The evaluation of treatment outcomes has, until recently, been dominated by a nomothetic approach. However, a growing body of expert opinion has recommended that idiographic, or individualised, information should also be used for outcome measurement purposes (Ashworth et al.
2019; Alves et al.
2015; Neale and Strang
2015). Combining nomothetic and idiographic approaches has been described as an ‘optimal way of understanding and measuring patient reported outcomes of addiction and its related constructs’ (Neale and Strang
2015, p. 1216). However, little is known about the psychometric properties of individualised outcome measures when tested within the context of substance misuse treatment services and the validity of self-reported outcomes in this setting.
Broadly speaking, outcome measures aim to quantify changes that occur in a patient’s clinical status over a course of treatment. The commonest strategy involves the use of standardised outcome measures, based on pre-set questions administered to a group of patients. The standardised structure of these measures allows for mechanisation of the outcome measurement process, since all individuals are presented with the same pre-determined questions (OECD
2013). The generation of large-scale data from standardised instruments has given these measures a golden status in the field of outcome evaluation (Evans et al.
2000).
In recent years, individualised outcome measures have gained ground in health care (Fitzpatrick et al.
1998) for a number of reasons. First, they provide patients with an opportunity to indicate items to evaluate the outcome of their treatment (Barkham
2016); second, they allow patients to rate the intensity or level of distress caused by their own problem, corresponding to their priorities (Elliott et al.
2016; Sales and Alves
2012,
2016); third, they have a greater sensitivity to clinical change than standardised outcome measures (Ashworth et al.
2009; Elliott et al.
2016); fourth, they are likely to capture information overlooked by standardised measures (Alves et al.
2018); and fifth, patients value the opportunity to define and express their own range of concerns (Alves et al.
2016); sixth, there is recognition of the clinical utility of PQ and PSYCHLOPS, since both contain items of high relevance for patients (Ashworth et al.
2005; Sales et al.
2007); and seventh, therapist satisfaction has also been reported for both measures for a variety of clinical tasks including outcome assessment (Sales et al.
2007; Sales and Alves
2012).
For Lambert and Hawkins (
2004), to be appropriate, outcome measures must be ‘psychometrically strong, applicable and practical’ (p. 493). A growing body of literature has explored these properties among individualised outcome measures. These studies have focused mostly on the Simplified Personal Questionnaire (PQ; Elliott et al.
2016) and the Psychological Outcome Profiles (PSYCHLOPS; Ashworth et al.
2004). PQ and PSYCHLOPS are individualised measures targeting general psychological distress, based on items generated by patients, and widely used in mental health care (Sales and Alves
2016).
Regarding psychometric properties, both PQ and PSYCHLOPS have demonstrated reliability and validity within a range of mental health settings (e.g. university counselling units, mental health primary care) (Ashworth et al.
2009; Elliott et al.
2016). However, further studies to extend psychometric testing are required to diminish scepticism about the use of individualised measures (Elliott et al.
2016).
Substance misuse treatment is one of the fields where individualised measures have been little explored. In this client group, outcome measurement tends to focus on specific drug-related issues, as well as psychosocial variables, including general psychological distress and specific problems such as depression or suicidal thoughts (Darke et al.
2007; Gossop et al.
2003; Jones et al.
2009; Wanigaratne et al.
2005). Outcomes tend to be assessed with standardised instruments and it is unknown whether individualised outcome measures in this context are feasible and psychometrically robust for outcome measurement purposes, as observed in other fields (Alves et al.
2015).
The first recorded use of PQ and PSYCHLOPS in a substance misuse treatment setting was in Portugal in 2013 and has formed the basis of a longer term study which includes the present study (Alves et al.
2013). Preliminary findings show that patients value these measures for being easy to understand; helping them to reflect about personal difficulties; providing them with freedom to talk about problems, related or not to substance misuse; and making them ‘feel like normal people’ (Alves et al.
2016). As a downside, patients reported that the level of self-exposure required by these instruments was sometimes uncomfortable and might contribute to non-completion (Alves et al.
2016). This project also revealed that PQ and PSYCHLOPS elicit problems overlooked by standardised measures (Alves et al.
2018). For instance, more than two-thirds of themes indicated by patients in these individualised measures were absent from the Treatment Outcomes Profile (TOP; Marsden et al.
2008), including problems such as ‘money worries’ and ‘self-image/self-worth’ (Alves et al.
2018). The present study builds on these findings by exploring the feasibility of PQ and PSYCHLOPS, as well as their psychometric properties in this sample.
