What is longitudinal data and why do we need it?
Longitudinal data can provide a real-world picture of patient journeys, treatment pathways and health outcomes. It can help NHS organisations – both locally and nationally – measure variation and see how clinical decisions impact public health.
What are the benefits of longitudinal research?
Benefits of Longitudinal Research A longitudinal study can provide unique insight that might not be possible any other way. This method allows researchers to look at changes over time. Because of this, longitudinal methods are particularly useful when studying development and lifespan issues.
What is a longitudinal study?
A longitudinal study is a type of correlational research study that involves looking at variables over an extended period of time. This research can take place over a period of weeks, months, or even years. In some cases, longitudinal studies can last several decades.
Why do participants drop out of a longitudinal study?
Participants might drop out for a number of reasons, like moving away from the area, illness, or simply losing the motivation to participate. In some cases, this can influence the results of the longitudinal study. If the final group no longer reflects the original representative sample, attrition can threaten the validity of the experiment.
Why are longitudinal studies effective?
The benefit of a longitudinal study is that researchers are able to detect developments or changes in the characteristics of the target population at both the group and the individual level. The key here is that longitudinal studies extend beyond a single moment in time.
What can longitudinal data be used for?
Longitudinal data allow for the measurement of within-sample change over time, enable the measurement of the duration of events, and record the timing of various events.
Are longitudinal studies effective?
What are the pros and cons of a longitudinal study? Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.
What is longitudinal data management?
Longitudinal studies are often designed as systems in which separate batches of data are managed for each type of demographic event, with periodic episodes of merging, matching, and linking of batches to construct relational files of longitudinal event histories for analysis.
What is longitudinal data in healthcare?
The Longitudinal Record is a single comprehensive patient record comprised of data from numerous data sources across the healthcare continuum. It is designed to be one record per patient by using comprehensive patient matching logic wrapped in a consent management model.
What is longitudinal data?
A dataset is longitudinal if it tracks the same type of information on the same subjects at multiple points in time. For example, part of a longitudinal dataset could contain specific students and their standardized test scores in six successive years.
What is longitudinal studies in research?
A longitudinal study is a correlational research method that helps discover the relationship between variables in a specific target population. It is pretty similar to a cross-sectional study, although in its case, the researcher observes the variables for a longer time, sometimes lasting many years.
How do you do longitudinal data analysis?
0:313:35Introduction to analysing longitudinal data - YouTubeYouTubeStart of suggested clipEnd of suggested clipChanges over time longitudinal studies such as panel studies collect the same information from theMoreChanges over time longitudinal studies such as panel studies collect the same information from the same individuals or the same households at multiple time points which allows them to examine.
How is longitudinal data collected?
Longitudinal data is data that is collected sequentially from the same respondents over time. This type of data can be very important in tracking trends and changes over time by asking the same respondents questions in several waves carried out of time.
What is an example of longitudinal research?
For example, a five-year study of children learning to read would be a cohort longitudinal study. Researchers might compare environmental and other factors in the children and measure outcomes over time. Some longitudinal studies are retrospective in nature; these examine data and evidence after the fact.
Why is longitudinal research important?
This method allows researchers to look at changes over time. Because of this, longitudinal methods are particularly useful when studying development and lifespan issues.
What is longitudinal research?
Longitudinal research is often contrasted with cross-sectional research. While longitudinal research involves collecting data over an extended period of time, cross-sectional research involves collecting data at a single point in time.
How long does a longitudinal study last?
This research can take place over a period of weeks, months, or even years. In some cases, longitudinal studies can last several decades.
What are the different types of longitudinal studies?
There are three major types of longitudinal studies: 1 Panel study: Involves sampling a cross-section of individuals. 2 Cohort study: Involves selecting a group based on a specific event such as birth, geographic location, or historical experience. 3 Retrospective study: Involves looking to the past by looking at historical information such as medical records.
How do researchers look at how certain things may change at different points in life?
1. For example, consider longitudinal studies that looked at how identical twins reared together versus those reared apart differ on a variety of variables.
Why are longitudinal studies so expensive?
Longitudinal studies require enormous amounts of time and are often quite expensive. Because of this, these studies often have only a small group of subjects, which makes it difficult to apply the results to a larger population.
Why do people drop out of a longitudinal study?
Participants might drop out for a number of reasons, like moving away from the area, illness, or simply losing the motivation to participate. In some cases, this can influence the results of the longitudinal study.
Steve Bradley, Group Managing Director, Cegedim UK, outlines how data holds the key to better patient care
It’s no secret that the digitisation of healthcare services and smarter use of patient data can have a transformative impact on the NHS.
The value of patient data
The NHS, like most advanced systems, captures huge amounts of data across multiple touchpoints. The most prolific is clinical consultation, with around 6 million GP appointments every week – and almost 120 million outpatient appointments a year – in England alone.
