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Methodologies

Methodologies

Executing a successful Research, Monitoring, or Evaluation services is tailored to meet the diverse needs of projects, ensuring that every initiative is grounded in rigorous and scientifically robust methods for evaluation and evaluation techniques. At DevInsights, we understand that the choice between qualitative, quantitative, or mixed methods is critical, and our experienced team is adept at innovatively exploring alternative approaches. Our decision-making process is informed by key parameters such as study objectives, target respondents, user needs, geographical considerations, data collector identity, analysis plans, and ethical considerations.

The DevInsights research team is not only hands-on but also well-versed in employing the most fitting techniques and designs to meet project requirements. Some of the methodologies we expertly adopt include:

Methodologies

Randomized Control Trials

A Randomized Control Trial (RCT) is a stringent, experimental study design conducted under controlled conditions. Widely recognized as the ‘gold standard,’ this methods for evaluation involves the random allocation of participants to treatment and control or comparison groups. RCTs are instrumental in establishing cause-effect relationships between planned interventions and outcomes. The key to RCTs is the random selection of populations for both the treatment and control groups.

This design requires meticulous planning before the intervention begins, making it particularly valuable for impact evaluations, especially when dealing with large samples and easily measurable intended impacts. The randomization in an RCT can take the form of an individual-level RCT (IRCT) or a Cluster RCT, depending on whether randomization occurs at the individual or cluster (group) level within the program implementation. RCTs are regarded as a robust methodology for determining the true efficacy of interventions, providing valuable insights into the causal relationships at play.

Quasi Experimental Design

Similar to experimental design, Quasi-Experimental Design (QED) serves to assess causal hypotheses and understand the cause-effect relationship. In these cases, our Quasi Experimental Designs serve as robust evaluation techniques to assess cause-effect relationships without random assignment. Instead, the control or comparison group is chosen to resemble the treatment group as closely as possible before intervention implementation.

By selecting a comparable control group, QED aims to capture the population’s status in the absence of intervention, effectively revealing what would have occurred without the intervention. This design can also be applied retrospectively. Various techniques, such as Regression Discontinuity Design and Propensity Score Matching (PSM), are employed to establish a statistically significant treatment and control sample, mitigating the risk of selection bias.

Propensity Score Matching

These evaluation techniques are pivotal in our quasi-experimental setups. The Difference-in-Differences (DID) method is employed during the analysis phase in quasi-experimental designs to compare changes in outcomes over time between treatment and control groups, aiming to estimate the impact of the treatment. Also referred to as the double difference method, DID determines the impact estimate by contrasting the difference in outcomes between treatment and comparison groups both before the intervention (baseline) and after the intervention (end line).

This method involves identifying the indicators of interest and comparing the difference in the values of these indicators before and after the intervention for the treatment group with the corresponding difference for the comparison group. DID effectively controls for factors that remain constant over time in both groups, providing a robust means of isolating the true impact of the treatment.

Descriptive Research

Descriptive Research

These evaluation techniques are vital for monitoring and evaluation of projects that require an understanding of evolving dynamics or the enduring impacts of interventions.

Cross-Sectional 

A cross-sectional study, a form of descriptive research, is employed to determine the prevalence of a specific outcome within a given population at a particular point in time. This study design involves a one-time measurement of both exposure and outcome variables, making it particularly useful for establishing prevalence rates, making comparisons among groups, or examining the distribution of variables at a specific moment.

The fundamental characteristic of cross-sectional studies is their ability to provide a snapshot of a particular situation, intervention, condition, or group within a population at a specific moment in time. This instantaneous view allows researchers to capture a comprehensive overview of the prevalence and distribution of variables of interest.

Longitudinal Cohort

A longitudinal study, a subtype of descriptive research, involves the repeated measurement of the same sample on the same variable over an extended period. This approach allows for the continuous tracking of individuals or groups, providing a more nuanced understanding of changes and trends over time. Commonly referred to as a panel study, the longitudinal design enables researchers to make more acute observations and discern patterns over time, offering a valuable tool for investigating causal relationships compared to cross-sectional designs.

One distinctive type of longitudinal study is the Longitudinal Cohort, where the study sample forms cohorts that are examined over time on the same variables. Cohorts consist of individuals who share a specific defining characteristic, often tied to a common event such as joining or leaving an institution, or a shared birth period. In essence, a cohort study, falling under the umbrella of descriptive research, systematically analyzes the statistical occurrences within a subgroup that shares a relevant characteristic pertaining to the research question.

EXPLORATORY RESEARCH

Exploratory research serves as a valuable tool to investigate problems or issues where existing knowledge is insufficient. Its primary goal is to build familiarity with basic details, generate new assumptions and ideas, and develop tentative theories or hypotheses in areas lacking a comprehensive understanding. Various methods are employed in exploratory research, including secondary research, focus group discussions, in-depth interviews, and the use of standardized patients. These methods collectively contribute to gathering insights and laying the groundwork for more in-depth studies in the future.

