Does the lived experience of gambling accord with quantitative self-report scores of gambling-related harm?

Abstract

A broad quantitative literature has explored the extent and distribution of gambling-related harm. However, any quantitative measure involves a number of statistical decisions around item selection and weighting that may affect its ability to provide an accurate summary of a gambler’s lived experience. This may especially be an issue with a condition as varied and multifaceted as gambling-related harm. The present research therefore used qualitative methods to validate the categorization of gamblers into four levels of harm via the Gambling Harms Scale (10-items) (GHS-10) through an analysis of 30 semi-structured interviews with gamblers. Results showed that unharmed gamblers saw gambling as just another leisure activity, which relieved stress and brought them closer to other people. Low harm gamblers were similar but could experience emotional stresses over their level of gambling expenditure. Just under half of all moderate harm gamblers experienced occasional severe financial impacts and emotional stresses from their gambling. Finally, all high harm gamblers experienced chronic financial impacts and emotional stresses, which spilled over into relationship problems for three quarters of this group, and negative impacts on health or work/study for around half of this group. These results showed that the severity of participants’ lived experience of gambling increased with their GHS-10 score, providing a qualitative validation for this quantitative self-report measure. This qualitative validation for a quantitative scale is argued to be a promising avenue for future gambling research.

Keywords:

• Gambling harm
• problem gambling severity index
• gambling harms scale (10 items)
• qualitative research
• thematic analysis

Introduction

Previous research has used a range of quantitative methods to estimate the extent and distribution of gambling-related harm in the population (Raisamo et al. 2014; Browne et al. 2016, 2023; Salonen et al. 2016; Castrén et al. 2021; Muggleton et al. 2021; Tulloch et al. 2021). Previous research has, for example, suggested that the extent of harm for the most severely affected gamblers might be similar to that of bipolar disorder or alcohol use disorder (Browne et al. 2017). Furthermore, Browne and Rockloff (2018) have estimated that up to half of all gambling-related harm is occurring to individuals who are not problem gamblers as classified by the Problem Gambling Severity Index (PGSI; Ferris and Wynne 2001). This last result occurs because the distribution of gambling-related harm is generally skewed in the population such that a substantially higher number of low- and moderate-harm gamblers exist compared to high-harm gamblers. This finding is consistent with the ‘prevention paradox’ concept (Rose 1992), which suggests that for many health conditions, a large proportion of the population’s overall harm arises from those who are at low or moderate risk, simply because these groups are much larger than the high-risk group. In the context of gambling, this means that while individuals with severe gambling problems may experience the highest levels of harm on an individual basis, the cumulative impact of harm experienced by low and moderate-risk gamblers may be substantial at the population level, as has been found in a recent representative Australian study (Tulloch et al. 2024). This highlights the importance of considering the full spectrum of gambling-related harm, and of developing prevention and intervention strategies that target individuals across all risk levels.

Researchers have previously developed a 10-item scale for measuring gambling-related harm in the population, known as the Short Gambling Harms Screen (SGHS; Browne et al. 2018), now known as the Gambling Harms Scale (10 items) (GHS-10). The GHS-10 (Browne et al. 2018) was derived from a set of 72 candidate items. These 72 items were themselves produced from a conceptual framework that was synthesized from a series of focus groups, analysis of online support forum data, and an in-depth literature review (Langham et al. 2016). Numerous subsequent studies (see Browne et al. 2021, for a review) have demonstrated that it yields a unitary measure of gambling-related harm, across the six domains identified in the Langham et al. (2016) framework: financial, relationship, emotional/psychological, health, work/study and criminality/anti-social behavior. This scale is intended as a unidimensional measure of all of these different aspects of gambling-related harm, with the 10 items included from the original 72 chosen to most efficiently measure the overall construct of harm. Other commonly-used problem-gambling scales such as the PGSI contain items relating to behavioral addiction in addition to measuring harm and are therefore not specific to the task of measuring harm (Browne and Rockloff 2019). Importantly for the present research, the GHS-10 has been subject to a number of critiques from other researchers that attempt to cast doubt on the validity of the scale for measuring gambling harm (Delfabbro and King 2019).

Any quantitative self-report measure uses a number of conceptual and statistical assumptions that can affect its ability to provide a valid measurement of the underlying construct (Rust and Golombok 2014). For example, each item will provide different response options to a participant, such as ‘never’, ‘sometimes’, ‘most of the time’, and ‘almost always’ as used by the PGSI (Ferris and Wynne 2001). These response options are each given a numerical score, in this case 0, 1, 2, or 3, respectively. This allows the PGSI to measure each of its nine items on a scale of severity, such as ‘Have you borrowed money or sold anything to get money to gamble?’. In comparison, the GHS-10’s ten items are scored over two responses, simply ‘yes’ and ‘no’ (Browne et al. 2018). Researchers have therefore critiqued the GHS-10 for its lack of sensitivity to the severity of each of its ten harms (Delfabbro and King 2019). Although this particular feature of the GHS-10 has been addressed in follow-up work which suggested that any effect of this response scale is relatively minor (McLauchlan et al. 2020), there are other potential critiques.

There are many ways that a person can be harmed by their gambling, which can vary in terms of severity. Psychometric scales may be scored in different ways. One of the most common ways is to sum or average scores for each item, such as in the PGSI where the four response options (each with potential scores of 0 to 3) are summed across the nine items for a total score ranging from 0 to 27. In this scenario, each item has the same weight on the total score. An alternative is for different items to carry different weights, such as scaled scores, whereby the same response (e.g. ‘never’) on two different items may contribute a different amount to the scale score depending on the weight of each response or each item. An example of a scale scored in this way is the SF-12, a measure of wellbeing (Ware et al. 1996). Scaled scoring is generally based on empirical data from particular populations, and therefore may require different scaling for different populations, which means that it may not be applicable in populations where scaling has not yet been quantified; for example the SF-12 employs different weights for different countries. The GHS-10 uses the simpler sum scoring method, whereby a ‘yes’ response on any item adds one to the total score, whether the item is, ‘Less spending on recreational expenses such as eating out, going to movies or other entertainment’, or ‘Felt ashamed of my gambling’, making it applicable across different populations (Browne et al. 2018). It is possible that the psychological distress associated with the latter, for example, is more severe than the psychological impacts from a reduction of recreational expenses associated with the former. This is an important issue for future research to investigate, although beyond the scope of the current work.

