended questions, there are four types of options to respond the questions: You can have a two-option as the responses possibilities which are known as dichotomous scales. If you add more than two options for the respondents, the scale is known as nominal polychromous. In ordinal-polytomous scales, you prepare more than two options which are also ordinal. Finally, you can use continuous or bounded types which use a continuous scale as a possible response case.

10. The mode of administration Questionnaires can be implemented in different ways. A face-to-face questionnaire mode can be used which provides the chance of presenting the questions orally, paper-and-pencil types can be utilized with the items presented in the paper or computerized questionnaires for data collection. Questionnaires can be also utilized through telephone, online, or even posting. An online questionnaire is a cost-efficient option; however, you should consider the possibility of missing samples due to problems with internet access.

11. General rules for constructing a questionnaire Use simple and short questions as much as possible; Navigate respondents clearly to avoid any difficulty and motivate participants through answering questions. Use understandable, simple, and clear statements for all respondents with different educational levels. Utilize positive sentences Do not use more than one question (double-barreled) in one item. Add an open-answer possibility after providing the listed answers and where possible. Avoid making assumptions for the respondents. Try to increase reliability by appropriate word selection. Avoid directing the respondent to any answer using objective questions including clues, suggestions. Explain the importance of the questionnaire in its content as well as its cover letter

12. Advantages of Questionnaires Questionnaires provide several merits in comparison to other survey methods as listed in the following: Collecting a large amount of data from a large sample size. Time saver. Cost-effective options. Highly structured. The possibility of gaining high accurate data. Analyzing the results easily by entering the achieved data to the software quickly in the majority of cases;

13. Disadvantages of Questionnaires Hard or inadequate to perceive gathered data in some cases such as emotional, feelings, and behavioral changes, Human errors for example if the respondent is forgetful and cannot consider the whole concept truly. Determining the reliability of answers is not possible. The possibility of misunderstanding the questions which can overshadow the answers. Low response rates if respondents’ low interests cannot be addressed to answer questions. The possibility of illegible answers. Useless and wrong answers are prevalent.

14. 2. Interviews In interviews, as a fundamental way of social interaction, questions are asked and data is collected using provided answers and it is in contrast to the questionnaire with indirectly collected data methodology. Researchers can employ different methods to conduct an interview and perform them in individual, or group face-to-face interviews, as well as not personally for example using telephone, computer, etc.

15. ADVANTAGES AND DISADVANTAGES OF DIFFERENT INTERVIEW TYPES Types Advantages Disadvantages Face-to-face Interviews -Asking detailed questions. -Obtaining rich data. -Literacy requirements are not an issue. -Possibility of clarifying questions. -High response rate. -Exploring complex and sensitive issues. -Expensive. -Effects of interviewers’ biases. -Possibility of facing some challenges for sensitive issues. -Training interviewers is necessary. Telephone Interviews -Cheap and accurate data. -Quick. -Possibility of clarifying questions. -Literacy requirements are not an issue. -Using fewer resources than face-to face -Possibility of not accessing to the participants easily and the first time. -Only possible for interviewees who access telephone. -Not possible to discover sensitive issues.

16. Types of Interviews Interview types can be structured, semi-structured, and unstructured. Structured interviews: In these kinds of interviews, interviewees face the same set of standardized questions which are pre-prepared before the interview session. The possible responses are limited, and participants may just face a few open-ended questions.

17. Semi-structured Interviews Semi-structured interviews are formal and are conducted based on a guide. The interviewers ask questions considering the guidance; however, when researchers or interviewers need extra information, they can continue the conversation based on the questions provided ahead of time. Unstructured interviews Unstructured interviews are informal methods of interviewing without using a specific structure. There is no guide in this type, and they just conduct casual conversations. Interviewers collect data using brief notes and try to memorize the responses.

18. The process of executing an interview Address entry requirements such as suitable appearance Introduce yourself and the organization for maximum 20-30 sec Explain the concept of study Ask the provided questions by the order given Reach enough responses and record them Conclude the interview and thank the participants

19. Advantages Gathering rich, in-depth, and detailed data directly. The opportunity of obtaining knowledge about past and future for particular events and features. The flexibility of administration of interviews. The possibility of an explanation of the questions to the interviewees to clarify the questions

20. Disadvantages On the other hand, there are some difficulties that may be faced when conducting an interview method including: Hiring and training interviewers. Complex process. Scheduling where and when to meet people and the possibility of changing plans at the last minutes. The possibility of missing information. The coding process can be difficult and long. Being expensive.

21. 3. Focus Groups Discussion (FGD) This method, simply, is a mixture of interviewing and observation. This method is used to discover human behavior, attitudes, and respondents facing a particular concept. This in-depth field method gathers a group of individuals, normally between 6-12 people in each group, commonly with a shared characteristic such as sex, age, and educational status to discuss a specific study field. For this purpose, data regarding a particular subject is collected using a semi-structured interview.

