Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Ordinal Logistic Regression to Determine Predictors of Stigma Against People with Substance Use Disorders

Kash, Madeline M (2023) Ordinal Logistic Regression to Determine Predictors of Stigma Against People with Substance Use Disorders. Master's Thesis, University of Pittsburgh. (Unpublished)

Download (799kB) | Preview


The opioid epidemic is an ongoing public health crisis in the United States. While there is continued effort to stop the epidemic through measures such as increasing access to naloxone, a medication designed to rapidly reverse opioid overdoses, and implementing treatment referral protocols, there is concern that stigma against people with Substance Use Disorders (SUD), particularly in people on the front lines of the epidemic, is an obstacle to progress. Previous studies show that first responders do have stigma against people with SUD which influences their perceptions of naloxone and substance use treatments and their interaction with people with SUD. This thesis analyzes responses from Pennsylvania’s First Responder Addiction and Connection to Treatment (FR-ACT) program pre-training survey to determine statistically significant predictors for stigma against people with SUD. Specifically, this study looked at three Likert-type questions that were designed to gauge stigma against people with SUD by asking about related topics: connection to treatment, continued drug use, and naloxone use. This is significant to public health because increased understanding of stigma related to SUD can be used to tailor training programs for first responders, and others on the front lines of the epidemic, to reduce stigma and improve the effectiveness of the response to the opioid epidemic. To determine statistically significant predictors for stigma, ordinal logistic regression models were fit for each question. Ordinal logistic regression allowed the natural ordering of the outcome variable, which indicated stigma, to be maintained. The final models were compared to determine if there were consistent predictors for stigma. The results showed that gender was the only consistent predictor for stigma, with males having more stigma than non-males. Other statistically significant predictors varied depending on the topic being addressed, including organization, experience level, education level, number of overdoses responded to, and region. This suggests that training sessions aimed to reduce stigma and improve responses to opioid overdoses should adjust tactics based on the audience and stigma related topic they intend to cover. The results also suggest that addressing job related burnout and compassion fatigue may help reduce stigma.


Social Networking:
Share |


Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Kash, Madeline Mmmk86@pitt.edummk86
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairBuchanich, Jeaninejeanine@pitt.edujeanine
Committee CoChairYouk, Adaayouk@pitt.eduayouk
Committee MemberDauria, Emilyefd16@pitt.eduefd16
Date: 11 May 2023
Date Type: Publication
Defense Date: 24 April 2023
Approval Date: 11 May 2023
Submission Date: 25 April 2023
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 89
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Biostatistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Opioid, stigma, substance use disorders, ordinal logistic regression
Date Deposited: 11 May 2023 15:46
Last Modified: 11 May 2023 15:46


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item