A widely accepted questionaire set from the NIH. Standard pricing, unlimited data points during your collection period.

Powerful

Standard onboarding for NeuroQOL domain modules.

Easy to use

Clear analytics and easy to use interface

NIH Neuro-QOL Positive affect and well-being

NIH Neuro-QOL Ability to Participate in social roles and activities

NIH Neuro-QOL Stigma

NIH Neuro-QOL Satisfaction with Roles and Activities

NIH Neuro-QOL Emotional Behavioral Dyscontrol

Neuro-QOL Peds

Neuro-QOL Fatigue

Introduction

WHAT IS NEURO-QoL?

Neuro-QoL (Quality of Life in Neurological Disorders) is measurement system that evaluates and monitors different parameters such as physical, mental, and social effects experienced by adults and children with neurological disorders. The assessment tool contains item sets and scales which evaluate concerns, symptoms, and issues necessary for a specific control group. Moreover, Neuro-QoL instruments are validated and established for mutual neurological conditions as well.

WHO CAN USE IT?

Neuro-QoL is an assessment tool for adults and children who have neurological conditions or disorders such as multiple sclerosis, muscular dystrophies stroke, epilepsy, Parkinson’s disease, traumatic brain injury (TBI), amyotrophic lateral sclerosis (ALS), Huntington’s disease (HD), spinal cord injury (SCI) and military deployment-related traumatic brain injury (MDR-TBI). In addition, this system provides data to the clinicians and researchers as well.

Domains

HRQOL (health-related quality of life) domains contained within Neuro-QoL were recognized through several sources for both adults and children. Adult assessment is a set of HRQOL measures designed for adults with neurological disorders. It is a self-report measure that can be accomplished by a substitute when required. On the other hand, pediatric assessment is a set of measures for 8-17-year-old respondents who have a neurological disorder. A caregiver or parent can assist the self-report measures.  There are 11 HRQOL domains for Pediatrics (Fig.1) while the adult domain comprises of 17 domains (Fig.2). Neuro-QoL contains item banks and scales that assess concerns, symptoms, and issues related to disorders along with instruments that assess areas relevant for specific patient populations.

Administration

There are three ways to administer Neuro-QoL surveys; paper and pencil method, CATs, or through an application such as Qolty.

THINGS TO CONSIDER

  • Respondent should complete the Neuro-QoL self-report measures solely without any assistance from anybody.
  • A proxy may interfere provided that the respondent is a young child, a person with dementia, intellectual or communication deficits because it hinders the respondent to perform the assessment accordingly. Instructions are provided for proxy-respondents before completing the procedure.
  • Allow the respondent to answer the measures privately.

SELECTING AN INSTRUMENT

With the aid of computer platform, Neuro-QoL assessment can be performed and scored simultaneously. The length of the measurement varies depending on the bank/scales selected by the respondent. Moreover, selecting the right instrument or a study is essential in acquiring accurate and reliable results. Here are the following considerations:

  • Domain Selection

Neuro-QoL instruments are established for a range of neurological conditions, but they are not intended for a specific disease. So, the key is to select a domain that truly covers all the aspects of a neurological disorder.

  • Instrument Type

The instrument used for Neuro-QoL measures are CAT and static short forms. These two general options can guide your optimum selection with its several precise considerations.

  • Precision

To achieve precision in Neuro-QoL measurement, adding the same questions from the same item banks are increased. It is evident that a 6-item scale is more accurate than a 1-item scale. The best evaluation for precision is CAT compared to fixed short form because of its standard for individual level assessment.

  • Brevity

The iterative item selection nature of CAT assessment makes it brief and precise as compared to static short forms considering their same length. However, for some applications like broad studies that require population estimations or group comparisons for large sample clinical trials; T-scores is the best choice. In this measurement, a small number of questions are selected per bank which makes large cluster averages more reliable.

