Self-Regulatory Processes, Motivation to Conserve Resources and Activity Levels in People With Chronic Pain: A Series of Digital N-of-1 Observational Studies

Predictors of self-regulation fatigue patterns in patients before total knee arthroplasty: A cross-sectional study

BACKGROUND

Patients with total knee arthroplasty encounter stressful events that consume their coping resources, resulting in self-control fatigue. Few studies have focused on this phenomenon.

AIM

To identify subgroups of patients before total knee arthroplasty according to the heterogeneous patterns of self-regulation fatigue and to analyse the predictors of subtypes.

METHODS

A total of 210 patients awaiting total knee arthroplasty were enrolled. Data of demographic characteristics, clinical characteristics, psychological and social factors were collected. Latent profile analysis was employed to define the subgroups. Predictors of patterns were identified using multinomial logistic regression.

RESULTS

Three latent classes were identified: the low, medium, and high self-regulation fatigue classes. For the high self-regulation fatigue class, lower levels of hope, social support, self-efficacy and education were major predictors.

CONCLUSION

These predictors of patients with different levels of self-regulation fatigue provide evidence for the identification of vulnerable populations and lay a foundation for targeted interventions.

Slow and Steady But Not Related to HIV Stigma: Physical Activity in South Africans Living with HIV and Chronic Pain

HIV stigma may influence physical activity in people living with HIV (PLWH) and chronic pain. We prospectively examined the relationship between stigma, activity and chronic pain in a convenience sample of PLWH initiating antiretroviral therapy in an inner-city clinic in Johannesburg, South Africa. Participants wore accelerometers to measure daily duration and intensity of activity for 2 weeks. Stigma was assessed with the Revised HIV Stigma Scale. Participants [n = 81, 89% female, age mean (SD) 42 (8)] were active for a median of 7 h daily (IQR 5.2, 9.2), but at very low intensity, equivalent to a slow walk [median (IQR): 0.39 m s^-1 (0.33, 0.50)]. Duration and intensity of activity was not associated with stigma, even after controlling for age, self-assessed wealth, pain intensity and willingness to engage in physical activity (p-values > 0.05). As stigma did not associate with greater activity, drivers of sustained activity in South African PLWH remain unclear.

Perspective: Application of N-of-1 Methods in Personalized Nutrition Research

Personalized and precision nutrition aim to examine and improve health on an individual level, and this requires reconsideration of traditional dietary interventions or behavioral study designs. The limited frequency of measurements in group-level human nutrition trials cannot be used to infer individual responses to interventions, while in behavioral studies, retrospective data collection does not provide an accurate measure of how everyday behaviors affect individual health. This review introduces the concept of N-of-1 study designs, which involve the repeated measurement of a health outcome or behavior on an individual level. Observational designs can be used to monitor a participant's usual health or behavior in a naturalistic setting, with repeated measurements conducted in real time using an Ecological Momentary Assessment. Interventional designs can introduce a dietary or behavioral intervention with predictors and outcomes of interest measured repeatedly either during or after 1 or more intervention and control periods. Due to their flexibility, N-of-1 designs can be applied to both short-term physiological studies and longer-term studies of eating behaviors. As a growing number of disease markers can be measured outside of the clinic, with self-reported data delivered via electronic devices, it is now easier than ever to generate large amounts of data on an individual level. Statistical techniques can be utilized to analyze changes in an individual or to aggregate data from sets of N-of-1 trials, enabling hypotheses to be tested on a small number of heterogeneous individuals. Although their designs necessitate extra methodological and statistical considerations, N-of-1 studies could be used to investigate complex research questions and to study underrepresented groups. This may help to reveal novel associations between participant characteristics and health outcomes, with repeated measures providing power and precision to accurately determine an individual's health status.