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Appendix to:

Impact of gambling supply reduction during COVID-19 shutdowns on gambling problems and

gambling behaviour in Australia: A national longitudinal study

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Email

Subject: Gambling and COVID-19 survey | Your response will make a difference!

Thank you for signing up to hear about our research following your participation in our previous surveys.

We are conducting a brief survey on the impacts of COVID-19 on gambling in Australia and would greatly value your response. We expect the survey will take around 10 minutes to complete.

If you have spent money on gambling in the past 12 months, we want to hear from you.

To find out more, go to bit.ly/ AusGamblingStudy

After completing the survey, you will have the option to provide your contact details for the purpose of entering a prize draw to win one of five $50 gift cards.

Your response will contribute to the findings which will make an important contribution to policy and practice to enhance health and wellbeing among Australians.

Thank you!

Associate Professor Sally GainsburyGambling Treatment & Research ClinicThe University of Sydney

Why am I being contacted?

We are contacting you as you have previously indicated that you would like to be contacted regarding opportunities to participate in research studies.

Participation in this study is completely voluntary.

If you wish to be removed from this mailing list, please reply to psych.gtrc@sydney.edu.au with the word ‘UNSUBSCRIBE’ in the subject line.

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Covariates

Supplemental Table A1

Covariates used in the Present Paper, their Measurement, and their Coding for Analyses

Variable Measure Coding

Age What is your age? Age in years. Mean-centred.

Gender What is your gender? Female Male Other

1=male, 0=femaleNote: three individuals indicated ‘other’ in the first survey; however, none of these individuals consented to follow-up and hence are not included in the present study.

Relationship status

Which of the following best describes your current marital status?

Single Widowed Divorced Separated Married De facto

For analyses coded as 1=in a relationship (married and de facto), or 0=single (single, widowed, divorced, and separated)

Language spoken at home

What is the primary language spoken at your home?

English Arabic Cantonese Italian Mandarin Vietnamese Other – please specify..............

For analyses coded as 1=English, 0=other

Neighbourhood advantage/ disadvantage

What is your postcode? Calculated by linking participants’ postcodes to Australian Bureau of Statistics Index of Relative Socioeconomic Advantage and Disadvantage (IRSAD) data (Australian Bureau of Statistics, 2018)

Education What is the highest level of education you have completed?

High school, Year 10 or below Certificate I or II High school, Year 11 or 12 Certificate III or IV Diploma or Advanced Diploma Bachelor Degree Graduate Diploma or Graduate

Certificate

For analyses coded according to an abbreviated version of the 2011 International Standard Classification of Education categories.0=lower secondary or below (high school, year 10 or below); 1=upper secondary (high school, year 11 or 12); 2=post-secondary non-tertiary

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Variable Measure Coding

Postgraduate Degree (certificates I-IV); 3=short-cycle tertiary (diploma or advanced diploma); 4=bachelor or equivalent (bachelor degree, graduate diploma or graduate certificate); 5=master or doctoral or equivalent (postgraduate degree)

Psychological distress

Kessler 6 (Kessler et al., 2002) Per standard scoring procedures

Gambling problems

Problem gambling severity index (Ferris and Wynne, 2001)

Per standard scoring procedures

Frequency of land-based gambling

The next questions ask you about any gambling activities you took part in before the shutdown of gambling venues (i.e., prior to 26th March 2020). Gambling includes any activity where you bet money on an unknown outcome (e.g., a game or sporting event) for the chance to win money. Thinking about a TYPICAL MONTH in the last 12 months before the shutdown, how often did you spend any money on any of the following activities, either in a LAND-BASED gambling venue (e.g., pub, club, casino, etc.) and/or ONLINE (on a computer, mobile/smart phone, iPad, etc.)?1. Instant scratch tickets (“scratchies”), or lotto

or lottery games, like Powerball or Oz Lotto, from a LAND-BASED retailer (e.g., newsagent)

