How Are Age, Gender, and Country Differences Associated With PROMIS Physical Function, Upper Extremity, and Pain Interference Scores?

BACKGROUND: The interpretation of patient-reported outcomes requires appropriate comparison data. Currently, no patient-specific reference data exist for the Patient-Reported Outcome Measurement Information System (PROMIS) Physical Function (PF), Upper Extremity (UE), and Pain Interference (PI) scales for individuals 50 years and older. QUESTIONS/PURPOSES: (1) Can all PROMIS PF, UE, and PI items be used for valid cross-country comparisons in these domains among the United States, the United Kingdom, and Germany? (2) How are age, gender, and country related to PROMIS PF, PROMIS UE, and PROMIS PI scores? (3) What is the relationship of age, gender, and country across individuals with PROMIS PF, PROMIS UE, and PROMIS PI scores ranging from very low to very high? METHODS: We conducted telephone interviews to collect custom PROMIS PF (22 items), UE (eight items), and PI (eight items) short forms, as well as sociodemographic data (age, gender, work status, and education level), with participants randomly selected from the general population older than 50 years in the United States (n = 900), United Kingdom (n = 905), and Germany (n = 921). We focused on these individuals because of their higher prevalence of surgeries and lower physical functioning. Although response rates varied across countries (14% for the United Kingdom, 22% for Germany, and 12% for the United States), we used existing normative data to ensure demographic alignment with the overall populations of these countries. This helped mitigate potential nonresponder bias and enhance the representativeness and validity of our findings. We investigated differential item functioning to determine whether all items can be used for valid crosscultural comparisons. To answer our second research question, we compared age groups, gender, and countries using median regressions. Using imputation of plausible values and quantile regression, we modeled age-, gender-, and country-specific distributions of PROMIS scores to obtain patient-specific reference values and answer our third research question. RESULTS: All items from the PROMIS PF, UE, and PI measures were valid for across-country comparisons. We found clinically meaningful associations of age, gender, and country with PROMIS PF, UE, and PI scores. With age, PROMIS PF scores decreased (age ß Median = -0.35 [95% CI -0.40 to -0.31]), and PROMIS UE scores followed a similar trend (age ß Median = -0.38 [95% CI -0.45 to -0.32]). This means that a 10-year increase in age corresponded to a decline in approximately 3.5 points for the PROMIS PF score-a value that is approximately the minimum clinically important difference (MCID). Concurrently, we observed a modest increase in PROMIS PI scores with age, reaching half the MCID after 20 years. Women in all countries scored higher than men on the PROMIS PI and 1 MCID lower on the PROMIS PF and UE. Additionally, there were higher T-scores for the United States than for the United Kingdom across all domains. The difference in scores ranged from 1.21 points for the PROMIS PF to a more pronounced 3.83 points for the PROMIS UE. Participants from the United States exhibited up to half an MCID lower T-scores than their German counterparts for the PROMIS PF and PROMIS PI. In individuals with high levels of physical function, with each 10-year increase in age, there could be a decrease of up to 4 points in PROMIS PF scores. Across all levels of upper extremity function, women reported lower PROMIS UE scores than men by an average of 5 points. CONCLUSION: Our study provides age-, gender-, and country-specific reference values for PROMIS PF, UE, and PI scores, which can be used by clinicians, researchers, and healthcare policymakers to better interpret patient-reported outcomes and provide more personalized care. These findings are particularly relevant for those collecting patient-reported outcomes in their clinical routine and researchers conducting multinational studies. We provide an internet application ( www.common-metrics.org/PROMIS_PF_and_PI_Reference_scores.php ) for user-friendly accessibility in order to perform age, gender, and country conversions of PROMIS scores. Population reference values can also serve as comparators to data collected with other PROMIS short forms or computerized adaptive tests. LEVEL OF EVIDENCE: Level II, diagnostic study.

Psychological treatment of depression with other comorbid mental disorders: systematic review and meta-analysis.

