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Background: Psychological models predict behaviour in a wide range of settings. The aim of this study was to explore the usefulness of a range of psychological models to predict the health professional behaviour 'referral for lumbar spine x-ray in patients presenting with low back pain' by UK primary care physicians. Methods: Psychological measures were collected by postal questionnaire survey from a random sample of primary care physicians in Scotland and north England. The outcome measures were clinical behaviour (referral rates for lumbar spine x-rays), behavioural simulation (lumbar spine x-ray referral decisions based upon scenarios), and behavioural intention (general intention to refer for lumbar spine x-rays in patients with low back pain). Explanatory variables were the constructs within the Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-Regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Weinstein's Stage Model termed the Precaution Adoption Process (PAP), and knowledge. For each of the outcome measures, a generalised linear model was used to examine the predictive value of each theory individually. Linear regression was used for the intention and simulation outcomes, and negative binomial regression was used for the behaviour outcome. Following this 'theory level' analysis, a 'cross-theoretical construct' analysis was conducted to investigate the combined predictive value of all individual constructs across theories. Results: Constructs from TPB, SCT, CS-SRM, and OLT predicted behaviour; however, the theoretical models did not fit the data well. When predicting behavioural simulation, the proportion of variance explained by individual theories was TPB 11.6%, SCT 12.1%, OLT 8.1%, and II 1.5% of the variance, and in the cross-theory analysis constructs from TPB, CS-SRM and II explained 16.5% of the variance in simulated behaviours. When predicting intention, the proportion of variance explained by individual theories was TPB 25.0%, SCT 21.5%, CS-SRM 11.3%, OLT 26.3%, PAP 2.6%, and knowledge 2.3%, and in the cross-theory analysis constructs from TPB, SCT, CS-SRM, and OLT explained 33.5% variance in intention. Together these results suggest that physicians' beliefs about consequences and beliefs about capabilities are likely determinants of lumbar spine x-ray referrals. Conclusions: The study provides evidence that taking a theory-based approach enables the creation of a replicable methodology for identifying factors that predict clinical behaviour. However, a number of conceptual and methodological challenges remain. [ABSTRACT FROM AUTHOR]

Among health professionals, there is wide variation in the practice of disclosing a diagnosis of dementia to patients. The purpose of this study was to evaluate the effect of one theory-based and two pragmatic interventions on intention to perform three behaviors, namely (1) finding out what the patient already knows or suspects about their diagnosis; (2) using the actual words “dementia” or “Alzheimer’s disease” when talking to the patient (i.e., the use of explicit terminology); (3) exploring what the diagnosis means to the patient. Within an intervention-modeling process, members of old-age mental health teams in England were sent postal questionnaires measuring psychological variables. Respondents were randomized by team to one of four groups to receive: theory-based intervention; evidence-based communication; patient-based intervention; or no intervention (control). Interventions were delivered as pen-and-paper exercises at the start of a second postal questionnaire that remeasured the same psychological variables. The outcome measures were intention and scenario-based behavioral simulation. Responses were received from 644 of 1,103 (58%) individuals from 179 of 205 (87%) mental health teams. There were no significant differences in terms of intention or simulated behavior between the trial groups. The theory-based intervention significantly increased scores for attitudes to ( p = 0.03) and perceived behavioral control ( p = 0.001) for the behavior of “finding out what the patient already knows or suspects about their diagnosis.” The intervention had a limited effect. This may be partly explained by clinical or methodological factors. The use of a systematic intervention modeling process allows clearer understanding of the next appropriate steps which should involve further evaluation of the interventions using an interactive delivery method in a less selected group of study participants. [ABSTRACT FROM AUTHOR]

