Study Design & Data Collection
This study used data from the BC Centre for Disease Control’s (BCCDC) GSDOA Survey, administered from October 2020 to April 2021 (See Additional File 1). A cross-sectional survey was designed collaboratively by a team of researchers, regional health authority representatives, harm reduction coordinators, people with lived and living experience (PWLLE) of substance use, youth organizations and youth representatives. Research team members at Foundry, a provincial network of health and social services for youth, provided input throughout the study and members of the Youth4Youth advisory group provided input as youth representatives. Findings were also presented to the Métis Nation of BC as well as peer groups which include the Professionals for Ethical Engagement of Peers (PEEP) and Peer2Peer Project (P2P), and their feedback was incorporated into our analysis and interpretation of findings.
Using input from regional harm reduction coordinators, 19 THN sites with sufficient capacity (staff and physical space accounting for COVID-19 guidelines i.e. physical distancing) from across the province were invited and agreed to participate. In-person survey participants (n = 416) were provided $10 CAD and an additional $5 CAD was provided to the participating THN site for each participant enrolled. An online version of the survey was available through Qualtrics [37]. This was offered as an option to respond by THN sites and was advertised by Foundry to recruit youth participants, who were defined as 16-24 years old [38]. Persons completing the survey online (n = 77) were offered participation in a raffle for a 1 in 10 chance of obtaining a $50 VISA gift card. Eligibility criteria at THN sites were age (18 years and over) and being at risk of witnessing an overdose. This included PWLLE, peer responders and family or friends of people who use drugs as these individuals have a higher likelihood of witnessing an overdose [39-41]. Institutional ethics approval was obtained through the University of British Columbia’s Behavioural Research Ethics Board (# H19-01842).
Study Variables
Outcome Variable
The primary outcome variable for this study was “Intention to call 9-1-1 at an overdose event”. After being provided with a definition of the GSDOA (Figure 1), participants were asked “Based on this description, if you were to witness someone overdose in the future, would you call 9-1-1?” to which they could answer one of “yes”, “no” or “prefer not to say”. Included in the question was the note “Disclaimer: We cannot guarantee that police and emergency health responders will be knowledgeable about the GSDOA and will follow the Act.”
Explanatory Variables
Explanatory variables of interest included participants’ sociodemographic and substance use characteristics as well as variables that reflected participants’ GSDOA knowledge and awareness. Sociodemographic characteristics included age group (16-24, 25-34, 35-54, ≥55 years), gender (cisgender men, cisgender women, transgender and gender expansive [trans-men, trans-women, gender non-binary], prefer not to say), Indigenous identity (non-Indigenous, Indigenous [First Nations, Métis, Inuit], prefer not to say), geographic health region as defined by the five health authorities within the province (Fraser Health, Interior Health, Island Health, Northern Health, Vancouver Coastal Health), employment status (yes, no, prefer not to say), housing status (private alone, private with other(s), supportive or unstable housing [hotel, motel, rooming house, single room occupancy, shelter], homeless, prefer not to say) and cellphone possession (yes, no, prefer not to say). Due to a small number of participants reporting gender identity as “trans and gender expansive”, we excluded this group and used a binary gender identity variable of “cis man” and “cis woman” for statistical analyses, though they were retained for descriptive analysis (Table 1).
Table 1
Demographics of the GSDOA Survey (2020 – 2021) by the BC health regions (N = 493).