It has been argued that several of the GHS-10’s items, such as the first example item, reflect what an economist would call a rational ‘opportunity cost’ (Delfabbro and King 2019). In the rational actor model from economics, an individual consumer will spend their recreational budget on whatever it is that brings them the most satisfaction (Varian 1999). If a rational consumer decides to spend $30 on a Friday evening on an electronic gaming machine, then this must be because they anticipated more satisfaction from gambling than alternative leisure activities, such as going to the movies. Therefore, it has been argued that a response of ‘yes’ to these opportunity cost items need not correspond to genuine instances of gambling-related harm (Delfabbro and King 2019). In response to this critique, researchers have compared the GHS-10 with another alternative 10-item measure of gambling-related harm with items of ‘unimpeachable’ levels of face validity (Murray Boyle et al. 2021). This study identified 10 harms with content that indicate uncontroversial indicators of true harm; they included not attending to the needs of children, less spending on essential expenses, feeling worthless, and loss of sleep due to time spent gambling. If the GHS-10 was a worse indicator of real harm than the unimpeachable harms, then we would have expected to see relatively lower correlations between the GHS-10 with the PGSI and with the latent construct of harm, which was derived from all 72 items. However, both the GHS-10 and the unimpeachable harm scale had identical correlations with the PGSI (.68), and the GHS-10 had a slightly higher correlation with the underlying construct of harm (.87 versus .85). Accordingly, this means that the GHS-10 does not reflect opportunity costs or trivial annoyances, but rather real underlying harm (Murray Boyle et al. 2021). These ‘opportunity cost’ harms nonetheless are efficient indicators of undeniably severe harms.

However, all of this research might be subject to another critique: that short quantitative measures might fail to accurately capture the lived experience of a condition as varied as gambling-related harm. For example, researchers have used qualitative methods to identify up to 72 unique potential harms from gambling (Langham et al. 2016). Although statistical techniques can be used to select candidate items that are the best predictors of the underlying latent construct of gambling-related harm (Browne et al. 2018), these procedures are not infallible. A short quantitative measure might produce ‘false positives’, where someone appears to be experiencing high levels of harm but such harms are not substantive (such as from the earlier opportunity cost argument). But measures might also produce ‘false negatives’, where someone who is actually experiencing harm scores low on the measure due to issues such as the stigma around admitting to harm. These potential issues might be especially significant with a condition as varied and multifaceted as gambling-related harm, a number of aspects of which have been highlighted by previous qualitative research (Cassidy et al. 2013; Reith and Dobbie 2013; Deans et al. 2016; Hing et al. 2021; McCarthy et al. 2021).

Despite the growing body of research on gambling-related harm, most studies have relied primarily on quantitative measures, such as the Problem Gambling Severity Index (PGSI; Ferris and Wynne 2001) and the GHS-10 (Browne et al. 2018). While these measures provide valuable insights into the prevalence and distribution of harm, they may not fully capture the nuanced experiences of gamblers across different levels of harm. The present study aims to address these gaps by providing a qualitative validation of the GHS-10 through semi-structured interviews with gamblers across different levels of harm. By exploring the alignment between gamblers’ lived experiences and the GHS-10's harm categories, this study seeks to contribute to a more nuanced understanding of gambling-related harm and inform the interpretation and application of quantitative harm scales in various settings.

The present work therefore uses qualitative methods to validate the scores and resulting categorisations from the GHS-10 on a sample of gamblers (Browne et al. 2023). The purpose of the study was to produce detailed descriptions of the lived experiences of people who are – presumably – harmed by gambling to differing degrees. If the GHS-10 is a valid measure of harm, the descriptions of experiences of harmed gamblers should align with their scores on the scale. Importantly, gamblers who score low on the GHS-10 should subjectively have some description of their lives being impacted negatively by gambling to counter the argument that some or most of these gamblers are only experiencing opportunity costs – and not harm. Should the lived experiences of participants be found to accord with the levels of harm identified by the GHS-10, then this accordance would signify a form of qualitative validation of the GHS-10.

Method

Ethical approval was obtained from the CQUniversity Human Research Ethics Committee (#22830).

Participants

This study was part of a larger programme of research examining gambling-related harm. Thirty gamblers were recruited from a previous research study conducted by the research team (see Browne et al., 2023, for review). The previous study involved a quantitative survey of 2603 gamblers and examined health and gambling-harm outcomes. All participants in the current study had agreed to be recontacted for a telephone research interview at the end of the previous survey. Recruitment criteria for the current study included being aged 18+ years, residing in Australia, having gambled¹ within the past 12 months, and providing informed consent.

The sample was stratified by GHS-10 (Browne et al. 2018) score to ensure it included gamblers across the harm spectrum (from no harm to high harm). We aimed to recruit approximately equal numbers across individuals who scored 0, 1-2, 3-5, and 6-10 on the GHS-10. The rationale for selecting these scoring categories was based on previous findings which showed significant decrements to health for GHS-10 scores 1-2 (decrement of −0.020), 3-5 (−0.062), and 6-10 (−0.109) (Browne et al. 2023). It was important to include participants who scored zero harm as control cases and to also evaluate the potential for the GHS-10 measure to produce false negatives. In addition to the GHS-10 scores, Problem Gambling Severity Index (PGSI) scores were also obtained for each participant to provide further context on their gambling severity. Where possible we also aimed to have a diverse representation of ages and genders within each subsample. Participant details are summarized in Table 1.

