Department of Plastic, Reconstructive, and Hand Surgery, Erasmus MC, Rotterdam, the Netherlands.
Department of Rehabilitation Medicine, Erasmus MC, Rotterdam, the Netherlands.
Clin Orthop Relat Res. 2023 May 1;481(5):994-1005. doi: 10.1097/CORR.0000000000002540. Epub 2023 Jan 24.
Multiple studies have shown that more-positive outcome expectations are associated with better treatment outcomes. Although this has not been shown to represent a causal relationship, there nonetheless is an interest in positively modifying outcome expectations to improve treatment outcomes. However, little is known about what is independently associated with outcome expectations in clinical practice. For example, it is unknown to what extent expectations are associated with treatment or patient characteristics such as sociodemographics or with patient-reported outcome measures (PROMs) on patient perceptions of physical or mental health or illness. Studying factors associated with outcome expectations may provide relevant information for clinicians and researchers aiming to improve outcome expectations. Improving expectations might, in turn, improve treatment outcomes.
QUESTION/PURPOSE: Which factors (that is, sociodemographics, PROMs, illness perceptions, treatment, surgeon, and location) are independently associated with outcome expectations in patients with hand or wrist conditions?
This was a cross-sectional study. Between July 2018 and December 2021, we screened 21,327 patients with a diagnosed hand or wrist condition with complete baseline sociodemographic data such as age and workload. Sixty percent (12,765 of 21,327) of patients completed all relevant PROMs. We excluded patients receiving rare treatments, leaving 58% (12,345 of 21,327) for inclusion in the final sample. Those who participated were more often scheduled for surgical treatment and had higher expectations. We performed a multilevel analysis involving two steps. First, we evaluated whether patients receiving the same treatment, being counseled by the same surgeon, or being treated at the same location have more similar outcome expectations. We found that only patients receiving the same treatment had more similar outcome expectations. Therefore, we used a multilevel regression model to account for this correlation within treatments, and added treatment characteristics (such as nonsurgical versus minor or major surgery) to potential explanatory factors. Second, in the multilevel hierarchical regression analysis, we added sociodemographics (Model 1), PROMs for physical and mental health (Model 2), illness perceptions (Model 3), and treatment characteristics (most-definitive model) to assess the explained variance in outcome expectations per step and the relative association with outcome expectations.
Sociodemographic factors such as age and workload explained 1% of the variance in outcome expectations. An additional 2% was explained by baseline PROMs for physical and mental health, 9% by illness perceptions, and 18% by treatment characteristics, resulting in an explained variance of 29% of the most-definitive model. A large number of patient and treatment characteristics were associated with outcome expectations. We used standardized betas to compare the magnitude of the effect of the different continuous and categorical variables. Among the associated variables, minor surgery (standardized beta [β] = 0.56 [95% confidence interval 0.44 to 0.68]; p < 0.001) and major surgery (β = 0.61 [95% CI 0.49 to 0.73]; p < 0.001) had the strongest positive association with outcome expectations (receiving surgery is associated with higher outcome expectations than nonsurgical treatment). A longer illness duration expected by the patient (-0.23 [95% CI -0.24 to -0.21]; p < 0.001) and being treated for the same condition as before (-0.08 [95% CI -0.14 to -0.03]; p = 0.003) had the strongest negative association with outcome expectations.
Outcome expectations are mainly associated with the invasiveness of the treatment and by patients' illness perceptions; patients before surgical treatment have more positive expectations of the treatment outcome than patients before nonsurgical treatment, even after accounting for differences in clinical and psychosocial profiles. In addition, patients with a more-positive perception of their illness had more-positive expectations of their treatment. Our findings suggest expectation management should be tailored to the specific treatment (such as surgical versus nonsurgical) and the specific patient (including their perception of their illness). It may be more beneficial to test and implement expectation management strategies for nonsurgical treatments such as physical therapy than for surgical treatments, given that our findings indicate a greater need to do so. An additional advantage of such a strategy is that successful interventions may prevent converting to surgical interventions, which is a goal of the stepped-care principles of standard care. Future studies might investigate the causality of the association between pretreatment expectations and outcomes by performing an experimental study such as a randomized controlled trial, in which boosting expectations is compared with usual care in nonsurgical and surgical groups.