Demographic Characteristics
|
Fraser Health
n (row %)
|
Interior Health
n (row %)
|
Island Health
n (row %)
|
Northern Health
n (row %)
|
Vancouver Coastal Health
n (row %)
|
Total
N (column %)
|
Participants
|
104 (21.1)
|
128 (26.0)
|
100 (20.3)
|
46 (9.3)
|
115 (23.3)
|
493 (100)
|
Age (years)
|
|
|
|
|
|
|
16 – 24 years
|
16 (14.2)
|
14 (12.4)
|
17 (15.0)
|
9 (8.0)
|
57 (50.4)
|
113 (22.9)
|
25 – 34 years
|
22 (23.7)
|
25 (26.9)
|
24 (25.8)
|
9 (9.7)
|
13 (14.0)
|
93 (18.9)
|
35 – 44 years
|
25 (23.4)
|
36 (33.6)
|
23 (21.5)
|
10 (9.3)
|
13 (12.1)
|
107 (21.7)
|
45 – 54 years
|
17 (17.3)
|
30 (30.6)
|
24 (24.5)
|
12 (12.2)
|
15 (15.3)
|
98 (19.9)
|
55 years and over
|
20 (28.2)
|
20 (28.2)
|
11 (15.5)
|
5 (7.0)
|
15 (21.1)
|
71 (14.4)
|
Unknown
|
4 (36.4)
|
3 (27.3)
|
1 (9.1)
|
1 (9.1)
|
2 (18.2)
|
11 (2.2)
|
Gender identity
|
|
|
|
|
|
|
Cis man
|
62 (22.0)
|
79 (28.0)
|
61 (21.6)
|
21 (7.4)
|
59 (20.9)
|
282 (57.2)
|
Cis woman
|
37 (20.1)
|
46 (25.0)
|
35 (19.0)
|
24 (13.0)
|
42 (22.8)
|
184 (37.3)
|
Trans and gender expansive a
|
4 (17.4)
|
3 (13.0)
|
3 (13.0)
|
1 (4.3)
|
12 (52.2)
|
23 (4.7)
|
Unknown
|
1 (25.0)
|
0 (0.0)
|
1 (25.0)
|
0 (0.0)
|
2 (50.0)
|
4 (0.8)
|
Indigenous identityb
|
|
|
|
|
|
|
First Nations
|
25 (18.8)
|
30 (22.6)
|
19 (14.3)
|
20 (15.0)
|
39 (29.3)
|
133 (27.0)
|
Métis
|
12 (19.4)
|
21 (33.9)
|
11 (17.7)
|
13 (21.0)
|
5 (8.1)
|
62 (12.6)
|
Inuit
|
2 (66.7)
|
0 (0.0)
|
1 (33.3)
|
0 (0.0)
|
0 (0.0)
|
3 (0.6)
|
Non-indigenous
|
54 (21.4)
|
60 (23.8)
|
63 (25.0)
|
10 (4.0)
|
65 (25.8)
|
252 (51.1)
|
Unknown
|
11 (25.6)
|
17 (39.5)
|
6 (14.0)
|
3 (7.0)
|
6 (14.0)
|
43 (8.7)
|
Health regions in increasing order of population are: Northern Health, Interior Health, Island Health, Vancouver Coastal Health, Fraser Health.
a “Trans and gender expansive” identities include trans man, trans woman and gender non-conforming people.
b The authors recognize that Indigenous identity is often a proxy for factors associated with colonialism including intergenerational trauma, systemic racism, criminalization and discrimination.
|
Indigenous identity is understood to act as a proxy for factors associated with colonialism including intergenerational trauma, systemic racism, criminalization and discrimination [42-45]. Descriptive analyses of First Nations, Métis, Inuit, and non-Indigenous identity were included in recognition of the heterogeneity of Indigenous peoples and their experiences (Table 1). However, Indigenous identity was dichotomized to maintain sample size in statistical analysis and regression models (Table 2 and 3).
Table 2
Factors associated with intention to call 9-1-1 at a future overdose among survey respondents.