2. Keno in a LAND-BASED gambling venue (including via the app while in a gambling venue)

3. Private betting for real money (e.g., playing cards or mah-jong with friends and family) in a LAND-BASED setting (e.g., at home)

4. Poker in a LAND-BASED casino5. Table games (e.g., blackjack, roulette) in a

LAND-BASED casino6. Poker machines (“pokies”) or slot machines

in a LAND-BASED gambling venue7. Betting on horse or dog races in a LAND-

BASED gambling venue8. Betting on sports (excluding esports) in a

LAND-BASED gambling venueAll response options: 0=Not at all, 1=1–3 times per month, 2=Once a week, 3=2–6 times per week, 4=Daily

Responses recoded as follows and then summed to indicated number of engagements per month: not at all = 0; 1–3 times per month = 2; once a week = 4.29; 2–6 times per week = 17.14; daily = 30.

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Variable Measure Coding

Frequency of online gambling

[Same introduction text as land-based gambling items]1. Lottery tickets, like Powerball or Oz Lotto,

(not including instant scratch tickets) ONLINE2. Keno ONLINE (i.e., not including in a land-

based gambling venue)3. Private betting for real money (e.g., playing

cards or mah-jong with friends and family) ONLINE

4. Poker ONLINE5. Casino table games (e.g., blackjack, roulette),

poker machines/slots, instant scratch tickets, or bingo ONLINE

6. Betting on horse or dog races ONLINE7. Betting on sports (excluding esports) ONLINE8. Betting on esports ONLINE9. Betting on non-sporting events (e.g., politics,

weather events) ONLINEAll response options: 0=Not at all, 1=1–3 times per month, 2=Once a week, 3=2–6 times per week, 4=Daily

Responses recoded as follows and then summed to indicated number of engagements per month: not at all = 0; 1–3 times per month = 2; once a week = 4.29; 2–6 times per week = 17.14; daily = 30.

Gambling breadth (number of gambling activities)

As per above (frequency of land-based gambling and online-gambling)

Count of each of the 17 different gambling activities on which the participant indicated engagement in the past year

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Participant characteristics associated with attrition

There were several statistically significant differences between those who did and did not

complete the Waves 2 and 3 surveys (presented in full in Supplemental Tables 2-5, below). Those

who completed Wave 2 tended to be older; were more likely to be male; more highly educated;

experiencing higher financial wellbeing; demonstrated different patterns of employment, 2020

personal income, and household composition; were less likely to have had their employment

impacted by COVID-19; experiencing lower levels of psychological distress, gambling problems, and

land-based gambling engagement; engaging in fewer different modes of gambling; less likely to

intend to decrease their online gambling engagement; and less likely to perceive themselves to have

a gambling problem. Those who completed Wave 3 tended to be older; demonstrated different

patterns of employment; experiencing higher levels of financial wellbeing; experiencing lower levels

of psychological distress; engaging in fewer different modes of gambling; engaging in land-based

gambling less frequently; and less likely to perceive themselves to have a gambling problem. Per

recommendations (White et al., 2011) and as described in the main text, to increase the validity of

the multiple imputation model we included all these variables that differed between completers and

non-completers.

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Supplemental Table A2

Comparison (Wilcoxon Signed-Rank Test) Between Participants Who Completed and Did Not Complete the Wave 2 Survey on Continuous Variables at Wave 1

