Pain Prediction Via Machine Learning: Electrical Thresholds and Interoception
Machine Learning-Based Pain Prediction in University Students: Electrical Threshold Measurements and Interoception
The goal of this observational study is to predict (retrospective and prospective) musculoskeletal pain in university students using machine learning models based on electrical threshold measurements and interoceptive awareness. The main question it aims to answer is:
Can electrical sensory, motor, and pain thresholds, along with interoceptive awareness scores, predict musculoskeletal pain status in young adults using machine learning algorithms?
Participants will:
Complete demographic, healthy lifestyle (physical activity, sitting time, meal frequency), and substance use (ASSIST v3.0) questionnaires.
Complete self-report surveys including the Nordic Musculoskeletal Questionnaire (NMQ) and the Multidimensional Assessment of Interoceptive Awareness (MAIA-2).
Undergo quantitative electrical threshold testing on their dominant hand, which includes 3 consecutive measurements of sensory threshold, motor threshold (after a 10-minute rest), and pain threshold (after another 10-minute rest).
調査の概要
状態
状態
条件
条件
介入・治療
介入・治療
詳細な説明
The aim of this study is to investigate the relationship between musculoskeletal pain, electrical threshold values, and interoception in healthy university students, and to evaluate the predictive accuracy of machine learning models for both retrospective and prospective musculoskeletal pain.
Designed as an observational, analytical, and cross-sectional study with a prospective follow-up component, this study will include approximately 550 healthy, right-hand dominant students aged 18-25 who provide written informed consent.
Participants' demographic data and healthy lifestyle behaviors (physical activity, sitting time, nutrition, and tobacco/alcohol/substance use via ASSIST) will be recorded. Musculoskeletal complaints will be evaluated using the Nordic Musculoskeletal Questionnaire, and interoception will be assessed using the Multidimensional Assessment of Interoceptive Awareness-II. Finally, electrical sensory, motor, and pain thresholds will be measured using a combined electrotherapy device with electrodes placed over the flexor muscles of the forearm. One week later, participants will be contacted again to re-evaluate their pain complaints during the preceding 7 days.
In statistical analyses, in addition to correlation and regression analyses among parameters, the performance of three machine learning models-Logistic Regression, Random Forest, and XGBoost-in predicting participants' retrospective and prospective pain will be evaluated.
The research results will demonstrate several key outcomes. First, they will elucidate the relationship between musculoskeletal pain, electrical threshold values, and interoception in university students, while testing the utility of electrical threshold values as an objective tool in musculoskeletal pain assessment. Furthermore, the study will evaluate the accuracy of machine learning models in predicting both retrospective and prospective pain within this population. By leveraging objective measurements obtained from widely accessible clinical devices, the findings will contribute to digital health approaches and applications that guide researchers and clinicians throughout pain evaluation and treatment processes. Ultimately, this work will provide critical insights into the efficacy of the proposed research methodology before its implementation in diverse patient populations.