Most people with a mental disorder meet criteria for multiple disorders. We conducted a systematic review and meta-analysis of randomized trials comparing psychotherapies for people with depression and comorbid other mental disorders with non-active control conditions. We identified studies through an existing database of randomized trials on psychotherapies for depression. Thirty-five trials (3,157 patients) met inclusion criteria. Twenty-seven of the 41 interventions in the 35 trials (66%) were based on CBT. The overall effect on depression was large (g = 0.65; 95% CI: 0.40 ~ 0.90), with high heterogeneity (I2 = 78%; 95% CI: 70 ~ 83). The ten studies in comorbid anxiety showed large effects on depression (g = 0.90; 95% CI: 0.30 ~ 1.51) and anxiety (g = 1.01; 95% CI: 0.28 ~ 1.74). For comorbid insomnia (11 comparisons) a large and significant effect on depression (g = 0.99; 95% CI: 0.16 ~ 1.82) and insomnia (g = 1.38; 95% CI: 0.38 ~ 2.38) were found. For comorbid substance use problems (12 comparisons) effects on depression (g = 0.25; 95% CI: 0.06 ~ 0.43) and on substance use problems (g = 0.25; 95% CI: 0.01 ~ 0.50) were significant. Most effects were no longer significant after adjustment for publication bias and when limited to studies with low risk of bias. Therapies are probably effective in the treatment of depression with comorbid anxiety, insomnia, and substance use problems.

Digital mental health interventions for the treatment of depression: A multiverse meta-analysis.

BACKGROUND: The varying sizes of effects in published meta-analyses on digital interventions for depression prompt questions about their efficacy. METHODS: A systematic search in Embase, PsycINFO, and PubMed identified 125 randomised controlled trials up to February 2023, comparing digital interventions for depression against inactive controls. The stability of results was evaluated with a multiverse meta-analysis, thousands of meta-analyses were conducted based on different combinations of analytical choices, like target populations, intervention characteristics, and study designs. RESULTS: A total of 3638 meta-analyses were performed based on 125 randomised controlled trials and 263 effect sizes, with a total of 32,733 participants. The average effect size was Hedges' g = 0.43, remaining positive at both the 10th (g = 0.16) and 90th percentiles (g = 0.74). Most meta-analyses indicated a statistically significant benefit of digital interventions. Larger effects were observed in meta-analyses focusing on adults, low- and middle-income countries, guided interventions, comparing interventions with waitlist controls, and patients with major depressive or unipolar mood disorders. Smaller effects appeared when adjusting for publication bias and in assessments after 24 weeks. LIMITATIONS: While multiverse meta-analysis aims to exhaustively investigate various analytical decisions, some subjectivity remains due to the necessity of making choices that affect the methodology. Additionally, the quality of the included primary studies was low. CONCLUSIONS: The analytical decisions made during performing pairwise meta-analyses result in vibrations from small to medium effect sizes. Our study provides robust evidence for the effectiveness of digital interventions for depression while highlighting important factors associated with treatment outcomes.

Exploring the efficacy of psychotherapies for depression: a multiverse meta-analysis.

BACKGROUND: Hundreds of randomised controlled trials and dozens of meta-analyses have examined psychotherapies for depression-yet not all points in the same direction. Are these discrepancies a result of specific meta-analytical decisions or do most analytical strategies reaching the same conclusion? OBJECTIVE: We aim to solve these discrepancies by conducting a multiverse meta-analysis containing all possible meta-analyses, using all statistical methods. STUDY SELECTION AND ANALYSIS: We searched four bibliographical databases (PubMed, EMBASE, PsycINFO and Cochrane Register of Controlled Trials), including studies published until 1 January 2022. We included all randomised controlled trials comparing psychotherapies with control conditions without restricting the type of psychotherapy, target group, intervention format, control condition and diagnosis. We defined all possible meta-analyses emerging from combinations of these inclusion criteria and estimated the resulting pooled effect sizes with fixed-effect, random-effects, 3-level, robust variance estimation, p-uniform and PET-PEESE (precision-effect test and precision-effect estimate with SE) meta-analysis models. This study was preregistered (https://doi.org/10.1136/bmjopen-2021-050197). FINDINGS: A total of 21 563 records were screened, and 3584 full texts were retrieved; 415 studies met our inclusion criteria containing 1206 effect sizes and 71 454 participants. Based on all possible combinations between inclusion criteria and meta-analytical methods, we calculated 4281 meta-analyses. The average summary effect size for these meta-analyses was Hedges' g mean=0.56, a medium effect size, and ranged from g=-0.66 to 2.51. In total, 90% of these meta-analyses reached a clinically relevant magnitude. CONCLUSIONS AND CLINICAL IMPLICATIONS: The multiverse meta-analysis revealed the overall robustness of the effectiveness of psychotherapies for depression. Notably, meta-analyses that included studies with a high risk of bias, compared the intervention with wait-list control groups, and not correcting for publication bias produced larger effect sizes.