Table 1. Characteristics for gamblers.

GHS-10 group	ID	GHS-10 score	PGSI score	Gender	Age
No harm	G1	0	0	M	50
	G10	0	0	M	73
	G11	0	0	M	59
	G12	0	0	F	43
	G20	0	0	M	32
	G21	0	0	M	40
	G30	0	0	F	37
Low harm	G2	2	0	F	67
	G3	2	0	F	73
	G9	2	0	M	73
	G22	1	0	F	49
	G23	1	0	F	63
	G24	1	2	F	36
	G25	2	2	M	33
	G26	1	1	F	36
Moderate harm	G5	4	1	F	39
	G6	5	5	F	71
	G13	4	8	M	48
	G16	4	8	M	31
	G18	3	5	M	52
	G19	5	6	M	55
	G27	3	1	M	58
High harm	G4	6	5	M	37
	G7	7	3	F	70
	G8	7	10	M	67
	G14	6	14	M	30
	G15	8	13	F	29
	G17	10	24	M	35
	G28	8	24	M	36
	G29	9	11	M	43

Procedure

Participants were invited into the study via an email which included an information sheet and informed consent information. All interviews were conducted via telephone and scheduled at a time convenient to the participant. Interviews were conducted by a researcher with several years’ experience in gambling research. Participants provided verbal informed consent prior to the interview and were compensated for their time with a $50 shopping voucher. Participants were also offered helpline information at debrief.

Semi-structured interviews were conducted between May and July 2021 and involved probes that encouraged the participant to describe the role that gambling played in their lives. Probes included gambling’s importance and its relationship relative to their hobbies, activities, and social relationships. Participants were asked to describe potential harms from gambling, as well as any positive impacts experienced from their gambling. Previous qualitative research has shown that gambling-related harm is a multidomain construct (Langham et al. 2016). Nevertheless, quantitative research has shown that, of Langham et al. (2016) categories, ‘social deviance’ harms such as criminality or neglect of children are substantially less common than other domains; for example financial harms (Browne and Rockloff 2018). Furthermore, despite harms being describable across multiple domains (financial, relationship, etc.), people who experience harm in one domain are likely to also have harms in another. Measured harms are a unitary construct whereby harms do not tend to cluster within one domain but are rather just as likely to be spread across domains. Therefore, the interviews focused on financial, relationship, emotional/psychological, health, and work/study harms (Langham et al. 2016). Harms related to criminal activity were not explicitly queried due to ethical/privacy concerns. However, the interviews also gave participants opportunities to talk about impacts outside of these categories, and allowed participants the space to reflect on more general issues, such as the impact that they thought gambling had on society in general. Finally, participants were asked about the types of gambling that they had engaged in and any gambling-related harms (including items from the GHS-10) they had previously endorsed.

Interviews were digitally recorded and lasted between 15 and 53 min, with a mean length of 31 min. The recordings were transcribed and anonymised to remove any personally identifying information (e.g. names and specific locations).

Data analysis

Interview transcripts were imported into Nvivo software version 20 and analyzed using reflexive thematic analysis (Braun and Clarke 2019). First, the transcripts were read and reread so the analyst could familiarize themself with the data. During this stage, numerous quotes were selected for the generation of an initial set of codes, reflecting patterns of shared meaning across the data. Major themes across the entire sample of potential financial, relationship, emotional, health, and work/study harms were derived deductively, based on Langham et al. (2016) and Browne et al. (2018). However, the way that each of these themes was expressed in each individual harm group via the relevant sub theme for that group was arrived at ‘inductively’, as being developed purely from the interview transcripts. This provisional set of themes was then discussed with other members of the research team, whose input led to further refinement in terms of the scope and interpretation of these generated themes. The analyst then used this feedback to reflect both on the set of transcripts and the generation of the themes. Given that the research team has performed a variety of previous qualitative and quantitative research on gambling related harm, an important part of this process involved the team’s reflection on how their own experiences might impact the generation of themes. This inclusion of reflexivity into the theme generation process was designed to ensure that as full a spectrum of themes as possible could be generated from the data, thereby minimizing the influence of overly relying on a single researcher’s dominant perspective (Braun and Clarke 2019).

All authors agreed on the final set of themes. Additional steps were taken to increase the trustworthiness of the findings. The sample size was relatively large for a qualitative study, which enabled exploration of themes across different GHS-10 scores, and increased the likelihood of achieving saturation for themes. The triangulation in reporting across the semi-structured interviews and participants’ previous self-report scores on the GHS-10 enhanced the dependability of the findings. It should be noted, however, that the initial thematic analysis was conducted without reference to GHS-10 scores in order not to introduce bias into the construction of categories. The use of direct quotes enhanced their authenticity.

Given that the research question was to explore how participants’ self-reports of gambling correspond to their responses on the GHS-10, the results were stratified with respect to the GHS-10: no (0), low (1 or 2), moderate (3 to 5), and high (6+) harm. Table 1 also shows participants’ PGSI scores, indicating that 12 were recreational gamblers, 5 were low risk gamblers, 5 were moderate risk gamblers, and 8 were problem gamblers (Ferris and Wynne 2001). The Pearson pairwise correlation between GHS-10 and PGSI per-person total scores was 0.84, which is considered high, suggesting that the two measures are similar. Table 2 shows the sub themes for each harm group based on our analysis. These findings are discussed below.

Table 2. Sub themes for each harm group.

