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<div align="center">
  <h1>MindScale Sample Data</h1>
  <p><strong>Questionnaire-based mental health screening and symptom assessment</strong></p>
  <p>
    <img src="https://img.shields.io/badge/Format-JSON-2E8B57" alt="Data format: JSON">
    <img src="https://img.shields.io/badge/Samples-100-4C78A8" alt="100 sample records">
  </p>
  <p>
    <a href="#overview">Overview</a> &middot;
    <a href="#contents">Contents</a> &middot;
    <a href="#data-format">Data Format</a> &middot;
    <a href="#using-with-mindscale">Using with MindScale</a> &middot;
    <a href="#usage-notes">Usage Notes</a>
  </p>
</div>
<a id="overview"></a>

## 📋 Overview

This directory contains **100 questionnaire-format sample records** for
inspecting MindScale's data structure and preparing input demonstrations.
Each JSON file represents one sample.

- **Screening:** 50 samples covering anxiety, depression, life satisfaction,
  and life stress.
- **Assessment:** 50 samples covering five questionnaire-derived symptom
  domains, with target categories defined below.
- **Scope:** These examples are a small sample collection, not the full study
  cohort. They are not sufficient to reproduce the paper's population-scale
  performance estimates.

<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

<a id="contents"></a>

## 📂 Contents

```text
open_data/
|-- README.md
|-- At_risk_samples/       50 screening JSON files
`-- Assessment_samples/    50 assessment JSON files
```

Both folders include primary- and secondary-school questionnaire formats.
The number and names of questionnaire items therefore vary by school stage.
Sample manifests and sampling-weight files are not included in this directory.

<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

<a id="data-format"></a>

## 🧾 Data Format

All sample files use UTF-8 JSON encoding.

| Field | Contents |
| --- | --- |
| `input` | Observed background and environmental questionnaire responses as key-value pairs |
| `mask` | Item response records, each containing `value` and an ordered `candidate` list |
| `label` | Four screening targets in `At_risk_samples` |
| `re_label` | Five assessment targets in `Assessment_samples`; some screening files also contain ancillary assessment results here |
| `anxiety_depression` | Auxiliary anxiety and depression outcomes in assessment samples |

### Item Response Records

The following is an illustrative entry within `mask`:

```json
{
  "Self-strength": {
    "value": "Basically agree",
    "candidate": [
      "Strongly disagree",
      "Not quite agree",
      "Basically agree",
      "Strongly agree"
    ]
  }
}
```

- **Meaning of `mask`:** This field contains response values, not only missing
  items. Pretraining predicts these responses, while downstream input builders
  incorporate their values as questionnaire features.
- **Missing responses:** Some assessment item records use `"-"` for an
  unavailable response. Preserve this marker and the original candidate list.
- **Auxiliary outcomes:** `label` and `re_label` are stage-specific fields, not
  interchangeable aliases. Ancillary outcomes should be kept separate from the
  selected prediction targets.

### Screening Targets

Read the screening target mapping from `label`.

| Target key | Candidate labels, in model order |
| --- | --- |
| `anxiety` | `No anxiety`, `Mild anxiety`, `Severe anxiety` |
| `depression` | `No depression`, `Mild depression`, `Severe depression` |
| `satisfaction` | `Low life satisfaction`, `High life satisfaction` |
| `stress` | `No life stress`, `Low life stress`, `High life stress` |

### Assessment Targets

Read the assessment target mapping from `re_label`.

| Target key | Candidate labels, in model order |
| --- | --- |
| `re_suicidal` | `Mild suicidal ideation`, `Severe suicidal ideation` |
| `re_obsessive` | `Mild obsessive symptoms`, `Severe obsessive symptoms` |
| `re_psychotic` | `Mild psychotic symptoms`, `Severe psychotic symptoms` |
| `re_mania` | `Mild mania`, `Severe mania` |
| `re_ADHD` | `Mild ADHD`, `Severe ADHD` |

These strings are the model's questionnaire-derived categories, not clinical
diagnoses. Preserve their spelling and capitalization when using released
adapters; the corresponding mappings are defined in the code's `dataset_info.py`.

<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

<a id="using-with-mindscale"></a>

## 🚀 Using with MindScale

- **Select the stage**

  Use `At_risk_samples` for `--task_type Screen` and `Assessment_samples` for
  `--task_type Assessment`. The screening samples' `input` and `mask` fields can
  also supply pretraining inputs; screening outcomes are not pretraining targets.