Complete IncompleteM SD M SD W p

Age 48.26 14.7 41.9 14.75 33221 <.001 ***Index of Relative Advantage and Disadvantage decile 7.01 2.92 6.82 2.82 27621 .346Kessler 6 3.67 4.23 5.44 5.02 20770 <.001 ***Problem Gambling Severity Index 3.97 5.05 5.76 6.4 22348 .003 **Financial wellbeing 67.9 19.05 59.27 21.15 32991 <.001 ***Gambling breadth 3.98 2.26 4.85 2.8 21700 .001 ***Pre-COVID-19 land-based gambling engagement 9.46 12.06 13.01 19.69 23009 .011 *Early COVID-19 (May) land-based gambling engagement 1.25 3.57 1.81 5.63 25018 .157Pre-COVID-19 online gambling engagement 21.16 17.51 23.14 21.46 25747 .538Early COVID-19 (May) online gambling engagement 17.74 16.49 19.68 23.2 25943 .630Pre-COVID-19 gambling expenditure (AUD per month) 2547.42 9644.45 4307.76 32684.36 25746 .537Early COVID-19 (May) gambling expenditure (AUD per month) 1404.13 4128.92 2016.7 13185.17 27176 .703

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Supplemental Table A3

Comparison (Chi Squared Test) Between Participants Who Completed and Did Not Complete the Wave 2 Survey on Categorical Variables at Wave 1

Complete IncompleteVariable Categories n % n % Chi2 df pEducation Lower secondary or below 11 4.98 29 12.03 19.05 5 .002 **

Upper secondary 41 18.55 52 21.58Post-secondary non-tertiary 25 11.31 33 13.69Short-cycle tertiary education 31 14.03 36 14.94Bachelor or equivalent 78 35.29 77 31.95Master or doctoral or equivalent 35 15.84 14 5.81

State Non-Victorian 174 78.73 179 74.27 0.89 1 .347Victorian 47 21.27 61 25.31Missing 0 0.00 1 0.41

Gender Male 204 92.31 197 81.74 10.33 1 .001 **Female 17 7.69 44 18.26

Relationship status In a relationship 147 66.52 152 63.07 0.46 1 .499Not in a relationship 74 33.48 89 36.93

Language spoken at home English spoken at home 217 98.19 232 96.27 0.94 1 .333Language other than English spoken at home 4 1.81 9 3.73

Household composition Single person, no children 48 21.72 38 15.77 14.72 5 .012 *Single parent, with children 6 2.71 7 2.90Couple, no children 59 26.70 78 32.37Couple, with children 88 39.82 76 31.54Group/share household 10 4.52 31 12.86Other 10 4.52 11 4.56

Citizenship status Australian citizen or permanent resident 217 98.19 233 96.68 0.53 1 .468Not an Australian citizen or permanent resident

4 1.81 8 3.32

Indigenous status Aboriginal 4 1.81 8 3.32 1.04 2 .594Both Aboriginal and Torres Strait Islander 1 0.45 1 0.41Non-Indigenous 216 97.74 232 96.27

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Complete IncompleteVariable Categories n % n % Chi2 df pEmployment status Employed, working full-time 124 56.11 144 59.75 19.04 6 .004 **

Employed, working part-time 14 6.33 17 7.05Student 6 2.71 4 1.66Home duties / full-time carer 1 0.45 8 3.32Retired 46 20.81 22 9.13Job currently suspended due to COVID-19 but expected to resume after the shutdown

16 7.24 28 11.62

Unemployed 14 6.33 18 7.47Employment affected by COVID-19

Yes 34 15.38 66 27.39 9.10 1 .003 **No 187 84.62 175 72.61

Intended gambling modalities once COVID-19 shutdowns are lifted

Both in land-based venues and online 107 48.42 102 42.32 6.29 4 .179In land-based venues only 15 6.79 27 11.20Online only 73 33.03 73 30.29Neither in land-based venues nor online 9 4.07 9 3.73I don't know 17 7.69 30 12.45

Intended changes to land-based gambling once COVID-19 shutdowns are lifted (compared to pre-COVID-19 levels)

Increase a lot 2 0.90 3 1.24 6.71 4 .152Increase a little 10 4.52 18 7.47Stay much the same 156 70.59 149 61.83Decrease a little 32 14.48 33 13.69Decrease a lot 21 9.50 38 15.77

Intended changes to online gambling once COVID-19 shutdowns are lifted (compared to pre-COVID-19 levels)