Level III, prognostic study.
多项研究表明，更积极的治疗结果预期与更好的治疗结果相关。尽管这尚未表明存在因果关系，但人们仍然有兴趣积极改变治疗结果预期，以改善治疗结果。然而，在临床实践中，哪些因素与治疗结果预期独立相关尚不清楚。例如，尚不清楚期望与治疗或患者特征（如社会人口统计学特征）之间的关联程度，或者与患者对身体或心理健康或疾病的感知的患者报告结局测量（PROMs）之间的关联程度。研究与治疗结果预期相关的因素可以为旨在改善治疗结果预期的临床医生和研究人员提供相关信息。提高期望可能会反过来改善治疗结果。
问题/目的：手部或腕部疾病患者的哪些因素（即社会人口统计学特征、PROMs、疾病认知、治疗、外科医生和就诊地点）与治疗结果预期独立相关？
这是一项横断面研究。在 2018 年 7 月至 2021 年 12 月期间，我们筛选了 21327 名患有手部或腕部疾病且具有完整基线社会人口统计学数据（如年龄和工作量）的患者。其中 60%（12765 名/21327 名）的患者完成了所有相关的 PROMs。我们排除了接受罕见治疗的患者，最终样本为 58%（12345 名/21327 名）。参与研究的患者更常接受手术治疗，且具有更高的预期。我们进行了一项涉及两步的多级分析。首先，我们评估了接受相同治疗、由同一位外科医生提供咨询或在同一地点接受治疗的患者是否具有更相似的治疗结果预期。我们发现只有接受相同治疗的患者具有更相似的治疗结果预期。因此，我们使用多级回归模型来解释治疗过程中的这种相关性，并将治疗特征（如非手术与小手术或大手术）添加到潜在的解释因素中。其次，在多级层次回归分析中，我们在每个步骤中添加了社会人口统计学因素（模型 1）、身体和心理健康的 PROMs（模型 2）、疾病认知（模型 3）和治疗特征（最明确模型），以评估治疗结果预期的解释方差和与治疗结果预期的相对关联。
社会人口统计学因素，如年龄和工作量，解释了治疗结果预期方差的 1%。基线身体和心理健康的 PROMs 额外解释了 2%，疾病认知解释了 9%，治疗特征解释了 18%，导致最明确模型的解释方差为 29%。大量患者和治疗特征与治疗结果预期相关。我们使用标准化β来比较不同连续和分类变量的影响大小。在相关变量中，小手术（标准化β[β]=0.56[95%置信区间 0.44 至 0.68]；p<0.001）和大手术（β=0.61[95%置信区间 0.49 至 0.73]；p<0.001）与治疗结果预期具有最强的正相关（接受手术治疗比非手术治疗具有更高的治疗结果预期）。患者预期的疾病持续时间较长（-0.23[95%置信区间-0.24 至-0.21]；p<0.001）和以前接受过相同的治疗（-0.08[95%置信区间-0.14 至-0.03]；p=0.003）与治疗结果预期呈最强的负相关。
治疗结果预期主要与治疗的侵袭性和患者的疾病认知有关；与非手术治疗相比，术前接受手术治疗的患者对治疗结果的预期更为积极，即使考虑到临床和心理社会特征的差异也是如此。此外，对疾病的感知越积极的患者对治疗的预期也越积极。我们的研究结果表明，应该根据特定的治疗（如手术与非手术）和特定的患者（包括他们对疾病的感知）来调整治疗结果预期的管理。与手术治疗相比，测试和实施针对物理治疗等非手术治疗的预期管理策略可能会更有益，因为我们的研究结果表明需要进行此类干预。这种策略的另一个优势是，成功的干预措施可能会阻止手术干预的转化，这是标准护理阶梯式治疗原则的目标。未来的研究可以通过进行实验研究（如随机对照试验）来研究治疗前预期与结局之间的关联的因果关系，比较在非手术组和手术组中提高预期与常规护理的效果。
III 级，预后研究。
