Depending on disease stage, head and neck cancer (HNC) can be cured either with a single modality or with multimodal treatments, consisting of various combinations of surgery, radiotherapy, and chemotherapy. Despite treatment with curative intent, loco-regional recurrences and/or distant relapses are frequent. Moreover, these therapeutic approaches result in significant acute toxicities and late sequelae. Therefore, quality of life (QoL) is often impaired in these survivors. It is known that QoL is a prognostic factor because it is related to overall survival in cancer patients and to loco-regional control in HNC patients.

The adoption of mobile technologies of common use (i.e. embedded into standard mobile phones) for behavior reconstruction and linkage of behavior modifications to quality of life indicators, and the realization of predictive models for quality of life modifications will allow seamless and unobtrusive data capture over time, making the execution of clinical investigations more precise and less burdensome as compared to standard (manual) data capture.

The main aim of the present study is to reduce and to anticipate, with the use of the non-invasive Big data for quality of life (BD4QoL) platform, the proportion of HNC survivors experiencing a clinically meaningful reduction in QoL.

The BD4QoL platform consists of a set of services to allow patient monitoring and empowerment, through two main tools: Point of Care application to manage all patients data and follow-up by clinical investigators, and a mobile application (App) installed on participating subject's smartphone. Also, a web-form tool is delivered to allow the QoL questionnaire completion.

To achieve the study objectives, the BD4QoL platform will use the following sensors embedded in a smartphone to collect data which will be used to identify behavioral and affective traits associated with study outcomes. Sensors at mobile phone used to collect relevant data are the following:

• Accelerometer (x,y,z measurements)
• Global Positioning System - GPS (Lat, Long)
• Ambient light (measurement of light in the room / area where the mobile device is located)
• Screen (Status ON or OFF for smartphone device screen)
• Activity (type of activity with which the person engages,which can be one of these: Still, Walking, Running, On_Bicycle, In_Vehicle)
• Steps (total number of steps per day and per hour)
• Daily connections to wifi networks (naming of wifi connections as well as corresponding duration)
• Data detected from the mobile device's operating system (phone usage logs, phone applications usage) and from external datasets (steps, identification of places (Points of Interest) visited based on participant's permissions, through the correlation of one's GPS signal with external datasets from Foursquare and OpenStreet maps) The above data will be used to detect activities and behaviors which have a high likelihood of being meaningfully related with participants' QoL trajectories.

The BD4QoL App, available for Android, will be able to collect and store data about the following domains: mobility, physical activity, activities of daily living, instrumental activities of daily living, socialization, cognitive function, health related activities as well as affective personal data. A summary of the findings and the supporting data will be available to the patient and clinical investigators , through a dashboard available on mobile devices for patients and through the Point of Care (PoC) web tool for clinical investigators. The data collected by the mobile App will not be available to the technology manufacturer and will be transferred in almost-real-time (real-time when possible, as soon as data transfer is available) to the central BD4QoL repository (as long as there is available storage in the local memory storage of the mobile device).

In the interval between visits, study participants, allocated in the intervention arm, will be able to interact electronically with a chatbot, which will be part of the BD4QoL platform, implementation based on IBM Watson technology. The chatbot is an application to empower patients to manage their QoL and health, under the supervision of clinical investigators. The chatbot will have a series of e-coaching (electronic coaching) functions that include: (i) dialogue management that allows the patient to be counselled by chatting electronically in a structured and effective way; (ii) management of two-way communications with healthcare professionals [e.g. for the patient to request specific support in case of special needs, or for the chatbot to invite the patient for a visit in case of an early detection of health-related QoL (HRQoL) or health issues; identified people will have to be listed on the delegation log by the Principal Investigator (PI)]; (iii) detection of affective traits embodied in the e-coach / patient dialogue, through sentiment analysis and emotion analysis technologies to gather data about the participant mood. The latter element can be used to both re-adapt the chatbot counselling strategy, as well as to provide additional information on subjects mood to clinical investigators. The adverse events that the chatbot will be able to recognise will be the following: fatigue, malaise, fever, excessive sleepiness, difficulty sleeping, depression, change in social circumstances, neck swelling, facial pain, difficulty breathing, nose bleeds, difficulty speaking, dry mouth, tooth loss, muscle weakness, ear pain, difficulty hearing, tinnitus, vertigo, nausea, diarrhea, constipation, difficulty seeing, dry eye, eye pain, nervous eyelid, eye floaters, swollen eye, bleeding eyes, eye watering, sexuality issues, weight loss, difficulty swallowing, mouth sores, appetite loss, difficulty opening mouth, difficulty eating, increased sensitivity to smells, no taste.