22. After identifying the suitable target group considering shared required characteristics, a short explanation about the concept should be provided to help the participants get familiar with the background and the meaning of the concept. Then, the standardized questions should be discussed based on the protocol and the responses of the group to issues should be written. Discussions about the concept should be also facilitated to gain more than just normal question-answer interactions. To obtain a comprehensive investigation, more than one focus group (minimum three) should be managed. After summarizing the results of the discussions, the meeting can be finalized, although sometimes more than one session is needed.

23. General steps of conducting an FGD Selecting the topic and planning the entire FGD Selecting the participants & choosing a suitable mediator Considering physical arrangements such as the qualities of meeting place Conducting the meeting Encouraging the participants and the discussion Controlling time without being obtrusive Collecting and summarizing the findings, appreciating the participants at the end of the session Analyzing the results

24. Advantages They can help to discover social, health, and cultural concepts for example by considering humans' behavior facing different situations. Literacy of individuals is not an issue. They are suitable to explore complex subjects. They are useful for the development of hypotheses.

25. Disadvantages On the contrary, they are also: Can be expensive and time-consuming. Face privacy lacks. Need trained facilitators. Can face the issues due to the domination of limited individuals in the focus groups.

26. 4. Observational Methods In these techniques, first-hand data is gathered through the observation of events, behaviors, interactions, processes, etc. directly to obtain an understanding of the concepts. Observation helps the researcher to find out what is going on in the community. However, as a data collection method, it is further than just listening and looking. This method includes an engagement with the community, a clear expression of the events, technical inventions, high attention, and good recording.

27. This method can collect both qualitative and quantitative data. The qualitative data is gathered as a description of events in the setting. The quantitative data can be obtained by using the duration or frequency of the particular subjects.

28. Advantages The advantages are as the following: Gathering direct information. The participation of evaluators in the natural setting. Free from biases. Can be generalized as large samples can be covered in the studies. High reliable and precise data can be achieved.

29. Disadvantages These techniques also provide some difficulties as: They can be time-consuming and not economical. The training of observers is cost effective. Observers can be selective and distort data. It can be sometimes unreliable due to the misrepresenting of the qualitative data measurement.

30. 5. Community mapping Community mapping is a valuable tool in community diagnosis, allowing for the visual representation of various community attributes and resources. Here are some advantages and disadvantages of using community mapping:

31. Advantages Visual Representation: Community maps provide a visual representation of the community's assets, resources, and challenges, making it easier for community members to understand and engage in the diagnosis process. Comprehensive Understanding: Mapping helps capture a wide range of information, including healthcare facilities, environmental factors, social services, and community assets, enabling a holistic view of the community. Community Engagement: Involving community members in the mapping process promotes their active participation and empowers them to identify their own needs and solutions. Data Integration: Mapping allows the integration of both quantitative and qualitative data, providing a more complete picture of the community's health and social dynamics. Decision-Making:

32. Disadvantages Resource-Intensive: Creating detailed and accurate community maps can be resource-intensive, requiring time, expertise, and access to mapping tools or software. Data Accuracy: The accuracy of the map depends on the quality of the data collected. Errors or outdated information can lead to incorrect conclusions. Technological Barriers: In communities with limited access to technology, creating digital maps may be challenging, and traditional paper maps might be more appropriate.

33. Subjectivity: The process of mapping can be influenced by the perspectives and biases of those involved, potentially leading to incomplete or skewed representations. Data Privacy: Mapping community data may raise privacy concerns, especially when collecting data about individuals or sensitive topics. Limited Use for Certain Data: Community mapping may not be suitable for collecting certain types of data, such as quantitative health statistics or medical records.

34. How to conduct a community mapping Define Objectives: Clearly define the objectives of the community mapping exercise. What specific information or insights are you seeking to gain through the mapping process? Assemble a Team: Form a team of community members, experts, or volunteers to assist with the mapping process. Ensure that team members are familiar with the community and its dynamics.

35. Identify Data Sources: Determine the sources of data you'll use for the mapping, which may include surveys, interviews, field observations, existing documents, or local knowledge. Select Mapping Tools: Choose the appropriate mapping tools, whether digital (GIS software, online mapping platforms) or traditional (paper maps, markers).

36. Data Collection: Collect data on various aspects of the community, such as healthcare facilities, schools, transportation, housing, environmental factors, social services, and community assets. Use surveys, interviews, and observations as needed. Data Validation: Verify the accuracy and reliability of the collected data to ensure that the mapping reflects the true state of the community. Cross-check information with multiple sources, when possible

37. Mapping Process: Create maps that represent the collected data. Include key community features, locations, and labels. Depending on your resources, you can create digital or physical Community Engagement: Involve community members throughout the mapping process. Seek their input, feedback, and insights to ensure that the map accurately reflects their experiences and needs.

38. Data Analysis: Analyze the mapped data to identify patterns, trends, and areas of concern within the community. Look for opportunities and challenges. Feedback and Review: Share the mapped data with the community, stakeholders, and experts for feedback and validation. Make necessary adjustments based on their input.