Study Rationale
The current study focussed mainly on the feasibility and psychometric properties of PQ and PSYCHLOPS and standardised comparators. Additionally, we explored potential factors that may influence PQ and PSYCHLOPS scores (e.g. socio-demographic, substance misuse, treatment history and other variables of interest), to gain further knowledge about the psychometric value of these instruments. We also aimed to contrast the scorings obtained with PQ and PSYCHLOPS, since both are individualised measures albeit with different characteristics (e.g. mode of administration). To our knowledge, this is the first study to explore these three questions within the context of substance misuse services.
Methods
This was a cross-sectional study with a sample of adult patients entering treatment in four services for drug and alcohol substance misuse in Portugal, between July 2013 and May 2015. Approval was granted by the Committee for Health of Lisbon and surrounding areas (ARSLVT, Ref. 8251/CES/2012).
Participants
The sample comprised of patients aged 18 years and older, who were starting a treatment episode (i.e. first episode or treatment of a relapse) and were fluent in Portuguese. We excluded patients who were not motivated to participate or were too distressed to complete the evaluation protocol. This decision was made by researchers in consultation with the administrative/clinical staff available. We calculated our proposed sample size based on previously reported alpha scores of .80 for PSYCHLOPS, with 114 patients, and .86 for PQ, with 72 patients (Ashworth et al.
2009; Elliott et al.
2016). Based on these findings, we sought to recruit a sample of 100 patients. Of the 102 individuals who met the inclusion criteria, 94 (92%) consented to participate. One was excluded because of non-completion of PQ and PSYCHLOPS, resulting in a final sample of 93 patients.
Procedure
Researchers invited patients attending the treatment centres to take part in the study prior to commencing treatment. Written consent was obtained and participants completed the evaluation protocol immediately prior to the first treatment session.
Patients were presented with the evaluation protocol containing the five outcome measures, followed by a socio-demographic and treatment history form. Patients were offered assistance if they needed additional help with self-completion questionnaires. We randomised the order in which instruments were presented to patients, to control for sequencing effects and avoid bias arising from patient responses in one instrument influencing responses in a subsequent instrument. The presentation order of TOP was not randomised. TOP was invariably presented at the end of the protocol because it focusses specifically on drug-related topics and little or no influence was expected.
Results
The 93 patients who participated in our study consisted of a higher proportion of men (59%); the mean age was 43 years (SD = 11). Tables
1,
2 and
3 show further characteristics of the sample, as well as their substance use and treatment history, respectively.
Table 1
Patient characteristics (N = 93)
Relationship status | Single | 45 (48.4%) |
Married/cohabiting | 19 (20.4) |
Divorced/separated | 29 (31.2%) |
Educational level | Illiterate | 3 (3.2%) |
Literate, but not completed primary school | 1 (1.1%) |
Basic school (years 1–9) | 64 (68.8%) |
Secondary school (years 10–12) | 15 (16.1%) |
University (years > 12) | 10 (10.8%) |
Employment status | Paid work (full-time/part-time) | 26 (28.0%) |
Unemployed | 52 (55.9%) |
Retired | 8 (8.6%) |
Other (e.g. housewife/househusband) | 7 (7.5%) |
Accommodation status | Rented/owned house | 84 (90.3%) |
Temporary accommodation (e.g. guesthouse) | 1 (1.1%) |
Homeless | 2 (2.2%) |
Shared supported accommodation (e.g. community shelters) | 6 (6.5%) |
Table 2
Substance misuse—age of onset and usage in the last 12 months (N = 93)
Alcohol | Age of onset | 16.5 (7.7) | 58 (62.4%) |
Used in the last 12 months (yes) |
Heroin | Age of onset | 20.2 (6.7) | 10 (10.8%) |
Used in the last 12 months (yes) |
Cocaine (powder) | Age of onset | 20.3 (6.7) | 4 (4.3%) |
Used in the last 12 months (yes) |
Crack cocaine | Age of onset | 28.0 (12.8) | 1 (1.1%) |
Used in the last 12 months (yes) |
Cannabis | Age of onset | 14.7 (2.5) | 14 (15.1%) |
Used in the last 12 months (yes) |
Ecstasy | Age of onset | 16.3 (1.7) | 1 (1.1%) |
Used in the last 12 months (yes) |
Tobacco | Age of onset | 14.1 (3.3) | 58 (62.4%) |
Used in the last 12 months (yes) |
Table 3
Substance misuse treatment history
First treatment episode | 49 (52.7%) |
Type of previous treatment | Psychological treatment | 15 (17.4%) |
Opioid substitution treatment | 7 (8.1%) |
Alcohol dependence medication | 11 (12.8%) |
Inpatient therapeutic community | 13 (15.1%) |
Detoxification unit | 17 (19.8%) |
Self-help groups | 4 (4.7%) |
Feasibility of Individualised vs. Standardised Outcome Measures
The mean time required for completion of the five instruments within the evaluation protocol was 30.1 min (SD = 11.4, range 10–61 min). Regarding the acceptability, the number and proportion of patients who responded to each instrument were as follows: PQ, 92 (99%); PSYCHLOPS, 88 (95%); CORE-OM, 92 (99%); PHQ-9, 93 (100%); TOP, 90 (97%). Concerning the mode of administration, PQ and TOP were delivered in an interview-based format, as required by their instructions. The self-report tools often required research administrator completion. PSYCHLOPS was administered orally to 37 (41%) patients, CORE-OM to 36 (40%) patients and PHQ-9 to 35 (39%) patients. Patients requested assistance because of literacy issues, self-reported anxiety and poor sight.