EXPLORATORY RESEARCH

Focus Group Discussions

Focus group discussions serve as a qualitative research method designed to delve into the intricacies and depth of opinions surrounding a particular issue. By bringing together a diverse group of participants, the aim is to facilitate open and dynamic conversations that go beyond simple answers, allowing researchers to uncover a range of perspectives and attitudes.

One of the primary strengths of focus group discussions lies in their ability to explore nuances. Participants are encouraged to express their thoughts, share experiences, and engage in dialogue with one another. This interactive setting enables researchers to probe deeper into the reasons behind certain opinions, gaining insights into the underlying motivations and attitudes that may not be apparent in a quantitative survey or individual interview.

In-depth Interviews

In-depth interviews (IDIs) can be characterized as qualitative key informant conversations, involving loosely structured discussions with clients and individuals possessing knowledge relevant to the explored topic. These interviews provide a valuable avenue for researchers to thoroughly investigate a subject, scrutinize systems and processes, and fine-tune data collection efforts. The semi-structured nature of IDIs allows for a nuanced exploration of the topic while maintaining a level of flexibility for in-depth exploration.

Conducted in a one-on-one format, in-depth interviews enable the researcher to delve deeply into the perspectives and experiences of participants. This method is particularly beneficial when seeking detailed insights, uncovering subtle nuances, and understanding the intricacies of a given subject.

Dyad Interviews

Dyad interviews, involving both spouses, offer a unique lens to examine the interdependent relationships within married couples. This approach recognizes the complexities of roles and dynamics within the family. By simultaneously engaging both partners, researchers gain a more comprehensive understanding of shared experiences, communication patterns, and collaborative decision-making within the marriage. Dyad interviews provide a nuanced exploration of the interplay between individual perspectives and shared realities, offering valuable insights into the intricacies of married life.

PRA/PLA

Participatory Rural Appraisal (PRA) methods are characterized by their collaborative and participatory nature, involving hands-on practical training in monitoring and evaluation techniques for partners and stakeholders. This approach actively engages program implementers in every step of the evaluation process. PRA tools can be categorized into three types: Space-related tools, Time-related tools, and Rationale tools. This inclusive methods of evaluation that empowers stakeholders, fosters a sense of ownership, and enhances the effectiveness of evaluation techniques efforts in rural contexts.

PRA/PLA

Space related

Space-related Participatory Rural Appraisal (PRA) techniques serve as valuable tools for exploring the spatial dimensions of people’s realities. The main goal is to gain insights into how individuals perceive and interact with space within their communities. These methods for evaluation often involve the use of various types of visual maps to facilitate the exploration and representation of spatial information. Visual mapping tools, such as community maps or resource mapping, allow participants to express their knowledge of local spaces, resources, and relationships, providing a visual representation of their perspectives and experiences. This approach enhances the understanding of the community’s spatial dynamics and contributes to more holistic and community-centered development initiatives.

Time-related

Time-related Participatory Rural Appraisal (PRA) methods play a crucial role in examining the temporal dimensions of people’s realities. What sets these methods apart is their ability to allow individuals to express and use their own concepts of time. Unlike more standardized approaches, time-related PRA methods recognize and incorporate the diverse ways in which people perceive and experience time in their communities. This can involve activities like seasonal calendars, historical timelines, or other participatory exercises that help capture the community’s unique temporal dynamics.

By acknowledging and incorporating local perspectives on time, these methods for evaluation contribute to a more nuanced understanding of the temporal aspects of community life and enhance the relevance of development initiatives.

Rationale related

Rationale-related Participatory Rural Appraisal (PRA) techniques serve as valuable tools to delve into the underlying reasons behind specific actions, primarily aimed at establishing cause-effect relationships. These methods are designed to uncover the rationale behind the decisions and behaviors of individuals or communities, providing insights into the motivations and factors influencing their choices. By exploring the reasoning behind actions, these techniques contribute to a deeper understanding of cause-and-effect relationships.

 These methods for evaluation are designed to uncover the rationale behind the decisions and behaviors of individuals or communities, providing insights into the motivations and factors influencing their choices.

STANDARDISED PATIENTS/MYSTERY CLIENTS

A standardized patient is a healthy individual who undergoes training to accurately portray the personal history, physical symptoms, emotional characteristics, and everyday concerns of an authentic patient. Rigorously recruited and trained, a standardized patient effectively mimics a real patient, creating a lifelike encounter for clinicians to learn and be assessed on their acquired skills within a simulated clinical environment. These individuals offer a valuable opportunity for learners at various stages of training to receive constructive feedback from a patient’s perspective, enhancing their clinical competence and interpersonal skills.