Cognitive behavior therapy vs. control conditions, other psychotherapies, pharmacotherapies and combined treatment for depression: a comprehensive meta-analysis including 409 trials with 52,702 patients.

Cognitive behavior therapy (CBT) is by far the most examined type of psychological treatment for depression and is recommended in most treatment guide-lines. However, no recent meta-analysis has integrated the results of randomized trials examining its effects, and its efficacy in comparison with other psychotherapies, pharmacotherapies and combined treatment for depression remains uncertain. We searched PubMed, PsycINFO, Embase and the Cochrane Library to identify studies on CBT, and separated included trials into several subsets to conduct random-effects meta-analyses. We included 409 trials (518 comparisons) with 52,702 patients, thus conducting the largest meta-analysis ever of a specific type of psychotherapy for a mental disorder. The quality of the trials was found to have increased significantly over time (with increasing numbers of trials with low risk of bias, less waitlist control groups, and larger sample sizes). CBT had moderate to large effects compared to control conditions such as care as usual and waitlist (g=0.79; 95% CI: 0.70-0.89), which remained similar in sensitivity analyses and were still significant at 6-12 month follow-up. There was no reduction of the effect size of CBT according to the publication year (<2001 vs. 2001-2010 vs. >2011). CBT was significantly more effective than other psychotherapies, but the difference was small (g=0.06; 95% CI: 0-0.12) and became non-significant in most sensitivity analyses. The effects of CBT did not differ significantly from those of pharmacotherapies at the short term, but were significantly larger at 6-12 month follow-up (g=0.34; 95% CI: 0.09-0.58), although the number of trials was small, and the difference was not significant in all sensitivity analyses. Combined treatment was more effective than pharmacotherapies alone at the short (g=0.51; 95% CI: 0.19-0.84) and long term (g=0.32; 95% CI: 0.09-0.55), but it was not more effective than CBT alone at either time point. CBT was also effective as unguided self-help intervention (g=0.45; 95% CI: 0.31-0.60), in institutional settings (g=0.65; 95% CI: 0.21-1.08), and in children and adolescents (g=0.41; 95% CI: 0.25-0.57). We can conclude that the efficacy of CBT in depression is documented across different formats, ages, target groups, and settings. However, the superiority of CBT over other psychotherapies for depression does not emerge clearly from this meta-analysis. CBT appears to be as effective as pharmacotherapies at the short term, but more effective at the longer term.

Item response theory may account for unequal item weighting and individual-level measurement error in trials that use PROMs: a psychometric sensitivity analysis of the TOPKAT trial.

OBJECTIVES: To apply item response theory as a framework for studying measurement error in superiority trials which use patient-reported outcome measures (PROMs). METHODS: We reanalyzed data from the The Total or Partial Knee Arthroplasty Trial, which compared the Oxford Knee Score (OKS) responses of patients undergoing partial or total knee replacement, using traditional sum-scoring, after accounting for OKS item characteristics with expected a posteriori (EAP) scoring, and after accounting for individual-level measurement error with plausible value imputation (PVI). We compared the marginalized mean scores of each group at baseline, 2 months, and yearly for 5 years. We used registry data to estimate the minimal important difference (MID) of OKS scores with sum-scoring and EAP scoring. RESULTS: With sum-scoring, we found statistically significant differences in mean OKS score at 2 months (P = 0.030) and 1 year (P = 0.030). EAP scores produced slightly different results, with statistically significant differences at 1 year (P = 0.041) and 3 years (P = 0.043). With PVI, there were no statistically significant differences. CONCLUSION: Psychometric sensitivity analyses can be readily performed for superiority trials using PROMs and may aid the interpretation of results.

Item response theory assumptions were adequately met by the Oxford hip and knee scores.