New data, new opportunity
Alongside longitudinal patient data, the emergence of new data streams is helping health stakeholders develop a more granular understanding of patient populations, local variation and unmet needs.
Trust in data
The aggregation and use of patient data is heavily regulated. Patient confidentiality must always be protected, irrespective of the potential opportunities that data sharing creates. Thankfully, governance surrounding the use of patient data is well understood and (largely) well observed. However, all data isn’t equal.
Taking the longitudinal view
As health and care organisations battle to deliver safe, equitable and sustainable care, smart use of data is increasingly being recognised as a fundamental driver of service improvements and enhanced patient outcomes.
What is an overlooked group necessary in developing and implementing an effective treatment plan?
An often overlooked group necessary in developing and implementing an effective treatment plan is family members. In the beginning process of reaching out for help, those who suffer from the disease of addiction are not always equipped to provide the most accurate information about their condition.
What are the factors that determine a treatment plan?
Factors influencing the type of treatment plan, which is best suited for one person over another, includes appropriate screening and assessment of a variety of factors including: 1 Disease severity 2 Age 3 Gender 4 Ethnicity 5 Sexual orientation 6 The presence of co-occurring mental health diagnosis (-es) 7 Drug (s) of choice 8 Trauma 9 Chronic pain 10 Family dynamics
What is missing in substance abuse treatment?
One of the crucial things missing within the substance abuse treatment space is outcomes data documenting the success or failure of a given treatment plan for a given person. Such longitudinal outcomes data would help everyone involved in the care continuum. It certainly would be of immediate benefit to those individuals who need to re-engage treatment after a relapse because providers would be better informed as to what methods were effective or ineffective for an individual. The ideal result of better outcomes data would be a healthcare system where individual treatment plans—measured over time from hundreds and then thousands of individuals and families—are utilized to inform the treatment plans of others from similar background, characteristics, families, drug (s) of choice, etc.
What are the things that complicate treatment planning?
One of the things which complicate treatment planning is the variety of services that need to be brought to bear in promoting healing and growth. Such services may include detox, medication, other medical care, dental care, individual counseling, group counseling, family counseling, peer support, recovery fellowships, sponsorship, ...
When individuals and their families reach out to treatment providers, devising a plan of healing for everyone involved in the process
When individuals and their families reach out to treatment providers, devising a plan of healing for everyone involved in the process is as complicated as the disease itself . Each patient or client deserves a plan of treatment individualized to their specific situation , which addresses their challenges and enhances their specific strengths.
Can repeated relapse lead to death?
Tragically, oftentimes, repeated relapse leads to death. With effective treatment planning and successful implementation of the plan, many people can find wellness and return to being productive family members, employees, and citizens.
Summary
Purpose
- So why would researchers want to conduct studies that take a very long time to complete? One reason is that a longitudinal study can be used to discover relationships between variables that are not related to various background variables. This observational research technique involves studying the same group of individuals over an extended period. So what are some of the reaso…
Analysis
- Data is first collected at the outset of the study, and may then be repeatedly gathered throughout the length of the study. Doing this also allows researchers to observe how variable may change over time.
Example
- For example, imagine that a group of researchers is interested in studying how exercise during middle age might impact cognitive health as people age. The researchers hypothesize that people who are more physically fit in their 40s and 50s will be less likely to experience cognitive declines in their 70s and 80s.
Benefits
- The benefit of this type of research is that it allows researchers to look at changes over time. Because of this, longitudinal methods are particularly useful when studying development and lifespan issues. Researchers can look at how certain things may change at different points in life and explore some of the reasons why these developmental shifts...
Applications
- An example of how this research can be used include longitudinal studies that look at how identical twins reared together versus those reared apart differ on a variety of variables. Researchers track these participants from childhood into adulthood to look at how growing up in a different environment influences things such as personality and achievement.
Advantages
- As with other types of psychology research, longitudinal studies have both their strengths and weaknesses. There are some important advantages to conducting longitudinal research, but there are also a number of drawbacks that need to be considered.
Risks
- Longitudinal studies require enormous amounts of time and are often quite expensive. Because of this, these studies often have only a small group of subjects, which makes it difficult to apply the results to a larger population. Another problem is that participants sometimes drop out of the study, shrinking the sample size and decreasing the amount of data collected.
Causes
- This tendency for some participants to be more likely to drop out of a study is known as selective attrition. In our example above, participants might drop out for a number of reasons. Some might move away from the area while others simply lose the motivation to participate. Others might become housebound due to illness or age-related difficulties, and some participants will pass a…
Criticisms
- In some cases, this can lead to an attrition bias and influence the results of the longitudinal study. If the final group no longer reflects the original representative sample, this attrition can also threaten the validity of the experiment. Validity refers to whether or not a test or experiment accurately measures what it claims to measure. If the final group of participants is not a represe…
Significance
- A longitudinal study can provide a wealth of information on a topic. Such studies can be expensive, costly, and difficult to carry out, but the information obtained from such research can be very valuable.