Short and long-term predictors of pain severity and interference in primary care patients with chronic musculoskeletal pain and depression

BACKGROUND

Chronic pain and depression are frequent comorbidities in primary care. Depression among other psychosocial factors play a role in the clinical course of chronic pain.

OBJECTIVE

To study the short and long-term predictive factors of severity and interference of chronic pain in primary care patients with chronic musculoskeletal pain and major depression.

METHODS

Longitudinal study of a cohort of 317 patients. The outcomes are severity and functional interference of pain (Brief Pain Inventory) measured at 3 and 12 months. We performed multivariate linear regression models to estimate the effects the explanatory baseline variables on the outcomes.

RESULTS

83% participants were women; average age was 60.3 years (SD = 10.2). In multivariate models, baseline pain severity predicted pain severity at 3 months (β = 0.53; 95% CI = 0.37-0.68) and at 12 months (β = 0.48; 95% CI = 0.29-0.67). Also, pain > 2 years of evolution predicted long term pain severity (β = 0.91; CI95%=0.11-1.71). Baseline pain interference predicted interference at 3 and 12 months (β = 0.27; 95%CI = 0.11-0.43 and β = 0.21; 95%CI = 0.03-0.40, respectively). Baseline pain severity predicted interference at 3 and 12 months (β = 0.26; 95%CI = 0.10-0.42 and β = 0.20; 95%CI = 0.02-0.39, respectively). Pain > 2 years predicted greater severity and greater interference at 12 months (β = 0.91; CI95%=0.11-1.71, and β = 1.23; CI95%=0.41-2.04). Depression severity predicted more interference at 12 months (β = 0.58; CI95%=0.04-1.11). Occupational status as active worker predicted less interference throughout the follow-up (β=-0.74; CI95%=-1.36 to -0.13 and β=-0.96; CI95%=-1.71 to -0.21, at 3 and 12 months). Currently working also predicts less pain severity at 12 months (β=-0.77; CI95%=1.52 - 0.02). With regard to the psychological variables, pain catastrophizing predicted pain severity and interference at three months (β = 0.03; 95% CI = 0.00-0.05 and β = 0.03; 95% CI = 0.00-0.05), but not at long term.

CONCLUSION

In a sample of adults with chronic pain and depression, this primary care study has identified prognostic factors that independently predict the severity and functional interference of pain. If confirmed in new studies, these factors should be targeted for individualized interventions.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT02605278), registered 16/11/2015.

Complex multidisciplinary intervention to improve Initial Medication Adherence to cardiovascular disease and diabetes treatments in primary care (the IMA-cRCT study): mixed-methods process evaluation protocol

INTRODUCTION

Medication non-initiation, or primary non-adherence, is a persistent public health problem that increases the risk of adverse clinical outcomes. The initial medication adherence (IMA) intervention is a complex multidisciplinary intervention to improve adherence to cardiovascular and diabetes treatments in primary care by empowering the patient and promoting informed prescriptions based on shared decision-making. This paper presents the development and implementation strategy of the IMA intervention and the process evaluation protocol embedded in a cluster randomised controlled trial (the IMA-cRCT) to understand and interpret the outcomes of the trial and comprehend the extent of implementation and fidelity, the active mechanisms of the IMA intervention and in what context the intervention is implemented and works.

METHODS AND ANALYSIS

We present the protocol for a mixed-methods process evaluation including quantitative and qualitative methods to measure implementation and fidelity and to explore the active mechanisms and the interactions between the intervention, participants and its context. The process evaluation will be conducted in primary care centres and community pharmacies from the IMA-cRCT, and participants include healthcare professionals (general practitioners, nurses and community pharmacists) as well as patients. Quantitative data collection methods include data extraction from the intervention operative records, patient clinical records and participant feedback questionnaires, whereas qualitative data collection involves semistructured interviews, focus groups and field diaries. Quantitative and qualitative data will be analysed separately and triangulated to produce deeper insights and robust results.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from the Research Ethics Comittee (CEIm) at IDIAP Jordi Gol (codeCEIm 21/051 P). Findings will be disseminated through publications and conferences, as well as presentations to healthcare professionals and stakeholders from healthcare organisations.

TRIAL REGISTRATION NUMBER

NCT05026775.

Increasing Cervical Cancer Screening Coverage: A Randomised, Community-Based Clinical Trial

BACKGROUND

Opportunistic cervical cancer screening can lead to suboptimal screening coverage. Coverage could be increased after a personalised invitation to the target population. We present a community randomized intervention study with three strategies aiming to increase screening coverage.

METHODS

The CRICERVA study is a community-based clinical trial to improve coverage of population-based screening in the Cerdanyola SAP area in Barcelona.A total of 32,858 women residing in the study area, aged 30 to 70 years were evaluated. A total of 15,965 women were identified as having no registration of a cervical cytology in the last 3.5 years within the Public Health data base system. Eligible women were assigned to one of four community randomized intervention groups (IGs): (1) (IG1 N = 4197) personalised invitation letter, (2) (IG2 N = 3601) personalised invitation letter + informative leaflet, (3) (IG3 N = 6088) personalised invitation letter + informative leaflet + personalised phone call and (4) (Control N = 2079) based on spontaneous demand of cervical cancer screening as officially recommended. To evaluate screening coverage, we used heterogeneity tests to compare impact of the interventions and mixed logistic regression models to assess the age effect. We refer a "rescue" visit as the screening visit resulting from the study invitation.

RESULTS

Among the 13,886 women in the IGs, 2,862 were evaluated as having an adequate screening history after the initial contact; 4,263 were lost to follow-up and 5,341 were identified as having insufficient screening and thus being eligible for a rescue visit. All intervention strategies significantly increased participation to screening compared to the control group. Coverage after the intervention reached 84.1% while the control group reached 64.8%. The final impact of our study was an increase of 20% in the three IGs and of 9% in the control group (p<0.001). Within the intervention arms, age was an important determinant of rescue visits showing a statistical interaction with the coverage attained in the IGs. Within the intervention groups, final screening coverage was significantly higher in IG3 (84.4%) (p<0.001). However, the differences were more substantial in the age groups 50-59 and those 60+. The highest impact of the IG3 intervention was observed among women 60+ y.o with 32.0% of them being rescued for screening. The lowest impact of the interventions was in younger women.

CONCLUSIONS

The study confirms that using individual contact methods and assigning a fixed screening date notably increases participation in screening. The response to the invitation is strongly dependent on age.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01373723.