Increase a lot 4 1.81 8 3.32 9.50 4 .050 *Increase a little 28 12.67 25 10.37Stay much the same 154 69.68 146 60.58Decrease a little 21 9.50 30 12.45Decrease a lot 14 6.33 32 13.28

Self-perceived impact of COVID-19 on financial wellbeing

Made much easier 13 5.88 18 7.47 6.59 4 .159Made somewhat easier 40 18.10 47 19.50No change 124 56.11 109 45.23Made somewhat more difficult 38 17.19 55 22.82Made much more difficult 6 2.71 12 4.98

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Complete IncompleteVariable Categories n % n % Chi2 df pSelf-perceived gambling problems

Yes 40 18.10 66 27.39 5.11 1 .024 *No 181 81.90 175 72.61

Gross personal income (2019) Nil income 2 0.90 1 0.41 16.55 15 .347$1 – $7,799 per year 6 2.71 9 3.73$7,800 – $15,599 per year 7 3.17 7 2.90$15,600 – $20,799 per year 8 3.62 11 4.56$20,800 – $25,999 per year 9 4.07 14 5.81$26,000 – $33,799 per year 8 3.62 7 2.90$33,800 – $41,599 per year 9 4.07 8 3.32$41,600 – $51,999 per year 15 6.79 17 7.05$52,000 – $64,999 per year 17 7.69 39 16.18$65,000 – $77,999 per year 25 11.31 22 9.13$78,000 – $90,999 per year 17 7.69 26 10.79$91,000 – $103,999 per year 22 9.95 22 9.13$104,000 – $155,999 per year 45 20.36 33 13.69$156,000 or more per year 23 10.41 19 7.88I don’t know 0 0.00 1 0.41I prefer not to say 8 3.62 5 2.07

Gross personal income (2020) Nil income 2 0.90 0 0.00 25.10 15 .049 *$1 – $7,799 per year 8 3.62 9 3.73$7,800 – $15,599 per year 9 4.07 5 2.07$15,600 – $20,799 per year 7 3.17 8 3.32$20,800 – $25,999 per year 6 2.71 21 8.71$26,000 – $33,799 per year 11 4.98 9 3.73$33,800 – $41,599 per year 14 6.33 9 3.73$41,600 – $51,999 per year 13 5.88 21 8.71$52,000 – $64,999 per year 14 6.33 32 13.28$65,000 – $77,999 per year 27 12.22 24 9.96$78,000 – $90,999 per year 21 9.50 23 9.54$91,000 – $103,999 per year 17 7.69 24 9.96

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Complete IncompleteVariable Categories n % n % Chi2 df p

$104,000 – $155,999 per year 40 18.10 33 13.69$156,000 or more per year 21 9.50 13 5.39I don’t know 5 2.26 5 2.07I prefer not to say 6 2.71 5 2.07

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Supplemental Table A4

Comparison (Wilcoxon Signed-Rank Test) Between Participants Who Completed and Did Not Complete the Wave 3 Survey on Continuous Variables at Wave 1

Complete IncompleteM SD M SD W p

Age 48.84 15.32 42.14 14.25 32547 <.001 ***Index of Relative Advantage and Disadvantage decile 7.19 2.79 6.71 2.91 27859 .108Kessler 6 4.19 4.76 4.88 4.71 22948 .032 *Problem Gambling Severity Index 4.39 5.50 5.28 6.09 23578 .090 †Financial wellbeing 66.40 20.77 61.25 20.26 29780 .007 **Gambling breadth 4.13 2.57 4.65 2.58 22410 .011 *Pre-COVID-19 land-based gambling engagement 10.18 17.95 12.12 15.49 22281 .009 **Early COVID-19 (May) land-based gambling engagement 1.60 5.40 1.50 4.26 25363 .596Pre-COVID-19 online gambling engagement 23.08 19.82 21.56 19.58 27370 .318Early COVID-19 (May) online gambling engagement 21.27 24.95 16.95 15.90 28405 .083 †Pre-COVID-19 overall gambling engagement 33.26 32.01 33.68 28.84 26147 .895Early COVID-19 (May) overall gambling engagement 22.87 27.99 18.45 17.21 28594 .062 †Pre-COVID-19 gambling expenditure (AUD per month) 5920.78 37564.57 1704.24 3994.54 26372 .770Early COVID-19 (May) gambling expenditure (AUD per month) 2682.36 14975.01 1035.84 2836.75 28318 .095 †