|
Intention to call 9-1-1 at overdose events
|
|
|
Yes
(N = 404)
n (row %)
|
No
(N = 47)
n (row %)
|
Total
(N = 451)
n (column %)
|
P-value a
|
Age (years)
|
|
|
|
0.126
|
16 – 24 years
|
101 (94.4)
|
6 (5.6)
|
107 (23.7)
|
|
25 – 34 years
|
70 (85.4)
|
12 (14.6)
|
82 (18.2)
|
|
35 – 44 years
|
86 (87.8)
|
12 (12.2)
|
98 (21.7)
|
|
45 – 54 years
|
87 (94.6)
|
5 (5.4)
|
92 (20.4)
|
|
55 years and over
|
57 (89.1)
|
7 (10.9)
|
64 (14.2)
|
|
Unknown
|
3 (37.5)
|
5 (62.5)
|
8 (1.8)
|
|
Gender identity b
|
|
|
|
0.091
|
Cis man
|
225 (87.5)
|
32 (12.5)
|
257 (57.0)
|
|
Cis woman
|
159 (93.0)
|
12 (7.0)
|
171 (37.9)
|
|
Trans and gender expansive
|
20 (90.9)
|
2 (9.1)
|
22 (4.9)
|
|
Unknown
|
0 (0.0)
|
1 (100.0)
|
1 (0.2)
|
|
Indigenous identityc
|
|
|
|
0.164
|
Indigenous
|
150 (87.2)
|
22 (12.8)
|
172 (38.1)
|
|
Non-Indigenous
|
216 (91.9)
|
19 (8.1)
|
235 (52.1)
|
|
Unknown
|
38 (86.4)
|
6 (13.6)
|
44 (9.8)
|
|
Health region
|
|
|
|
0.683
|
Fraser
|
86 (89.6)
|
10 (10.4)
|
96 (21.3)
|
|
Interior
|
106 (89.1)
|
13 (10.9)
|
119 (26.4)
|
|
Island
|
81 (86.2)
|
13 (13.8)
|
94 (20.8)
|
|
Northern
|
36 (92.3)
|
3 (7.7)
|
39 (8.6)
|
|
Vancouver Coastal
|
95 (92.2)
|
8 (7.8)
|
103 (22.8)
|
|
Housing status
|
|
|
|
<0.01
|
Private/Alone
|
40 (71.4)
|
16 (28.6)
|
56 (12.4)
|
|
Private/With Other(s)
|
107 (93.0)
|
8 (7.0)
|
115 (25.5)
|
|
Supportive/Unstable Housing
|
193 (92.8)
|
15 (7.2)
|
208 (46.1)
|
|
Homeless
|
53 (89.8)
|
6 (10.2)
|
59 (13.1)
|
|
Unknown
|
11 (84.6)
|
2 (15.4)
|
13 (2.9)
|
|
Employment
|
|
|
|
0.029
|
Yes
|
126 (85.1)
|
22 (14.9)
|
148 (32.8)
|
|
No
|
264 (92.0)
|
23 (8.0)
|
287 (63.6)
|
|
Unknown
|
14 (87.5)
|
2 (12.5)
|
16 (3.5)
|
|
Cellphone possession
|
|
|
|
0.027
|
Yes
|
269 (91.8)
|
24 (8.2)
|
293 (65.0)
|
|
No
|
118 (84.3)
|
22 (15.7)
|
140 (31.0)
|
|
Unknown
|
17 (94.4)
|
1 (5.6)
|
18 (4.0)
|
|
Previous GSDOA awareness
|
|
|
|
0.019
|
Yes
|
205 (92.8)
|
16 (7.2)
|
221 (49.0)
|
|
No
|
173 (85.2)
|
30 (14.8)
|
203 (45.0)
|
|
Unknown
|
26 (96.3)
|
1 (3.7)
|
27 (6.0)
|
|
Complete knowledge of whom the GSDOA protects d
|
|
|
|
0.116
|
Yes
|
106 (95.5)
|
5 (4.5)
|
111 (24.6)
|
|
No
|
99 (90.0)
|
11 (10.0)
|
110 (24.4)
|
|
Unaware
|
173 (85.2)
|
30 (14.8)
|
203 (45.0)
|
|
Unknown
|
26 (96.3)
|
1 (3.7)
|
27 (6.0)
|
|
