Diagnosing and maintaining records of mental health can be challenging as the diagnosis is based on clinical interviews where recall bias and affective state can hinder accuracy. Nonetheless, data collection and how we maintain this data are important for research. Additionally, with the emergence of technology and digital platforms, diagnosing and recording mental illness has evolved.

Cross-Sectional Self Report Studies

Cross-sectional studies are widely used in developmental psychology as it looks at data from a population at a specific point in time. Participants are recruited based on a variable of interest (Kesmodel, 2018; Spector, 2019). This means that data from the population is collected but no variables are manipulated. Therefore, cross-sectional studies are observational where characteristics of a community can be described but cannot conclude on any cause and effects. This type of study can be used to establish if exposure to specific risk factors might associate with particular outcomes.

Advantages

• Inexpensive and Quick: Cross-sectional studies provide researchers with a large amount of information quickly. The use of self-reporting, allows researchers to collect data from a large number of participants. Since the data is collected at once, incomplete or missing data from participants is limited.
• Can examine multiple variables: Researchers can look at numerous factors at once. For example in the Kisley study, the authors were able to look at age, gender, income, and other social determinants that may contribute to a child being vulnerable to maltreatment and mental illness.

Disadvantages

• Cohort Differences: Differences may arise in cross-sectional cohorts as people of the same age may have different experiences. This is where social determinants might have the greatest impact
• Report Bias: how a participant recalls their experience may not be accurate and researchers cannot fact check a participants’ memory. For example, the description of a participant’s maltreatment or how many times abuse occurred may not be accurate.

Longitudinal Studies

Similar to cross-sectional studies, longitudinal studies are also correlational and observational research. They look at variables over an extended period of time (Weeks, Months, Years, Decades) for the same group of participants (Frey, 2018). Once data is initially collected, the study methods may be repeated over time to examine how the variables of interest change with time.

Advantages

• Allows for the observation of variables as they change over time. Researchers can look at how variables change at different points in life. For example, phenotypes of mental illness may be displayed differently when participants are juveniles, a teen, or an adult. Additionally, as participant ages, social determinants might change impacting recovery or worsening of mental health outcomes.

Disadvantages

• Longitudinal studies can be expensive and require dedication to slow collection of data
• Longitudinal studies can often have a small sample size as participants may not want to commit to a long timeframe
• Participants may also withdraw from the study influencing the results of the study.

DSM-5

Diagnostic and Statistical Manual of Mental Disorders (DSM) 5th Edition is the current manual in diagnosing Mental disorders. It provides information for clinicians and researchers to understand common health issues with guidelines for diagnoses (Frey, 2018).

Advantages

• Provides codes that summarize mental health disorders
• Standardizes mental health conditions. This can be advantageous and disadvantageous. It is beneficial to research as it eases data organization and statistical analysis.

Disadvantages

• Mental health is complicated with an array of symptoms with varying degrees unique to each individual. Therefore, an absolute diagnosis may not be valid
• This also increases the risk of over-diagnosis and misdiagnosis.