Ignite Creation Date:
2024-05-06 @ 2:50 PM
Last Modification Date:
2024-10-26 @ 1:38 PM
Study NCT ID:
NCT04444505
Status:
UNKNOWN
Last Update Posted:
2020-06-24
First Post:
2020-06-19
Brief Title:
Trait Versus State The Differential Impact of Personality Traits Coping Behaviors and Cognitions on Depression and Anxiety
Sponsor:
University of Oslo
Organization:
University of Oslo
Study Overview
Official Title:
Trait Versus State The Differential Impact of Personality Traits Coping Behaviors and Cognitions on Depression and Anxiety
Status:
UNKNOWN
Status Verified Date:
2020-06
Last Known Status:
NOT_YET_RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The present study aims to investigate the differential impact of different types of variables on depression and anxiety In particular the impact of trait-variables ie personality measured with the brief Big Five Inventory BFI-10 are contrasted against state-variables including unhelpful coping behavior measured with CAS-1 and cognitions including positive metacognitions and negative metacognitions both measured with CAS-1
Personality is defined as a set of traits that is relatively consistent over time and situation and is subsequently less susceptible as a target mechanisms for therapy Still researchers have devoted great efforts toward describing personality traits as related to different psychopathological disorders Consequently the present study aims to investigate the differential associations of traits ie personality versus state variables metacognitions and coping behaviors on depression and anxiety
The findings of the present study will provide important insights in finding important associations between trait and state variables in relation to psychopathology providing an important foundation for further directional investigations with temporal data
Hypothesis 1 Neuroticism measured with BFI-10 positive metacognitions negative metacognitions and unhelpful coping strategies the latter three measured with CAS-1 will predict higher levels of depression and anxiety
Research Question 1 How and to what extent are different traits related measured with BFI-10 related to depression and anxiety in the present pandemic sample
Research Question 2 Are the trait or state variables most strongly associated with depressive and anxiety symptoms This question will be investigated using part correlations in the multiple regression analyses
Personality is defined as a set of traits that is relatively consistent over time and situation and is subsequently less susceptible as a target mechanisms for therapy Still researchers have devoted great efforts toward describing personality traits as related to different psychopathological disorders Consequently the present study aims to investigate the differential associations of traits ie personality versus state variables metacognitions and coping behaviors on depression and anxiety
The findings of the present study will provide important insights in finding important associations between trait and state variables in relation to psychopathology providing an important foundation for further directional investigations with temporal data
Hypothesis 1 Neuroticism measured with BFI-10 positive metacognitions negative metacognitions and unhelpful coping strategies the latter three measured with CAS-1 will predict higher levels of depression and anxiety
Research Question 1 How and to what extent are different traits related measured with BFI-10 related to depression and anxiety in the present pandemic sample
Research Question 2 Are the trait or state variables most strongly associated with depressive and anxiety symptoms This question will be investigated using part correlations in the multiple regression analyses
Detailed Description:
Hypothesis 1 Neuroticism measured with BFI-10 positive metacognitions negative metacognitions and unhelpful coping strategies the latter three measured with CAS-1 will predict higher levels of depression and anxiety
Research Question 1 How and to what extent are different traits related measured with BFI-10 related to depression and anxiety in the present pandemic sample
Research Question 2 Are the trait or state variables most strongly associated with depressive and anxiety symptoms This question will be investigated using part correlations in the multiple regression analyses
Statistical analysis
Two hierarchical regression analyses will be conducted 1 with PHQ-9 as the dependent variable and 2 the second with GAD-7 at as the dependent variable Both analyses will include the following variables and the following steps In step 1 the demographic variables age gender and education will be included in the model In step 2 two the trait-variables ie all five personality traits measured with BFI-10 will be included In the final step the three state-variables positive metacognitions negative metacognitions CAS-1 and unhelpful coping strategies CAS-1 will be included
Part correlations will be reported for each regression analysis presenting the effect size of the hypothesized predictors on depression and anxiety A part semi-partial correlation gives the least biased and easiest interpretable estimate of the strength of a predictive relationship Dudgeon 2016 It is the correlation between the outcome and the aspects of the predictor unique from all the other predictors As a type of correlation its size can be evaluated according to Cohens 1988 criteria small 010 medium 030 large 050
Both analysis include the following 5 trait-predictor variables Neuroticism BFI-10 Openness BFI-10 Conscientiousness BFI-10 Extroversion-Introversion BFI-10 and Agreeableness BFI-10
The state-predictor variables are as mentioned positive metacognitions CAS-1 subscale negative metacognitions CAS-1 subscale unhelpful coping behaviors CAS-1 subscale
Multicollinearity and other statistical assumptions will be checked using examined Multicollinearity will be assessed with common guidelines VIF 5 and Tolerance 02 Hocking 2003 OBrian 2007
If any further analyses or questions are addressed in the forthcoming paper that are not pre-specified in this pre-registered protocol they will be explicitly defined as exploratory
Sensitivity analyses and random subsample replications of the main findings will be conducted following selection of a random sample of participants that ensure a proportionate ratio between the collected sample and the adult population of Norway