Complete knowledge of when the GSDOA protects e
|
|
|
|
0.646
|
Yes
|
71 (94.7)
|
4 (5.3)
|
75 (16.6)
|
|
No
|
134 (91.8)
|
12 (8.2)
|
146 (32.4)
|
|
Unaware
|
173 (85.2)
|
30 (14.8)
|
203 (45.0)
|
|
Unknown
|
26 (96.3)
|
1 (3.7)
|
27 (6.0)
|
|
Perceived risk of experiencing an overdose (last 6 months)
|
|
|
|
0.721
|
Never
|
192 (90.6)
|
20 (9.4)
|
212 (47.0)
|
|
Ever
|
204 (89.1)
|
25 (10.9)
|
229 (50.8)
|
|
Unknown
|
8 (80.0)
|
2 (20.0)
|
10 (2.2)
|
|
Perceived risk of witnessing an overdose (last 6 months)
|
|
|
|
0.292
|
Never
|
45 (84.9)
|
8 (15.1)
|
53 (11.8)
|
|
Ever
|
348 (90.6)
|
36 (9.4)
|
384 (85.1)
|
|
Unknown
|
11 (78.6)
|
3 (21.4)
|
14 (3.1)
|
|
Opioid use (last 6 months)
|
|
|
|
0.999
|
Yes
|
224 (89.2)
|
27 (10.8)
|
251 (55.7)
|
|
No
|
141 (89.8)
|
16 (10.2)
|
157 (34.8)
|
|
Unknown
|
39 (90.7)
|
4 (9.3)
|
43 (9.5)
|
|
Opioid overdose (last 6 months) e
|
|
|
|
0.854
|
Yes
|
73 (90.1)
|
8 (9.9)
|
81 (18.0)
|
|
No
|
307 (90.8)
|
31 (9.2)
|
338 (74.9)
|
|
Unknown
|
24 (75.0)
|
8 (25.0)
|
32 (7.1)
|
|
Stimulant overdose (last 6 months)
|
|
|
|
0.066
|
Yes
|
58 (84.1)
|
11 (15.9)
|
69 (15.3)
|
|
No
|
321 (92.0)
|
28 (8.0)
|
349 (77.4)
|
|
Unknown
|
25 (75.8)
|
8 (24.2)
|
33 (7.3)
|
|
Opioid overdose witnessed (last 6 months)
|
|
|
|
0.611
|
Yes
|
233 (90.3)
|
25 (9.7)
|
258 (57.2)
|
|
No
|
133 (92.4)
|
11 (7.6)
|
144 (31.9)
|
|
Unknown
|
38 (77.6)
|
11 (22.4)
|
49 (10.9)
|
|
Stimulant overdose witnessed (last 6 months)
|
|
|
|
0.675
|
Yes
|
159 (90.9)
|
16 (9.1)
|
175 (38.8)
|
|
No
|
204 (89.1)
|
25 (10.9)
|
229 (50.8)
|
|
Unknown
|
41 (87.2)
|
6 (12.8)
|
47 (10.4)
|
|
a Chi square test exclude participants with unknown independent variables
b “Trans and gender expansive” is shown but is not included in the chi square test due to small sample size
c The authors recognize that Indigenous identity is often a proxy for factors associated with colonialism including intergenerational trauma, systemic racism, criminalization and discrimination.
d “Unaware” is shown but is not included in the chi square test
e “Didn’t use opioids” is shown but is not included in the chi square test
|
Table 3
Estimated odds ratios (OR) and adjusted odds ratios (AOR) for predictors of intention to call 911 at a future overdose among participants.