Descriptive Analyses of PQ and PSYCHLOPS Mean Scores
The mean number of items in PQ was 2.9 (SD = 2.1), range 1 to 12. The mean severity score for PQ items was 5.3 (SD = 1.7). Eighty-two (89%) patients had mean PQ severity scores above the clinical cutoff value of 3.25 points, as defined in Elliott et al. (
2016). Problems described in PQ had lasted, on average, 1 to 2 years; however, the longest duration problem was 3 to 5 years.
For PSYCHLOPS, the mean number of patient-generated items (P1 + P2 + function) was 2.3 (SD = .8), range 0 to 3 items. The mean item severity scores were as follows: problems, 7.1 (SD = 2.9, range 0–10); function, 3.4 (SD = 1.7, range 0–5); well-being, 2.3 (SD = 1.8). The mean total PSYCHLOPS score was 13.8 (SD = 4.9, range 0–20). Even though we collected 88 PSYCHLOPS, the total score could only be computed for 58 (66%) because of insufficient data (i.e. two problems missing and/or function, and/or well-being item missing). The duration of problems reported in PSYCHLOPS was 3 months to 1 year. In this sample, the PSYCHLOPS problem of the longest duration was 1 to 5 years.
Internal Reliability of PQ and PSYCHLOPS Mean Scores
Both individualised measures showed good internal reliability, with alpha scores for PQ of .79 (mean) and for PSYCHLOPS .72 (Table
4).
Table 4
Internal reliability (Cronbach’s alpha) of PQ and PSYCHLOPS
PQ | PQ items 1–2 | PQ items 1–3 | PQ items 1–4 | PQ items 1–5 | Mean (SD) |
.69 | .75 | .83 | .88 | .79 (.09) |
PSYCHLOPS | Problem items 1–2 | Problem + functioning items 1–3 (individualised component) | All items 1–4 (individualised items + standardised item) |
.42 | .69 | .72 |
Convergent Validity of PQ and PSYCHLOPS vs. Standardised Outcome Measures
Table
5 shows the correlation matrix between the five instruments. We found a weak and significant convergence between PQ and PSYCHLOPS (
r = .28) total scores. Correlations between PQ and PSYCHLOPS problem scores were similar when self-completed (
r = .25) or when researcher administered (
r = .25). The correlations between PQ and the total scores of CORE-OM, PHQ-9 and TOP (psychological health) were weak at .27, .22 and .21 respectively (see Table
5). In contrast, correlations between CORE-OM, PHQ-9 and TOP (psychological health) with PSYCHLOPS were moderate at .50, .39 and .40, respectively.
Table 5
Convergent validity of PQ and PSYCHLOPS with CORE-OM, PHQ-9 and TOP
PSYCHLOPS | Problems | .35** | | | | |
Functioning | .23 | .53** | | | |
Well-being | .17 | .39** | .27* | | |
Total score | .28** | .89** | .73** | .70** | |
CORE-OM | Problems | .31** | .39** | .38** | .49** | .48** |
Functioning | .12 | .20 | .31* | .53** | .39** |
Well-being | .30** | .41** | .35** | .52** | .49** |
Risk | .19 | .32** | .16 | .37** | .37** |
Total score | .27** | .38** | .37** | .54** | .50** |
PHQ-9 | | .22* | .39** | .28* | .52** | .39** |
TOP | Psychological health | − .21 | − .33** | − .12 | − .60** | − .40** |
Physical health | − .12 | − .15 | − .01 | − .26* | − .07* |
Quality of life | − .24* | − .30** | − .30* | − .48 | − .44** |
Association Between PQ/PSYCHLOPS Scores and Demographic and Clinical Variables
Discussion
Previous findings have demonstrated the importance of PQ and PSYCHLOPS as sources of qualitative, personalised information about patients undergoing treatment for substance misuse (Alves et al.