Group	Sub themes
No harm	Gambling as just another leisure activity in financial terms
	A glue for maintaining and creating relationships
	A healthy leisure activity without emotional consequences or impact on work/study
Low harm	Gambling is still a way to build relationships
	Gambling is financially within budget, but the potential for regret appears
	Gambling can still bring emotional benefits, but also small regrets
Moderate harm	Gambling was still seen as something to bring them closer to other people
	Serious financial harms were experienced occasionally
	A range of negative emotional impacts (e.g. annoyed, guilty)
	Occasional health and work/study harms
High harm	Negative effects on finances (e.g. loss of all income, unwanted debt)
	Emotional strains caused by loss chasing
	Loss chasing affected their relationships with others
	Negative impacts on health experienced by a majority of this group
	Work/study affected for some high harm gamblers

Reflexivity statement

As researchers involved in the study of gambling-related harm, we acknowledge that our experiences and perspectives may have influenced the analysis and interpretation of the data. This research was, in part, designed to address issues raised by other researchers regarding gambling harms measures, such as the GHS-10, which some but not all of our team were involved in constructing. While we aimed to approach the data with an open mind and by following best qualitative research practices, our prior work in this field may have shaped our understanding of participants’ experiences.

It is important to note that we do not receive funding from the gambling industry, nor do we consider ourselves advocates for any particular position. Our goal is to contribute to a better understanding of gambling-related harm and its measurement through rigorous and transparent research. We also acknowledge that our geographical locations, cultural contexts and absence of any lived experience of gambling harm ourselves may have influenced our interpretations of the data.

Throughout the research process, we engaged in ongoing reflection and discussion as a team to minimize the impact of our individual biases and to ensure that our analysis remained grounded in the data. We believe that by explicitly acknowledging our positions and potential influences, we can provide readers with a more comprehensive understanding of the context in which this study was conducted.

Results

No harm

This group of seven gamblers reported experiencing no harms as a consequence of their gambling. Instead, gambling was a source of enjoyment for them, which they took part in due to its ability to enhance social activities and relieve stress. This is consistent with their ‘no harm’ categorization from the GHS-10.

Gambling as just another leisure activity in financial terms

None of this group reported any issues with their household budgets in managing the financial cost of gambling against other expenses. The financial sub theme for this group could be expressed in economic terms that their expenditure on gambling was an ‘opportunity cost’, in that it only reduced their potential expenditure on other consumer activities, to which gambling was actively preferred in the moments that it was chosen (Delfabbro and King 2019):

No as I say, I don’t think to me, there’s any detrimental effects other than the fact that I’m wasting my money. Some people collect stamps and spend a fortune on that (G10).

For this group, gambling was just another leisure activity, and there was no risk of spending more than they had intended to on gambling. In other words, they experienced no temptations to ‘chase their losses’ (Zhang and Clark 2020), and were able to keep their losses within affordable limits: ‘I can afford to have a go’ (G1) and ‘it’s like pocket money’ (G21):

Before I leave the house, I know whether I want to go or not. And if I feel like it’s gonna be a problem with my finances, I don’t go at all… If things were to get worse with my finances, I would easily completely change all the gambling that I’m doing (G12).

A glue for maintaining and creating relationships

Gambling was a positive for this group when it came to their relationships with other people. This positive effect on relationships is perhaps not surprising given that in financial terms gambling expenditure represented just another leisure activity for them. Leisure activities are often enjoyed because a shared experience can bring people together. The relationship sub theme for this group was that gambling was seen as something that brought them closer to groups of people as diverse as their partner, their family members, friends, and colleagues.

For some participants, gambling brought them closer to their partner and strengthened social bonds with others. This increased closeness could occur through a shared interest and a topic of conversation and friendly banter:

I guess my husband and I have bonded a lot more over that sport [NRL] now because we can actually have a conversation about the different players and what’s going on in different teams and that - outside of gambling (G30).

Colleagues and friends, and also me and my wife … dates, we come together, clubs, the RSL, we have dinner or something and then we go into the app and put some money into horses, yeah (G21).

It’s just a social thing, just something to do when you’re either with people, or even if you’re not … like my brother lives interstate so we’ll be on the phone or something and we might put a bet on or something at the same time and just like to bond over, I guess (G20).

A healthy leisure activity without emotional consequences or impact on work/study

Given that for this group, gambling was something that could always be kept within budget and helped bring them closer to other people, there were no perceived negative emotional consequences (‘Like I don’t get excited or sad or anything like that’; G11), and could act as a way of relieving stress, just like other recreational activities:

I would say: it is fun. Say after work, some sort of an excitement and fun, socialising. Takes out all the stress from work. When I go with my wife it doesn’t create any problems at all. We spend a lot of time together. It’s like a fun activity that takes out all the stress (G21).

Low harm

The eight gamblers in the low harm group scored 1 or 2 (out of 10) on the GHS-10. Their experiences were similar to the no harm group in that gambling was still seen as a fundamentally social activity which could relieve stress and came without any negative impacts on health or work/study. However, the chief novel theme in this group was that some low harm gamblers experienced some regrets over their level of financial expenditure, which had the potential to affect them emotionally.

Gambling is still a way to build relationships

As with the no harm group, most participants (five) in the low harm group saw gambling as something that brought them closer to family, friends and work colleagues:

The other positive I’ve had was playing two-up on ANZAC Day with my kids and we all had a good time. I think we lost about 10 bucks in the end … it wasn’t really a big gamble, but it was fun because it was ANZAC Day and it was an activity we did with the kids (G22).

For me a part is to make enough, or exaggerate enough, how the whole good feel, getting with people, laughing, being part of a crowd - when you live alone, it’s significant (G2).

Gambling is financially within budget, but the potential for regret appears

Gambling was still largely seen by the low harm group as a leisure activity, with gambling expenditure competing with other recreational activities in the ‘opportunity cost’ sense:

I see gambling as a recreational thing as well, so I mean if I’m spending on that then I’m not going to the movies. Or I’m not you know going out for dinner or something like that. Because I’ve spent it this way instead (G26).