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Supplemental Table A5

Comparison (Chi Squared Test) Between Participants Who Completed and Did Not Complete the Wave 3 Survey on Categorical Variables at Wave 1

Complete IncompleteVariable Categories n % n % Chi2 df pEducation Lower secondary or below 12 6.22 28 10.41 5.24 5 .387

Upper secondary 36 18.65 57 21.19 Post-secondary non-tertiary 22 11.40 36 13.38 Short-cycle tertiary education 30 15.54 37 13.75 Bachelor or equivalent 68 35.23 87 32.34 Master or doctoral or equivalent 25 12.95 24 8.92

State Non-Victorian 143 74.09 210 78.07 0.91 1 .339Victorian 50 25.91 58 21.56 Missing 0 0.00 1 0.37

Gender Male 171 88.60 230 85.50 0.69 1 .406Female 22 11.40 39 14.50

Relationship status In a relationship 123 63.73 176 65.43 0.08 1 .781Not in a relationship 70 36.27 93 34.57

Language spoken at home English spoken at home 189 97.93 260 96.65 0.28 1 .595Language other than English spoken at home 4 2.07 9 3.35

Household composition Single person, no children 44 22.80 42 15.61 7.26 5 .202Single parent, with children 7 3.63 6 2.23 Couple, no children 55 28.50 82 30.48 Couple, with children 68 35.23 96 35.69 Group/share household 13 6.74 28 10.41 Other 6 3.11 15 5.58

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Complete IncompleteVariable Categories n % n % Chi2 df pCitizenship status Australian citizen or permanent resident 190 98.45 260 96.65 0.81 1 .370

Not an Australian citizen or permanent resident 3 1.55 9 3.35

Indigenous status Aboriginal 2 1.04 10 3.72 4.68 2 .096 †Both Aboriginal and Torres Strait Islander 0 0.00 2 0.74Non-Indigenous 191 98.96 257 95.54

Employment status Employed, working full-time 98 50.78 170 63.20 26.28 6 <.001 ***Employed, working part-time 14 7.25 17 6.32 Student 7 3.63 3 1.12 Home duties / full-time carer 2 1.04 7 2.60 Retired 45 23.32 23 8.55 Job currently suspended due to COVID-19 but expected to resume after the shutdown

14 7.25 30 11.15

Unemployed 13 6.74 19 7.06

Employment affected by COVID-19

Yes 33 17.10 67 24.91 3.59 1 .058 †No 160 82.90 202 75.09

Intended gambling modalities once COVID-19 shutdowns are lifted

Both in land-based venues and online 89 46.11 120 44.61 1.90 4 .753In land-based venues only 15 7.77 27 10.04 Online only 65 33.68 81 30.11 Neither in land-based venues or online 6 3.11 12 4.46 I don't know 18 9.33 29 10.78

Intended changes to land-based gambling once COVID-19 shutdowns are lifted (compared to pre-COVID-19 levels)

Increase a lot 2 1.04 3 1.12 3.72 4 .446Increase a little 8 4.15 20 7.43Stay much the same 135 69.95 170 63.20 Decrease a little 27 13.99 38 14.13

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Complete IncompleteVariable Categories n % n % Chi2 df p

Decrease a lot 21 10.88 38 14.13

Intended changes to online gambling once COVID-19 shutdowns are lifted (compared to pre-COVID-19 levels)

Increase a lot 4 2.07 8 2.97 6.55 4 .162Increase a little 27 13.99 26 9.67Stay much the same 131 67.88 169 62.83Decrease a little 17 8.81 34 12.64Decrease a lot 14 7.25 32 11.90

