Cross-cultural Adaptation Into German and Italian, Validation, Reproducibility, and Responsiveness of the Single-item Sleep Quality Scale in Spine Patients

Low back pain (LBP) consistently ranks as the leading cause of disability globally, prompting individuals affected by LBP to frequently seek healthcare. Utilizing reliable Patient-Reported Outcome Measures (PROMs) aids healthcare providers in assessing pain, functional impairment, disability, satisfaction, and quality of life in a standardized manner. However, the use of a validated questionnaire to assess each of these domains is not practicable in clinical practice. To solve this problem, the multidimensional Core Outcome Measures Index (COMI) was developed to assess the impact of LBP, using a brief set of questions. COMI has been demonstrated as a valuable metric when compared to alternative methods, exhibiting no significant limitations in terms of floor or ceiling effects and demonstrating outstanding construct validity. Moreover, it has also been established as a sensitive tool for assessing the perceived changes in patients following treatment. Recently, a complementary set of single-item measures to assess four of the "core" yellow flags (depression, anxiety, catastrophizing, and fear-avoidance) has been developed and defined as the "Core Yellow Flags Index" (CYFI). THE CYFI has been proven to be a valid and brief instrument for the assessment of key psychological factors in patients undergoing spine surgery and it also made a relevant contribution in predicting postoperative outcomes in this population. The brevity of the CYFI makes it a useful addition to the COMI in the self-assessment of baseline status before surgery.

Curiously, sleep has rarely been studied in this population and both the COMI and the CYFI do not evaluate this important variable. Assessing sleep in patients affected by spine disorders, including LBP, is of paramount importance due to the significant impact sleep disturbances can have on both the progression and management of these conditions. Sleep plays a crucial role in various physiological processes, including pain modulation, tissue repair, immune function, and psychological well-being. Therefore, disruptions in sleep patterns can exacerbate symptoms, impair recovery, and diminish the overall quality of life for individuals with back disorders. Recognizing the substantial impact of sleep-related challenges on individuals and their consequential implications, it becomes crucial to employ tools for assessing sleep quality in clinical settings.

Sleep assessment involves the measurement of various parameters, including sleep duration, sleep architecture, sleep latency, and the frequency and duration of nocturnal awakenings. Objective methods such as polysomnography (PSG) and/or actigraphy, or the use of sleep-rating questionnaires, are typically employed to quantitatively assess these metrics. The established benchmark for evaluating sleep quality continues to be PSG and/or electroencephalographic spectral analysis, despite the effectiveness of behavioural parameters in certain contexts, such as actigraphy. However, both PSG and EEG analyses may pose logistical challenges in large-scale and field studies. To address these constraints and to obtain preliminary insights into potential sleep disorders in different populations, several sleep questionnaires have been formulated and validated. Despite their efficacy in gauging sleep quality, these tools exhibit limitations when applied in clinical trials. A case in point is the Pittsburgh Sleep Quality Index (PSQI), a commonly utilized measure for assessing sleep quality, since its extended format incorporating 19 rating items may render it impractical for administration to participants in clinical trials. Further, the PSQI exhibits limitations due to its utilization of only four potential response levels for the sleep quality question. This constraint could restrict respondents when assigning grades to their sleep quality, potentially compromising the precision of their responses. Moreover, such a limited scale may fail to capture minor or nuanced changes in sleep quality. Consequently, despite the existence of alternative sleep quality questionnaires, there persists a requirement to create and validate innovative instruments explicitly tailored for assessing sleep quality in the framework of clinical trials. These novel questionnaires should address the shortcomings associated with response level constraints to enhance the accuracy and sensitivity of sleep quality evaluations in research settings.

Recently, the single-item sleep quality scale (SQS) was developed as a simple and practical sleep quality assessment. The authors reported that the SQS possesses excellent concurrent criterion validity and strong correlations between the SQS and the sleep quality items of the PSQI in patients with insomnia were detected. The SQS represents a pragmatic advancement in sleep quality assessment within clinical settings, distinguishing itself from conventional standards. Developed as a self-rated global tool, SQS offers an efficient approach based on a comprehensive review of pertinent sleep quality aspects, incorporating critical components from the PSQI, and incorporating expert and patient feedback. The single-item format permits patients to provide a self-assessment of sleep quality over a 7-day recall period without significant additional burden. Employing a visual analogue scale (VAS) enhances the potential for a more sensitive measurement, contributing to the utility of SQS in capturing nuanced variations in sleep quality. This innovation addresses the need for a streamlined yet effective tool for sleep quality evaluation in clinical contexts. However, the SQS has not yet been adapted for the German and Italian languages, nor it has been validated in spine patients.

Regarding risk category, the project shall be identified as Category A (only minimal risk and burden regarding the planned measures for sampling biological material or collecting personal data). The rationale for the categorization is based on the study objectives and study design.