39. Interpretation and Action: Interpret the mapped data in the context of community health and social issues. Identify potential interventions, resource allocations, and areas for improvement Communication: Communicate the findings and recommendations from the mapping exercise to the community and relevant authorities, fostering a collaborative approach to addressing community needs.

40. Long-Term Use: Continue to update and use the community maps as a resource for ongoing community development and health planning. Regularly review and revise the maps to reflect changes in the community. Community mapping is an ongoing and participatory process that empowers the community to take ownership of their health and well-being. It can be a valuable tool for community diagnosis and action planning.

41. Other primary data collection methods Health Assessments: Physical health assessments, such as measuring vital signs or conducting screenings, can help identify prevalent health conditions. Geographic Information Systems (GIS): GIS technology can be used to map health data, helping to identify areas with specific health concerns. Community Health Surveys: These comprehensive surveys collect data on various health determinants, including demographics, socioeconomic factors, and health behaviors.

42. Community Walks or Tours: Physically exploring the community can help identify environmental factors affecting health, such as pollution or safety issues. Key Informant Interviews: Interviews with individuals who have specific knowledge or expertise on community health issues can provide valuable information. Participatory Appraisal Techniques: These involve engaging the community in data collection, analysis, and decision-making, promoting community ownership of the process. Social Media and Online Surveys: Utilizing digital platforms for data collection can be effective, especially in communities with high internet access.

43. Secondary Data Sources Existing data from government agencies, health records, and community organizations can be valuable for community diagnosis

44. Government Health Agencies: Obtain health-related data from government agencies, such as the Department of Health, which may provide information on disease prevalence, vaccination rates, and healthcare facilities. Census Data: Census data, available from national statistics agencies, provides demographic information, socioeconomic indicators, and population trends that are essential for understanding a community's composition Health Records: Access medical and healthcare records from local clinics and hospitals to gather data on diseases, patient demographics, and treatment outcomes

45. Educational Institutions: Schools and universities may have data on educational attainment, school enrollment, and academic performance, which can offer insights into the community's educational status. Nonprofit Organizations: Many nonprofit organizations and research institutions conduct studies and collect data on various health and social issues. These reports and datasets can be valuable secondary sources Community Surveys: Past surveys and studies conducted within the community or by organizations may contain relevant data on health behaviors, community needs, and social determinants of health.

46. Environmental Agencies: Data from environmental agencies can provide information about air and water quality, pollution levels, and environmental hazards in the community. Social Services Agencies: Social service agencies often maintain data related to social support, welfare programs, and access to services that can impact community well-being

47. How to Obtain and Use Secondary Data: Identify Relevant Sources: Identify the most relevant secondary data sources based on the specific aspects of community health and social conditions you are investigating. Access Data: Contact the respective organizations or agencies to request access to the data you need. Some data may be available for free, while others may require permissions, subscriptions, or fees. Review Data Quality: Examine the quality and reliability of the data to ensure it's suitable for your analysis. Assess factors like data completeness, accuracy, and timeliness.

48. Data Analysis: Analyze the secondary data to identify trends, patterns, and correlations. Use statistical and analytical methods to draw insights and conclusions. Combine with Primary Data: Integrate secondary data with primary data collected through community surveys, interviews, or observations to provide a more comprehensive understanding of the community's health and social dynamics. Interpretation: Interpret the data in the context of community diagnosis, focusing on the community's strengths, weaknesses, needs, and potential interventions.

49. Visualization: Create visual representations, such as graphs, charts, and maps, to effectively communicate the findings to stakeholders and the community. Action Planning: Use the insights from secondary data to inform community action planning, resource allocation, and the development of interventions to address identified issues.

50. Advantages of Using Secondary Data: Cost-Efficiency: Secondary data is often readily available and can be obtained at a lower cost compared to collecting primary data, which requires resources for surveys, interviews, and data collection. Time-Saving: Secondary data can be quickly accessed and analyzed, which can expedite the community diagnosis process, especially when time is a critical factor.

51. Historical Trends: Secondary data can provide historical context and trends, allowing for long-term analysis of health and social issues within the community. Large-Scale Data: Government agencies and organizations often collect data on a large scale, providing a comprehensive view of community conditions and trends. Wide Range of Variables: Secondary data sources can offer a broad range of variables and indicators, allowing for comprehensive community assessment

52. Disadvantages: Data Quality: The quality of secondary data can vary, and it may not always be reliable or up-to-date. It's essential to assess the source's credibility and the methods used in data collection and Limited Control: Researchers have limited control over the data collection process, making it challenging to tailor data to specific research questions or objectives. Lack of Specific Information: Secondary data may not always include the specific information needed for a particular community diagnosis, potentially leading to gaps in the analysis.

53. Data Bias: Secondary data sources may have inherent biases, and the data may not precisely reflect the unique characteristics of the community being studied. Privacy and Ethics: Accessing and using secondary data can raise ethical concerns, especially if the data contains personally identifiable information. Researchers must adhere to data protection regulations and ensure privacy.