However, one participant (out of eight) thought that all the money that she had spent on gambling might have brought greater satisfaction if it had gone on other recreational expenses, such as taking more holidays:

Part of me thinks ‘could that be spent on something else’? Like it’s not like I’m eating into mortgage money, but I think that frivolous money, could that be spent on something else, so it’s not like I’m spending our utilities money but it does go through my head that … if I add that up over the years what could I have spent that on … a trip away or something? (G24).

Gambling can still bring emotional benefits, but also small regrets

Two participants noted the emotional benefits from gambling, and how the benefits it brought them were overall worth the expenditure:

I go with the intention of ‘most of the times you’re gonna lose anyway’. So generally, I lose and I’m like ‘oh well that’s okay, I had a good time, we enjoyed ourselves, so it’s okay’ (G26).

In contrast, two other participants noted some small regrets about gambling losses, such as being ‘disappointed in myself’ (G22). However, the financial amounts were small, and they did not report any more severe harms such as damage to relationships or health, and nor did it affect their work/study:

And I think that’s my money that I’m allowed to spend so it’s kind of like a psychological merry go round. ‘Oh, I shouldn’t do that.’ ‘Oh, but it’s my money.’ ‘But oh, if only…’ (G24).

Moderate harm

The seven gamblers in the moderate harm group reported more negative experiences overall than those in the no harm and low harm groups. It is important to note that while these participants were categorized as ‘moderate’ based on their GHS-10 scores, some of them reported severe financial and emotional impacts that may be more typically associated with higher levels of harm. The PGSI scores of participants in this group (ranging from 1 to 8) also suggest a range of gambling severities within this category, with three of them being placed in the PGSI’s highest-risk category (8+; Ferris and Wynne 2001). Moderate harm gamblers still found that gambling was on average something that brought them closer to other people. However, financial harms in the moderate harm group moved beyond mere regrets; serious effects on household budgets were occasionally experienced by about half of the moderate harm group. Furthermore, moderate harm gamblers experienced a range of emotions from their gambling, but with a skew toward negative emotions. Moderate harm gamblers were also the first group to, upon occasion, report more severe harms to either health or work/study.

Gambling was still seen as something to bring them closer to other people

Like the no harm and low harm groups, moderate harm gamblers still saw gambling as something that on balance brought them closer to other people, and an activity that could help reduce feelings of loneliness. No participants in this group explicitly reported issues with their relationships with others occurring from gambling, whereas two participants explicitly reported benefits of increased social bonding from gambling:

There’s certainly positives. I think the biggest one is, for me is that social aspect. Like being a sports person, all your mates they’re interested in a certain type of sport. We always go ‘did you see the basketball last night’, ‘I need the Bucks to win tonight because it’s in me multi’, and then all of a sudden you wake up and did the Bucks win for me mate? … and ‘oh yeah that’s awesome’, ‘good on ya man’. So I think that’s probably biggest positive, more so than the money or anything (G16).

Well, it sort of gets me out and about, sort of a certain element of socialising – a little bit at the casino more at the pokie lounge, you have a chat with the regulars there and the nice girls make you a cup of coffee and come around with a little fruit salad and things like, so it just gets one out into the community a bit and chatting with other people (G19).

Serious financial harms were experienced occasionally

Just under half of participants (three) in the moderate harm group occasionally experienced serious financial harms which impacted their living situation. This was definitely a more severe pattern than was observed in the two previous groups. However, it is important to note that this unique financial-harm sub theme was only felt occasionally, and was generally not chronic:

I can think of one month, in particular, where I just wasn’t on a hot streak. I was on a cold streak, just got pumped and I remember like looking at the bank account like ‘god am I going down this again?’. Like ‘am I going down this path of really bad gambling?’ and I sat back and spoke to the missus about it … you just sorta went ‘okay we’re not gonna go out, you need to have a think about what you’re gambling on’ (G16).

Oh, actually, I did, and I found I had to get an advance on a pension. So, I haven’t done it since because it was humiliating, I hate the idea of borrowing money. I’ve always had enough to pay bills/everything, I’ve never had to … and I found it really shocking. So, I’m much more disciplined now (G6).

A range of negative emotional impacts

Compared to the two previous groups, moderate harm gamblers experienced a range of negative emotional impacts from their gambling. One participant explicitly mentioned the emotional benefits from gambling (‘It’s made time more pleasant’; G6). However, it was more common for participants in this group (three participants) to mention emotional difficulties from their gambling, including worry that they were losing control over their gambling (‘am I going down that same path again?’ G16) and guilt (‘a waste of time … I should’ve been doing something else’ G19). Negative emotions about their gambling were expressed by half of the group (four participants):

Generally, when I’m losing. During and then afterwards I get angry with myself and then I’m like ‘right it’s done, you gotta stop thinking about it’ because I just end up ruminating and getting annoyed and that feels terrible, so I do sort of put a cap on it and say, ‘right it’s done you just gotta forget about it’ (G27).

Occasional health and work/study harms

Finally, two participants mentioned more significant occasional harms on either their health or work/study, which are rarer harms (Browne and Rockloff 2018) that did not occur in either the no harm or low harm groups (‘Oh my god why did I spend, why did I do that, why did I do that? Then you can’t sleep.’; G6). For one participant, gambling led to a negative impact on their work:

Yes. That sort of relates back to the other thing of just spending too much time on it and feeling a bit guilty about it and that I should’ve been spending it on work or other things … because I’m at the pokie lounge or casino instead of at work (G19).

High harm

The eight gamblers in the high harm group all reported serious financial harms that affected their living situation, and these harms were often chronically reoccurring. Gambling losses caused all eight high harm gamblers to feel emotional strains, which could be magnified by periods of loss chasing or preexisting psychological vulnerabilities. Most high harm gamblers (six out of eight) reported that gambling negatively affected their relationships with members of their family, and also experienced negative effects on their sleep or health in general (five out of eight). High harm gamblers were also more likely to experience negative effects on their work/study than the lower risk groups (three out of eight).