- **Prepare the target mapping for the current input builder**

  The comparative builder reads targets from `label`, whereas the
  non-comparative builder reads them from `re_label`. Prepare working copies
  with the selected stage's target mapping in the required field:

| Stage | Source target field | Comparative mode | Non-comparative mode |
| --- | --- | --- | --- |
| `Screen` | `label` | Keep screening targets in `label` | Copy screening targets to `re_label` in a working copy |
| `Assessment` | `re_label` | Copy assessment targets to `label` in a working copy | Keep assessment targets in `re_label` |

Preserve any original auxiliary outcomes separately when preparing these copies.

- **Prepare manifests**

  For downstream runs, create the following UTF-8 text files. Sample paths must
  be relative to `--data_path`, with one entry per line.

```text
train.txt          Reference/training sample paths
grade_train.txt    School-stage label for each reference/training sample
mean_IP_train.txt  Template-sampling weight for each reference/training sample
test.txt           Test sample paths
grade_test.txt     School-stage label for each test sample
```

The three training files must be line-aligned with one another; the two test
files must be line-aligned with one another. Use separate reference and test
samples, and calculate sampling weights from reference/training labels only.

- **Map school stages**

  The grade manifests use the following labels, derived from
  `input["School-status"]`:

| Sample value | Grade-manifest label |
| --- | --- |
| `Schoolchild` | `Primary school` |
| `Middle school student` | `Middle school` |
| `High school student` | `Middle school` |

With two templates, each school-stage group used during training needs at least
three reference samples; evaluation needs at least two reference samples.
Templates must be drawn from the reference/training set.

- **Load model weights**

  Follow the accompanying MindScale code README for installation, checkpoint
  loading, and prediction export. Three-stage LoRA adapters are available on
  [Hugging Face](https://huggingface.co/Rango001/Adolescent-mental-health).

<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

<a id="usage-notes"></a>

## 📝 Usage Notes

- **Research scope:** Use these samples for authorized research, schema
  inspection, and integration checks. They are not a clinical assessment service.
- **Privacy:** Questionnaire records contain sensitive background and mental
  health information. Protect participant privacy and do not attempt to
  re-identify individuals or link records to identifiable people.
- **Release permissions:** Availability in this directory does not by itself
  establish permission for unrestricted reuse or redistribution. Follow the
  data provider's applicable authorization and data-use terms.

<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

	<a id="readme-top"></a>

	<div align="center">
	<h1>MindScale Sample Data</h1>
	<p><strong>Questionnaire-based mental health screening and symptom assessment</strong></p>
	<p>
	<img src="https://img.shields.io/badge/Format-JSON-2E8B57" alt="Data format: JSON">
	<img src="https://img.shields.io/badge/Samples-100-4C78A8" alt="100 sample records">
	</p>
	<p>
	<a href="#overview">Overview</a> ·
	<a href="#contents">Contents</a> ·
	<a href="#data-format">Data Format</a> ·
	<a href="#using-with-mindscale">Using with MindScale</a> ·
	<a href="#usage-notes">Usage Notes</a>
	</p>
	</div>

	<a id="overview"></a>

	## 📋 Overview

	This directory contains 100 questionnaire-format sample records for
	inspecting MindScale's data structure and preparing input demonstrations.
	Each JSON file represents one sample.

	- Screening: 50 samples covering anxiety, depression, life satisfaction,
	and life stress.
	- Assessment: 50 samples covering five questionnaire-derived symptom
	domains, with target categories defined below.
	- Scope: These examples are a small sample collection, not the full study
	cohort. They are not sufficient to reproduce the paper's population-scale
	performance estimates.

	<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

	<a id="contents"></a>

	## 📂 Contents

	```text
	open_data/
	\|-- README.md
	\|-- At_risk_samples/ 50 screening JSON files
	`-- Assessment_samples/ 50 assessment JSON files
	```

	Both folders include primary- and secondary-school questionnaire formats.
	The number and names of questionnaire items therefore vary by school stage.
	Sample manifests and sampling-weight files are not included in this directory.

	<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

	<a id="data-format"></a>

	## 🧾 Data Format

	All sample files use UTF-8 JSON encoding.

	\| Field \| Contents \|
	\| --- \| --- \|
	\| `input` \| Observed background and environmental questionnaire responses as key-value pairs \|
	\| `mask` \| Item response records, each containing `value` and an ordered `candidate` list \|
	\| `label` \| Four screening targets in `At_risk_samples` \|
	\| `re_label` \| Five assessment targets in `Assessment_samples`; some screening files also contain ancillary assessment results here \|
	\| `anxiety_depression` \| Auxiliary anxiety and depression outcomes in assessment samples \|

	### Item Response Records

	The following is an illustrative entry within `mask`:

	```json
	{
	"Self-strength": {
	"value": "Basically agree",
	"candidate": [
	"Strongly disagree",
	"Not quite agree",
	"Basically agree",
	"Strongly agree"
	]
	}
	}
	```

	- Meaning of `mask`: This field contains response values, not only missing
	items. Pretraining predicts these responses, while downstream input builders
	incorporate their values as questionnaire features.
	- Missing responses: Some assessment item records use `"-"` for an
	unavailable response. Preserve this marker and the original candidate list.
	- Auxiliary outcomes: `label` and `re_label` are stage-specific fields, not
	interchangeable aliases. Ancillary outcomes should be kept separate from the
	selected prediction targets.