Self-perceived impact of COVID-19 on financial wellbeing

Made much easier 9 4.66 22 8.18 3.90 4 .420Made somewhat easier 41 21.24 46 17.10 No change 100 51.81 133 49.44 Made somewhat more difficult 37 19.17 56 20.82 Made much more difficult 6 3.11 12 4.46

Self-perceived gambling problems

Yes 35 18.13 71 26.39 3.88 1 .049 *No 158 81.87 198 73.61

Gross personal income (2019) Nil income 1 0.52 2 0.74 14.48 15 .489$1 – $7,799 per year 6 3.11 9 3.35$7,800 – $15,599 per year 7 3.63 7 2.60$15,600 – $20,799 per year 10 5.18 9 3.35$20,800 – $25,999 per year 11 5.70 12 4.46$26,000 – $33,799 per year 7 3.63 8 2.97$33,800 – $41,599 per year 11 5.70 6 2.23$41,600 – $51,999 per year 11 5.70 21 7.81$52,000 – $64,999 per year 23 11.92 33 12.27$65,000 – $77,999 per year 16 8.29 31 11.52$78,000 – $90,999 per year 15 7.77 28 10.41$91,000 – $103,999 per year 15 7.77 29 10.78$104,000 – $155,999 per year 30 15.54 48 17.84

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Complete IncompleteVariable Categories n % n % Chi2 df p

$156,000 or more per year 22 11.40 20 7.43I don’t know 0 0.00 1 0.37I prefer not to say 8 4.15 5 1.86

Gross personal income (2020) Nil income 1 0.52 1 0.37 23.65 15 .071 †$1 – $7,799 per year 8 4.15 9 3.35$7,800 – $15,599 per year 7 3.63 7 2.60$15,600 – $20,799 per year 11 5.70 4 1.49$20,800 – $25,999 per year 9 4.66 18 6.69$26,000 – $33,799 per year 12 6.22 8 2.97$33,800 – $41,599 per year 11 5.70 12 4.46$41,600 – $51,999 per year 12 6.22 22 8.18$52,000 – $64,999 per year 15 7.77 31 11.52$65,000 – $77,999 per year 21 10.88 30 11.15$78,000 – $90,999 per year 16 8.29 28 10.41$91,000 – $103,999 per year 9 4.66 32 11.90$104,000 – $155,999 per year 32 16.58 41 15.24$156,000 or more per year 19 9.84 15 5.58I prefer not to say 6 3.11 5 1.86I don’t know 4 2.07 6 2.23

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Supplemental Table A6

Results of Ordinal Logistic Regression Analysis Predicting Problem Gambling Severity Index at Wave 2 (N = 462)

Predictor Coefficient SE OR t df pIntercepts No problems - low risk intercept -2.00 0.85 0.14 -2.36 368.00 .019 *

Low risk - moderate risk intercept -0.46 0.84 0.63 -0.54 363.32 .590Moderate risk - problems intercept 1.60 0.85 4.97 1.89 362.89 .060 †

Hypothesis test Victorian (1=yes, 0=no) -0.13 0.25 0.88 -0.51 287.61 .610Covariates Age (mean centred) -0.03 0.01 0.97 -3.28 236.52 .001 **