Negative effects on finances

All eight participants in the high harm group reported negative effects on their finances from gambling. Compared to the negative financial effects reported by some participants in the low and moderate harm groups, the harms could be noticeably more severe in this group. Some participants in this group did report some similar financial harms to lower risk gamblers, such as expenditure exceeding the opportunity cost level. However, the unique sub theme in this group is how financial harms could also become much more severe, including the complete loss of discretionary spending power and savings for a period of years:

I lost basically all my income. So I was, I wouldn’t say ‘smart’, but I was cautious enough to not go above my budget… like I never went into a debt. I never spent what I didn’t have so I’m happy I never went down this alley. But I was able to calculate basically my next payday would be next Tuesday, I need to pay my rent blah blah blah, but I still have that much of the money, so sometimes I put my account into zero knowing that the next day will be a payday and that I will cover my rent. So yeah, it killed all my savings so for the time being that I had these gambling problems I haven’t been able to save for almost three years, four years (G28).

Furthermore, the chronic strain from repeated financial losses affected other high harm gamblers too and involved unwanted debt and also the unwanted expenditure of an inheritance. These are chronic strains that were not reported by any lesser harmed gamblers:

Yeah, so it was a few years ago that I guess gambling’s always one of those things that you think you’re always gonna win and I had a credit card that I sorta maxed out using to bet. And then eventually got to the point where I had to tell my wife so that was the main experience … I obviously ended up racking up a bit of debt that had to be paid off in the end (G29).

Quite an impact. I’d received some inheritance money, so I was using quite a bit of that. And unfortunately, that dwindled down (G7).

Emotional strains caused by loss chasing

All eight participants in the high harm group also felt emotional strains from their gambling. Although these participants could often feel moments of happiness after a big win, these positives were overall outweighed by the negative effects of losing. The unique emotional sub theme in this group was the emotional effects from periods of loss chasing, where attempts to recoup losses led to further losses and additional strain:

It did start to play on my mind a lot. Particularly as some of those losses were mounting. And I just felt like well there’s always another weekend and I’m sure we’ll get it right again. It did start to play on my mind. Especially when financially, I was sitting there looking at it going, ‘uh okay what I was expecting to happen financially hasn’t really worked out that way. And so now I’m going to have to dig us out of this’. Yeah, that’s where it was sort of the worst (G17).

But it was up and down up and down always with the anxiety that this is all the money that I lost. I wanna get it back so it was more of, um, yeah try to remedy the problem, but it was getting worse and worse (G28).

Loss chasing affected their relationships with others

The unique relationship sub theme in this group was how the financial losses and emotional strains from gambling could affect their relationships with others. This theme was expressed in various ways by six out of eight participants in this group. Importantly, for this group, gambling led to difficulties with others, either by a loss of attentional focus, or by the lies and deception brought on by loss chasing:

I guess it’s all around that thing when you’re not winning that you’re, yeah as I said before, you get angry, you get frustrated very easily, but yeah it affects your relationships with your family and friends and you sort of always sitting there on your phone, so people know something’s going on. And you’re always there wondering where you’re gonna get some more money to try and get your wins back and those type of things (G29).

They say ‘where have you been, how much did you spend?’, and then you go and dodge your way around that and had enough to get through the fortnight. It does cause you to tell lies, I guess (G8).

Negative impacts on health experienced by a majority of this group

A majority of participants in the high harm group (five out of eight) reported at least one significant health impact. For a majority of this five, the impact was felt through a negative effect on their sleep. However, their descriptions of the embodied nature of gambling’s effect on them were richer than what was provided by the single gambler in the moderate harm group. Their descriptions evoked the potentially all-encompassing nature of gambling related harm:

I would say sleep definitely because you would think about certain things, and you know gambling is a part of that. Eating potentially, you’d comfort eat to make yourself feel good again I suppose, but not so much in that space. It would be more so your sleep side of things and because you’ve got a load of wheels turning in your head obviously about a whole heap of life issues and that obviously compounds it and adds to it (G14).

Um, when I was gambling hard, unfortunately it became more of an addiction than a hobby that I enjoyed. So, my body was asking me to do it… And many time I would just wake up in the middle of the night with anxiety attacks (G28).

Work/study affected for some high harm gamblers

Finally, three participants in the high harm group mentioned how gambling affected them at work, which was a higher proportion of this group than the single participant in the moderate harm group. This highlights how high harm gamblers can experience their gambling related harm wherever they are. Although these participants may not have been gambling at work, the financial losses, associated worries, increased social isolation, and health impacts affected their performance at work:

And sometimes I lost focus and then I went into a place I was not allowed to go into, and then of course my managers would be like ‘what the hell are you doing in there?’ … Yeah. So I had to have a really massive stress to control, otherwise I would just have burst into tears in the middle of work, yeah (G28).

Yeah, so um I suppose distracted by bets that I had on, during office hours. So not primarily using office hours to do that activity but I might have had something that I’d put on previously or checking scores between meetings kind of thing. So, I found myself not being able to give full focus to what I was here to do which is worse. So that had a big impact on me (G14).

Discussion

Previous research has aimed to describe the distribution and extent of gambling related harm in the population (Raisamo et al. 2014; Browne et al. 2016, 2023; Salonen et al. 2016; Castrén et al. 2021; Muggleton et al. 2021; Tulloch et al. 2021). However, most of this research has used quantitative measures, such as the GHS-10, which has been criticized on the basis of face validity of some constituent items. Specifically, Delfabbro and King (2019) have argued that harms included in the GHS-10 might reflect non-substantive harms, or rational economic ‘opportunity costs’, or potentially lead to false negatives due to the multidimensional nature of gambling related harm (Langham et al. 2016). In order to address this and other potential critiques, the current research analyzed 30 semi-structured interviews across the spectrum of harm, in order to characterize the lived experience of those who fall into different ranges based on the GHS-10. In response to the opportunity cost critique, we found that only the no harm group had zero regrets about their level of gambling expenditure. This is the only group consistent with an opportunity cost explanation of gambling expenditure, as rational actors never regret their decisions (Varian 1999). Participants in all groups from low harm onwards had at least some regrets about their level of gambling expenditure.

