When a person suffers an injury to their muscles, bones, or joints (known as a musculoskeletal or MSK injury), healthcare providers often use special questionnaires to predict how well and how quickly that person will recover. These prediction tools help guide early treatment decisions. However, a person's social identity—factors like their age, gender, race, and economic situation—might influence how they experience and report their symptoms. This could affect the accuracy of these prediction tools. This study aimed to identify which of these social factors are connected to a person's scores on common prediction questionnaires or to the accuracy of those questionnaires.
The research involved analyzing information from a group of 203 workers who had recently experienced an MSK injury. At the start of the study, these workers completed several questionnaires. These included the Numeric Pain Rating Scale (NPRS), where patients rate their pain on a scale, the Traumatic Injuries Distress Scale (TIDS), which measures emotional distress following an injury, and the EuroQoL (EQ5D-5L), a survey that assesses a person's overall health-related quality of life. Participants also provided information about their age, sex, race, income, education level, and whether they had experienced discrimination.
Researchers first looked for differences in the initial, or baseline, scores on these questionnaires among the different social groups. They then tracked the workers to see if they recovered. Recovery was sorted into two categories—"fully recovered" or "not fully recovered"—based on three different measures of recovery. The study then evaluated how well the initial questionnaire scores could predict who would recover. This predictive accuracy was measured for the entire group and also for smaller subgroups, which were created by separating the workers based on their social identity factors.
The results showed that at the beginning of the study, older participants reported significantly higher pain scores (an average of 5.5 out of 10) compared to younger participants (who averaged 4.3). Additionally, workers who reported experiencing more discrimination had higher scores for post-injury emotional distress (an average of 11.1 out of 24) compared to those who reported fewer experiences of discrimination (who averaged 9.2).
After eight weeks, the proportion of workers who were considered fully recovered ranged from 21.7% to 54.7%, with the exact percentage depending on which of the three recovery definitions was used. The study also found that having a lower level of education was associated with not achieving full recovery, but this connection was only seen when using one specific type of administrative data to measure recovery.
When comparing the prediction tools, the distress scale (TIDS) and the quality of life survey (EQ5D-5L) were both significantly better at predicting recovery than the simple pain rating scale (NPRS). When the researchers analyzed the data separately for different social groups, they found that the distress scale (TIDS) worked significantly better for predicting recovery in females than it did in males. In contrast, the quality of life survey (EQ5D-5L) was found to work similarly well for predicting recovery across all the social groups examined in the study.
The study concludes that to accurately predict a person's recovery from an MSK injury, it may be necessary to use different scoring systems or even different prediction tools for people with different overlapping social identities (for example, a person's combined identity of age, race, and gender). The researchers acknowledge a limitation in their study, which is that some identities had to be grouped into broad categories. While most prediction tools for MSK recovery use a single, universal score to separate low-risk from high-risk individuals, this study provides only partial support for that common practice.