The platform will provide the investigators with real time data of device usage (e.g number and type of alerts and chatbot interactions by patients) and it will integrate the electronic case report forms (eCRFs) as a study monitoring dashboard.

The BD4QoL platform used in this trial is not to be considered a medical device and is used for experimental assessment only. No drugs will be suggested by the automated chatbot responses. Tips provided by the chatbot regarding detected symptoms are also not to be considered clinical advice by any means and should not be a substitute for conversations with a member of a trained medical personnel.

Inclusion Criteria:

1. Effectively cured histologically defined head and neck squamous cell carcinoma (HNSCC) from one of these subsites: oral cavity, nasopharynx, hypopharynx, larynx, Human Papillomavirus (HPV)-positive or negative oropharynx, nasal cavity, paranasal sinuses (ICD codes in Annex 12). Non-metastatic salivary gland cancer (SGC) of any histological type can be included only if curative or postoperative radiotherapy included the neck:

   1. For p16-negative or p16-unknown HNSCC (including nasal cavity and paranasal sinuses), stage I, II, III, IVa or IVb (no IVc) according to UICC/AJCC 8th edition22. Regional neck metastases from squamous cell carcinoma from unknown primary head and neck sites are allowed.
   2. For nasopharyngeal cancer (NPC), stage I, II, III, IVa (no IVb) according to UICC/AJCC 8th edition22. Regional neck metastases from EBV-positive carcinoma from unknown primary head and neck sites are allowed.
   3. For SGCs, stage III, IVa or IVb according to UICC/AJCC 8th edition22 treated with radiotherapy that included the neck (either post-operative radiation or radical treatment in case of unresectable disease).
   4. For p16-positive oropharyngeal squamous cell carcinoma, stage I, II or III according to UICC/AJCC 8th edition22. Regional neck metastases from p16-positive and/or HPV-positive squamous cell carcinoma from unknown primary head and neck sites are allowed.

2. Patients having completed treatment with curative intent (including any single modality or multimodal approach) within 10 years at the time of accrual.

3. Patients being disease-free at the time of accrual. Patients will be deemed in complete remission if the clinical examination is negative for recurrence; clinical examination should be preferably, but not mandatorily, integrated with unequivocal radiological imaging that shows the absence of disease (in case of doubt, further radiological imaging should be performed or integrated with cyto/histological samples of the area with suspected disease persistence and the exams will have to be consistently negative) after at least three months following treatment completion.

4. Ability to fill in questionnaires as per protocol.

5. Geographical accessibility and willingness to be followed-up for up to 2 years with information-technology (IT) devices in addition to questionnaires.

6. Age ≥ 18 years.

7. Signed informed consent.

8. Willingness to use their smartphone and their Internet access for the study.

9. Smartphone having the following minimum characteristics:

   1. RAM: Minimum of 2 GB
   2. Storage: Minimum of 512 MB free storage
   3. Operating system: Android version 7 (Nougat) or upper.

Exclusion Criteria:

1. Distant metastases (the following populations are excluded: stage IVc HPV-negative HNSCC and SGC, stage IV p16-positive oropharyngeal squamous cell carcinoma, stage IVb NPC).
2. Thyroid cancers, non-melanoma skin cancers (e.g. squamous cell carcinoma of the skin, skin basal cell carcinoma, skin adnexal carcinoma), and non-carcinoma of the head and neck area (e.g. melanoma, sarcoma, etc.) are excluded.
3. Subjects with previous malignancies (except localized non-melanoma skin cancers, and the following in situ cancers: bladder, gastric, colon, esophageal, endometrial, cervical/dysplasia, melanoma, or breast) unless a complete remission was achieved at least 5 years prior to study entry AND no additional therapy is required during the study period. Premalignant lesions (e.g. leukoplakia, erythroplakia, lichen etc.) are allowed.
4. Participation in clinical trials with other experimental agents within 30 days of study entry or concomitant treatment with experimental drugs.
5. Patients unable to comply with the protocol, in the opinion of the investigator.
6. Any known or underlying medical conditions that, in the opinion of the investigator, could adversely affect the ability of the participating subject to comply with the study.
7. Having a smartphone operating system other than Android.