Psychiatric Comorbidity In Galicia by Kaggle | Healthcare

About this Dataset

Psychiatric Comorbidity In Galicia

Psychiatric Comorbidity in Galicia

Examining the Prevalence of Dual Diagnosis in Addiction Assistance Units

About this dataset

This dataset provides incredibly important insight into the prevalence of psychiatric comorbidity, or psychological conditions that occur at the same time, among patients receiving treatment at addiction assistance units in Galicia, Spain. By examining twenty-three-hundred patients across twenty-one treatment centers and harnessing information from sixtyfour healthcare professionals, COPSIAD has created an invaluable resource for exploring how mental disorders impact and interact with substance abuse/dependency. The results demonstrate that overhalf of all people undergoing assistance for addictive behaviors suffer from some type of mental disorder — be it an Axis I or II diagnosis. In particular, mood disorders, anxiety disorders, borderline personality disorder (BPD), and antisocial personality disorder (ASPD) are found to be among the most common comorbid conditions that these individuals face. Accurately understanding this data helps us gain a deeper comprehension into an otherwise surprisingly complex landscape — providing a path forward in finding new treatments and solutions to help these patients lead healthier lives

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How to use the dataset

Start by exploring the descriptive data associated with each column in the dataset. This will help you get a better understanding of the information included and how to interpret it.

Consider which questions you would like to answer with this dataset before beginning your analysis.

Use any appropriate statistical methods to make comparisons or draw conclusions from your data set, such as Chi-square tests for categorical variables or linear regressions for continuous variables.

Visualize any significant findings through charts and graphs, as this can be quite helpful in understanding the implications of your results more clearly and easily sharing them with others without having to go into detail about each statistic generated by your analysis techniques
5a.. Utilize appropriate methods of error handling, such as confidence intervals or p-values, if applicable to explore further nuances within your results and better explain them logically
6b.. Finally, consider other datasets that may be able to provide complementary information that could add further context necessary for making more informed decisions based on your analysis results

Research Ideas

Developing targeted interventions and treatments for patients suffering from comorbid psychiatric disorders in Galician addiction assistance units, based on analysis of the prevalence of individuals with dual diagnoses in this dataset.

Perception analyses to better understand healthcare professionals’ views of comorbidity shifts over time, allowing us to assess whether increased awareness has changed mental health treatment programs or patient response rates within Galicia's addiction assistance units.

Establishing diagnostic information systems that allow us to analyze regional trends in terms of changes in the types and prevalence rates of psychiatric disorder comorbidity amongst addiction and abuse patients within Galicia's assistance units, leading towards improved diagnosis accuracy and treatment effectiveness

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: 2012BASECOPSIAD ingles (2).csv

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

N 2012basecopsiad Ingles 2

@kaggle.thedevastator_psychiatric_comorbidity_in_galicia.n_2012basecopsiad_ingles_2

78.02 KB
2300 rows
81 columns


CREATE TABLE n_2012basecopsiad_ingles_2 (
  "case" BIGINT,
  "age" BIGINT,
  "sex" BIGINT,
  "primdrug" BIGINT,
  "var00001" VARCHAR,
  "drugrecod" BIGINT,
  "drugrecod2" BIGINT,
  "polycons" BIGINT,
  "secdrug" VARCHAR,
  "deldemamn" BIGINT,
  "delirium" BIGINT,
  "dementia" BIGINT,
  "schizpsych" BIGINT,
  "schizophrenia" BIGINT,
  "schizophreniform" BIGINT,
  "schizoaffective" BIGINT,
  "delusional" BIGINT,
  "briepsych" BIGINT,
  "substpsych" BIGINT,
  "psychnotspe" BIGINT,
  "mood" BIGINT,
  "mayordepres" BIGINT,
  "dysthymic" BIGINT,
  "manic" BIGINT,
  "hypomanic" BIGINT,
  "bipolar" BIGINT,
  "cyclothymic" BIGINT,
  "substmood" BIGINT,
  "moodnotspe" BIGINT,
  "anxiety" BIGINT,
  "panic" BIGINT,
  "agoraphobia" BIGINT,
  "specifphobia" BIGINT,
  "socialphobia" BIGINT,
  "obsescompul" BIGINT,
  "postraum" BIGINT,
  "acutestress" BIGINT,
  "genanxiety" BIGINT,
  "medicanxiety" BIGINT,
  "substanxiety" BIGINT,
  "anxietynotspe" BIGINT,
  "somatoform" BIGINT,
  "somatization" BIGINT,
  "undifsomatof" BIGINT,
  "conversion" BIGINT,
  "pain" BIGINT,
  "hypochondriasis" BIGINT,
  "dysmorphic" BIGINT,
  "somatofnotspe" BIGINT,
  "tdisociativo" BIGINT,
  "amnesiadis" BIGINT,
  "fugadis" BIGINT,
  "tidentidaddis" BIGINT,
  "despersonal" BIGINT,
  "eating" BIGINT,
  "anorexia" BIGINT,
  "bulimia" BIGINT,
  "eatingnotspe" BIGINT,
  "impulscontrol" BIGINT,
  "explosive" BIGINT,
  "kleptom" BIGINT,
  "pyroman" BIGINT,
  "pathgambling" BIGINT,
  "trichotill" BIGINT,
  "impulcontrolnotspe" BIGINT,
  "adjustment" BIGINT,
  "comorbaxisone" BIGINT,
  "paranoidpd" BIGINT,
  "schizoidpd" BIGINT,
  "schizotypalpd" BIGINT,
  "histrionicpd" BIGINT,
  "borderlinepd" BIGINT,
  "antisocialpd" BIGINT,
  "narcisspd" BIGINT,
  "obscomppd" BIGINT,
  "avoidantpd" BIGINT,
  "dependentpd" BIGINT,
  "persondisnotspe" BIGINT,
  "comorbaxistwo" VARCHAR,
  "psychdiagnum" VARCHAR,
  "filter" BIGINT
);