By choosing DevInsights, you’re partnering with an evaluation company that not only specializes in advanced monitoring and evaluation techniques but also values the integration of innovative methods for evaluation tailored to your specific needs. Our dedication to employing both traditional and cutting-edge evaluation techniques ensures that every aspect of monitoring and evaluation is handled with precision, delivering insights that are both reliable and actionable. Whether you are looking to evaluate societal impacts, business performance, or project effectiveness, our monitoring and evaluation services are designed to provide the clarity and detail you need to make informed decisions and drive positive change.

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In order to carry out a Research, Monitoring or Evaluation project, choosing the right kind of methodology is paramount. Usually research methodologies are determined by the research objectives. Irrespective of whether the study is qualitative or quantitative or mixed, it is important to choose the method that best suits the study needs. DevInsights experienced team is creative and innovative in exploring alternative methods that can be adopted in a research. The decision to adopt a method is based on some key parameters such as objectives of the study, target respondents, users of research, geography, who collects the data, the analysis plan, ethical issues etc.
The research team at DevInsights is completely hands on and well equipped in utilizing the most appropriate techniques and designs suiting the requirements of the project. Some of the methodologies that we adopt are:

CAUSAL RESEARCH

Causal research is conducted to identify and establish the extent and nature of the cause and effect relationships between variables. Causal research is utilised to determine how the changes to the independent variables influence the dependent variables. It is conducted using different methods that include experimental, quasi-experimental and non-experimental techniques.

a. Randomized Control Trials

Randomised Control Trails (RCT) is a comparative, experimental study design that is performed under controlled conditions whereby the allocation of participants is random to treatment and control or comparison groups. Considered as the ‘gold standard’, it is a rigorous design that helps to determine the existences of cause-effect relationship between the intervention planned and the outcome. The study design requires that the population receiving the treatment is chosen at random and so is the population for the control or comparison group. Essentially an RCT involves planning at the stages before the intervention is initiated and is thus beneficial for impact evaluation wherein the sample is large and the intended impacts could be measured readily. The randomization that is undertaken in an RCT is dependent upon the implementation level of the programme and thus can either be an Individual level RCT (IRCT) or Cluster RCT, wherein the randomization occurs at the cluster level.

b. Quasi Experimental Design

Similar to the experimental design, the Quasi-Experimental Design is used to establish or test the causal hypothesis to identify the extent and nature of the cause-effect relationship. As the name suggests, this design is quasi-experimental and thus remains less robust and rigorous than an experimental design. The QED does not include random allocation of the treatment group. In this design, the control or comparison group is identified in terms of being as similar as possible to the treatment group before the implementation of the intervention. This comparison or control group is utilised to capture the status of population in terms of outcomes in the absence of such intervention. This helps to establish effectively what would have happened in the absence of the intervention. The QED methods could also be used in retrospective manner.
To establish or generate a valid control or comparison group, various techniques can be adopted, including Regression Discontinuity Design, and Propensity Score Matching (PSM). These techniques help to establish a statistically significant treatment and control sample and to reduce the risk of bias of selection of sample.

c. Propensity Score Matching

The method of matching is utilised to construct a comparison group while relying on matching the observed characteristics of the treatment group using statistical techniques. The assumption underneath the method of matching remains that, based on the unobserved characteristics there is no difference in the treatment and control groups.
One of the matching techniques is the Propensity Score Matching (PSM) which attempts to estimate the effect of an intervention or treatment by accounting for the covariates that predict being part of the intervention. Essentially PSM is used to estimate the difference in outcomes between the treatment and control group, so the individuals are matched on their propensity score. This score is calculated, as the likelihood that the individual would receive the treatment, given their observable characteristics. The samples are restricted to the units whereby the region of common support appears in the propensity score distribution. The individuals from treatment group are matched with similar individuals from comparison group and then the average difference between certain chosen indicators (of interest) is calculated.

d. Difference in Difference

Difference-in-differences (DID) is a method utilised at the time of analysis in the quasi-experimental design whereby the changes in the outcomes over time between the treatment and control groups are compared to estimate the impact of the treatment. Also known as the double difference method, DID is used to establish the impact estimate through comparing the difference in outcomes between treatment and comparison groups before the intervention (baseline) and following the intervention (end line). The method involves that the indicators of interest are identified and then the difference in the values of these indicators before and after for the treatment groups are compared with the difference in the values before and after for the comparison group. It controls the factors, which are constant over time in both the groups.

