Treatment of Insomnia in Primary Care Study

The ISI is a validated self-report tool for assessing the severity, and impact of current insomnia symptoms. It consists of 7 Likert-scale questions with a total score ranging from 0 to 28 (with higher scores indicating more severe insomnia). Change = Week 8 score - Baseline score.

PHQ-9 is a validated self-administered instrument assessing each of the 9 Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria for depression as 0 (not at all) to 3 (nearly every day), and the severity of depression. Possible scores range from 0 to 27. Change = Week 8 score - Baseline score.

EUROHIS Quality of Life 8-item Index is a validated instrument for the assessment of general quality of life. There are altogether eight questions about the general, physical, psychological, social, and environmental aspects of quality of life. Every question is scored from 1 (very poor) to 5 (very good). All scores can be added together and divided by 8 (the sum of the questions) to obtain the EUROHIS-QOL mean score. Change = Week 8 score - Baseline score.

The WAS is the first item of the Work Ability Index (WAI), a validated instrument for the assessment of work ability. WAS is a single question "What is your current work ability compared to your lifetime best?" It has a 0-10 response scale, where 0 stands for "completely unable to work" and 10 stands for "work ability at its best." The WAS has been shown to have a strong association with the WAI and is reliable in evaluating work ability. Change = Week 8 score - Baseline score.

Information about sleep duration is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep duration. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep duration.

Information about sleep stages is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep stages. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep stages.

Information about objective sleep quality is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep quality. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep quality.

Information about sleep duration is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep duration. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep duration.

Information about sleep stages is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep stages. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep stages.

Information about objective sleep quality is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep quality. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep quality.

The ISI is a validated self-report tool for assessing the severity, and impact of current insomnia symptoms. It consists of 7 Likert-scale questions with a total score ranging from 0 to 28 (with higher scores indicating more severe insomnia). Change = Week 16 score - Week 8 score.

PHQ-9 is a validated self-administered instrument assessing each of the 9 DSM-IV criteria for depression as 0 (not at all) to 3 (nearly every day), and the severity of depression. Possible scores range from 0 to 27. Change = Week 16 score - Baseline score.

EUROHIS Quality of Life 8-item Index is a validated instrument for the assessment of general quality of life. There are altogether eight questions about the general, physical, psychological, social, and environmental aspects of quality of life. Every question is scored from 1 (very poor) to 5 (very good). All scores can be added together and divided by 8 (the sum of the questions) to obtain the EUROHIS-QOL mean score. Change = Week 16 score - Baseline score.

The WAS is the first item of the Work Ability Index (WAI), a validated instrument for the assessment of work ability. WAS is a single question "What is your current work ability compared to your lifetime best?" It has a 0-10 response scale, where 0 stands for "completely unable to work" and 10 stands for "work ability at its best." The WAS has been shown to have a strong association with the WAI and is reliable in evaluating work ability. Change = Week 16 score - Baseline score.

Information about sleep duration is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep duration. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep duration.

Information about sleep stages is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep stages. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep stages.

Information about objective sleep quality is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep quality. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep quality.

The ISI is a validated self-report tool for assessing the severity, and impact of current insomnia symptoms. It consists of 7 Likert-scale questions with a total score ranging from 0 to 28 (with higher scores indicating more severe insomnia). Change = Week 26 score - Week 8 score.

PHQ-9 is a validated self-administered instrument assessing each of the 9 DSM-IV criteria for depression as 0 (not at all) to 3 (nearly every day), and the severity of depression. Possible scores range from 0 to 27. Change = Week 26 score - Baseline.

EUROHIS Quality of Life 8-item Index is a validated instrument for the assessment of general quality of life. There are altogether eight questions about the general, physical, psychological, social, and environmental aspects of quality of life. Every question is scored from 1 (very poor) to 5 (very good). All scores can be added together and divided by 8 (the sum of the questions) to obtain the EUROHIS-QOL mean score. Change = Week 26 score - Baseline score.

The WAS is the first item of the Work Ability Index (WAI), a validated instrument for the assessment of work ability. WAS is a single question "What is your current work ability compared to your lifetime best?" It has a 0-10 response scale, where 0 stands for "completely unable to work" and 10 stands for "work ability at its best." The WAS has been shown to have a strong association with the WAI and is reliable in evaluating work ability. Change = Week 26 score - Baseline score.

Information about sleep duration is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep duration. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep duration.

Information about sleep stages is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep stages. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep stages.

Information about objective sleep quality is collected with smart watches using a validated method. The method is based on assessment of biological signals with artificial intelligence algorithms. With a smart watch, the participant's heart rate, movements, oxygen saturation, and photoplethysmography signal is measured from the wrist. The photoplethysmography signal measures optically the changes in blood volume, which enables the assessment of the function of the sympathetic and parasympathetic nervous system. Albeit having different units, our previously developed deep learning applications utilize information from heart rate, movements, oxygen saturation, and photoplethysmography signals to assess sleep quality. Thus, regardless of the units of measured signals, information from all of these signals are combined by automatic algorithms to report one single value: sleep quality.

The ISI is a validated self-report tool for assessing the severity, and impact of current insomnia symptoms. It consists of 7 Likert-scale questions with a total score ranging from 0 to 28 (with higher scores indicating more severe insomnia). Change = 12 Month score - Week 8 score.

PHQ-9 is a validated self-administered instrument assessing each of the 9 DSM-IV criteria for depression as 0 (not at all) to 3 (nearly every day), and the severity of depression. Possible scores range from 0 to 27. Change = 12 Month score - Baseline score.

EUROHIS Quality of Life 8-item Index is a validated instrument for the assessment of general quality of life. There are altogether eight questions about the general, physical, psychological, social, and environmental aspects of quality of life. Every question is scored from 1 (very poor) to 5 (very good). All scores can be added together and divided by 8 (the sum of the questions) to obtain the EUROHIS-QOL mean score. Change = 12 Month score - Baseline score.

The WAS is the first item of the Work Ability Index (WAI), a validated instrument for the assessment of work ability. WAS is a single question "What is your current work ability compared to your lifetime best?" It has a 0-10 response scale, where 0 stands for "completely unable to work" and 10 stands for "work ability at its best." The WAS has been shown to have a strong association with the WAI and is reliable in evaluating work ability. Change = 12 Month score - Baseline score.