The document discusses various tools and techniques for data collection in community diagnosis, covering primary and secondary data collection methods. It details different approaches, such as questionnaires, interviews, focus groups, observational methods, and community mapping, along with their advantages and disadvantages. Additionally, it outlines steps for conducting these methods effectively and emphasizes the importance of engaging community members in the data collection process.

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.