This pilot study aimed to explore the clinical outcomes and therapeutic relationship for clients of an adult mental health service using Beating the Blues, a computerised cognitive behaviour therapy (CCBT) package. Sixteen participants completed the programme and reported a significant reduction in Beck Depression Inventory scores posttreatment. Participants' mean item ratings on the relationship measure were above the neutral midpoint, but no association was found between the therapeutic relationship and outcome. The results are discussed in terms of the utility of CCBT as part of a stepped-care model and how further research might usefully explore the nature of the relationship formed between clients and CCBT programmes.
The present experiments focus on whether the post-identification feedback effect can be reduced by providing participants with warnings. Participants viewed a crime on video and identified a suspect from a target-absent lineup (Experiment 1) or target-present lineup (Experiment 2). Participants then received positive feedback, negative feedback or no feedback. Half of the participants received a warning saying their feedback was randomly generated by the computer, and the other half received no warning. Robust post-identification feedback effects were observed in both experiments in the no warning condition. These effects were largely eliminated when participants received a warning. In Experiments 3 and 4, we failed to find an ameliorative effect of a forensically realistic warning. These results indicate that warnings can reduce the effect of post-identification feedback in principle, but the application of warnings in practice may be more difficult.
Objective
To examine how consumer satisfaction ratings differ between mental health providers and to determine if comparison of ratings between providers is biased by differences in survey response rates or characteristics of consumers served.
Methods
Secondary analysis of routinely mailed consumer satisfaction surveys in a mixed-model prepaid health plan. Satisfaction survey data were linked to computerized record data regarding consumers’ demographic (age, sex, type of insurance coverage) and clinical (primary diagnosis, initial vs. return visit) characteristics. Statistical models examined both probability of returning the mailed satisfaction survey and (among those returning surveys) probability of giving an “Excellent” satisfaction rating. Variability in consumer characteristics was decomposed into within-provider effects and between-provider effects.
Results
Overall response rate was 33.8%, and 49.9% of those responding reported “Excellent” satisfaction. Neither response rate nor satisfaction rating was related to primary diagnosis. Within the practices of individual providers, both response rate and receiving an “Excellent” rating were significantly associated with female sex, older age, longer enrollment in the health plan, and making a return (vs. initial) visit. Analyses of between-provider effects, however, found that only having a higher proportion of return visitors was significantly associated with higher response rates and higher satisfaction ratings.
Conclusions
There is little evidence that differences in response rate or differences in consumers served bias comparison of satisfaction ratings between mental health providers. Bias might be greater in a setting with more heterogeneous consumers or providers. Returning consumers give higher ratings than first-time visitors, and analyses of satisfaction ratings may need to account for this difference. Extremely high or low ratings should be interpreted cautiously, especially for providers with a small number of surveys.
Patient satisfaction is increasingly becoming an important component of quality for behavioral health care systems. The following report describes Group Health Cooperative's Behavioral Health Services department experiences over a 5-year period in moving from uncertainty about the value of patient satisfaction and the ability to positively impact patient ratings to achieving a significant improvement in patient ratings of satisfaction with mental health care. In this process, the Behavioral Health Department developed a deeper understanding of patient requirements and improvement strategies which could impact these requirements. A description of the results achieved along with the role of quality improvement processes in understanding and improving patient satisfaction in mental health care is presented.
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