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Differences in Connection Strength between Mental Symptoms Might Be Explained by Differences in Variance: Reanalysis of Network Data Did Not Confirm Staging

View Article: PubMed Central - PubMed

ABSTRACT

Background: The network approach to psychopathology conceives mental disorders as sets of symptoms causally impacting on each other. The strengths of the connections between symptoms are key elements in the description of those symptom networks. Typically, the connections are analysed as linear associations (i.e., correlations or regression coefficients). However, there is insufficient awareness of the fact that differences in variance may account for differences in connection strength. Differences in variance frequently occur when subgroups are based on skewed data. An illustrative example is a study published in PLoS One (2013;8(3):e59559) that aimed to test the hypothesis that the development of psychopathology through “staging” was characterized by increasing connection strength between mental states. Three mental states (negative affect, positive affect, and paranoia) were studied in severity subgroups of a general population sample. The connection strength was found to increase with increasing severity in six of nine models. However, the method used (linear mixed modelling) is not suitable for skewed data.

Methods: We reanalysed the data using inverse Gaussian generalized linear mixed modelling, a method suited for positively skewed data (such as symptoms in the general population).

Results: The distribution of positive affect was normal, but the distributions of negative affect and paranoia were heavily skewed. The variance of the skewed variables increased with increasing severity. Reanalysis of the data did not confirm increasing connection strength, except for one of nine models.

Conclusions: Reanalysis of the data did not provide convincing evidence in support of staging as characterized by increasing connection strength between mental states. Network researchers should be aware that differences in connection strength between symptoms may be caused by differences in variances, in which case they should not be interpreted as differences in impact of one symptom on another symptom.

No MeSH data available.


Boxplots of the distributions of the negative affect score across severity subgroups.The “boxes” indicate the interquartile ranges (IQR). The median observations are indicated by thick lines in the boxes. The “whiskers” extend to the highest (and lowest) observations not further away from the box than 1.5 times the IQR. Outliers are represented by small circles.
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pone.0155205.g004: Boxplots of the distributions of the negative affect score across severity subgroups.The “boxes” indicate the interquartile ranges (IQR). The median observations are indicated by thick lines in the boxes. The “whiskers” extend to the highest (and lowest) observations not further away from the box than 1.5 times the IQR. Outliers are represented by small circles.

Mentions: By shifting the cut-offs on the SCL-score we attempted to create new severity subgroups with (about) equal variances of NA and PAR. However, these attempts failed due to the fact that considerable proportions of measurements were at the floor of the NA and PAR scales, across all severity levels, except the highest SCL-score (Fig 3). Note, however, that the highest SCL-scores in Fig 3 concerned only two women with 24 and 26 measurements respectively. The number of measurements declined rapidly with increasing severity. So, irrespective of the exact locations of the cut-off points, in all groups considerable proportions of measurements remained at the floors of the scales, while as severity increased, increasing (but still relatively small) proportions of measurements reached higher scores, producing increasing variances (Fig 4). This pattern of having the greatest variance in the most severe group and the smallest variance in the least severe group remained the same irrespective of whichever way the cut-off points were shifting.


Differences in Connection Strength between Mental Symptoms Might Be Explained by Differences in Variance: Reanalysis of Network Data Did Not Confirm Staging
Boxplots of the distributions of the negative affect score across severity subgroups.The “boxes” indicate the interquartile ranges (IQR). The median observations are indicated by thick lines in the boxes. The “whiskers” extend to the highest (and lowest) observations not further away from the box than 1.5 times the IQR. Outliers are represented by small circles.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5120783&req=5

pone.0155205.g004: Boxplots of the distributions of the negative affect score across severity subgroups.The “boxes” indicate the interquartile ranges (IQR). The median observations are indicated by thick lines in the boxes. The “whiskers” extend to the highest (and lowest) observations not further away from the box than 1.5 times the IQR. Outliers are represented by small circles.
Mentions: By shifting the cut-offs on the SCL-score we attempted to create new severity subgroups with (about) equal variances of NA and PAR. However, these attempts failed due to the fact that considerable proportions of measurements were at the floor of the NA and PAR scales, across all severity levels, except the highest SCL-score (Fig 3). Note, however, that the highest SCL-scores in Fig 3 concerned only two women with 24 and 26 measurements respectively. The number of measurements declined rapidly with increasing severity. So, irrespective of the exact locations of the cut-off points, in all groups considerable proportions of measurements remained at the floors of the scales, while as severity increased, increasing (but still relatively small) proportions of measurements reached higher scores, producing increasing variances (Fig 4). This pattern of having the greatest variance in the most severe group and the smallest variance in the least severe group remained the same irrespective of whichever way the cut-off points were shifting.

View Article: PubMed Central - PubMed

ABSTRACT

Background: The network approach to psychopathology conceives mental disorders as sets of symptoms causally impacting on each other. The strengths of the connections between symptoms are key elements in the description of those symptom networks. Typically, the connections are analysed as linear associations (i.e., correlations or regression coefficients). However, there is insufficient awareness of the fact that differences in variance may account for differences in connection strength. Differences in variance frequently occur when subgroups are based on skewed data. An illustrative example is a study published in PLoS One (2013;8(3):e59559) that aimed to test the hypothesis that the development of psychopathology through “staging” was characterized by increasing connection strength between mental states. Three mental states (negative affect, positive affect, and paranoia) were studied in severity subgroups of a general population sample. The connection strength was found to increase with increasing severity in six of nine models. However, the method used (linear mixed modelling) is not suitable for skewed data.

Methods: We reanalysed the data using inverse Gaussian generalized linear mixed modelling, a method suited for positively skewed data (such as symptoms in the general population).

Results: The distribution of positive affect was normal, but the distributions of negative affect and paranoia were heavily skewed. The variance of the skewed variables increased with increasing severity. Reanalysis of the data did not confirm increasing connection strength, except for one of nine models.

Conclusions: Reanalysis of the data did not provide convincing evidence in support of staging as characterized by increasing connection strength between mental states. Network researchers should be aware that differences in connection strength between symptoms may be caused by differences in variances, in which case they should not be interpreted as differences in impact of one symptom on another symptom.

No MeSH data available.