OBJECTIVES: To develop item response theory (IRT) models for the Oxford hip and knee scores which convert patient responses into continuous scores with quantifiable precision and provide these as web applications for efficient score conversion. STUDY DESIGN AND SETTING: Data from the National Health Service patient-reported outcome measures program were used to test the assumptions of IRT (unidimensionality, monotonicity, local independence, and measurement invariance) before fitting models to preoperative response patterns obtained from patients undergoing primary elective hip or knee arthroplasty. The hip and knee datasets contained 321,147 and 355,249 patients, respectively. RESULTS: Scree plots, Kaiser criterion analyses, and confirmatory factor analyses confirmed unidimensionality and Mokken analysis confirmed monotonicity of both scales. In each scale, all item pairs shared a residual correlation of ≤ 0.20. At the test level, both scales showed measurement invariance by age and gender. Both scales provide precise measurement in preoperative settings but demonstrate poorer precision and ceiling effects in postoperative settings. CONCLUSION: We provide IRT parameters and web applications that can convert Oxford Hip Score or Oxford Knee Score response sets into continuous measurements and quantify individual measurement error. These can be used in sensitivity analyses or to administer truncated and individualized computerized adaptive tests.

Psychological treatment of depression: A systematic overview of a 'Meta-Analytic Research Domain'.

BACKGROUND: Over the past 16 years, we have developed a 'Meta-analytic Research Domain' (MARD) of all randomized trials of psychological treatments of depression. A MARD is a living systematic review of a research field, that cannot be otherwise covered by one (network) meta-analysis and includes multiple PICOs. In this paper we give an overview of the findings of this MARD. METHODS: A narrative review of the results of the 118 meta-analyses on psychotherapies for depression that were published within our MARD. RESULTS: Most research has been conducted on cognitive-behavioral therapy (CBT), but several other psychotherapies are also effective, with few differences between therapies. They can be effectively delivered in individual, group, telephone and guided self-help format and are effective in many different target groups and across different age groups, although the effects are significantly smaller in children and adolescents. Psychotherapies have comparable effects as pharmacotherapy at the short term but are probably more effective at the longer term. Combined treatment is more effective than either psychotherapy or pharmacotherapy alone at the short, but also at the longer term. LIMITATIONS: We did not summarize all published meta-analyses (protocols, methodological studies) and have not compared our results to those found in other meta-analyses on comparable subjects. CONCLUSION: Psychotherapies can contribute considerably to a reduction of the disease burden of depression. MARDs are an important next step in the aggregation of knowledge from randomized controlled trials in psychological treatments of depression as well as in other healthcare sectors.

Exploring the efficacy of psychological treatments for depression: a multiverse meta-analysis protocol.

INTRODUCTION: In the past four decades, over 700 randomised controlled trials (RCTs) and 80 meta-analyses have examined the efficacy of psychological treatments for depression. Overwhelming evidence suggests that all types of psychological treatments are effective. Yet, many aspects are still unexplored. Meta-analysts could perform hundreds of potential meta-analyses with the current literature, and a comprehensive bird's-eye view of all published studies is missing. This protocol outlines how a multiverse meta-analysis can evaluate the entire body of the literature on psychological treatments of depression in a single analysis. Thereby, gaps of evidence and areas of robustness are highlighted. METHODS AND ANALYSIS: We will conduct systematic literature searches in bibliographical databases (PubMed, Embase, PsycINFO and Cochrane Register of Controlled Trials) up until 1 January 2021. We will include all RCTs comparing a psychological treatment with a control condition. We will include studies published in English, German, Spanish or Dutch, and exclude trials on maintenance and relapse prevention as well as dissertations. Two independent researchers will check all records. All self-reported and clinician-rated instruments measuring depression are included. We will extract information on recruitment settings, target groups, age groups, comorbidity, intervention formats, psychotherapy types, number of sessions, control conditions and country. Two independent researchers will assess risk of bias using the Cochrane Risk of Bias assessment tool. As part of the multiverse meta-analysis, unweighted, fixed effect and random effects models will be calculated. ETHICS AND DISSEMINATION: As we will not collect any primary data, an ethical approval of this protocol is not required. We will publish the results in a peer-review journal and present them at international conferences. We will follow open science practices and provide our code and data.