Sample size and power calculation
The present study is part of a larger project with the first part aiming to investigate information source predictors of mental health through regression analyses and the second part aiming to examine directional relations amongst specific sources of information and their centrality through complex systems approaches ie network analysis Consequently power calculations are based on power required for network analyses Following power analysis guidelines by Fried Cramer 2017 it is recommended that the number of participants are three times larger than the number of estimated parameters However more conservative recommendations by Roscoe 1975 for multivariate research recommends sample size that is ten times larger than the number of estimated parameters Thus following these two approaches respectively between 1305 to 4350 participants are required Data will be collected for three weeks and participants are based on a representative and random sample of Norwegian adults randomly selected and provided equal opportunity to partake in the study providing digital consent
Missing data
The TSD system Services for Sensitive Data a platform used in Norway to store person-sensitive data verifies participants officially through a kind of national ID number to give them full right to withdraw their data at any time following the European GDPR General Data Protection Regulation laws Accordingly participants are allowed to withdraw their own data at any time The survey includes mandatory fields of response Participation is voluntarily and withdrawal of provided data is possible at any moment The investigators do not expect participants to withdraw their data and thus expect no missing data However if participants do withdraw their data the investigators will conduct state-of-art missing data analyses and investigate whether data is missing at random
Research Question 1 How and to what extent are different traits related measured with BFI-10 related to depression and anxiety in the present pandemic sample
Research Question 2 Are the trait or state variables most strongly associated with depressive and anxiety symptoms This question will be investigated using part correlations in the multiple regression analyses
Statistical analysis
Two hierarchical regression analyses will be conducted 1 with PHQ-9 as the dependent variable and 2 the second with GAD-7 at as the dependent variable Both analyses will include the following variables and the following steps In step 1 the demographic variables age gender and education will be included in the model In step 2 two the trait-variables ie all five personality traits measured with BFI-10 will be included In the final step the three state-variables positive metacognitions negative metacognitions CAS-1 and unhelpful coping strategies CAS-1 will be included
Part correlations will be reported for each regression analysis presenting the effect size of the hypothesized predictors on depression and anxiety A part semi-partial correlation gives the least biased and easiest interpretable estimate of the strength of a predictive relationship Dudgeon 2016 It is the correlation between the outcome and the aspects of the predictor unique from all the other predictors As a type of correlation its size can be evaluated according to Cohens 1988 criteria small 010 medium 030 large 050
Both analysis include the following 5 trait-predictor variables Neuroticism BFI-10 Openness BFI-10 Conscientiousness BFI-10 Extroversion-Introversion BFI-10 and Agreeableness BFI-10
The state-predictor variables are as mentioned positive metacognitions CAS-1 subscale negative metacognitions CAS-1 subscale unhelpful coping behaviors CAS-1 subscale
Multicollinearity and other statistical assumptions will be checked using examined Multicollinearity will be assessed with common guidelines VIF 5 and Tolerance 02 Hocking 2003 OBrian 2007
If any further analyses or questions are addressed in the forthcoming paper that are not pre-specified in this pre-registered protocol they will be explicitly defined as exploratory
Sensitivity analyses and random subsample replications of the main findings will be conducted following selection of a random sample of participants that ensure a proportionate ratio between the collected sample and the adult population of Norway
Sample size and power calculation
The present study is part of a larger project with the first part aiming to investigate information source predictors of mental health through regression analyses and the second part aiming to examine directional relations amongst specific sources of information and their centrality through complex systems approaches ie network analysis Consequently power calculations are based on power required for network analyses Following power analysis guidelines by Fried Cramer 2017 it is recommended that the number of participants are three times larger than the number of estimated parameters However more conservative recommendations by Roscoe 1975 for multivariate research recommends sample size that is ten times larger than the number of estimated parameters Thus following these two approaches respectively between 1305 to 4350 participants are required Data will be collected for three weeks and participants are based on a representative and random sample of Norwegian adults randomly selected and provided equal opportunity to partake in the study providing digital consent
Missing data
The TSD system Services for Sensitive Data a platform used in Norway to store person-sensitive data verifies participants officially through a kind of national ID number to give them full right to withdraw their data at any time following the European GDPR General Data Protection Regulation laws Accordingly participants are allowed to withdraw their own data at any time The survey includes mandatory fields of response Participation is voluntarily and withdrawal of provided data is possible at any moment The investigators do not expect participants to withdraw their data and thus expect no missing data However if participants do withdraw their data the investigators will conduct state-of-art missing data analyses and investigate whether data is missing at random
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None