The findings of this study have important implications for the use of the GHS-10 in clinical practice, research, and policy-making. By providing a qualitative validation of the scale’s harm categories, our results can guide the interpretation of GHS-10 scores and inform the development of more targeted interventions that address the specific needs and experiences of gamblers at different levels of harm. Moreover, the study highlights the value of incorporating qualitative methods in the assessment of gambling-related harm, as this approach can provide a more comprehensive understanding of the complex nature of harm and its impact on individuals’ lives. The present study also contributes to ongoing discussions about the conceptualization and measurement of gambling-related harm. The findings underscore the importance of considering the full spectrum of harm, including lower-level harms that may be viewed as opportunity costs rather than genuine harms. By providing a more nuanced understanding of the experiences of gamblers across different levels of harm, this study can inform the refinement of existing harm assessment tools and stimulate further research on the complex nature of gambling-related harm.

In accordance with previous findings that gambling can improve health and wellbeing for some people due to the psychological and social benefits derived from entertainment (Latvala et al. 2019; Rockloff et al. 2019), the no harm group described their gambling as just another leisure activity that they chose to spend modest amounts on, in preference to some alternative leisure activities. Gambling provided social benefits, being an enjoyable shared interest and pastime that strengthened family and friendship bonds. No negative emotional or vocational consequences were reported. In the low harm group, gambling was still said to be a shared social activity that was fun, strengthened relationships, and was financially affordable. However, the potential for regret appeared in this group’s accounts. Some participants felt guilt and had disappointments in themselves, and regrets that their gambling expenditure could have been used for more satisfying activities.

The moderate harm group generally reported that gambling was still a social activity with social benefits, but occasional serious financial harms were reported that impacted on household budgets. They also reported negative emotional responses to gambling, such as concern they were losing control over their gambling, and anger, annoyance and rumination over gambling losses. Some moderate harm participants also reported that gambling negatively affected their sleep or work. All participants in the high harm group reported serious, persistent and reoccurring financial impacts from their gambling, including loss of savings and debt. Chasing gambling losses was frequently reported, leading to emotional distress and strain on some personal relationships. Most high harm participants reported detriments to their health, such as anxiety and sleep disturbance. Some participants also reported that being distracted and stressed by gambling impacted on their work. These experiences reflect an increasing concentration in the higher harm groups of the individual costs of gambling identified in public health models (Latvala et al. 2019), including financial problems, impaired work performance, relationship problems, emotional stress, and physical symptoms. The findings of this study highlight the issues inherent in turning any continuous measure, such as gambling harm in this instance, into discrete categorical groups. While the GHS-10 provides a valuable tool for assessing gambling-related harm, the experiences reported by some participants in the moderate harm group suggest that there may be considerable variability within this category. The use of additional measures, such as the PGSI, can provide further context and help to capture the nuances of gambling-related harm.

Patterns in each domain of harm were observed across the four quantitatively assigned harm groups. The differing pattern of harms across groups can be understood in an item-theoretic sense; i.e. in terms of more severe symptomatology arising as the underlying degree of impact increases. However, given that the subjective experience of severe versus mild harm may be qualitatively very different, further research might investigate whether identifying meaningful thresholds could be of benefit to researchers and clinicians. Financial effects of gambling started at pure opportunity costs for the no harm group, proceeded to mild regrets for some in the low harm group, and then to occasional financial harms for those moderately harmed and finally chronic financial harms in the high harm group. Gambling had positive effects on gamblers’ relationships in the no and low harm groups, before becoming more neutral for moderate harm gamblers, and sharply negative for high harm gamblers. Emotional effects were either neutral or positive for no harm gamblers, small negatives appeared for low harm gamblers, before becoming more significant for moderate harm gamblers. All high harm gamblers experienced quite severe negative emotional effects. Health harms were only first reported for one moderate harm gambler and were experienced by most high harm gamblers. Work/study harms were quite similar to health harms, although were perhaps slightly less common. Overall, the lived experience of gambling harm across all domains of harm became noticeably more severe as GHS-10 scores increased.

Limitations

For a qualitative study, the sample of 30 can be considered sizeable and is a strength of the research. However, the study also has limitations. The sample sizes for each harm group in this study may be considered relatively small for qualitative research despite the sample size of 30 participants generally considered as adequate for achieving saturation in qualitative studies, particularly when the research focuses on a specific, well-defined topic (Guest et al. 2006). In this study, the use of semi-structured interviews with a focus on gambling-related harm allowed for a targeted exploration of the topic, increasing the likelihood of reaching saturation. Nevertheless, the smaller sample sizes within each harm group may limit the generalizability of the findings and the ability to capture the full range of experiences within each group. The experience of gambling harms can be idiosyncratic, and despite the healthy sample size, we did not observe concrete evidence of saturation. The sample size per harm group is smaller, and this increases the risk that differences between the harm groups may reflect random fluctuations in sampling rather than genuine differences between the harm groups.

Our priority in the conduct of the interviews was to ask non-leading and non-loaded prompting questions. However, the study authors have attempted to reflect on how their own position in the production of gambling-related harm research may have affected the interviews and the conclusions drawn from them. Nevertheless, all qualitative research contains an aspect of subjectivity, and these results should also be replicated by other investigators. In particular, replication across different populations is important, as these results may be specific to the location, time, or characteristic demographics of the Australian participants. Participants for the initial study were originally recruited with the help of a panel provider for an earlier quantitative study, and this may have also impacted the obtained results. Recruitment of gamblers more directly from the community may help ameliorate potential concerns around participants who take part in gambling research in return for financial compensation (Pickering and Blaszczynski 2021).