Gender (1=male, 0=female) 0.45 0.35 1.56 1.27 210.78 .206In a relationship (1=yes, 0=no) 0.05 0.22 1.05 0.24 313.45 .814Speaks English at home (1=yes, 0=no) -0.19 0.69 0.83 -0.27 418.32 .785IRSAD decile (mean centred) -0.01 0.04 0.99 -0.38 283.95 .708Education (Upper secondary) -0.40 0.44 0.67 -0.92 248.89 .357Education (Post-secondary, non-tertiary) -0.54 0.44 0.58 -1.24 320.04 .217Education (Short-cycle tertiary) 0.04 0.44 1.04 0.10 293.09 .922Education (Bachelors or equivalent) -0.18 0.40 0.83 -0.46 281.96 .648Education (Masters, Doctorate, or equivalent) -0.33 0.46 0.72 -0.72 321.67 .469Kessler 6 (mean centred) 0.02 0.03 1.02 0.56 239.84 .577Problem Gambling Severity Index (mean centred) 0.30 0.03 1.35 8.60 222.70 <.001 ***Gambling breadth (mean centred) 0.02 0.06 1.02 0.30 232.27 .767Land-based gambling engagement (mean centred) 0.03 0.01 1.03 2.67 288.71 .008 **Online gambling engagement (mean centred) 0.02 0.01 1.02 2.90 324.14 .004 **

Notes: All covariates measured at Wave 1. IRSAD = Index of Relative Advantage and Disadvantage (an indicator of neighbourhood advantage/disadvantage, where higher scores indicate higher advantage and lower disadvantage); *** p < .001, ** p < .01, * p < .05, † p < .1.

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Supplemental Table A7

Results of Multiple Linear Regression Analysis Predicting Online Gambling Engagement at Wave 2 (N = 462)

Predictor Coefficient SE t df pIntercept Intercept 21.34 9.98 2.14 58.22 .037 *Hypothesis test Victorian (1=yes, 0=no) 4.48 2.46 1.82 104.99 .071 †Covariates Age (mean centred) 0.01 0.07 0.18 150.15 .855

Gender (1=male, 0=female) 0.72 3.77 0.19 71.50 .850In a relationship (1=yes, 0=no) 0.25 2.35 0.11 95.41 .916Speaks English at home (1=yes, 0=no) 0.41 7.78 0.05 67.69 .958IRSAD decile (mean centred) 0.60 0.37 1.62 115.66 .107Education (Upper secondary) 0.91 5.39 0.17 61.42 .866Education (Post-secondary, non-tertiary) 1.47 5.39 0.27 69.71 .786Education (Short-cycle tertiary) 1.94 4.95 0.39 78.20 .696Education (Bachelors or equivalent) -0.55 5.00 -0.11 64.93 .913Education (Masters, Doctorate, or equivalent) -2.44 5.44 -0.45 79.66 .655Kessler 6 (mean centred) 0.16 0.26 0.61 95.95 .541Problem Gambling Severity Index (mean centred) 0.12 0.22 0.54 101.84 .587Gambling breadth (mean centred) 0.46 0.53 0.87 90.85 .385Land-based gambling engagement (mean centred) -0.19 0.09 -2.06 78.09 .042 *Online gambling engagement (mean centred) 0.73 0.06 12.48 119.47 <.001 ***

Notes: All covariates measured at Wave 1. IRSAD = Index of Relative Advantage and Disadvantage (an indicator of neighbourhood advantage/disadvantage, where higher scores indicate higher advantage and lower disadvantage); *** p < .001, ** p < .01, * p < .05, † p < .1.

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Deviations from pre-registered analysis plan

We pre-specified (https://osf.io/d6jc4) that we would log-transform the online gambling

engagement dependent variable, as well as some of the covariates, in order to achieve a normal

distribution and meet model assumptions. Subsequent to pre-registering our analyses, we

remembered that the models do not require the predictor variables nor the dependent variables to

be normally distributed, and hence we did not log-transform them.

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References

Australian Bureau of Statistics. (2018) Socio-Economic Indexes for Areas (SEIFA) Technical Paper. 2016 ed. Canberra, 1-39.

Ferris JA and Wynne HJ. (2001) The Canadian problem gambling index: Canadian Centre on Substance Abuse Ottawa, ON.

Kessler RC, Andrews G, Colpe LJ, et al. (2002) Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine 32: 959-976.

White IR, Royston P and Wood AM. (2011) Multiple imputation using chained equations: Issues and guidance for practice. Statistics in Medicine 30: 377-399.