|
Calling 911 at an OD eventa
|
Variables
|
Bivariate
OR (95% CI)
|
Block 1 (Demographics)
AOR (95% CI)
|
Block 2 (Indigenous Identity)
AOR (95% CI)
|
Block 3 (SES)
AOR (95% CI)
|
Block 4
(OD Response)
AOR (95% CI)
|
Block 5 (OD Characteristics)
AOR (95% CI)
|
Demographic Characteristics
|
|
|
|
|
|
|
Age (years)
|
|
|
|
|
|
|
16 – 24
|
—
|
—
|
—
|
—
|
—
|
—
|
25 – 34
|
0.35 (0.09, 1.40)
|
0.41 (0.10, 1.70)
|
0.40 (0.10, 1.66)
|
0.35 (0.08, 1.57)
|
0.28 (0.06, 1.31)
|
0.20 (0.04, 0.98) *
|
35 – 44
|
0.34 (0.09, 1.35)
|
0.43 (0.11, 1.74)
|
0.41 (0.10, 1.65)
|
0.34 (0.08, 1.52)
|
0.32 (0.07, 1.47)
|
0.24 (0.05, 1.18)
|
45 – 54
|
0.71 (0.15, 3.28)
|
0.88 (0.19, 4.13)
|
0.91 (0.19, 4.30)
|
0.81 (0.16, 4.12)
|
0.81 (0.15, 4.29)
|
0.55 (0.10, 3.07)
|
55 +
|
0.24 (0.06, 1.03)
|
0.30 (0.07, 1.32)
|
0.26 (0.06, 1.13)
|
0.25 (0.05, 1.18)
|
0.25 (0.05, 1.25)
|
0.17 (0.03, 0.90) *
|
Gender
|
|
|
|
|
|
|
Cis man
|
—
|
—
|
—
|
—
|
—
|
—
|
Cis woman
|
2.90 (1.15, 7.35) *
|
2.59 (1.01, 6.68) *
|
3.00 (1.15, 7.83) *
|
3.05 (1.14, 8.15) *
|
3.24 (1.19, 8.84) *
|
3.37 (1.19, 9.50) *
|
Indigenous Identityb
|
|
|
|
|
|
|
Non-indigenous
|
—
|
|
—
|
—
|
—
|
—
|
Indigenous
|
0.46 (0.21, 1.01)
|
|
0.38 (0.17, 0.85) *
|
0.43 (0.18, 1.00)
|
0.48 (0.20, 1.15)
|
0.64 (0.25, 1.64)
|
SES Factors
|
|
|
|
|
|
|
Housing Status
|
|
|
|
|
|
|
Private - Alone
|
—
|
|
|
—
|
—
|
—
|
Private - With others
|
4.85 (1.37, 17.21) *
|
|
|
3.90 (1.01, 15.03) *
|
3.65 (0.94, 14.26)
|
4.96 (1.21, 20.29) *
|
Supportive/Unstable Housing
|
3.17 (1.18, 8.51) *
|
|
|
3.40 (1.18, 9.78) *
|
3.56 (1.20, 10.64) *
|
3.96 (1.31, 11.98) *
|
Homeless
|
2.04 (0.61, 6.81)
|
|
|
1.91 (0.51, 7.16)
|
2.08 (0.53, 8.16)
|
2.39 (0.58, 9.82)
|
Employment Status
|
|
|
|
|
|
|
Not employed
|
—
|
|
|
—
|
—
|
—
|
Employed
|
0.65 (0.30, 1.43)
|
|
|
0.52 (0.21, 1.26)
|
0.51 (0.20, 1.28)
|
0.46 (0.18, 1.18)
|
Overdose Response Resources
|
|
|
|
|
|
|
Previous awareness of GSDOA
|
|
|
|
|
|
|
Unaware
|
—
|
|
|
|
—
|
—
|
Aware
|
3.16 (1.35, 7.41) **
|
|
|
|
3.52 (1.42, 8.69) **
|
4.16 (1.62, 10.7) **
|
Overdose Characteristics
|
|
|
|
|
|
|
Stimulant OD
|
|
|
|
|
|
|
No
|
—
|
|
|
|
|
—
|
Yes
|
0.36 (0.15, 0.81) *
|
|
|
|
|
0.24 (0.09, 0.65) **
|
LR Pseudo–R2
|
|
0.054
|
0.083
|
0.123
|
0.166
|
0.206
|
Pseudo–R2 change
|
|
0.054
|
0.029 *
|
0.040
|
0.043 **
|
0.040 **
|
Note: SES = socioeconomic status, OD = overdose. Reference categories are denoted by —. *p<0.05, **p<0.01
a Final model size N = 327 after excluding individuals with “unknown” responses for all variables
b The authors recognize that Indigenous identity is often a proxy for factors associated with colonialism including intergenerational trauma, systemic racism, criminalization and discrimination
|
Prior awareness of the GSDOA was determined by asking participants if they were aware of the GSDOA before the definition of the Act was provided. To evaluate understanding of the GSDOA, a set of questions were included that had been used previously in Mehta et al. [33]. Briefly, hypothetical overdose scenarios were outlined and participants were asked true or false questions to assess their knowledge of when and to whom protection is offered under the GSDOA. Knowledge was considered “complete” if all questions were answered correctly and “incomplete” if otherwise (See Additional File 1).