2018). The present study adds to that body of literature by providing estimates about the practicability, reliability and validity of such individualised outcome measures in this context.
Are Individualised Measures Feasible for Use in Substance Misuse Treatment?
We found that the administration of the whole evaluation protocol took approximately 30 min (i.e. approximately half the typical duration of a clinical session). This meant that individualised measures were completed relatively quickly, suggesting that adopting one or other of these measures might not be a burden in real clinical settings. Replicating previous findings in a primary care mental health setting (Ashworth et al.
2005), the completion rates of individualised measures were above 90%, demonstrating high levels of patient acceptability and comparable to completion rates of the standardised measures included in our study, showing that both types of measures are equally received by patients. However, nearly half our sample missed at least two responses in PSYCHLOPS, hindering the calculation of total scores and raising concerns about its feasibility as a self-report instrument. This was a low number in comparison with previous studies, where more than 90% of patients’ responses to PSYCHLOPS allowed total score calculation (Ashworth et al.
2004,
2005,
2009). In other studies, PSYCHLOPS has been administered as an interview measure, to ensure no missing data in populations with literacy issues (Harper Shehadeh et al.
2019).
Regarding the mode of administration, although designed to be self-completed, almost half the sample asked for PSYCHLOPS to be researcher administered. This may have been due to low literacy skills, high levels of patient distress on entering treatment and patients may have felt more supported by being able to talk about their problems during assessment (Harper Shehadeh et al.
2019). Patients reported higher severity scores in the written format, implying that they might feel less comfortable verbalising their distress or that responses may be moderated by perceptions of social disapproved, or even illegal, behaviours. Although contradictory, our results were consistent with Bowling’s observation (Bowling
2005) that interviewer-based methods are likely to increase response accuracy, but self-report questionnaires may encourage the sharing of more sensitive information. Conversely, no difference was observed between self-report or researcher administered scores on the standardised measures CORE-OM and PHQ-9.
Overall, our findings indicate that PQ and PSYCHLOPS are practicable in substance misuse treatment settings. Nearly all patients invited to participate in the study were motivated to complete the individualised measures, even though not all responded to them in the expected format. In particular, there were many patients requesting the instruments to be administered verbally by the researcher. This suggests that, even when self-report measures such as PSYCHLOPS are selected, researchers and clinicians may have to enhance their interview skills to ensure that data collection is not negatively affected for patients requesting assistance.
Do Individualised Measures Generate Robust Psychometric Data?
Both PQ and PSYCHLOPS elicited fewer items than when used in other clinical populations. For instance, in Elliott et al. (
2016), the mean number of items created across five samples of patients in general mental health treatment was 10, compared with three items in the present study. Similar findings were reported in the previous section, when we observed that patients in our sample tended to omit PSYCHLOPS items more often than other samples (Ashworth et al.
2004, 2007,
2009). When combined, these results indicate that substance misuse patients provide less information in individualised measures than other clinical populations. Further research is needed to explore why this occurred. However, we hypothesise that being admitted for a specialist treatment, targeting a specific behaviour, might have led patients to think that it was inappropriate, or unnecessary, to disclose too much information about their lives. On the other hand, item scores and mean problem duration were similar to those reported in previous studies (Ashworth et al.
2005; Elliott et al.
2016), indicating that patients experience similar levels of psychological distress as in other generalist mental health samples, emphasising the importance of addressing psychological health in this population (Wanigaratne et al.
2005).
Concerning psychometric properties, our analyses revealed good internal reliability for PQ and PSYCHLOPS in the context of substance misuse therapy. Such reliability values were similar to those previously reported in Elliott et al. (
2016) (.86) and Ashworth et al. (
2005) (.79). On the other hand, the convergence between individualised and standardised outcome measures was weak to moderate. This might reflect the diversity of problems experienced by our sample of patients, often unrelated to health and including concerns such as housing or finances not covered by the standardised comparators used (Alves et al.
2007,
2018). PSYCHLOPS correlated more strongly with standardised measures than did PQ. This might be a feature of the structural characteristics of PSYCHLOPS which is a hybrid instrument containing one standardised well-being item which correlated more strongly with the standardised measures, whilst PQ is a pure patient-generated instrument, only containing personalised items.
A weak correlation was found between the two individualised measures. This was expected for several reasons: the different structures of PQ and PSYCHLOPS may have prompted patients to respond differently to both measures; a previous study (Alves et al.