  • Item Content

Some researchers opt to determine which questions in a bank can be administered for the sake of clinical relevance in a specific subset of items. Correspondingly, some researchers can ensure that same questions are administered each time in a continuous design. The best assessment for this item content is static short forms.

  • Flexibility

Neuro-QoL banks can be administered in different procedures. With respondents that have computer accessibility, CAT administration can be performed. However, with the Qolty application, these items can be directly assessed on your smartphones irrespective of time and location; making it the fastest and most practical option.

Translations

Besides English, the NeuroQol domains are successfully translated into Spanish, German, Swedish, French, Czech, Italian, Norwegian, Polish, Chinese-Traditional, etc. Each domain has specific translations, and these languages are not available for all the domains.

Scoring and Interpretation

NeuroQol measures are automatically scored and can be interpreted using an algorithm. The measures rely on a T-score metric in which 50 is the mean of the relevant reference, and 10 is the standard deviation of that population. So, 10 points in the scoring mean 1 standard deviation, where a score of 40 will be one standard deviation below the average score of the reference population, similarly a score of 70 will be two standard deviations higher than the average of the reference population. The main feature of the tool is that it specifies the range of answers using the normative scale or reference groups. The normative scale or the reference group is the scale where the answers from the average population are recorded for comparison. When the patient answers questions from NeuroQol, the tool shows the difference between the results. This reference guide helps the users to distinguish the intensity of their symptoms.

  • Scores 0.5 – 1.0 SD depict mild symptoms/impairment
  • Scores 1.0 – 2.0 SD demonstrate moderate symptoms/impairment
  • Scores 2.0 SD show severe symptoms/impairment

Cosmin

Test-retest Reliability:

  • Excellent test-retest reliability was validated in multiple populations with stroke with mean ICC range of 0.73 to 0.94.
  • Adequate test-retest reliability was observed by Lai et al. 2015 among children with epilepsy with the interclass correlation coefficient range of 0.44 to 0.94.

Internal Consistency

Excellent internal consistency of 13 item banks that ranges from 0.85 to 0.97 used in three samples (n = 2133; n= 533; n = 581).

Criterion Validity

Neuro-QoL report addressed a criterion validity among populations by correlating disease specific QoL measure with Neuro-QoL scores, but not with Traumatic Brain Injury (TBI).

Construct Validity

Cella et al. 2012 compared the Spearman’s correlation coefficients of full length to short forms item banks (r = 0.82 – 0.96). They observed that there was an excellent correlation between the stated item banks. Moreover, short forms could identify people with 0. 1-2, and 3 described diagnoses and activity restrictions.

Content Validity

The researchers directed a structured interview among clustered respondents to determine the content validity of standard Neuro-QoL items.

References

Chan, A.M., Selvaraj, N., Ferdosi, N., & Narasimhan, R. (2013). Wireless Patch sensor for Remote Monitoring of Heart Rate, Respiration, Activity, and Falls. 35th Annual International Conference of the IEEE EMBS.

Chan, A.M., Ferdosi, N., & Narasimhan, R. (2013). Ambulatory Respiratory Rate Detection using ECG and a Tri-Axial Accelerometer. 35th Annual International Conference of the IEEE EMBS.

Narasimhan, R. (2012). Skin-Contact Sensor for Automatic Fall Detection. 34th Annual International Conference of the IEEE EMBS.

Rosenberg, R. (2015). Early inroads for wearable devices in clinical trials. The CenterWatch Monthly, 22(8).

Selvaraj, N., & Doan, T. (2014). Performance of energy expenditure assessment using a chest-worn wireless patch sensor. MobiHealth. DOI 10.4108/icst.mobihealth.2014.257292

Selvaraj, N. (2014). Long-term Remote Monitoring of Vital Signs using a Wireless Patch Sensor. 2014 Health Innovations and Point-of-Care Technologies Conference.

Selvaraj, N., & Narasimhan, R. (2013). Detection of Sleep Apnea on a Per-Second Basis Using Respiratory Signals35th Annual International Conference of the IEEE EMBS.