DESCRIPTIVE RESEARCH

Conducted to describe the characteristics of a population or phenomenon, descriptive research is utilised to identify variable and hypothetical constructs.

a. Cross-sectional

One of the types of descriptive research, cross-sectional study is utilised to establish the prevalence of the outcome of interest for a given population within the universe at a given point in time. The essential aspect of cross-sectional studies is that this design is a one-time measurement of exposure and outcome and thus is mostly relevant to establish prevalence or comparisons among groups or distribution of variables at any given point of time. A cross sectional study design provides the snapshot of particular situation/intervention/condition/groups at a given moment of time. Furthermore, cross-sectional study can assess several outcomes and risk factors due to studying populations at a single point of time. It is due to the aspect of being a one-time measurement, that the cross sectional studies cannot be effectively utilised to derive cause-effect relationships.

b. Longitudinal Cohort

Another type of descriptive research, longitudinal study involves measurement of the same sample (which remains fixed) on the same variable repeatedly over a period of time. The essential concept of longitudinal study remains the tracking of the same people along the same variables taking multiple measures, bringing about more acute observations and discerning trends over time. Also known as a panel study, this type of research focusing upon the same sample allows for greater in-depth understanding and thus provides more scope to suggest a causal relationship than a cross-sectional design. The data from longitudinal studies can facilitate in analysing duration of a specific phenomenon due to repeated measurement over time.
A type of longitudinal study is the Longitudinal Cohort that involves the sample in the study to constitute cohorts who are examined over the time on same variables. A cohort can be understood to be a group of people sharing a particular defining characteristic, usually those who experience a common event in a given period, such as joining or leaving some institution, or birth. Thus a cohort study being a descriptive research, charts the statistical occurrence in a given sub group, that share similar or same characteristic that is relevant to the research problem. Longitudinal cohort studies have the advantage to establish a particular sequence of events, following a particular change over time and in identifying the relating events to specific exposures (defined in terms of timing, presence and chronicity).

EXPLORATORY RESEARCH

An exploratory research is utilised to address or investigate into a problem or issue where an inadequate knowledgebase exists to provide insights and understanding. This type of research helps to establish familiarity with basic details, and concerns, for generating new assumptions and ideas and developing a tentative theory or hypothesis. There are various methods used in exploratory research such as secondary research, focus group discussions, in –depth interviews, standardized patients.

a. Focus Group Discussions

The focus group discussions help to explore the nuances and depth of opinions regarding an issue and to understand differences in perspectives.

b. In-depth Interviews

In-depth interviews can be described as qualitative key informant interviews (loosely structured conversation) with the clients as well as people who have knowledge regarding the topic that is being explored. IDIs allow the researcher to explore the subject in depth, examine the systems and processes, and to also refine the data collection efforts. This format is guided through a structure providing space for detailing of necessary components that require enhanced focus from the point of view of the study.

c. Dyad Interviews

Embracing the phenomenon of interdependent relationships between married couples and taking into account their roles and dynamics within the family and as a couple, dyad interviews are generally conducted with married couples to garner information related to the particular aspects of study.

PRA/PLA

PRA methods are participatory or collaborative in nature, in which the evaluation approach provides hands-on practical training in monitoring and evaluation techniques to the partners and stakeholders involved. Here the program implementers are actively involved in all steps of the evaluation process. PRA Tools are of three types – Space-related tools, Time-related tools and Rationale tools

a. Space related

The space-related PRA techniques are useful tools to explore the spatial dimensions of people’s realities. The primary objective is to understand how people perceive and relate to space in their communities. Various types of visual maps are utilized in the application of space-related methods.

b. Time related

Time-related PRA methods assist in exploring the temporal dimensions of people’s realities. The originality of these PRA methods is that they allow people to use their own concept of time.

c. Rationale related

Rationale related PRA techniques are useful tools to explore the rationale behind specific actions and tried mostly to establish cause-effect relationship.

STANDARDISED PATIENTS/MYSTERY CLIENTS

Standardized patient is a healthy person trained to portray the personal history, physical symptoms, emotional characteristics and everyday concerns of an actual patient. A Standardized patient is a person carefully recruited and trained to take on the characteristics of a real patient thereby providing an opportunity for the clinicians to learn and to be evaluated on learned skills in a simulated clinical environment. Such participants provide constructive feedback from the patients’ unique perspective to learners at all levels of training.
  • Needs Assessment / Situational Analysis
  • Concurrent Evaluation / Project Evaluation / Impact Evaluation
  • Project Monitoring & MIS
  • Socio-Economic StudiesM
  • Knowledge Attitude Behavior and Practice (KABP) Studies
  • Formative Research / Communication Research
  • Literature / Systematic Reviews
  • Corporate Social Responsibility (CSR) support services
  • Mystery Client / Standardized Patients
  • PRA / PLA
  • Opinion / Exit polls
  • Data analytics / Visualization

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