Background: Following the introduction of a computerised diabetes register in part of the northeast of England, care initially improved but then plateaued. We therefore enhanced the existing diabetes register to address these problems. The aim of the trial was to evaluate the effectiveness and efficiency of an area wide 'extended,' computerised diabetes register incorporating a full structured recall and management system, including individualised patient management prompts to primary care clinicians based on locally-adapted, evidence-based guidelines. Methods: The study design was a pragmatic, cluster randomised controlled trial, with the general practice as the unit of randomisation. Set in 58 general practices in three Primary Care Trusts in the northeast of England, the study outcomes were the clinical process and outcome variables held on the diabetes register, patient-reported outcomes, and service and patient costs. The effect of the intervention was estimated using generalised linear models with an appropriate error structure. To allow for the clustering of patients within practices, population averaged models were estimated using generalized estimating equations. Results: Patients in intervention practices were more likely to have at least one diabetes appointment recorded (OR 2.00, 95% CI 1.02, 3.91), to have a recording of a foot check (OR 1.87, 95% CI 1.09, 3.21), have a recording of receiving dietary advice (OR 2.77, 95% CI 1.22, 6.29), and have a recording of blood pressure (BP) (OR 2.14, 95% CI 1.06, 4.36). There was no difference in mean HbA1c or BP levels, but the mean cholesterol level in patients from intervention practices was significantly lower (-0.15 mmol/l, 95% CI -0.25, -0.06). There were no differences in patient-reported outcomes or in patient-reported use of drugs, or uptake of health services. The average cost per patient was not significantly different between the intervention and control groups. Costs incurred in administering the system at the register and in general practice were in addition to these. Conclusion: This study has shown benefits from an area-wide, computerised diabetes register incorporating a full structured recall and individualised patient management system. However, these benefits were achieved at a cost. In future, these costs may fall as electronic data exchange becomes a reliable reality. [ABSTRACT FROM AUTHOR]

Background: Healthcare professional response rates to postal questionnaires are declining and this may threaten the validity and generalisability of their findings. Methods to improve response rates do incur costs (resources) and increase the cost of research projects. The aim of these randomised controlled trials (RCTs) was to assess whether 1) incentives, 2) type of reminder and/or 3) reduced response burden improve response rates; and to assess the cost implications of such additional effective interventions., Methods: Two RCTs were conducted. In RCT A general dental practitioners (dentists) in Scotland were randomised to receive either an incentive; an abridged questionnaire or a full length questionnaire. In RCT B non-responders to a postal questionnaire sent to general medical practitioners (GPs) in the UK were firstly randomised to receive a second full length questionnaire as a reminder or a postcard reminder. Continued non-responders from RCT B were then randomised within their first randomisation to receive a third full length or an abridged questionnaire reminder. The cost-effectiveness of interventions that effectively increased response rates was assessed as a secondary outcome., Results: There was no evidence that an incentive (52% versus 43%, Risk Difference (RD) -8.8 (95%CI -22.5, 4.8); or abridged questionnaire (46% versus 43%, RD -2.9 (95%CI -16.5, 10.7); statistically significantly improved dentist response rates compared to a full length questionnaire in RCT A. In RCT B there was no evidence that a full questionnaire reminder statistically significantly improved response rates compared to a postcard reminder (10.4% versus 7.3%, RD 3 (95%CI -0.1, 6.8). At a second reminder stage, GPs sent the abridged questionnaire responded more often (14.8% versus 7.2%, RD -7.7 (95%CI -12.8, -2.6). GPs who received a postcard reminder followed by an abridged questionnaire were most likely to respond (19.8% versus 6.3%, RD 8.1%, and 9.1% for full/postcard/full, three full or full/full/abridged questionnaire respectively). An abridged questionnaire containing fewer questions following a postcard reminder was the only cost-effective strategy for increasing the response rate (£15.99 per response)., Conclusions: When expecting or facing a low response rate to postal questionnaires, researchers should carefully identify the most efficient way to boost their response rate. In these studies, an abridged questionnaire containing fewer questions following a postcard reminder was the only cost-effective strategy. An increase in response rates may be explained by a combination of the number and type of contacts. Increasing the sampling frame may be more cost-effective than interventions to prompt non-responders. However, this may not strengthen the validity and generalisability of the survey findings and affect the representativeness of the sample.

In interview studies, sample size is often justified by interviewing participants until reaching 'data saturation'. However, there is no agreed method of establishing this. We propose principles for deciding saturation in theory-based interview studies (where conceptual categories are pre-established by existing theory). First, specify a minimum sample size for initial analysis (initial analysis sample). Second, specify how many more interviews will be conducted without new ideas emerging (stopping criterion). We demonstrate these principles in two studies, based on the theory of planned behaviour, designed to identify three belief categories (Behavioural, Normative and Control), using an initial analysis sample of 10 and stopping criterion of 3. Study 1 (retrospective analysis of existing data) identified 84 shared beliefs of 14 general medical practitioners about managing patients with sore throat without prescribing antibiotics. The criterion for saturation was achieved for Normative beliefs but not for other beliefs or studywise saturation. In Study 2 (prospective analysis), 17 relatives of people with Paget's disease of the bone reported 44 shared beliefs about taking genetic testing. Studywise data saturation was achieved at interview 17. We propose specification of these principles for reporting data saturation in theory-based interview studies. The principles may be adaptable for other types of studies.