To assess perceived risks of experiencing or witnessing an overdose, respondents were asked to rate the degree to which they felt at risk of these events in the previous 6 months using a Likert-type scale. Possible responses were “never”, “rarely”, “sometimes”, “often” or “all the time” which was dichotomized as “never” and “ever”. Additional collected variables on substance use and overdose experience in the last 6 months included using opioids (yes, no, prefer not to say), overdosing on opioids (yes, no, don’t know, prefer not to say), witnessing an opioid overdose (yes, no, don’t know, prefer not to say), overdosing on stimulants (yes, no, don’t know, prefer not to say) and witnessing a stimulant overdose (yes, no, don’t know, prefer not to say).
Data Analysis
All analyses were conducted using R version 4.0.2 [46]. Frequency distributions and bivariate analyses with chi-square tests of independence were conducted to describe characteristics of participants and to explore relationships between intention to call 9-1-1 and the explanatory variables.
For multivariable analysis, candidate variables were separated into relevant categories, or blocks, that were organized by linking conceptual similarities through a concept map (See Supplementary Figure 1, Additional File 2). Notably, Indigeneity was separated from other demographic characteristics because it acts as a proxy for a number of other factors relating to colonialism as described above. Hierarchical logistic regression was then used to estimate the association of these blocks and their variables with intention to call 9-1-1 [47]. The final model was entered block by block in five steps:
- Demographic characteristics except for Indigeneity (age, gender, health region)
- Indigeneity (identifying as First Nations, Métis and/or Inuit)
- Socioeconomic status characteristics (housing status, employment status)
- Overdose response resources (cellphone possession, prior GSDOA awareness, complete understanding of the GSDOA)
- Overdose characteristics (perceived risk of overdose, perceived risk of witnessing an overdose, stimulant overdose experienced, stimulant overdose witnessed, opioid overdose experienced, opioid overdose witnessed)
To build the model within each block, bivariate logistic regression of each explanatory variable with the outcome variable was completed and variables with p value < 0.25 were considered for selection [48, 49]. Variables were then selected through a backwards selection approach based on minimizing the value of Akaike’s information criteria (AIC) [50]. Conceptually important variables were retained in the model (i.e. age). The final selected model included: age, gender, Indigenous identity, housing status, employment status, previous awareness of the GSDOA and having experienced a stimulant overdose in the past 6 months. To illustrate the relative contribution of each block to model fit, likelihood ratio R2 was calculated after incorporating each additional block [51]. Models were also compared using the Likelihood Ratio Test with each model being compared to the model generated in the previous step [48]. The theory of planned behaviour was used as a conceptual framework to inform interpretation and discussion of results [52]. Briefly, the theory of planned behaviour posits that attitudes toward a behaviour, subjective norms and perceived behavioural controls influence the formation of a behavioral intention and this can be used to predict or understand the context of certain behaviours which, in our current study, is calling 9-1-1 for an overdose.
Missing data
Complete case analysis (CCA) was used for this study. This resulted in the exclusion of individuals with missing, “prefer not to say” or “don’t know” responses which were categorized as “unknown” (Figure 2). In total, 153 (33.7%) observations were removed from the analysis and a total of 327 responses were used for the multivariable model. The model was rerun in sensitivity analyses with multiple imputation [53]. Briefly, a parallel analysis using ten imputed datasets each generated by ten cycles of multiple imputation by chained equation (MICE) was conducted [54]. Results were verified by comparing the imputed model to the unimputed model and there were no significant differences in the conclusions, confirming confidence in the results of the CCA.