研究の種類
研究の種類
入学 (推定)
入学
連絡先と場所
研究連絡先
研究連絡先
- 名前：Aybike Şenel, Assistant Professor
- 電話番号：+90 531 583 99 24
- メール：aybikesenel@hotmail.com
研究場所
-
-
Amasya
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Amasya、Amasya、トルコ（Türkiye）、05100
- Amasya University
-
コンタクト：
- Kübra Okuyucu
- 電話番号：4879 0(358)2115005
- メール：aybikesenel@hotmail.com
-
-
参加基準
適格基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
サンプリング方法
調査対象母集団
University students with healthy lifestyle
説明
Inclusion criteria:
- Being healthy and aged 18-25
- Having the right hand as the dominant extremity
- Being able to communicate effectively and understand the study procedure
- Being willing to participate in the study and having signed the written informed consent
Exclusion criteria:
- Presence of continuous or periodic pain in the same region over the last 3 months (presence of chronic pain)
- Presence of sleep problems
- History of severe menstrual or abdominal pain
- Diagnosis of an endocrinological, psychiatric, urogenital, neurological, dermatological, cardiorespiratory, or musculoskeletal disease and/or sleep disorder that could be related to the study outcomes
- Being pregnant or the possibility of pregnancy
Criteria for withdrawal from the study:
- Deciding not to participate in the study and not wishing to complete the assessments
- Experiencing discomfort due to the assessments and measurements and not wishing to complete them
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 観測モデル：COHORT
- 時間の展望：PROSPECTIVE
グループ/コホートの数
コホートと介入
グループ/コホートグループ/コホート |
介入・治療介入・治療 |
|---|---|
|
university students with healthy lifestyle
|
No Intervention: Observational Cohort |
この研究は何を測定していますか？
主要な結果の測定
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Retrospective Pain
時間枠：baseline
|
Self-reported musculoskeletal pain presence and anatomical localization over the preceding 12 months and past 7 days, assessed using the Nordic Musculoskeletal Questionnaire (NMQ). The NMQ is a standardized screening instrument that evaluates musculoskeletal symptoms (pain, ache, or discomfort) across 9 distinct body regions (neck, shoulders, elbows, wrists/hands, upper back, lower back, hips/thighs, knees, and ankles/feet). |
baseline
|
|
Prospective Pain
時間枠：1 week post-baseline
|
Presence and anatomical site of self-reported prospective musculoskeletal pain or discomfort experienced during the 1-week follow-up period. Participants will be re-evaluated via a structured telephone or digital questionnaire inquiring about any newly developed or ongoing musculoskeletal pain symptoms in the preceding 7 days. Pain presence is recorded as a binary outcome (Yes/No) for overall pain and for specific body regions. |
1 week post-baseline
|
|
Electrical Sensory, Motor, and Pain Thresholds
時間枠：baseline
|
Quantitative evaluation of somatosensory processing using a standardized monochromatic combined electrotherapy device (Intelect Advanced Monochromatic Combo). Electrodes 5x5 cm will be placed over the wrist flexor muscles on the anterior aspect of the dominant forearm using a symmetric biphasic square wave (100 Hz frequency, 100 µs phase duration, current increased at a rate of 1 mA/s). Three threshold parameters will be measured in milliamperes (mA):Electrical Sensory Threshold (EST): The minimum current intensity at which the participant first perceives a tingling or sensory stimulus.Electrical Motor Threshold (EMT): The minimum current intensity required to elicit a visible muscle contraction.Electrical Pain Threshold (EPT): The minimum current intensity at which the electrical sensation first becomes painful. |
baseline
|
|
Interoceptive Awareness
時間枠：baseline
|
Multidimensional self-reported interoceptive bodily awareness assessed using the Multidimensional Assessment of Interoceptive Awareness-2 (MAIA-2) scale. The MAIA-2 is a 37-item questionnaire evaluated on a 6-point Likert scale (0= Never to 5=Always) across 8 distinct subscales: Noticing, Not-Distracting, Not-Worrying, Attention Regulation, Emotional Awareness, Self-Regulation, Body Listening, Trust. Subscale scores are calculated as the mean of their respective items (range: 0 to 5), with higher scores indicating higher levels of interoceptive awareness. |
baseline
|
協力者と研究者
研究記録日
主要日程の研究
研究開始 (推定)
研究開始
一次修了 (推定)
一次修了
研究の完了 (推定)
研究の完了
試験登録日
最初に提出
最初に提出
QC基準を満たした最初の提出物
QC基準を満たした最初の提出物
最初の投稿 (実際)
最初の投稿
学習記録の更新
投稿された最後の更新 (実際)
投稿された最後の更新
QC基準を満たした最後の更新が送信されました
QC基準を満たした最後の更新が送信されました
最終確認日
最終確認日
詳しくは
本研究に関する用語
追加の関連 MeSH 用語
その他の研究ID番号
その他の研究ID番号
- 19092026-AS
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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