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Hence, we analyze their content by harnessing their network and bringing their content if it overlaps with other users within r/SuicideWatch (SW). We found, Stop Self Harm (SSH) > Self Harm (SLH) > Bipolar (BPR) > Borderline Personality Disorder (BPD) > Schizophrenia (SCZ) > Depression (DPR) > Addiction (ADD) > Anxiety (ANX) (User overlap between SW and other MH-Reddit is shown by thickness in the connecting line) to be the most active subreddits for suicidal users. After aggregating their content, we performed MedNorm using Lexicons to generate clinically abstracted content for effective assessment.
12. At the end of the Introduction section (line 143, p.5), there is a dataset of 448 redditors described. Then, the first paragraph of the Material and Method section (p.5) describe a dataset from >550K users, with a focus on users in the SuicideWatch subreddit. It is not clear whether the created dataset of 448 suicidal redditors is drawn from the dataset described in the first paragraph of the Materials and Methods section. This should be clarified.
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13. Moreover, it is mentioned at line 144 (p.5) that there is ">98,000 users' content on r/SuicideWatch". Then, line 170 (p.5) indicates "we primarily focused on users in the SuicideWatch subreddit (95K users)". What explains the distinct number of users?
23. Line 48, p.3: The acronym "MH-reddit" should be defined when first used in this sentence. Alternatively, the sentence could simply be reworded "There are three User-Types in mental health subreddits (MH-Reddits)".
12. At the end of the Introduction section (line 143, p.5), there is a dataset of 448 redditors described. Then, the first paragraph of the Material and Method section (p.5) describes a dataset from >550K users, with a focus on users in the SuicideWatch subreddit. It is not clear whether the created dataset of 448 suicidal redditors is drawn from the dataset described in the first paragraph of the Materials and Methods section. This should be clarified.
Response: We have revised the description of redditors for clarity. Please see the Lines 166-175 (in introduction) and 177-179 in Materials and Methods. Also, we have included Figure 3 (taken from our previous work Gaur et al. 2019) for illustration of the process for dataset creation.
Measure availability: We provide information on a variety of measures assessing trauma and PTSD. These measures are intended for use by qualified mental health professionals and researchers. Measures authored by National Center staff are available as direct downloads or by request. Measures developed outside of the National Center can be requested via contact information available on the information page for the specific measure.
Multiclassification of mental illness based on language has, in fact, been demonstrated. Gkotsis et al. (2017) used a deep-learning convolutional neural network to determine which of several subreddits (Borderline personality disorder, Bipolar, Schizophrenia, Anxiety, Depression, Selfharm, SuicideWatch) a particular Reddit post came from, with 71.37% accuracy. Critically, however, the multiclassification was not conducted prospectively.
The data preprocessing and the machine-learning model architecture and evaluation were identical to those components of Study 1. The total vocabulary size for Study 2 was 973,962 words. Class labels were assigned on the basis of the mental health subreddit that the individual had posted on in Study 1.
A content analysis of the depression results indicated that the same two clusters were most predictive of depression when the words were drawn from clinical subreddits as when the words were drawn from nonclinical subreddits. These clusters referred to Sadness and Life Problems. As expected, only a subset of the clusters based on the clinical subreddits emerged in language based on nonclinical subreddits. In a nonclinical context, people generally did not talk about Drugs for treating depression, Health-specific terms, Intensity of symptoms, Fantasization, or feelings of Emptiness. There was, however, some mention of Ugliness & Harm. Thus, when combined with the results from Study 1, the present results suggest that words concerning Sadness and Life Problems might be especially central to depression.
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The data preprocessing and the machine-learning model architecture and evaluation were identical to those aspects of Study 1. The total vocabulary size for Study 3 was 491,144 words. Class labels were assigned on the basis of the mental health subreddit that the individual had posted to in Study 1.
To enable comparisons across the different subreddits, we represented the 100 most predictive words for each disorder in the similarity space derived in Study 1. This analysis used the same methods as in Study 2. As in Study 2, document vectors were not available for a small proportion of words (7/400 words across all disorders, 1.75%), and these words were excluded from the clustering analysis.
It is possible that some users could post to more than one mental health subreddit. Such duplicate posting could either indicate noisy training labels, or alternatively could suggest that the individual really has more than one mental illness. We found that 5.7% of the users in Study 1 posted to more than one of the mental health subreddits. To evaluate the effect of these users, we excluded duplicate users from the data in Study 1 and retrained the model. We found little effect on model performance, F1 = .76 (without duplicate users) versus F1 = .77 (with duplicate users). We therefore retained these duplicate users, since such users appear to demonstrate real comorbidity between multiple disorders.
As upsetting as a diagnosis of schizophrenia can be, ignoring the problem won't make it go away. Beginning treatment as soon as possible with an experienced mental health professional is crucial to your recovery. At the same time, it's important not to buy into the stigma associated with schizophrenia or the myth that you can't get better. A diagnosis of schizophrenia is not a life-sentence of ever-worsening symptoms and recurring hospitalizations. With the right treatment and self-help, many people with schizophrenia are able to regain normal functioning and even become symptom-free.
Schizophrenia requires long-term treatment. Most people with schizophrenia need to continue treatment even when they're feeling better, in order to prevent new episodes and stay symptom-free. Treatment can change over time, though. As your symptoms improve, your doctor may be able to lower the dosage or change your medication.
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As far as I can remember I had to take responsibility as a girl of 18,My mom was co-dependent.I always thought I had to take care of everyone.I am now 59 have a daughter of 28.Felt I let her down so many times,because I cant seem to find my feet,to take care.Have my one sister which was with me since childhood and were both co-dependent.She is now with my ex even though she never even liked him,but grabbed onto him when she saw she might be left alone.We sold our home a d bought this place in a complex,which is on my daughters nameBut my sister lives for free just because my ex says she can.Told him her traumatic story,and says his seen it all.But before he came my daughter and myself were treated badly by her and sons.She gave a false report of us,and my ex believes it.So they live with me,my daughter moved to her boyfriend,which I think was just because of the situation here.The ex hit me now and then,when confronted.He pays everything for her.While we have to work.