Gambling stigma can be a concern in qualitative as well as quantitative research, so there is no way to completely eliminate this issue in research with recruited participants, with the analysis of anonymous online peer support forums being one rare instance of data where stigma is less of a limitation (Rodda et al. 2018; Van Baal et al. 2023). In the present study we attempted to mitigate the impact of stigma through several strategies. Participants were specifically recruited to discuss their experiences with gambling, which may have attracted individuals who were more open to sharing their experiences. Participants were also assured of anonymity and confidentiality, which may have encouraged more honest and open responses. Despite this, we still do not know the extent to which participants may have still underreported their experiences due to stigma. This should be considered when interpreting the results of this study.

As a final limitation, stratification was only performed over GHS-10 group. Although participants’ GHS-10 and PGSI scores had a high positive correlation, we did not explore sub theme variation across PGSI categories. Obtaining an accurate and unbiased picture of the experiences of affected gamblers demands triangulation of data from multiple methodologies. Future studies should continue to use a range of methodologies to explore gambling related harm beyond self-report surveys, such as the use of anonymous bank data (Muggleton et al. 2021; Marionneau et al. 2023).

Conclusion

An exclusive focus on quantitative self-report measures of gambling harm can lead to uncertainty as to what the scores genuinely mean in terms of the lived experience of those experiencing the impacts. Semi-structured interviews can be thought of as a form of ‘ground truth’ with which to evaluate these scores. We found that increasing GHS-10 scores accorded closely with more negative descriptions of interactions with gambling given by the gamblers themselves. Those scoring zero reported positive effects and almost no negative impacts, but individuals with higher positive scores tended to report increasingly serious financial, emotional and relationship issues, with those scoring the highest also reporting health and work/study problems.

This qualitative study provides a novel contribution to the field of gambling research by validating the GHS-10's harm categories through an exploration of gamblers’ lived experiences. The findings highlight the alignment between the scale’s categories and the experiences of gamblers across different levels of harm, supporting the validity of the GHS-10 as a tool for assessing gambling-related harm. Moreover, the study demonstrates the value of incorporating qualitative methods in the study of gambling-related harm, as this approach can provide a more nuanced understanding of the complex nature of harm and inform the development of more targeted prevention and intervention strategies. The results also shed a new light on the spectrum of gambling related harm, and illustrate how a mixed methods approach can improve the understanding of gambling related harm. Importantly, the study found that gamblers nominating only 1 or 2 harms on the GHS-10 expressed some guilt, disappointments or regret about their gambling. This finding undermines the argument that the GHS-10 measures opportunity costs and not real negative consequences from gambling.

Disclosure statement

PN is a member of the Advisory Board for Safer Gambling – an advisory group of the Gambling Commission in Great Britain, and in 2020 was a special advisor to the House of Lords Select Committee Enquiry on the Social and Economic Impact of the Gambling Industry. In the last three years, PN has contributed to research projects funded by the Academic Forum for the Study of Gambling, Clean Up Gambling, Gambling Research Australia, NSW Responsible Gambling Fund, and the Victorian Responsible Gambling Foundation. PN has received travel and accommodation funding from Alberta Gambling Research Institute, and received open access fee funding from Gambling Research Exchange Ontario. VR has received research funding from Gambling Research Australia, the New South Wales Responsible Gambling Fund, and the Victorian Responsible Gambling Foundation. He declares no conflicts of interest in relation to this manuscript. NH has received funding in the last five years from Gambling Research Australia, the Victorian Responsible Gambling Foundation, the NSW Responsible Gambling Fund and NSW Office of Responsible Gambling, the New Zealand Ministry of Health, the South Australian Office for Problem Gambling, Australia’s National Research Organization for Women’s Safety, and the Alberta Gambling Research Institute. She declares that she has no conflicts of interest in relation to this manuscript. MB has received research funds from the Gambling Research Australia, Victorian Responsible Gambling Foundation, Queensland Government Department of Health, South Australian Government, Australian Department of Social Services, and the New Zealand Ministry of Health. He declares no conflicts of interest in relation to this manuscript. AR has received funding from Victorian Responsible Gambling Foundation; New South Wales Office of Responsible Gambling; South Australian Government; Gambling Research Australia; New Zealand Ministry of Health; Australian Communications and Media Authority and the Alberta Gambling Research Institute. He has had travel expenses paid to present research by the Victorian Responsible Gambling Foundation, PsychMed and the Hawthorn Hawks Football Club Players Association. He has received an honorarium from Movember for assessing applications for funding and consulting fees from the Victorian Responsible Gambling Foundation. He declares no conflicts of interest in relation to this manuscript. EL has received research grants from the Victorian Responsible Gambling Foundation and Gambling Research Australia. He declares that he has no conflicts of interest in relation to this manuscript. MR has received research funds from Gambling Research Australia, Victorian Responsible Gambling Foundation, Queensland Treasury, Victorian Treasury, NSW Responsible Gambling Fund, NSW Office of Liquor & Gaming, Tasmanian Department of Treasury and Finance, New Zealand Ministry of Health, Department of Families, Housing, Community Services and Indigenous Affairs, Alberta Gambling Research Institute and the First Nations Foundation. He declares no conflicts of interest in relation to this manuscript. GD declares no conflicts of interest in relation to this manuscript.

Additional information

Funding

This research was funded and supported by the Victorian Responsible Gambling Foundation. The funding body had no role in the design of the study, analysis, interpretation of data, or writing the manuscript.

Notes

1 Gambling included participating in at least one of the following activities within the past 12 months: race betting, electronic gaming machines, casino table games, sports betting, informal private betting for money, Keno, bingo, esports betting and fantasy sports betting.