2018) had already found that patients tend not to repeat items/problems when answering both instruments as part of the same evaluation protocol. Moreover, the original self-report format of PSYCHLOPS was altered to an interview format in approximately half of the sample. Considering that the information provided in a questionnaire depends on its administration mode (Bowling
2005), it is unknown how much PSYCHLOPS responses were affected by researcher completion. It remains possible that differences also arose because these instruments were measuring differing underlying constructs, in spite of both focussing on patient-reported ‘problems’.
To sum up, even though individualised measures produce reliable measurements, their weak to moderate correlation with standardised measures suggests that they should complement standardised instruments rather than being used alone. Combining individualised and standardised measures has been suggested by authors working in other treatment contexts and may enhance their potential for outcome measurement (Barkham
2016; Sales and Alves
2012; Sales et al.
2014). As Möller (
2009) put it, whilst standardised measures can objectively quantify psychological constructs, individualised information is able to capture “distinctive characteristics of individuals” (p. 2016), giving a more meaningful context to the numbers obtained with standardised tools.
Which Individual or Treatment Characteristics May Influence PQ and PSYCHLOPS Scores?
Patients with past experience of substance misuse treatment were more likely to present higher distress in PQ and PSYCHLOPS, in comparison with those starting their first treatment episode. On the one hand, relapse may be particularly associated with distress and disruptive situations; also, patients who dropped out of previous treatment episode(s) without a successful therapeutic result may be more likely to have unresolved personal issues reported as problems on the individualised measures. Ramos and Brown (
2008) identified that, among substance misusers, the main reasons leading to substance misuse and relapse are social situations, coping with negative emotions and interpersonal conflicts. These types of concerns were reported by the same sample in PQ and PSYCHLOPS (Alves et al.
2018), which is in line with our findings.
Regarding the age of onset of drug use, our study was partly in line with the literature, which has reported that the younger individuals start to use drugs, the more severe their drug-related problems (Hser et al.
2007). In support of this was the negative correlation between age of first use of cannabis and PQ; and first use of LSD and PSYCHLOPS. However, for crack and LSD in PQ and ecstasy in PSYCHLOPS, the reverse was true. For these patients, it is likely that other bio-psycho-social factors may have contributed for their dependence disorder, reinforcing the importance of a multidimensional evaluation of clinical status (Alves et al.
2018). Divergence in total PQ and PSYCHLOPS scores according to age of first use for different substances indicates that they may be measuring different aspects of patient distress.
Limitations
The main limitation of our study is that it has not included post-treatment scores. Contrasting pre-post treatment data would allow an estimation of further psychometric parameters of PQ and PSYCHLOPS, such as sensitivity to change and temporal structure. High sensitivity to change is a central characteristic of patient-generated instruments and requires further evaluation within the context of dependence disorders (Ashworth et al.
2009; Elliott et al.
2016). Feasibility could be explored further by comparing patient and staff preferences for different combinations of instruments. Further feasibility comparisons could be made between pre-therapy and during-therapy administration of both patient-generated instruments since each adopts a different format after the start of therapy, with PQ only rating severity and PSYCHLOPS changing to a during-therapy version. We only collected the administration time for the entire protocol. Separate times would have provided a better estimate of individualised measures’ length and how they compare to their standardised counterparts. Moreover, we did not evaluate the quality of the items produced by patients in PQ and PSYCHLOPS which may have contributed to divergent results.
Conclusion
With this study, we have confirmed that individualised measures are feasible and reliable to use as outcome measures in substance misuse treatment, in line with previous studies on the psychometrics of PQ and PSYCHLOPS in other settings (Ashworth et al.
2005,
2009; Elliott et al.
2016). Convergent validity between individualised and standardised measures was weak to moderate, suggesting that standardised and individualised measures may be measuring different aspects of patient distress.
A further finding was the weak correlation between PQ and PSYCHLOPS and the variability of results produced by them, when in fact these measures were expected to measure distress due to similar constructs—patient’s individual concerns. Researcher and self-administered modes of completion may have influenced item generation, potentially leading to the differences between the scorings of PQ and PSYCHLOPS. The possibility remains that the two individualised measures were measuring different aspects of patient distress.
In summary, our study suggests that PQ and PSYCHLOPS contribute to the measurement of patient distress in substance misuse treatment. Both individualised measures are reliable and have high levels of patient acceptability. Low to moderate convergence with standardised instruments suggests that optimal outcome measurement may involve combining individualised and standardised measures since this may broaden the capture of underlying constructs.
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