	### Screening Targets

	Read the screening target mapping from `label`.

	\| Target key \| Candidate labels, in model order \|
	\| --- \| --- \|
	\| `anxiety` \| `No anxiety`, `Mild anxiety`, `Severe anxiety` \|
	\| `depression` \| `No depression`, `Mild depression`, `Severe depression` \|
	\| `satisfaction` \| `Low life satisfaction`, `High life satisfaction` \|
	\| `stress` \| `No life stress`, `Low life stress`, `High life stress` \|

	### Assessment Targets

	Read the assessment target mapping from `re_label`.

	\| Target key \| Candidate labels, in model order \|
	\| --- \| --- \|
	\| `re_suicidal` \| `Mild suicidal ideation`, `Severe suicidal ideation` \|
	\| `re_obsessive` \| `Mild obsessive symptoms`, `Severe obsessive symptoms` \|
	\| `re_psychotic` \| `Mild psychotic symptoms`, `Severe psychotic symptoms` \|
	\| `re_mania` \| `Mild mania`, `Severe mania` \|
	\| `re_ADHD` \| `Mild ADHD`, `Severe ADHD` \|

	These strings are the model's questionnaire-derived categories, not clinical
	diagnoses. Preserve their spelling and capitalization when using released
	adapters; the corresponding mappings are defined in the code's `dataset_info.py`.

	<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

	<a id="using-with-mindscale"></a>

	## 🚀 Using with MindScale

	- Select the stage

	Use `At_risk_samples` for `--task_type Screen` and `Assessment_samples` for
	`--task_type Assessment`. The screening samples' `input` and `mask` fields can
	also supply pretraining inputs; screening outcomes are not pretraining targets.

	- Prepare the target mapping for the current input builder

	The comparative builder reads targets from `label`, whereas the
	non-comparative builder reads them from `re_label`. Prepare working copies
	with the selected stage's target mapping in the required field:

	\| Stage \| Source target field \| Comparative mode \| Non-comparative mode \|
	\| --- \| --- \| --- \| --- \|
	\| `Screen` \| `label` \| Keep screening targets in `label` \| Copy screening targets to `re_label` in a working copy \|
	\| `Assessment` \| `re_label` \| Copy assessment targets to `label` in a working copy \| Keep assessment targets in `re_label` \|

	Preserve any original auxiliary outcomes separately when preparing these copies.

	- Prepare manifests

	For downstream runs, create the following UTF-8 text files. Sample paths must
	be relative to `--data_path`, with one entry per line.

	```text
	train.txt Reference/training sample paths
	grade_train.txt School-stage label for each reference/training sample
	mean_IP_train.txt Template-sampling weight for each reference/training sample
	test.txt Test sample paths
	grade_test.txt School-stage label for each test sample
	```

	The three training files must be line-aligned with one another; the two test
	files must be line-aligned with one another. Use separate reference and test
	samples, and calculate sampling weights from reference/training labels only.

	- Map school stages

	The grade manifests use the following labels, derived from
	`input["School-status"]`:

	\| Sample value \| Grade-manifest label \|
	\| --- \| --- \|
	\| `Schoolchild` \| `Primary school` \|
	\| `Middle school student` \| `Middle school` \|
	\| `High school student` \| `Middle school` \|

	With two templates, each school-stage group used during training needs at least
	three reference samples; evaluation needs at least two reference samples.
	Templates must be drawn from the reference/training set.

	- Load model weights

	Follow the accompanying MindScale code README for installation, checkpoint
	loading, and prediction export. Three-stage LoRA adapters are available on
	[Hugging Face](https://huggingface.co/Rango001/Adolescent-mental-health).

	<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>

	<a id="usage-notes"></a>

	## 📝 Usage Notes

	- Research scope: Use these samples for authorized research, schema
	inspection, and integration checks. They are not a clinical assessment service.
	- Privacy: Questionnaire records contain sensitive background and mental
	health information. Protect participant privacy and do not attempt to
	re-identify individuals or link records to identifiable people.
	- Release permissions: Availability in this directory does not by itself
	establish permission for unrestricted reuse or redistribution. Follow the
	data provider's applicable authorization and data-use terms.

	<p align="right"><a href="#readme-top">⬆️ Back to top</a></p>